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  • Climate, Vol. 12, Pages 28: Atmospheric Patterns in Porto Velho,
           Rondônia, Southwestern Amazon, in a Rhythmic Context between 2017
           and 2018

    • Authors: Graziela T. Tejas, Dorisvalder D. Nunes, Reginaldo M. S. Souza, Carlos A. S. Querino, Marlon R. Faria, Daiana C. B. Floresta, Emerson Galvani, Michel Watanabe, João P. A. Gobo
      First page: 28
      Abstract: This paper aims to analyze the weather conditions in Porto Velho (Rondonia, Brazil, Western Amazon) and the influence of air masses on the climatic elements between 2017 and 2018, using rhythmic analysis. Climatic data were obtained through the official weather station, tabulated and statistically organized, and processed in R Studio programming language. The monitoring of air masses occurred through the synoptic charts of the Navy Hydrography Center. The results were analyzed by dry–rainy transition season, rainy season, wet–dry transition season, and dry season. Thus, the results point out that the Tropical Continental mass (mTc) acted up to 62.9%, responsible for the low precipitation index in October 2017. Although the mass has characteristics of warm and unstable weather, it is even lower than the action of the mEc. In January 2018, there was an 85.5% prevalence of the Continental Equatorial Mass (mEc), added to the action of the South Atlantic Convergence Zone (ZCAS), which contributed to an accumulated rainfall of 443 mm/month. In April 2018, the mEC acted with 56.7%, reaching 35.5% in August. Another highlight was the performance of the Tropical Atlantic mass (mTa) (27.4%) and mTc (19.4%), both of which had a crucial role in the dry season, followed by the Polar Atlantic mass (mPa) (17.7%), that contributed to the phenomenon of “coldness” in the region. Therefore, the mEc is extremely important in the control of the relative humidity of the air and the precipitations, while the mTc is a dissipator of winds that, at times, inhibits the performance of the mEc.
      Citation: Climate
      PubDate: 2024-02-20
      DOI: 10.3390/cli12030028
      Issue No: Vol. 12, No. 3 (2024)
  • Climate, Vol. 12, Pages 13: Relationship between El Niño-Southern
           Oscillation and Atmospheric Aerosols in the Legal Amazon

    • Authors: Augusto G. C. Pereira, Rafael Palácios, Paula C. R. Santos, Raimundo Vitor S. Pereira, Glauber Cirino, Breno Imbiriba
      First page: 13
      Abstract: The El Niño-Southern Oscillation (ENSO) stands out as the most significant tropical phenomenon in terms of climatic magnitude resulting from ocean–atmosphere interaction. Due to its atmospheric teleconnection mechanism, ENSO influences various environmental variables across distinct atmospheric scales, potentially impacting the spatiotemporal distribution of atmospheric aerosols. Within this context, this study aims to evaluate the relationship between ENSO and atmospheric aerosols across the entire Legal Amazon during the period from 2006 to 2011. Over this five-year span, four ENSO events were identified. Concurrently, an analysis of the spatiotemporal variability of aerosol optical depth (AOD) and Black Carbon radiation extinction (EAOD-BC) was conducted alongside these ENSO events, utilizing data derived from the Aerosol Robotic Network (AERONET), MERRA-2 model, and ERSSTV5. Employing the Windowed Cross-Correlation (WCC) approach, statistically significant phase lags of up to 4 to 6 months between ENSO indicators and atmospheric aerosols were observed. There was an approximate 100% increase in AOD immediately after El Niño periods, particularly during intervals encompassing the La Niña phase. The analysis of specific humidity anomaly (QA) revealed that, contrary to expectations, positive values were observed throughout most of the El Niño period. This result suggests that while there is a suppression of precipitation events during El Niño due to the subsidence of drier air masses in the Amazon, the region still exhibits positive specific humidity (Q) conditions. The interaction between aerosols and humidity is intricate. However, Q can exert influence over the microphysical and optical properties of aerosols, in addition to affecting their chemical composition and aerosol load. This influence primarily occurs through water absorption, leading to substantial alterations in radiation scattering characteristics, and thus affecting the extinction of solar radiation.
      Citation: Climate
      PubDate: 2024-01-23
      DOI: 10.3390/cli12020013
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 14: Impacts of Climate Change in Baja California
           Winegrape Yield

    • Authors: Marilina Hernandez Garcia, María Cristina Garza-Lagler, Tereza Cavazos, Ileana Espejel
      First page: 14
      Abstract: We analyzed climate change scenarios and their possible impacts on winegrape yield in Baja California, the leading wine producer in Mexico. Linear regression models were used to predict the current yield based on climate and economic variables. Using future projections of the climate variables from two regional climate models (RegCM and RCA4), we evaluated the possible changes in yield for the Near Future (NF: 2021−2040) and Intermediate Future (IF: 2041−2060) periods under low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenarios. One regression model includes maximum and minimum temperatures (Tx and Tn) of the winegrape growing season and accumulated winter precipitation (Pre), and the other model also includes the real minimum wage and winegrape price to evaluate the operating cost paid by producers. The results show that the linear regression model with the climatic and economic variables explains 28% of the winegrape yield, and Tx and Tn had the greatest influence. The climate change scenarios show that during the winegrape growing season, these variables could increase more than 1 °C in the NF and more than 2 °C in the IF under the RCP8.5 scenario. These latter temperature changes could reduce the yield between 18% and 35% relative to the reference observed climate dataset (Livneh). However, winegrape yield is sensitive to economic factors, as the yield reduction increases at least 3% in all cases. Thus, adaptation strategies need to be implemented in the viticulture sector to reduce future impacts.
      Citation: Climate
      PubDate: 2024-01-25
      DOI: 10.3390/cli12020014
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 15: Net Zero Dairy Farming—Advancing Climate
           Goals with Big Data and Artificial Intelligence

    • Authors: Suresh Neethirajan
      First page: 15
      Abstract: This paper explores the transformative potential of Big Data and Artificial Intelligence (AI) in propelling the dairy industry toward net zero emissions, a critical objective in the global fight against climate change. Employing the Canadian dairy sector as a case study, the study extrapolates its findings to demonstrate the global applicability of these technologies in enhancing environmental sustainability across the agricultural spectrum. We begin by delineating the environmental challenges confronting the dairy industry worldwide, with an emphasis on greenhouse gas (GHG) emissions, including methane from enteric fermentation and nitrous oxide from manure management. The pressing need for innovative approaches in light of the accelerating climate crisis forms the crux of our argument. Our analysis delves into the role of Big Data and AI in revolutionizing emission management in dairy farming. This includes applications in optimizing feed efficiency, refining manure management, and improving energy utilization. Technological solutions such as predictive analytics for feed optimization, AI in herd health management, and sensor networks for real-time monitoring are thoroughly examined. Crucially, the paper addresses the wider implications of integrating these technologies in dairy farming. We discuss the development of benchmarking standards for emissions, the importance of data privacy, and the essential role of policy in promoting sustainable practices. These aspects are vital in supporting the adoption of technology, ensuring ethical use, and aligning with international climate commitments. Concluding, our comprehensive study not only suggests a pathway for the dairy industry towards environmental sustainability but also provides insights into the role of digital technologies in broader agricultural practices, aligning with global environmental sustainability efforts.
      Citation: Climate
      PubDate: 2024-01-25
      DOI: 10.3390/cli12020015
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 16: Land-Use Optimization and Allocation for
           Saltwater Intrusion Regions: A Case Study in Soc Trang Province, Vietnam

    • Authors: Quang Chi Truong, Thao Hong Nguyen, Vu Thanh Pham, Trung Hieu Nguyen
      First page: 16
      Abstract: Land-use planning plays an important role in agricultural development. However, the tools used to support planners in proposing land-use planning solutions are lacking, especially when considering saltwater intrusion conditions in coastal regions. In this study, optimization is applied by analyzing land use in developing solutions for agricultural land-use planning, wherein a multi-objective optimization model is developed to optimize land-use area, including land-use allocation, and taking into account socioeconomic and environmental factors. The model was applied to three districts of Soc Trang province, Vietnam (Long Phu, My Xuyen, and Tran De), representing three ecological regions of salt water, brackish water, and fresh water in the Mekong Delta of Vietnam. The results are shown for the implementation of two multi-objective optimization scenarios (in terms of profit, labor, environment benefits, and risk reduction) as follows: (i) multi-objective optimization of agricultural land use until 2030 under normal conditions; (ii) optimizing agricultural land use until 2030 under climate change conditions similar to the 2016 drought and saltwater intrusion phenomenon in the Mekong Delta. The results demonstrate that the second scenario is the preferred option for implementing land-use planning thanks to the balance between good profits and minimizing economic and environmental risk. Land allocation was carried out by taking into account the factors of household economics, the influence of adjacent production types, local traffic, and canal systems to allocate areas toward ensuring optimal land use. This process, involving a combination of land-use optimization and spatial allocation, can help planners to improve the quality of agricultural land-use planning.
      Citation: Climate
      PubDate: 2024-01-28
      DOI: 10.3390/cli12020016
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 17: Secondary School Students’ Perceptions
           and Concerns on Sustainability and Climate Change

    • Authors: Raquel de Rivas, Amparo Vilches, Olga Mayoral
      First page: 17
      Abstract: This research is framed in Education for Sustainability, aimed at promoting the inclusion of the principles and values of Sustainability in education from a holistic perspective. The study focuses on finding out the concerns and knowledge of secondary school students from Valencia (Spain), who were surveyed during the academic years 2019–2020, 2020–2021 and 2021–2022 about Sustainability and Climate Change. Examining their conceptions, initial ideas, possible shortcomings, and conceptual errors is necessary to build a teaching itinerary with the purpose of adapting and reorienting educational practice to changing situations and different social contexts. The analysis, which is part of a broader research project, focuses on studying what secondary school students know (or rather, what they do not know or are unaware of) about Sustainability and Climate Change, examining their interests and concerns. Our experimental design is based on a wide-ranging questionnaire addressed to students that also promotes initial reflections. The results show that the participating students are concerned about socio-environmental problems, particularly about Climate Change. Nevertheless, they show a limited knowledge of Sustainability. This situation must encourage the involvement of the whole educational community to achieve a greater understanding of the planetary crisis through Education for Sustainability with the final goal of ensuring an effective involvement of the younger generations who are beginning to make their own decisions.
      Citation: Climate
      PubDate: 2024-01-28
      DOI: 10.3390/cli12020017
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 18: A Pathway towards Climate Services for the
           Agricultural Sector

    • Authors: Ioannis Charalampopoulos, Fotoula Droulia
      First page: 18
      Abstract: Climate change is already having a negative impact on many areas of human activity, affecting life globally. It is more urgent than ever to increase our adaptive capacity to respond to current and future climate change risks. Climate services refer to a specialized sector that encompasses both research and operational activities. This sector is primarily focused on interpreting and communicating knowledge and information about climate risks in a manner that is tailored to meet the specific needs of diverse user communities. Climate services offer a range of specialized outputs, including forecasts, assessments, and advisories, which enable users to make decisions that are based on an understanding of the potential impacts of climate change. The outputs of climate services are designed to help diverse user communities effectively manage risks and capitalize on opportunities arising from climate variability and change. An attempt is made to outline the fundamental elements of climate services and point out their contribution to various aspects of human activity, focusing on their essential role in the adaptability of the priority for action agricultural sector, which appears as considerably vulnerable to the change of considerably susceptible to climate conditions. This article is structured to answer basic questions about climate services in general and to show the specificities of climate services in the agricultural sector.
      Citation: Climate
      PubDate: 2024-01-31
      DOI: 10.3390/cli12020018
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 19: Evaluation of Bias-Corrected GCM CMIP6
           Simulation of Sea Surface Temperature over the Gulf of Guinea

    • Authors: Oye Ideki, Anthony R. Lupo
      First page: 19
      Abstract: This study used an ERA5 reanalysis SST dataset re-gridded to a common grid with a 0.25° × 0.25° spatial resolution (latitude × longitude) for the historical (1940–2014) and projected (2015–2100) periods. The SST simulation under the SSP5-8.5 scenario was carried out with outputs from eight General Circulation Models (GCMs). The bias-corrected dataset was developed using Empirical Quantile Mapping (EQM) for the historical (1940–2015) and future (2030–2100) periods while the CMIP6 model simulation was evaluated against the ERA5 monthly observed reanalysis data for temperatures over the Gulf of Guinea. Overall, the CMIP6 models’ future simulations in 2030–20100 based on the SSP5-8.5 scenario indicate that SSTs are projected, for the Gulf of Guinea, to increase by 4.61 °C, from 31 °C in the coast in 2030 to 35 °C in 2100, and 2.6 °C in the Western GOG (Sahel). The Linux-based Ncview, Ferret, and the CDO (Climate Data Operator) software packages were used to perform further data re-gridding and assess statistical functions concerning the data. In addition, ArcGIS was used to develop output maps for visualizing the spatial trends of the historical and future outputs of the GCM. The correlation coefficient (r) was used to evaluate the performance of the CMIP6 models, and the analysis showed ACCESS 0.1, CAMS CSM 0.2, CAN ESM 0.3, CMCC 0.3, and MCM 0.4, indicating that all models performed well in capturing the climatological patterns of the SSTs. The CMIP6 bias-corrected model simulations showed that increased SST warming over the GOG will be higher in the far period than the near-term climate scenario. This study affirms that the CMIP6 projections can be used for multiple assessments related to climate and hydrological impact studies and for the development of mitigation measures under a warming climate.
      Citation: Climate
      PubDate: 2024-01-31
      DOI: 10.3390/cli12020019
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 20: Extremely Cold Climate and Social
           Vulnerability in Alaska: Problems and Prospects

    • Authors: Elena A. Grigorieva, John E. Walsh, Vladimir A. Alexeev
      First page: 20
      Abstract: Cold exposure remains a significant public health concern, particularly in the Arctic regions prone to extremely cold weather. While the physical health impacts of cold exposure are well documented, understanding the social vulnerability aspects is crucial for effective mitigation and policy development. This study investigates the multifaceted dimensions of social vulnerability in the face of cold temperatures across various communities in Alaska. Alaska, renowned for its extreme cold temperatures and harsh environmental conditions, poses unique challenges to its residents, particularly in the context of social vulnerability. Drawing on a combination of quantitative data analysis and qualitative insights, we examine the factors contributing to social vulnerability, including demographic, economic, geographic, and infrastructural elements, in terms of the Extremely Cold Social Vulnerability Index, for seven Public Health Regions in Alaska. The Universal Thermal Climate Index in two very cold categories (<−27 °C) was used to identify cold exposure. Factors such as income, housing quality, health status, and resilience of the population play crucial roles in determining an individual or community’s sensitivity to, and ability to cope with, cold temperatures. Our analysis reveals that social vulnerability in Alaska is not uniform but varies significantly among regions. The research findings highlight the importance of considering factors of both sensitivity and adaptivity in understanding and addressing social vulnerability, thereby informing the development of targeted strategies and policies to enhance the resilience of Alaskan communities. As cold temperatures are projected to continue to challenge the region, addressing social vulnerability is essential for ensuring the well-being and safety of Alaska’s diverse populations.
      Citation: Climate
      PubDate: 2024-02-02
      DOI: 10.3390/cli12020020
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 21: Reassessing and Extending the Composite
           Rainfall Record of Manchester, Northwest England: 1786–Present

    • Authors: Neil Macdonald, Robert Dietz
      First page: 21
      Abstract: A monthly composite rainfall record for the period 1786–present representative of Manchester, northwest England is presented. The 235-year record ranks as the second-longest instrumental rainfall record available for northern England, and the fifth-longest for the UK, and contributes to a growing network of long homogenous rainfall series. A composite record is constructed, extended, and homogenised, and the record is analysed in terms of annual and seasonal variability, with a focus on extreme wet/dry events. Three primary meteorological stations in Manchester, located within 2 km of one another, form the basis of the reconstruction, with other records identified for infilling and extension based on their longevity, continuity, and proximity to the primary stations. A linear regression analysis is applied to produce a continuous record, and adjustment factors are applied to ensure homogeneity. Record homogeneity is assessed via cross-comparison with long-term records from the region (Carlisle, Chatsworth House and HadNWEP), and the methods are applied to assess relative homogeneity include the double-mass curve and Standard Normal Homogeneity tests. The Manchester record is deemed to be homogenous overall but includes two periods of increased uncertainty: 1786–1819, comprising the earliest observations and greatest number of different stations, and 1883–1911, which encompasses multi-year and multi-decadal drought events of (1883–1885 and 1890–1910) as identified by other long-term meteorological studies. The analysis of the entire record reflects long-term rainfall variability with an increasing, although not significant, trend in annual rainfall observed. Seasonally, a significant increase in winter rainfall is exhibited, in keeping with patterns observed in other regional studies. Seasonal rainfall totals are found to be highly variable at the decadal timescale. Several well-documented extreme wet (e.g., autumn 2000) and dry (e.g., summer 1976) seasons are identified, including historic events (e.g., the floods of summer 1872 and drought of summer 1887) from the less-well documented eighteenth and nineteenth centuries.
      Citation: Climate
      PubDate: 2024-02-02
      DOI: 10.3390/cli12020021
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 22: Precipitation Anomalies and Trends Estimated
           via Satellite Rainfall Products in the Cananeia–Iguape Coastal
           System, Southeast Region of Brazil

    • Authors: Jakeline Baratto, Paulo Miguel de Bodas Terassi, Nádia Gilma de Beserra de Lima, Emerson Galvani
      First page: 22
      Abstract: The objective of this research is to select the best orbital sensor for rainfall estimates (monthly and annual scales) and to analyze the frequency and magnitude of extreme rainfall events and their trends and disruptions based on the use of satellite rainfall product data for the Cananeia–Iguape Coastal System (CICS). Data from four satellite rainfall products were used to identify the correspondence with seven points on the surface of the study area. Statistical metrics were used to identify the best satellite rainfall product. After identifying the sensor with the best performance in estimating orbital precipitation, extreme events were identified by the Standardized Precipitation Index (SPI) on a one-month (SPI-1), three-month (SPI-3), and twelve-month (SPI-12) scale. Trend and rupture detection in the time series were performed using different statistical techniques (Mann–Kendall, Pettitt, Standard Normal Homogeneity Test, or Buishand test). Among the satellite rainfall products, CHIRPS had the best measurements for the analyzed points on the surface. The year 1983 was characterized as very rainy, also marked by the occurrence of El Niño, and was marked by the rupture of the rains at all points (IDs 1, 2, 3, 4, 5, 6, and 7) analyzed in the month of June. The decrease in monthly rainfall was more significant in the months of February (at points IDs 1, 2, 3, 5, and 7) and April (IDs 1, 3, 5, and 7). Decreased rainfall may cause CICS mangrove shrinkage. These results showed the importance of studying rainfall in an area with mangroves in order to understand the dynamics of vegetation in the face of climate change.
      Citation: Climate
      PubDate: 2024-02-05
      DOI: 10.3390/cli12020022
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 23: Quantifying the Climate Co-Benefits of Hybrid
           Renewable Power Generation in Indonesia: A Multi-Regional and
           Technological Assessment

    • Authors: Mohamed Saad Suliman, Hooman Farzaneh, Eric Zusman, Alphonce Ngila Mulumba, Puji Lestari, Didin Agustian Permadi, Nandakumar Janardhanan
      First page: 23
      Abstract: Quantifying the co-benefits of renewable energy investments can aid policymakers in identifying technologies capable of generating significant social, economic, and environmental benefits to effectively offset mitigation costs. Although there has been a growing body of work evaluating co-benefits, few studies have compared the potential co-benefits of several technologies across different regions in key countries. This study fills this gap by formulating a new modeling structure to assess the environmental–health–economic co-benefits of hybrid renewable energy systems (HRESs) in different parts of Indonesia. The proposed model is unique in that it incorporates various techno-economic activities to assess air quality, health, and economic benefits and then presents results as part of a cost–benefit analysis. From the intervention scenario, the modeling results show that installing 0.5 GW grid-connected solar PV, 100 MW of wind turbines, and a 100 MW biomass generator to cover a total of 1.64 million residential load units in the Bali province can avoid GHGs, PM2.5, disability-adjusted life years (DALYs), and provide health savings of 1.73 Mt/y, 289.02 t/y, 1648, and 6.16 million USD/y, respectively. In addition, it shows that the payback period is enhanced by one year, while the net present value is increased by 14.6%. In Jakarta, a 3 GW solar PV plant and a 100 MW biomass generator that supply 5.8 million residential load units can deliver 32,490 averted DALYs and 652.81 million USD/y of health care savings. Nationally, the contribution of renewable energy to the electricity supply mix could grow from the 2020 baseline of 18.85% to 26.93%, reducing dependence on oil and coal contribution by 5.32%.
      Citation: Climate
      PubDate: 2024-02-08
      DOI: 10.3390/cli12020023
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 24: Addressing the Climate Change Adaptation Gap:
           Key Themes and Future Directions

    • Authors: Ishfaq Hussain Malik, James D. Ford
      First page: 24
      Abstract: Climate change adaptation is a critical response to the challenges posed by climate change and is important for building resilience. Progress in adaptation efforts has been made globally, nationally, and locally through international agreements, national plans, and community-based initiatives. However, significant gaps exist in knowledge, capacity, and finance. The Adaptation Gap Report 2023, published by the United Nations Environment Programme (UNEP), examines the status of climate change adaptation efforts globally. The report highlights the widening adaptation finance gap and the deepening climate crisis. We analyse the key themes of the report and incorporate an analysis of the wider literature and insights from COP28 to substantiate key points and identify gaps where more work is needed to develop an understanding of climate change adaptation. This paper focuses on the underfinanced and underprepared state of global climate change adaptation efforts, the widening adaptation finance gap, slow progress in adaptation, gender equality and social inclusion issues, and challenges in addressing loss and damage. We provide a way forward for climate change adaptation and offer recommendations for future actions.
      Citation: Climate
      PubDate: 2024-02-08
      DOI: 10.3390/cli12020024
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 25: Influence of Climatic Factors on the
           Occurrence of Vibrio parahaemolyticus Food Poisoning in the Republic of

    • Authors: Jong-Gyu Kim
      First page: 25
      Abstract: This study aimed to investigate the outbreaks and characteristics of Vibrio parahaemolyticus food poisoning in the Republic of Korea and the impact of climatic factors on the food poisoning occurrence. All data were obtained from the official statistics of the Republic of Korea (2002 to 2017). A trend analysis, Pearson’s correlation analysis, and regression analysis were used to determine the relationship between the outbreaks of V. parahaemolyticus food poisoning and climatic factors. During the study period, the number of outbreaks of V. parahaemolyticus food poisoning ranked third among bacterial food poisoning. The food poisoning incidences of V. parahaemolyticus occurred mostly from July to September. The average temperature, maximum and minimum temperatures, precipitation, number of days with rainfall, and humidity showed a significant positive correlation with the number of outbreaks of V. parahaemolyticus food poisoning (p < 0.001), but daytime hours showed a negative correlation (p < 0.01). The data further indicated that minimum temperature was the most influential variable on the outbreaks of food poisoning (p < 0.01). These results indicate that the outbreaks of V. parahaemolyticus food poisoning in the Republic of Korea are associated with climatic factors, suggesting that these incidences may have been impacted by climate change, especially due to warming around the Korean peninsula.
      Citation: Climate
      PubDate: 2024-02-09
      DOI: 10.3390/cli12020025
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 26: Annual Solar Geoengineering: Mitigating Yearly
           Global Warming Increases

    • Authors: Feinberg
      First page: 26
      Abstract: Solar geoengineering (SG) solutions have many advantages compared to the difficulty of carbon dioxide removal (CDR): SG produces fast results, is shown here to have much higher efficiency than CDR, is not related to fossil fuel legislation, reduces the GHG effect including water vapor, and is something we all can participate in by brightening the Earth with cool roofs and roads. SG requirements detailed previously to mitigate global warming (GW) have been concerning primarily because of overwhelming goals and climate circulation issues. In this paper, annual solar geoengineering (ASG) equations and estimated requirements for yearly solar radiation modification (SRM) of areas are provided along with the advantages of annual solar geoengineering (ASG) to mitigate yearly global warming temperature increases. The ASG albedo area modification requirements found here are generally 50 to potentially more than 150 times less compared to the challenge of full SG GW albedo mitigation, reducing circulation concerns and increasing feasibility. These reductions are applied to L1 space sunshading, Earth brightening, and stratosphere aerosol injection (SAI) SRM annual area requirements. However, SAI coverage compared to other methods will have higher yearly increasing maintenance costs in the annual approach. Results also show that because ASG Earth albedo brightening area requirements are much smaller than those needed for full mitigation, there are concerns that worldwide negative SG would interfere with making positive advances for several reasons. That is, negative SG currently dominates yearly practices with the application of dark asphalt roads, roofs, and building sides. This issue is discussed.
      Citation: Climate
      PubDate: 2024-02-12
      DOI: 10.3390/cli12020026
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 27: Downscaling Climatic Variables at a River
           Basin Scale: Statistical Validation and Ensemble Projection under Climate
           Change Scenarios

    • Authors: Renalda El-Samra, Abeer Haddad, Ibrahim Alameddine, Elie Bou-Zeid, Mutasem El-Fadel
      First page: 27
      Abstract: Climatic statistical downscaling in arid and topographically complex river basins remains relatively lacking. To address this gap, climatic variables derived from a global climate model (GCM) ensemble were downscaled from a grid resolution of 2.5° × 2.5° down to the station level. For this purpose, a combination of multiple linear and logistic regressions was developed, calibrated and validated with regard to their predictions of monthly precipitation and daily temperature in the Jordan River Basin. Seasonal standardized predictors were selected using a backward stepwise regression. The validated models were used to examine future scenarios based on GCM simulations under two Representative Concentration Pathways (RCP4.5 and RCP8.5) for the period 2006–2050. The results showed a cumulative near-surface air temperature increase of 1.54 °C and 2.11 °C and a cumulative precipitation decrease of 100 mm and 135 mm under the RCP4.5 and RCP8.5, respectively, by 2050. This pattern will inevitably add stress to water resources, increasing management challenges in the semi-arid to arid regions of the basin. Moreover, the current application highlights the potential of adopting regression-based models to downscale GCM predictions and inform future water resources management in poorly monitored arid regions at the river basin scale.
      Citation: Climate
      PubDate: 2024-02-14
      DOI: 10.3390/cli12020027
      Issue No: Vol. 12, No. 2 (2024)
  • Climate, Vol. 12, Pages 6: Microclimate Analysis of Outdoor Showcases in
           Tropical Climate—Two Case Studies in Al Ain, Abu Dhabi, United Arab

    • Authors: Dario Camuffo, Antonio della Valle, Roberta Giorio, Francesco Rizzi, Patrizia Barucco, Marivita Suma, Jalal Ahmed, Amel Chabbi, Ola Shaker, Peter Sheehan
      First page: 6
      Abstract: Al Ain, near Abu Dhabi, United Arab Emirates, is characterized by hot desert climate with high temperatures, aridity, and almost no rain. Several truncated earthen walls were discovered at the historic house of Sheikh Mohammed Bin Khalifa, a component of the World Heritage Cultural Sites. These remains are preserved in situ, outdoors, protected in glass showcases for public display. As this situation is not documented in the literature, the local Authority has requested to study the showcase environment to optimize conservation. The solar radiation and the projected shades have been modeled over one year; the temperature and humidity inside and outside the showcases, as well as the moisture content, have been measured to assess the potential preservation risks. The paper presents the results, i.e., the direct solar radiation generates extreme conditions of greenhouse effect with extremely high temperatures and forces evaporation from the remains. During the night, the excess moisture condenses on the inner surface of the glass panes, forming large drops that affect viewing and are dangerous for conservation. The repetition of evaporation–condensation cycles accumulates soluble salts on the remains. The paper discusses mitigation strategies (e.g., shading, ventilation, and cooling, to reduce the greenhouse effect) to improve conservation and fruition.
      Citation: Climate
      PubDate: 2024-01-06
      DOI: 10.3390/cli12010006
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 7: Mapping and Assessing Riparian Vegetation
           Response to Drought along the Buffalo River Catchment in the Eastern Cape
           Province, South Africa

    • Authors: Zolisanani Mpanyaro, Ahmed Mukalazi Kalumba, Leocadia Zhou, Gbenga Abayomi Afuye
      First page: 7
      Abstract: The increasing drought frequency poses a significant threat to global and regional river systems and ecosystem functioning, especially in the complex topographical Buffalo River catchment area of the Eastern Cape Province, South Africa. This study explored the impact of drought on riparian vegetation dynamics using the Normalize Difference Vegetation Index (NDVI), Transformed Difference Vegetation Index (TDVI) and Modified Normalized Difference Water Index (MNDWI) from satellite-derived Landsat data from 1990 to 2020. The least-squares linear regression and Pearson’s correlation coefficient were used to evaluate the long-term drought in riparian vegetation cover and the role of precipitation and streamflow. The correlation results revealed a moderate positive correlation (r = 0.77) between precipitation and streamflow with a significant p-value of 0.04 suggesting consequences on riparian vegetation health. Concurrent with the precipitation, the vegetation trends showed that precipitation increased insignificantly with less of an influence while the reverse was the case with the streamflow in the long term. The results show that the NDVI and TDVI were significant indices for detecting water-stressed vegetation in river catchment dynamics. Much of these changes were reflected for MNDWI in dry areas with a higher accuracy (87.47%) and dense vegetation in the upper catchment areas. The standardized precipitation index (SPI) revealed the inter-annual and inter-seasonal variations in drought-stressed years between 1991–1996, 2000–2004, 2009–2010, 2015, and 2018–2019, while 2020 exhibited slight sensitivity to drought. The findings of this study underscore the need for heightened efforts on catchment-scale drought awareness for policy development, programs, and practices towards ecosystem-based adaptation.
      Citation: Climate
      PubDate: 2024-01-11
      DOI: 10.3390/cli12010007
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 8: Climatology of Synoptic Non-Gaussian
           Meteorological Anomalies in the Northern Hemisphere during 1979–2018

    • Authors: Sergey Loginov, Evgeniia Moraru, Elena Kharyutkina, Ivan Sudakow
      First page: 8
      Abstract: The analysis of spatial and temporal variability in the number of non-Gaussian extreme anomalies of climatic parameters was carried out for both the initial time series and synoptic variability in the troposphere of the Northern Hemisphere over the period 1979–2018, based on ERA-Interim reanalysis data. There are predominantly three types of empirical distribution densities at 850 hPa, each characterizing the processes of advective and convective heat transfer. At the beginning of the 21st century, compared to the end of the 20th century, there was an increase in the number of anomalies in vertical wind speed and specific humidity for the Northern Hemisphere. Additionally, there is an increase in the number of zonal wind speed anomalies in the low and middle latitudes. Regions with the maximum number of anomalies are primarily located over the continents, while for vertical wind speed anomalies, they are predominantly over the oceans. The application of R/S analysis and multifractal analysis has established that the identified tendencies (which are persistent processes) will continue in the identified regions. The time series of non-Gaussian anomalies (both initial and synoptic scales) exhibit a long-term memory of approximately four years, and synoptic extreme anomalies were found to be more predictable.
      Citation: Climate
      PubDate: 2024-01-12
      DOI: 10.3390/cli12010008
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 9: Assessing Future Precipitation Patterns,
           Extremes and Variability in Major Nile Basin Cities: An Ensemble Approach
           with CORDEX CORE Regional Climate Models

    • Authors: Gamil Gamal, Pavol Nejedlik, Ahmed M. El Kenawy
      First page: 9
      Abstract: Understanding long-term variations in precipitation is crucial for identifying the effects of climate change and addressing hydrological and water management issues. This study examined the trends of the mean and four extreme precipitation indices, which are the max 1-day precipitation amount, the max 5-day precipitation amount, the consecutive wet days, and the consecutive dry days, for historical observations (1971–2000) and two future periods (2041–2060/2081–2100) under RCP2.6 and RCP8.5 emission scenarios over the Nile River Basin (NRB) at 11 major stations. Firstly, the empirical quantile mapping procedure significantly improved the performance of all RCMs, particularly those with lower performance, decreasing inter-model variability and enhanced seasonal precipitation variability. The Mann–Kendall test was used to detect the trends in climate extreme indices. This study reveals that precipitation changes vary across stations, scenarios, and time periods. Addis Ababa and Kigali anticipated a significant increase in precipitation across all periods and scenarios, ranging between 8–15% and 13–27%, respectively, while Cairo and Kinshasa exhibited a significant decrease in precipitation at around 90% and 38%, respectively. Wet (dry) spells were expected to significantly decrease (increase) over most parts of the NRB, especially during the second period (2081–2100). Thereby, the increase (decrease) in dry (wet) spells could have a direct impact on water resource availability in the NRB. This study also highlights that increased greenhouse gas emissions have a greater impact on precipitation patterns. This study’s findings might be useful to decision makers as they create NRB-wide mitigation and adaptation strategies to deal with the effects of climate change.
      Citation: Climate
      PubDate: 2024-01-14
      DOI: 10.3390/cli12010009
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 10: Local Context Capacity Building Needs for
           Climate Change Adaptation among Smallholder Farmers in Uganda: Policy and
           Practice Implications

    • Authors: David Mfitumukiza, Gordon Y. Mwesigwa, Ellen J. Kayendeke, Vincent B. Muwanika
      First page: 10
      Abstract: Climate change impacts threaten sustainable development efforts. The magnitude of the impacts, however, varies with the socio-ecological characteristics of locations. This is the reason there is consensus on the necessity for climate change adaptive capacity building that is country driven, and based on, and responsive to, local needs. However, information on context specific capacity building needs in developing countries is not readily available. The objective of this study was to establish location specific awareness, training, educational research and technology capacity building needs for climate change adaptation among smallholder farmers in Uganda. Semi-structured questionnaires were used with 465 households from five agro-ecological zones, selected based on the level of vulnerability of agricultural systems to the main climate variation and change hazards. Results reveal substantial capacity building needs in all the zones. The majority of the farmers needed capacity building for interventions on soil-water conservation practices for adapting to drought and unpredictable rainfall. For all zones, education, research, and technology were perceived as key needs. However, the needs varied among zones. These results demonstrate the importance of context specificity in adaptation efforts. The study provides agro-ecological and social system specific information for climate change adaptation planning and policy interventions for effective capacity building.
      Citation: Climate
      PubDate: 2024-01-19
      DOI: 10.3390/cli12010010
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 11: Assessment of Changes in Agroclimatic
           Resources of the Republic of Bashkortostan (Russia) under the Context of
           Global Warming

    • Authors: Rita Kamalova, Ekaterina Bogdan, Larisa Belan, Iren Tuktarova, Alexey Firstov, Ildar Vildanov, Irik Saifullin
      First page: 11
      Abstract: The process of climate warming significantly affects agroclimatic resources and agricultural production. We study the agroclimatic resources and their variability on the territory of the Republic of Bashkortostan (Russia). The Bashkortostan has a high agricultural potential and holds a leading position in the country in the production of grain crops, potatoes, milk, and honey. Currently, no detailed studies have been conducted for this area to assess the effects of global climate change on agro-climatic resources. World experience shows such research becomes strategically important for regions with powerful agricultural production. We used the sums of average daily air temperatures above 0 and 10 °C, the G.T. Selyaninov hydrothermal coefficient, and the Ped aridity (humidification) index as agroclimatic indicators. We used data of long-term meteorological observations of 30 meteorological stations for the period of 1961–2020. We revealed the long-term dynamics of the agroclimatic indicators and the spatial and temporal regularities in their distribution on the territory of Bashkortostan. There is a steady increase in the sums of average daily air temperatures above 0 and 10 °C. Against this background, aridity increases, which is especially manifested in the southern parts of the Republic of Bashkortostan. We assessed the impact of agroclimatic indicators on the main types of agricultural crops in the republic. We revealed that the greatest positive impact on the yield of oilseeds, cereals, and industrial crops is made by precipitation at the beginning (r = 0.50, r = 0.44, and r = 0.52, respectively) and in the middle of the growing season (r = 0.55, r = 0.76, and r = 0.51, respectively). Temperature and precipitation during the growing season have a complex effect on cereals. This is proven by correlations with HCS and the Ped index (r = 0.45 and r = −0.56, respectively). Aridity at the beginning of the growing season affects the yield of oilseeds and potatoes. This is confirmed by correlations with the Ped index (r = −0.49 and r = −0.52, respectively). In general, the aridity of the growing season has a significant impact on the yield of cereals (r = −0.57). Negative relationships have been found between the air temperature growing season and the yield of potatoes (r = −0.50) and cereals (r = −0.53). The results of the study were compared with data from the Copernicus Climate Change Service database. We identified climate trends under RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios. These scenarios should be taken into account when developing plans for the adaptation of agriculture in the Republic of Bashkortostan to changes in the regional climate. Maximum decrease in precipitation is established for the RCP 6.0 scenario. This can have an extremely negative impact on crop yields. This problem is especially relevant for the southern part of the Republic of Bashkortostan. The information presented in the study will allow for a more effective adaptation of the agricultural sector to current and future climate changes.
      Citation: Climate
      PubDate: 2024-01-22
      DOI: 10.3390/cli12010011
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 12: Development of Inherent Vulnerability Index
           within Jammu Municipal Limits, India

    • Authors: Simran Bharti, Adyan Ul Haq, L. T. Sasang Guite, Shruti Kanga, Fayma Mushtaq, Majid Farooq, Suraj Kumar Singh, Pankaj Kumar, Gowhar Meraj
      First page: 12
      Abstract: Evaluating inherent vulnerability, an intrinsic characteristic becomes imperative for the formulation of adaptation strategies, particularly in highly complex and vulnerable regions of Himalayas. Jammu City, situated in the north-western Himalayas within a transitional zone between the Himalayan range and the plains, is not only susceptible to intense seismic activities but also faces multiple hazards, including floods, earthquakes, avalanches, and landslides. In recent years, the region has experienced growth in population with rapid progress in infrastructure development, encompassing the construction of highways, dams, and tunnels as integral components of urban development initiatives. Therefore, this study has been conducted to assess the inherent vulnerability index (VI) in Jammu City at ward level as a function of sensitivity, adaptive capacity, and exposure, using ecological and social indicators in GIS environment. The primary objective was to identify the most vulnerable area and ascertain the corresponding municipal ward, aiming to formulate a comprehensive ranking. The 22 indicators analysed were from four major components, namely social, infrastructure, technological, and ecological. The ecological indicators like Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), and Land use/Land cover were derived from Landsat 8 OLI satellite data. The results show that the majority of the area of the city falls into the moderate (20%), high (25.49%), and very high (25.17%) vulnerability categories, respectively, clustered in north-western and south-western transects with densely populated residential areas. The results can assist policymakers in identification of components of inherent vulnerability for focused resource management and formulating adaptation strategies to address the current stressors in the region.
      Citation: Climate
      PubDate: 2024-01-22
      DOI: 10.3390/cli12010012
      Issue No: Vol. 12, No. 1 (2024)
  • Climate, Vol. 12, Pages 1: Equilibrium Climate after Spectral and
           Bolometric Irradiance Reduction in Grand Solar Minimum Simulations

    • Authors: Nazario Tartaglione, Thomas Toniazzo, Odd Helge Otterå, Yvan Orsolini
      First page: 1
      Abstract: In this study, we use the Whole Atmosphere Community Climate Model, forced by present-day atmospheric composition and coupled to a Slab Ocean Model, to simulate the state of the climate under grand solar minimum forcing scenarios. Idealized experiments prescribe time-invariant solar irradiance reductions that are either uniform (percentage-wise) across the total solar radiation spectrum (TOTC) or spectrally localized in the ultraviolet (UV) band (SCUV). We compare the equilibrium condition of these experiments with the equilibrium condition of a control simulation, forced by perpetual solar maximum conditions. In SCUV, we observe large stratospheric cooling due to ozone reduction. In both the Northern Hemisphere (NH) and the Southern Hemisphere (SH), this is accompanied by a weakening of the polar night jet during the cold season. In TOTC, dynamically induced polar stratospheric cooling is observed in the transition seasons over the NH, without any ozone deficit. The global temperature cooling values, compared with the control climate, are 0.55±0.03 K in TOTC and 0.39±0.03 K in SCUV. The reductions in total meridional heat transport outside of the subtropics are similar in the two experiments, especially in the SH. Despite substantial differences in stratospheric forcing, similarities exist between the two experiments, such as cloudiness; meridional heating transport in the SH; and strong cooling in the NH during wintertime, although this cooling affects two different regions, namely, North America in TOTC and the Euro–Asian continent in SCUV.
      Citation: Climate
      PubDate: 2023-12-19
      DOI: 10.3390/cli12010001
      Issue No: Vol. 12, No. 1 (2023)
  • Climate, Vol. 12, Pages 2: Analysis of Climate Variability and Its
           Implications on Rangelands in the Limpopo Province

    • Authors: Phumzile Maluleke, Mokhele E. Moeletsi, Mitsuru Tsubo
      First page: 2
      Abstract: In recent decades, southern Africa has experienced a shift towards hotter and drier climate conditions, affecting vital sectors like agriculture, health, water, and energy. Scientific research has shown that the combination of high temperatures and unreliable rainfall can have detrimental effects on agricultural production. Thus, this study focused on assessing climate variability, with implications on rangelands in the Limpopo Province of South Africa over 38 years. Historical climate data from 15 stations, including rainfall and minimum and maximum temperatures from 1980 to 2018, were analysed. To achieve the main objective, various statistics including mean, standard deviation, and coefficient of variation (CV) were computed for all variables across four seasons. The results highlighted significant variability in rainfall, with Musina (71.2%) and Tshiombo (88.3%) stations displaying the highest variability during the September-to-April season. Both minimum and maximum temperatures displayed low variability. The Mann–Kendall test revealed both increasing and decreasing trends in minimum temperatures and rainfall across different stations. Notably, there was a significant increase in maximum temperatures. This study provides valuable climate information for decision makers, aiding in the planning and management of agricultural activities, particularly in understanding how climate variations affect forage availability in rangelands.
      Citation: Climate
      PubDate: 2023-12-24
      DOI: 10.3390/cli12010002
      Issue No: Vol. 12, No. 1 (2023)
  • Climate, Vol. 12, Pages 3: Climate Risks Resilience Development: A
           Bibliometric Analysis of Climate-Related Early Warning Systems in Southern

    • Authors: Israel Edem Agbehadji, Stefanie Schütte, Muthoni Masinde, Joel Botai, Tafadzwanashe Mabhaudhi
      First page: 3
      Abstract: Early warning systems (EWS) facilitate societies’ preparedness and effective response capabilities to climate risks. Climate risks embody hazards, exposure, and vulnerability associated with a particular geographical area. Building an effective EWS requires consideration of the factors above to help people with coping mechanisms. The objective of this paper is to propose an approach that can enhance EWSs and ensure an effective climate risk resilience development. The paper focuses on the Southern African Development Community (SADC) region and highlights the issues with EWS, identifying weaknesses and characteristics of EWS to help in climate risk adaptation strategies. The SADC region was chosen as the context because it is a climate variability and change hotspot with many vulnerable populations residing in rural communities. Trending themes on building climate risk resilience were uncovered through scientific mapping and network analysis of published articles from 2008 to 2022. This paper contributes to on-going research on building climate risks resilience through early warning systems to identify hidden trends and emerging technologies from articles in order to enhance the operationalization and design of EWS. This review provides insight into technological interventions for assessing climate risks to build preparedness and resilience. From the review analysis, it is determined that there exists a plethora of evidence to support the argument that involving communities in the co-designing of EWS would improve risk knowledge, anticipation, and preparedness. Additionally, Fourth Industrial Revolution (4IR) technologies provide effective tools to address existing EWS’ weaknesses, such as lack of real-time data collection and automation. However, 4IR technology is still at a nascent stage in EWS applications in Africa. Furthermore, policy across societies, institutions, and technology industries ought to be coordinated and integrated to develop a strategy toward implementing climate resilient-based EWS to facilitate the operations of disaster risk managers. The Social, Institutional, and Technology model can potentially increase communities’ resilience; therefore, it is recommended to develop EWS.
      Citation: Climate
      PubDate: 2023-12-26
      DOI: 10.3390/cli12010003
      Issue No: Vol. 12, No. 1 (2023)
  • Climate, Vol. 12, Pages 4: Characterisation of Morphological Patterns for
           Land Surface Temperature Distribution in Urban Environments: An Approach
           to Identify Priority Areas

    • Authors: Karina Angélica García-Pardo, David Moreno-Rangel, Samuel Domínguez-Amarillo, José Roberto García-Chávez
      First page: 4
      Abstract: The validated influence of urban biophysical structure on environmental processes within urban areas has heightened the emphasis on studies examining morphological patterns to determine precise locations and underlying causes of urban climate conditions. The present study aims to characterise morphological patterns describing the distribution of Land Surface Temperature (LST) based on a prior classification of biophysical variables, including urban density (building intensity and average height), surface characteristics, shortwave solar radiation (broadband albedo), and seasonal variations in vegetation cover (high, medium, and low levels), retrieved from multisource datasets. To describe the distribution of LST, the variables were calculated, classified, and subsequently, analysed individually and collectively concerning winter and summer LST values applied in an urban neighbourhood in Madrid, Spain. The results from the analytical approaches (observation, correlations, and multiple regressions) were compared to define the morphological patterns. The selection of areas resulting from the morphological patterns with the most unfavourable LST values showed agreement of up to 89% in summer and up to 70% for winter, demonstrating the feasibility of the methods applied to identify priority areas for intervention by season. Notably, low and high vegetation levels emerged as pivotal biophysical characteristics influencing LST distribution compared to the other characteristics, emphasising the significance of integrating detailed seasonal vegetation variations in urban analyses.
      Citation: Climate
      PubDate: 2023-12-28
      DOI: 10.3390/cli12010004
      Issue No: Vol. 12, No. 1 (2023)
  • Climate, Vol. 12, Pages 5: Assessment of Climate Risks, Vulnerability of
           Urban Health Systems, and Individual Adaptation Strategies in the City of
           N’Djaména (Chad)

    • Authors: Ndonaye Allarané, Assouhan Jonas Atchadé, Vidjinnagni Vinasse Ametooyona Azagoun, Adanvo Isaac Houngnigbe, Romain Gouataine Seingue, Tob-Ro N’Dilbé, Follygan Hetcheli
      First page: 5
      Abstract: Climate variability and change are already having a negative impact on the health of tens of millions of Africans through exposure to sub-optimal temperatures and extreme weather conditions as well as increasing the range and transmission of infectious diseases. This study aims to identify climate risks and the vulnerability of health systems as well as individual coping strategies in the city of N’Djaména. To achieve this, we adopted a methodology combining both quantitative and qualitative approaches. Meteorological data on wind, temperature, and rainfall were collected at daily and monthly intervals from the National Meteorological Agency in N’Djaména. Qualitative data were collected via focus group discussions with targets of the city’s health system and quantitative data were collected from the population on the basis of oriented questionnaires. The results show that rising temperatures with heat waves, regular flooding, and strong winds are the major climate risks identified. These have numerous impacts and effects on the city’s health system due to the following vulnerability factors most recognized by city dwellers: insufficient medical equipment in health facilities (IEME), the fragile nature of people’s physiological state in the face of climatic risks (CFEP), and the failure of city sanitation strategies and policies (DSPA). This study proposes a set of recommendations for transformational adaptation of the healthcare sector, which remains vulnerable to climate risks.
      Citation: Climate
      PubDate: 2023-12-30
      DOI: 10.3390/cli12010005
      Issue No: Vol. 12, No. 1 (2023)
  • Climate, Vol. 11, Pages 175: Bamboo as a Nature-Based Solution (NbS) for
           Climate Change Mitigation: Biomass, Products, and Carbon Credits

    • Authors: Chunyu Pan, Guomo Zhou, Anil Kumar Shrestha, Jialu Chen, Robert Kozak, Nuyun Li, Jinliang Li, Yeyun He, Chunguang Sheng, Guangyu Wang
      First page: 175
      Abstract: Bamboo, a rapidly growing woody grass prevalent in pan-tropical zones, holds promising potential as a nature-based solution (NbS) for climate change mitigation. In this systematic review of 91 research articles, we critically assess the scope and constraints of bamboo’s role in mitigating climate change across three dimensions: as a carbon sink in biomass form, as carbon storage in bamboo products, and as a contributor to carbon project credits. Our analysis reveals that existing studies disproportionately focus on 36 limited species, such as Phyllostachys pubescens and Bambusa vulgaris, with geographic concentration in Asia (91%) and limited studies from Africa (7%) and South America (1%). While many studies emphasize the carbon-saving benefits of bamboo products compared with traditional goods, there is a noticeable gap in comprehensive evaluations of carbon pools from individual bamboo forests encompassing all product varieties. While bamboo forests offer significant carbon trading potential, their global role is restricted by the absence of internationally accepted methodologies and the presence of debates about classifying bamboo as a tree species. This extensive review highlights the multifaceted value of bamboo in climate change mitigation, thereby highlighting its significance as a critical component for informed policymaking and the development of sustainable practices in future climate strategies worldwide.
      Citation: Climate
      PubDate: 2023-08-24
      DOI: 10.3390/cli11090175
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 176: Projections of Changes in Atmospheric
           Conditions Leading to Storm Surges along the Coast of Santos, Brazil

    • Authors: Marcely Sondermann, Sin Chan Chou, Priscila Tavares, André Lyra, José A. Marengo, Celia Regina de Gouveia Souza
      First page: 176
      Abstract: This study aims to assess the changes in the atmospheric conditions favorable to storm surges over the Santos Coast in Southeast Brazil. Storm surges can favor high sea level rises and coastal erosion, affecting people and strategic structures in coastal areas. The assessment of the atmospheric conditions was based on the downscaling of climate simulations of the Brazilian Earth System Model by the Eta regional climate model at higher spatial resolution. The detection scheme used by the model was able to reproduce the three observed atmospheric patterns favorable to storm surges found by recent studies: Pattern 1 is characterized by a cyclone on the synoptic scale over the ocean; Pattern 2 presents an intense wind fetch from the southeast; Pattern 3 is characterized by winds parallel to the coast. The simulations underestimated the number of cases in Patterns 1 and 2. However, it overestimated the number of days in Pattern 3. The model presented more intense winds in the three patterns. The storm surges characterized by Pattern 1 will become more intense. However, it will be equal to or less frequent. In Pattern 2, the number of events will decrease. Nevertheless, these episodes will be associated with more precipitation along the coastline. Pattern 3 will have a similar number of storm surges.
      Citation: Climate
      PubDate: 2023-08-26
      DOI: 10.3390/cli11090176
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 177: Uganda’s Hydropower System Resilience
           to Extreme Climate Variability

    • Authors: Francis Mujjuni, Thomas Betts, Richard Blanchard
      First page: 177
      Abstract: This study was motivated by the high reliance on hydropower plants (HPPs) developed and planned along the river Nile and the fact that drought events are the most imminent and drastic threats to Uganda’s power production. The study aimed to assess HPPs’ resilience and the effectiveness of selected adaptation measures. The climate, land, energy, and water system (CLEWs) framework was employed to assess resilience amidst competing water demands and stringent environmental flow requirements. Under extreme dry conditions, power generation could plummet by 91% over the next 40 years, which translates into an annual per capita consumption of 19 kWh, barely sufficient to sustain a decent socioeconomic livelihood. During arid conditions, climate models predicted an increase in streamflow with increasing radiative forcing. Restricting the ecological flow to 150 m3/s could improve generation by 207%. In addition, if planned power plants were to be built 5 years ahead of schedule, the normalized mean annual plant production could increase by 23%. In contrast, increasing reservoir volumes for planned power plants will have no significant impact on generation. The path to HPP resilience could entail a combination of diversifying the generation mix, installing generators with varying capacities, and incorporating adjustable orifices on reservoirs.
      Citation: Climate
      PubDate: 2023-08-26
      DOI: 10.3390/cli11090177
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 178: Instrumental and Observational Problems of
           the Earliest Temperature Records in Italy: A Methodology for Data Recovery
           and Correction

    • Authors: Dario Camuffo, Antonio della Valle, Francesca Becherini
      First page: 178
      Abstract: A distinction is made between data rescue (i.e., copying, digitizing, and archiving) and data recovery that implies deciphering, interpreting, and transforming early instrumental readings and their metadata to obtain high-quality datasets in modern units. This requires a multidisciplinary approach that includes: palaeography and knowledge of Latin and other languages to read the handwritten logs and additional documents; history of science to interpret the original text, data, and metadata within the cultural frame of the 17th, 18th, and early 19th centuries; physics and technology to recognize bias of early instruments or calibrations, or to correct for observational bias; and astronomy to calculate and transform the original time in canonical hours that started from twilight. The liquid-in-glass thermometer was invented in 1641 and the earliest temperature records started in 1654. Since then, different types of thermometers have been invented, based on the thermal expansion of air or selected thermometric liquids with deviation from linearity. Reference points, thermometric scales, and calibration methodologies were not comparable, and not always adequately described. Thermometers had various locations and exposures, e.g., indoor, outdoor, on windows, gardens or roofs, facing different directions. Readings were made only one or a few times a day, not necessarily respecting a precise time schedule: this bias is analysed for the most popular combinations of reading times. The time was based on sundials and local Sun, but the hours were counted starting from twilight. In 1789–1790, Italy changed system and all cities counted hours from their lower culmination (i.e., local midnight), so that every city had its local time; in 1866, all the Italian cities followed the local time of Rome; in 1893, the whole of Italy adopted the present-day system, based on the Coordinated Universal Time and the time zones. In 1873, when the International Meteorological Committee (IMC) was founded, later transformed into the World Meteorological Organization (WMO), a standardization of instruments and observational protocols was established, and all data became fully comparable. In dealing with the early instrumental period, from 1654 to 1873, the comparison, correction, and homogenization of records is quite difficult, mainly because of the scarcity or even absence of metadata. This paper deals with this confused situation, discussing the main problems, but also the methodologies to recognize missing metadata, distinguish indoor from outdoor readings, correct and transform early datasets in unknown or arbitrary units into modern units, and, finally, in which cases it is possible to reach the quality level required by the WMO. The aim is to explain the methodology needed to recover early instrumental records, i.e., the operations that should be performed to decipher, interpret, correct, and transform the original raw data into a high-quality dataset of temperature, usable for climate studies.
      Citation: Climate
      PubDate: 2023-08-27
      DOI: 10.3390/cli11090178
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 179: The Detection and Attribution of Northern
           Hemisphere Land Surface Warming (1850–2018) in Terms of Human and
           Natural Factors: Challenges of Inadequate Data

    • Authors: Willie Soon, Ronan Connolly, Michael Connolly, Syun-Ichi Akasofu, Sallie Baliunas, Johan Berglund, Antonio Bianchini, William M. Briggs, C. J. Butler, Rodolfo Gustavo Cionco, Marcel Crok, Ana G. Elias, Valery M. Fedorov, François Gervais, Hermann Harde, Gregory W. Henry, Douglas V. Hoyt, Ole Humlum, David R. Legates, Anthony R. Lupo, Shigenori Maruyama, Patrick Moore, Maxim Ogurtsov, Coilín ÓhAiseadha, Marcos J. Oliveira, Seok-Soon Park, Shican Qiu, Gerré Quinn, Nicola Scafetta, Jan-Erik Solheim, Jim Steele, László Szarka, Hiroshi L. Tanaka, Mitchell K. Taylor, Fritz Vahrenholt, Víctor M. Velasco Herrera, Weijia Zhang
      First page: 179
      Abstract: A statistical analysis was applied to Northern Hemisphere land surface temperatures (1850–2018) to try to identify the main drivers of the observed warming since the mid-19th century. Two different temperature estimates were considered—a rural and urban blend (that matches almost exactly with most current estimates) and a rural-only estimate. The rural and urban blend indicates a long-term warming of 0.89 °C/century since 1850, while the rural-only indicates 0.55 °C/century. This contradicts a common assumption that current thermometer-based global temperature indices are relatively unaffected by urban warming biases. Three main climatic drivers were considered, following the approaches adopted by the Intergovernmental Panel on Climate Change (IPCC)’s recent 6th Assessment Report (AR6): two natural forcings (solar and volcanic) and the composite “all anthropogenic forcings combined” time series recommended by IPCC AR6. The volcanic time series was that recommended by IPCC AR6. Two alternative solar forcing datasets were contrasted. One was the Total Solar Irradiance (TSI) time series that was recommended by IPCC AR6. The other TSI time series was apparently overlooked by IPCC AR6. It was found that altering the temperature estimate and/or the choice of solar forcing dataset resulted in very different conclusions as to the primary drivers of the observed warming. Our analysis focused on the Northern Hemispheric land component of global surface temperatures since this is the most data-rich component. It reveals that important challenges remain for the broader detection and attribution problem of global warming: (1) urbanization bias remains a substantial problem for the global land temperature data; (2) it is still unclear which (if any) of the many TSI time series in the literature are accurate estimates of past TSI; (3) the scientific community is not yet in a position to confidently establish whether the warming since 1850 is mostly human-caused, mostly natural, or some combination. Suggestions for how these scientific challenges might be resolved are offered.
      Citation: Climate
      PubDate: 2023-08-28
      DOI: 10.3390/cli11090179
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 180: Evaluation of Gridded Meteorological Data for
           Crop Sensitivity Assessment to Temperature Changes: An Application with
           CERES-Wheat in the Mediterranean Basin

    • Authors: Konstantina S. Liakopoulou, Theodoros Mavromatis
      First page: 180
      Abstract: In areas with a limited or non-existent network of observing stations, it is critical to assess the applicability of gridded datasets. This study examined the agreement of Agri4Cast and E-OBS at two spatial resolutions (10 km (EOBS-0.1) and 25 km (EOBS-0.25)) in 13 Mediterranean stations nearby to wheat crops and how this agreement may influence simulated potential development and production with the crop simulation model (CSM) CERES-Wheat in historical and near-future (2021–2040) (NF) periods. A wide range of sensitivity tests for maximum and minimum air temperatures and impact response surfaces were used for the future projections. EOBS-0.1 showed the lowest discrepancies over observations. It underestimated statistical measures of temperature and precipitation raw data and their corresponding extreme indices and overestimated solar radiation. These discrepancies caused small delays (5–6 days, on average) in crop development and overestimations (8%) in grain production in the reference period. In the NF, the use of EOBS-0.1 reduced by a few (2–3) days the biases in crop development, while yield responses differed among stations. This research demonstrated the ability of EOBS-0.1 for agricultural applications that depend on potential wheat development and productivity in historical and future climate conditions expected in the Mediterranean basin.
      Citation: Climate
      PubDate: 2023-08-29
      DOI: 10.3390/cli11090180
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 181: Sensitivity Analysis of Heat Stress Indices

    • Authors: Ahmed Rachid, Aiman Mazhar Qureshi
      First page: 181
      Abstract: More than 40 heat indices are being used across the world to quantify outdoor thermal comfort. The selection of an Outdoor Heat Stress Index (OHSI) depends on several parameters, including clothing, age, awareness, local environment, food consumption, human activities, and resources. This study investigates various indicators of heat stress, including (i) OHSIs officially used to quantify heat stress worldwide, (ii) the estimation methods of these indices, and (iii) the sensitivity analysis of indices, namely, Corrected Effective Temperature (CET), Heat Index (HI), Wet Bulb Globe Temperature (WBGT), Universal Thermal Climate Index (UTCI), Discomfort Index (DI), Summer Simmer Index (SSI), and Predicted Mean Vote (PMV). The results indicate the degree of sensitivity of indices, with the HI being the most sensitive for estimating heat stress. Additionally, the WBGT, HI, and CET are recommended indices that can be directly measured using sensors instead of relying on calculated indices that are based on estimation techniques and some ideal physical assumptions.
      Citation: Climate
      PubDate: 2023-08-30
      DOI: 10.3390/cli11090181
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 182: Trees Diversity and Species with High
           Ecological Importance for a Resilient Urban Area: Evidence from Cotonou
           City (West Africa)

    • Authors: Assouhan Jonas Atchadé, Madjouma Kanda, Fousseni Folega, Hounnankpon Yédomonhan, Marra Dourma, Kperkouma Wala, Koffi Akpagana
      First page: 182
      Abstract: Rapid urbanization and climate change effects may cause dramatic changes in ecosystem functions in cities, thereby inevitably affecting the growth performance of old trees. Few studies have explored species diversity and spatial differentiation in Benin urban areas. This study aims to explore this dimension of urban ecology in order to build resilience to climate change in the city of Cotonou. Its objective was to determine the predominant level of tree diversity in the city’s land use units. The urban green frame was subdivided into six land use units, namely, establishments, residences, green spaces, commercial areas, administrative areas, and roads. The forest inventories were carried out in 149 plots with surfaces evaluated at 2500 m2 each. The IVI, an index that highlights the relative density, relative dominance, and relative frequency of species, has been used to characterize the place occupied by each species in relation to all species in urban ecosystems. This shows ecological importance through the diversity and quality of ecosystems, communities, and species. A total of 62 tree species in 55 genera and 27 families were recorded. The results show that the flora of the city of Cotonou is characterized by a strong preponderance of exotic species with some differences in species presence. The most abundant species with high ecological importance (IVI) in the different types of land use of the city are Terminalia catappa (IVI = 121.47%), Terminalia mantaly (IVI = 90.50%), Mangifera indica (IVI = 64.06%), and Khaya senegalensis (IVI = 151.16%). As the use of ecosystem services is recommended to tackle urban climate hazards, this study shows that direct development of this urban vegetation could improve the resilience of urban life to climate hazards through the provision of urban ecosystem services, potential ecological infrastructure foundations, and urban nature-based solutions.
      Citation: Climate
      PubDate: 2023-08-30
      DOI: 10.3390/cli11090182
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 183: Climate Change Perception and Vulnerability
           Assessment of the Farming Communities in the Southwest Parts of Ethiopia

    • Authors: Dessalegn Obsi Gemeda, Diriba Korecha, Weyessa Garedew
      First page: 183
      Abstract: This study assesses the perceptions and vulnerability of the farming communities to climate change in the southwestern parts of Ethiopia. Climate change vulnerability assessment is a prerequisite to designing climate change adaptation strategies. A multistage cluster sampling technique was used to select four of the six zones from the southwestern parts of Oromia. Close-ended and open-ended questionnaires were used to assess household perceptions of climate change and the degree of vulnerability to climate change by using five household capitals: natural, social, financial, physical, and human capital. Data were collected from 442 households in 4 districts: Jimma Arjo, Bako Tibe, Chewaka, and Sekoru. The vulnerability of the farming communities was assessed using the households’ livelihood vulnerability index. A total of forty indicators from five capitals were applied to calculate household livelihood vulnerability to climate change. Household perceptions of climate change had a statistically significant relationship with changes in rainfall pattern (75.6%, p < 0.001), temperature pattern (69.7%, p < 0.001), drought (41.6%, p = 0.016), flood (44.1%, p = 0.000), and occurrence of early (53.2%, p < 0.001) and late rain (55.9%, p < 0.001). The results show that households in the Sekoru district were the most vulnerable (0.61), while households in the Jimma Arjo district were less vulnerable (0.47) to the effect of climate change. Household vulnerability to climate change is mainly related to the occurrence of drought, lack of much-needed infrastructure facilities, and weak institutional support. Links with financial organizations are also lacking in the household. The findings of this study will help policymakers to address the impact of climate change. To support disaster risk management on the one hand and increase the resilience of vulnerable societies to climate change on the other, we recommend a detailed assessment of the remaining districts of the region.
      Citation: Climate
      PubDate: 2023-09-05
      DOI: 10.3390/cli11090183
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 184: Modeling Approaches for Residential Energy
           Consumption: A Literature Review

    • Authors: Thomas Nacht, Robert Pratter, Johanna Ganglbauer, Amanda Schibline, Armando Aguayo, Panagiotis Fragkos, Eleftheria Zisarou
      First page: 184
      Abstract: The interest in sustainability and energy efficiency is constantly increasing, and the noticeable effects of climate change and rising energy prices are fueling this development. The residential sector is one of the most energy-intensive sectors and plays an important role in shaping future energy consumption. In this context, modeling has been extensively employed to identify relative key drivers, and to evaluate the impact of different strategies to reduce energy consumption and emissions. This article presents a detailed literature review relative to modeling approaches and techniques in residential energy use, including case studies to assess and predict the energy consumption patterns of the sector. The purpose of this article is not only to review the research to date in this field, but to also identify the possible challenges and opportunities. Mobility, electrical devices, cooling and heating systems, and energy storage and energy production technologies will be the subject of the presented research. Furthermore, the energy upgrades of buildings, their energy classification, as well as the energy labels of the electric appliances will be discussed. Previous research provided valuable insights into the application of modeling techniques to address the complexities of residential energy consumption. This paper offers a thorough resource for researchers, stakeholders, and other parties interested in promoting sustainable energy practices. The information gathered can contribute to the development of effective strategies for reducing energy use, facilitating energy-efficient renovations, and helping to promote a greener and more sustainable future in the residential domain.
      Citation: Climate
      PubDate: 2023-09-07
      DOI: 10.3390/cli11090184
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 185: Thermodynamic Conditions during August 2022
           in Catalonia: The Monthly Record of Hail Days, Hail Size and the
           Differences in the Climatic Values

    • Authors: Tomeu Rigo
      First page: 185
      Abstract: The hailstorm of 30 August 2022 in the NE of Catalonia (NE of the Iberian Peninsula) produced the largest hail size, with diameters exceeding 10 cm. Furthermore, hail occurrence exceeded 2 cm in fourteen days and 4 cm in seven days during August 2022. The size and the days number constituted new records in Catalonia for at least the last 30 years. The analysis has compared the thermodynamic values derived from the sounding of Barcelona with the climatic data for 1998–2022 (25 years of data). This fact has allowed the selection and evaluation of different thermodynamic parameters’ behaviour during hail days in Catalonia. In this research, the precipitable water mass provided the best results as a hail forecaster. Second, the study has evaluated if the different parameters have a significant trend during the study period. The answer is yes in all cases, but some parameters presented a stepped rise while others increased smoothly. Finally, the research has analysed if the parameter values during August 2022 were extraordinary compared with the rest of the period. In this case, the thermodynamic parameters nature was well correlated with the hail size and occurrence maximums of August 2022.
      Citation: Climate
      PubDate: 2023-09-08
      DOI: 10.3390/cli11090185
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 186: Statistical Downscaling of Precipitation in
           the South and Southeast of Mexico

    • Authors: Mercedes Andrade-Velázquez, Martín José Montero-Martínez
      First page: 186
      Abstract: The advancements in global climate modeling achieved within the CMIP6 framework have led to notable enhancements in model performance, particularly with regard to spatial resolution. However, the persistent requirement for refined techniques, such as dynamically or statistically downscaled methods, remains evident, particularly in the context of precipitation variability. This study centered on the systematic application of a bias-correction technique (quantile mapping) to four designated CMIP6 models: CNRM-ESM2-6A, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0. The selection of these models was informed by a methodical approach grounded in previous research conducted within the southern–southeastern region of Mexico. Diverse performance evaluation metrics were employed, including root-mean-square difference (rmsd), normalized standard deviation (NSD), bias, and Pearson’s correlation (illustrated by Taylor diagrams). The study area was divided into two distinct domains: southern Mexico and the southeast region covering Tabasco and Chiapas, and the Yucatan Peninsula. The findings underscored the substantial improvement in model performance achieved through bias correction across the entire study area. The outcomes of rmsd and NSD not only exhibited variations among different climate models but also manifested sensitivity to the specific geographical region under examination. In the southern region, CNRM-ESM2-1 emerged as the most adept model following bias correction. In the southeastern domain, including only Tabasco and Chiapas, the optimal model was again CNRM-ESM2-1 after bias-correction. However, for the Yucatan Peninsula, the IPSL-CM6A-LR model yielded the most favorable results. This study emphasizes the significance of tailored bias-correction techniques in refining the performance of climate models and highlights the spatially nuanced responses of different models within the study area’s distinct geographical regions.
      Citation: Climate
      PubDate: 2023-09-08
      DOI: 10.3390/cli11090186
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 187: Unveiling Nature’s Resilience:
           Exploring Vegetation Dynamics during the COVID-19 Era in Jharkhand, India,
           with the Google Earth Engine

    • Authors: Tauseef Ahmad, Saurabh Kumar Gupta, Suraj Kumar Singh, Gowhar Meraj, Pankaj Kumar, Shruti Kanga
      First page: 187
      Abstract: The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive to human society, inadvertently led to environmental rejuvenation, particularly noticeable in decreased air pollution and improved vegetation health. This study investigates the lockdown’s impact on vegetation health in Jharkhand, India, employing the Google Earth Engine for cloud-based data analysis. MODIS-NDVI data were analyzed using spatio-temporal NDVI analyses and time-series models. These analyses revealed a notable increase in maximum vegetation greenery of 19% from April 2019 to 2020, with subsequent increases of 13% and 3% observed in March and May of the same year, respectively. A longer-term analysis from 2000 to 2020 displayed an overall 16.7% rise in vegetation greenness. While the maximum value remained relatively constant, it demonstrated a slight increment during the dry season. The Landsat data Mann–Kendall trend test reinforced these findings, displaying a significant shift from a negative NDVI trend (1984–2019) to a positive 17.7% trend (1984–2021) in Jharkhand’s north-west region. The precipitation (using NASA power and Merra2 data) and NDVI correlation were also studied during the pre- and lockdown periods. Maximum precipitation (350–400 mm) was observed in June, while July typically experienced around 300 mm precipitation, covering nearly 85% of Jharkhand. Interestingly, August 2020 saw up to 550 mm precipitation, primarily in Jharkhand’s southern region, compared to 400 mm in the same month in 2019. Peak changes in NDVI value during this period ranged between 0.6–0.76 and 0.76–1, observed throughout the state. Although the decrease in air pollution led to improved vegetation health, these benefits began to diminish post-lockdown. This observation underscores the need for immediate attention and intervention from scientists and researchers. Understanding lockdown-induced environmental changes and their impact on vegetation health can facilitate the development of proactive environmental management strategies, paving the way towards a sustainable and resilient future.
      Citation: Climate
      PubDate: 2023-09-08
      DOI: 10.3390/cli11090187
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 188: A Systematic Review of Existing Early Warning
           Systems’ Challenges and Opportunities in Cloud Computing Early
           Warning Systems

    • Authors: Israel Edem Agbehadji, Tafadzwanashe Mabhaudhi, Joel Botai, Muthoni Masinde
      First page: 188
      Abstract: This paper assessed existing EWS challenges and opportunities in cloud computing through the PSALSAR framework for systematic literature review and meta-analysis. The research used extant literature from Scopus and Web of Science, where a total of 2516 pieces of literature were extracted between 2004 and 2022, and through inclusion and exclusion criteria, the total was reduced to 98 for this systematic review. This review highlights the challenges and opportunities in transferring in-house early warning systems (that is, non-cloud) to the cloud computing infrastructure. The different techniques or approaches used in different kinds of EWSs to facilitate climate-related data processing and analytics were also highlighted. The findings indicate that very few EWSs (for example, flood, drought, etc.) utilize the cloud computing infrastructure. Many EWSs are not leveraging the capability of cloud computing but instead using online application systems that are not cloud-based. Secondly, a few EWSs have harnessed the computational techniques and tools available on a single platform for data processing. Thirdly, EWSs combine more than one fundamental tenet of the EWS framework to provide a holistic warning system. The findings suggest that reaching a global usage of climate-related EWS may be challenged if EWSs are not redesigned to fit the cloud computing service infrastructure.
      Citation: Climate
      PubDate: 2023-09-08
      DOI: 10.3390/cli11090188
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 189: Farmers Feel the Climate Change: Variety
           Choice as an Adaptation Strategy of European Potato Farmers

    • Authors: Philipp von Gehren, Svenja Bomers, Tanja Tripolt, Josef Söllinger, Noémie Prat, Berta Redondo, Romans Vorss, Markus Teige, Anita Kamptner, Alexandra Ribarits
      First page: 189
      Abstract: Effects associated with a changing climate could severely threaten potato production in Europe. Hence, farmers need to take up adaptation measures to safeguard agricultural production. Collecting data from 553 farmers from 22 different European countries, our survey evaluates European potato farmers’ perceptions regarding the influence of climate change on local potato production, and their willingness to implement adaptation strategies. An overwhelming majority of survey respondents had already experienced the effects of climatic changes on their potato production. Specifically, drought and heat were identified as the most significant threats. The planting of an adapted variety was the preferred adaptation strategy, while farmers were also willing to take up changes in agricultural management practices. Survey respondents predominantly considered yield stability as the most important characteristic of an adapted variety, closely followed by heat tolerance, disease resistance, drought tolerance, and yield potential. When choosing a variety, the personal experience of the survey respondents as well as the experience of their peers were identified as the most important sources of information. Our survey gives valuable insights into the challenges European potato farmers are facing in times of climate change. Supplying farmers with better-adapted varieties would be a well-targeted and well-accepted measure to advance climate change adaptation.
      Citation: Climate
      PubDate: 2023-09-09
      DOI: 10.3390/cli11090189
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 190: How Does Climate Change Worry Influence the
           Relationship between Climate Change Anxiety and Eco-Paralysis' A
           Moderation Study

    • Authors: Matteo Innocenti, Alessio Perilli, Gabriele Santarelli, Niccolò Carluccio, Doris Zjalic, Daniela Acquadro Maran, Lorenzo Ciabini, Chiara Cadeddu
      First page: 190
      Abstract: Climate change (CC) has a significant impact on human health, resulting in both physical and mental illnesses. Eco-anxiety—the excessive and pervasive fear about the consequences of CC—is the most studied psychoterratic state. This study presents the validation of Italian versions of Hogg’s Eco-Anxiety Scale (HEAS) and the Eco-Paralysis Scale. It also investigates the effects of worry on eco-anxiety and eco-paralysis. The study was conducted on 150 Italian individuals who responded to the two scales and to other questionnaires to make comparisons with the two above. Internal consistency and factorial structure were assessed through Cronbach’s alpha, Confirmatory Factor Analysis and Exploratory Factor Analysis. A median regression was used to assess the association between the EPS and the HEAS and Climate Change Worry Scale (CCWS) and their interaction. HEAS and EPS showed good psychometric properties: HEAS resulted in good internal consistency (Cronbach’s α = 0.986), and the Eco-Paralysis scale had good test-retest reliability (r = 0.988). In both cases, a one-factor structure was suggested to be retained. The interaction terms between HEAS and CCWS (β = −0.02; 95% CI: −0.03, −0.01; p < 0.001) and between HEAS and education (β = −0.05; 95% CI: −0.08, −0.02; p < 0.001) were significant. Therefore, the feeling of worry seems to act as a moderator between climate change anxiety and eco-paralysis since it may appear to influence individuals and their ability to transform anxiety into action. Education plays a role in reducing the risk of Eco-Paralysis in subjects affected by climate change anxiety. Thus, data suggest that working on reinforcing a more cognitive concern might result in more problem-solving-focused strategies to face climate change anxiety and eco-paralysis.
      Citation: Climate
      PubDate: 2023-09-13
      DOI: 10.3390/cli11090190
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 191: Analysis of the Composite Risk Grade for
           Multi Extreme Climate Events in China in Recent 60 Years

    • Authors: Cunjie Zhang, Chan Xiao, Shuai Li, Yuyu Ren, Siqi Zhang, Xiuhua Cai, Zhujie Sangbu
      First page: 191
      Abstract: Much attention has been given to the change rule of a single extreme event, and there are few reports on comprehensive characteristics of multiple extreme events in a certain region. Based on the analyzes of annual frequency of extreme high temperature, extreme low temperature, extreme drought, extreme precipitation, and extreme typhoon events in China from 1961 to 2020, a multi extreme events composite risk grade index (MXCI) was constructed and applied to the comprehensive characteristics analyzes of multiple extreme events in China. The results show that the high value areas of MXCI were mainly located in southeast China and southwest China. Over the past 60 years, the MXCI has shown a decreasing trend in western China and most of southeastern China, and an increasing trend in the middle zone from southwest China to northeast China. Through comparative analysis, MXCI can objectively reflect the comprehensive characteristics of multiple extreme climate events in a region, which is helpful to understand regional extreme climate characteristics and effectively cope with extreme climate risks.
      Citation: Climate
      PubDate: 2023-09-14
      DOI: 10.3390/cli11090191
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 192: Specifying the Gap between Nations’
           Outward-Looking and Domestic Climate Policies: A Call for Measures of
           Domestic Climate Policy Stringency

    • Authors: Todd A. Eisenstadt, Jennifer Lopez
      First page: 192
      Abstract: As nations fail to meet their climate emission mitigation goals, the ambition gap is widening between international climate policy (enacted by the United Nations) and domestic climate policy (what nations propose and enact). A widely held but little verified conventional wisdom exists that nations over-promise internationally and under-deliver domestically. While little data exist to directly test this hypothesis, we documented this gap by constructing heuristic indexes of domestic and international climate policy performance, showing that nations tend to “lead with the international”. We found that nations’ domestic policies are not significant in explaining emissions, although their international policies are significant. We concluded that beyond identifying this gap, analysts must devise metrics to assess domestic climate policy across a range of issue areas, as domestic policies are the foundation of any global effort to manage climate change.
      Citation: Climate
      PubDate: 2023-09-14
      DOI: 10.3390/cli11090192
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 193: Early Meteorological Observations in Almada
           (Portugal) for the Period 1788–1813 by Medical Doctors

    • Authors: Nieves Bravo-Paredes, María Cruz Gallego, Ricardo M. Trigo, José Manuel Vaquero
      First page: 193
      Abstract: Early meteorological observations have been found for the period 1788–1813 in a collection of historical documents entitled “Medical and meteorological observation books” (Livros de observações médicas e meteorológicas) that is preserved nowadays in the Municipal Historical Archive of Almada. Almada is a Portuguese city located on the southern bank of the Tagus River, near the mouth of the river, in front of the capital city of Lisbon, which is located on the northern bank. In this work, more than 5000 meteorological readings for the period 1788–1813 have been recovered and analyzed. Daily values have been preserved for the period 1788–1789. However, only monthly values have stood the test of time for the period 1792–1813. The meteorological variables recovered are temperature, pressure, wind direction and the state of the sky. A quality control was carried out to find possible errors, either in the original data or in the digitization process. Unfortunately, there is no information in the metadata about the instruments or the observational methodology. Pressure and temperature data from modern and reanalysis datasets were used as references to study the agreement between these datasets and the Almada dataset. Daily pressure and temperature values from the Almada dataset were used to study, in particular, the meteorological conditions of the winter of 1788/1789 in Almada because this season was one of the coldest in the last 300 years in Central Europe. The complete dataset of early meteorological observations in Almada is freely available to the scientific community.
      Citation: Climate
      PubDate: 2023-09-15
      DOI: 10.3390/cli11090193
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 194: Microeconomics of Nitrogen Fertilization in
           Boreal Carbon Forestry

    • Authors: Petri P. Kärenlampi
      First page: 194
      Abstract: The nitrogen fertilization of boreal forests is investigated in terms of microeconomics as a tool for carbon sequestration. The effects of nitrogen fertilization’s timing on the return rate on capital and the expected value of the timber stock are investigated within a set of semi-fertile, spruce-dominated boreal stands using an inventory-based growth model. Early fertilization tends to shorten rotations, reducing timber stock and carbon storage. The same applies to fertilization after the second thinning. Fertilization applied ten years before stand maturity is profitable and increases the timber stock, but the latter effect is small. The fertilization of mature stands, extending any rotation by ten years, effectively increases the carbon stock. Profitability varies but is increased by fertilization instead of merely extending the rotation.
      Citation: Climate
      PubDate: 2023-09-18
      DOI: 10.3390/cli11090194
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 195: Survey on Fungi in Antarctica and High Arctic
           Regions, and Their Impact on Climate Change

    • Authors: Masaharu Tsuji
      First page: 195
      Abstract: The Antarctica and High Arctic regions are extreme environments, with average maximum temperatures below 0 °C for most days of the year. Interestingly, fungi inhabit these regions. This review describes the history of fungal surveys near the Syowa Station and the fungal diversity in this region. In the High Arctic region, I summarize the changes in the fungal communities of the glacial retreat areas of Ny-Ålesund, Norway and Ellesmere Island, Canada, in response to climate change. In addition, the ability of Antarctic and Arctic fungi to secrete enzymes at sub-zero temperatures is presented. Finally, the future directions of Antarctic and Arctic fungal research are provided.
      Citation: Climate
      PubDate: 2023-09-20
      DOI: 10.3390/cli11090195
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 196: Credible Pathways to Catching Up with Climate
           Goals in Nigeria

    • Authors: Samuel Chukwujindu Nwokolo, Edson L. Meyer, Chinedu Christian Ahia
      First page: 196
      Abstract: This paper seeks to address Nigeria’s challenges in meeting its climate objectives by investigating feasible pathways that can be implemented to accelerate progress and ensure credibility in meeting these targets. By examining the current policies and practices in place as well as successful strategies employed by other countries, this paper aims to provide strategies and policy implications recommendations for Nigeria to enhance its climate action efforts. The potential scenarios developed in this study ranged from increasing renewable energy capacity to implementing stricter regulations and standards for industries to reduce their carbon footprint, promote sustainable production processes, and strengthen climate governance and policy frameworks. The authors further investigated these measures and discovered that implementing stricter regulations and standards for industries would reduce their carbon footprint, promote sustainable production processes, and strengthen climate governance and policy frameworks. As such, Nigeria will be able to meet its climate goals more quickly as a result of the following factors: preventing environmental degradation, funding environmentally friendly infrastructure, and improving public transportation systems that can reduce vehicle-related greenhouse gas emissions. The authors developed policy measures based on the proposed twelve credible pathways to catching up with climate goals in Nigeria, thereby promoting faster progress by the Nigerian government in achieving climate goals. By adopting these measures, Nigeria’s progress toward the proposed zero net by 2060 will be significantly accelerated. It will position Nigeria as a continental leader in sustainable development and contribute to the overall global efforts to mitigate climate change. This will not only benefit the environment but also lead to financial development and an improved standard of living for its citizens.
      Citation: Climate
      PubDate: 2023-09-21
      DOI: 10.3390/cli11090196
      Issue No: Vol. 11, No. 9 (2023)
  • Climate, Vol. 11, Pages 231: The Contribution of Low-Carbon Energy
           Technologies to Climate Resilience

    • Authors: Liliana Proskuryakova
      First page: 231
      Abstract: The UN vision of climate resilience contains three independent outcomes: resilient people and livelihoods, resilient business and economies, and resilient environmental systems. This article analyzes the positive contributions of low-carbon energy technologies to climate resilience by reviewing and critically assessing the existing pool of studies published by researchers and international organizations that offer comparable data (quantitative indicators). Compilation, critical analysis, and literature review methods are used to develop a methodological framework that is in line with the UN vision of climate resilience and makes it possible to compare the input of low-carbon energy technologies climate resilience by unit of output or during their lifecycle. The framework is supported by the three relevant concepts—energy trilemma, sharing economy/material footprint, and Planetary Pressures-Adjusted Human Development Index. The study identifies indicators that fit the suggested framework and for which the data are available: total material requirement (TMR), present and future levelized cost of electricity (LCOE) without subsidies, CO2 emissions by fuel or industry, lifecycle CO2-equivalent emissions, and mortality rates from accidents and air pollution. They are discussed in the paper with a focus on multi-country and global studies that allow comparisons across different geographies. The findings may be used by decision-makers when prioritizing the support of low-carbon technologies and planning the designs of energy systems.
      Citation: Climate
      PubDate: 2023-11-21
      DOI: 10.3390/cli11120231
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 232: Tropical Cyclonic Energy Variability in North
           Indian Ocean: Insights from ENSO

    • Authors: Debanjana Das, Sen Chiao, Chayan Roychoudhury, Fatema Khan, Sutapa Chaudhuri, Sayantika Mukherjee
      First page: 232
      Abstract: Tropical cyclones (TC) are one of the deadliest natural meteorological hazards with destructive winds and heavy rains, resulting losses often reach billions of dollars, imposing a substantial and long-lasting burden on both local and national economies. The El-Niño Southern Oscillation (ENSO), a tropical ocean–atmosphere interaction, is known to significantly impact cyclonic systems over global ocean basins. This study investigates the variability of TC activity in the presence of ENSO over the North Indian Ocean (NIO), comprising the Arabian Sea (ARB) and the Bay of Bengal (BOB) basins during the pre- and post-monsoon season, using accumulated cyclone energy (ACE) over the last 29 years. Our analysis reveals a significant rise in tropical cyclone energy intensity over the past two decades, with eight of the ten most active years occurring since the 2000s. Total ACE over the NIO is found to be higher in La-Niña. Higher ACE observed over ARB is strongly associated with a combination of elevated sea surface height (SSH) anomaly and low vertical wind shear during the El-Niño episodes, with higher sea surface temperatures (SST) during the post-monsoon season. Whereas in the BOB, El Niño not only reduces ACE, but also decreases basin-wide variability, and more pronounced effects during the post-monsoon season, coinciding with warmer SST and higher SSH along the coast during La-Niña.
      Citation: Climate
      PubDate: 2023-11-21
      DOI: 10.3390/cli11120232
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 233: The Roles of Four Important Contexts in
           Japan’s Carbon Neutrality Policy and Politics, 1990–2020

    • Authors: Christo Odeyemi, Takashi Sekiyama
      First page: 233
      Abstract: This study answers four research questions by contextualising the background to Japan’s “carbon neutrality and net-zero” (CNN) policy, which was announced in October 2020, and identifying important changes in Japanese climate policy between 1990 and 2020. What is the link between the problem of fairness under the Kyoto targets and the Japanese government’s initial reluctance towards ambitious carbon emission reductions' Why did the Japanese business sector initially resist the possibility of ambitious carbon emission reductions' How has the term “climate crisis” contributed to the need for CNN policy' Why did the Japanese government change its reluctant stance and announce the CNN policy in October 2020' Four main findings were extracted from a narrative technique-based analysis of Japan’s policy documents related to CNN. The following are the findings: [i] the framing of climate change as a “climate crisis” by influential Japanese climate stakeholders was a key motivation for Japan to formally announce its CNN policy in October 2020; [ii] pressure from the international community and the political leadership of the Yoshihide Suga administration are essential factors that led the Japanese government to change its stance and announced this policy; [iii] it is possible that the policy could have been announced sooner, but concern among Japanese climate stakeholders about the problem of fairness in the Kyoto Protocol’s emission reduction targets likely impeded such an announcement; and [iv] this concern underpinned Keidanren’s (or the business sector’s) consistent opposition to the introduction of regulatory schemes. These results emerge for the first time in a study of Japan’s carbon neutrality, particularly in terms of the broader context of climate politics. Finally, we offer a possible explanation for Suga’s deliberate announcement of the CNN policy. This opens up space for future research to complement our study by providing important indicators on the trajectory of this important policy.
      Citation: Climate
      PubDate: 2023-11-23
      DOI: 10.3390/cli11120233
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 234: The Shift to Synergies in China’s
           Climate Planning: Aligning Goals with Policies and Institutions

    • Authors: Qianyi Cai, Eric Zusman, Guobi Meng
      First page: 234
      Abstract: China has long sought to address climate change in line with other development goals. However, research supporting this alignment often employs data-driven models that downplay the policies and institutions needed to achieve the multiple benefits that studies feature in their analyses. This oversight is troubling because it neglects gaps between goals and the actual integration of climate and development or co-control of air pollution and greenhouse gases (GHGs). Additionally, this oversight may overlook growing implementation challenges as China pursues synergies between net-zero emissions, biodiversity, and circularity. This article illustrates these challenges by tracing the goals and policies/institutions in China over three phases: (1) integration (1979–2010), (2) co-control (2011–2019), and (3) synergies (2020–present). This article argues that China needs to strengthen the science–policy interface and ensure that new market-based policy instruments (such as emissions trading programs) as well as the leadership responsibility system incentivize reductions in overall GHG emissions while shrinking ecological footprints in the shifts to synergies.
      Citation: Climate
      PubDate: 2023-11-28
      DOI: 10.3390/cli11120234
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 235: Assessing Tropical Cyclone Risk in Australia
           Using Community Exposure–Vulnerability Indices

    • Authors: Kade Berman, Yuriy Kuleshov
      First page: 235
      Abstract: Tropical cyclones (TCs) are one of the most destructive natural hazards to impact on Australia’s population, infrastructure, and the environment. To examine potential TC impacts, it is important to understand which assets are exposed to the hazard and of these, which are vulnerable to damage. The aim of this study is to improve TC risk assessments through developing an exposure–vulnerability index, utilising a case study for the six Local Government Areas (LGAs) impacted by the landfall of TC Debbie in 2017: Burdekin Shire, Charters Towers Region, Isaac Region, Mackay Region, City of Townsville, and Whitsunday Region. This study utilised a natural hazard risk assessment methodology, linking exposure and vulnerability indicators related to social factors, infrastructure, and the environment. The two LGAs with the most extreme exposure–vulnerability values were the coastal regions of Mackay Region and the City of Townsville. This is consistent with urbanisation and city development trends, with these LGAs having more people (social) and infrastructure exposed, while the environmental domain was more exposed and vulnerable to TC impacts in rural LGAs. Therefore, further resilience protocols and mitigation strategies are required, particularly for Mackay Region and the City of Townsville, to reduce the damage and ultimate loss of lives and livelihoods from TC impacts. This study serves as a framework for developing a TC risk index based on hazard, exposure, and vulnerability indices, and insight into the improved mitigation strategies for communities to implement in order to build resilience to the impacts of future TCs.
      Citation: Climate
      PubDate: 2023-11-28
      DOI: 10.3390/cli11120235
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 236: Minimal Mechanisms Responsible for the
           Dispersive Behavior of the Madden–Julian Oscillation

    • Authors: Kartheek Mamidi, Vincent Mathew
      First page: 236
      Abstract: An attempt has been made to explore the relative contributions of moisture feedback processes on tropical intraseasonal oscillation or Madden–Julian Oscillation (MJO). We focused on moisture feedback processes, including evaporation wind feedback (EWF) and moisture convergence feedback (MCF), which integrate the mechanisms of convective interactions into the tropical atmosphere. The dynamical framework considered here is a moisture-coupled, single-layer linear shallow-water model on an equatorial beta-plane with zonal momentum damping. With this approach, we aimed to recognize the minimal physical mechanisms responsible for the existence of the essential dispersive characteristics of the MJO, including its eastward propagation (k>0), the planetary-scale (small zonal wavenumbers) instability, and the slow phase speed of about ≈5 m/s. Furthermore, we extended our study to determine each feedback mechanism’s influence on the simulated eastward dispersive mode. Our model emphasized that the MJO-like eastward mode is a possible outcome of the combined effect of moisture feedback processes without requiring additional complex mechanisms such as cloud radiative feedback and boundary layer dynamics. The results substantiate the importance of EWF as a primary energy source for developing an eastward moisture mode with a planter-scale instability. The eastward moisture mode exhibits the highest growth rate at the largest wavelengths and is also sensitive to the strength of the EWF, showing a significant increase in the growth rate with the increasing strength of the EWF; however, the eastward moisture mode remains unstable at planetary-scale wavelengths. Moreover, our model endorses that the MCF alone could not produce instability without surface fluxes, although it has a significant role in developing deep convection. It was found that the MCF exhibits a damping mechanism by regulating the frequency and growth rate of the eastward moisture mode at shorter wavelengths.
      Citation: Climate
      PubDate: 2023-11-29
      DOI: 10.3390/cli11120236
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 237: Residential Wind Loss Mitigation Case Study:
           An Analysis of Insurance Claim Data for Hurricane Michael

    • Authors: Aneurin Grant, Christopher L. Atkinson
      First page: 237
      Abstract: This study analyzes insurance claim data from an 11-county area in the Florida Panhandle following the landfall of Hurricane Michael. The data includes 1467 non-mobile home structures, with 902 (61.5%) storm-damaged structures in Bay County. The analysis focuses on Wind Mitigation form 1802. Specifically, building design variables were analyzed via linear regression as to their influence on the percent claim loss. The building design variables included total square footage, dwelling construction type, age of the building, roof type, roof cover type, roof deck attachment type, roof to wall attachment, the presence of secondary water resistance (or sealed roof deck), opening protection type, and roof shape. Results show that building design variables for insurance claims have a high predictive value relative to a Category 5 hurricane event. However, the predictive values of building design variables are also dependent on the dwelling’s proximity to the coast, its location relative to the strong or weak side of the storm, the diameter of the storm, and other wind field variables.
      Citation: Climate
      PubDate: 2023-12-04
      DOI: 10.3390/cli11120237
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 238: Climate Change and Extreme Events in
           Northeast Atlantic and Azores Islands Region

    • Authors: Fernanda Silva Carvalho, Maria Gabriela Meirelles, Diamantino Henriques, João Porteiro, Patrícia Navarro, Helena Cristina Vasconcelos
      First page: 238
      Abstract: In small island regions, the influence of climate change assumes particular relevance. In the Azores archipelago, made up of nine islands, the geographical circumstances, oceanic condition, territorial dispersion, land use model and other physiographic constraints reinforce and enhance the vulnerability of the islands to changes in current weather patterns. Coupled Model Intercomparison Phase 6 (CMIP6) projections are used for the northeast Atlantic region to evaluate daily extreme climate events in large scale for the Azores region. Results shows changes in the annual maximum number of consecutive dry days, the annual number of wet days, and especially in the annual number of tropical nights. Despite limitations due to the lack of spatial detail, the large-scale framework suggests changes that may be enhanced by topography, particularly with respect to precipitation. The conclusions point to the need to establish standard rules in the processes of design, reviewing and/or amending territorial management instruments at the municipal scale in the Autonomous Region of the Azores, with the goal of adapting to a different climate from the recent past.
      Citation: Climate
      PubDate: 2023-12-04
      DOI: 10.3390/cli11120238
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 239: The Umlindi Newsletter: Disseminating
           Climate-Related Information on the Management of Natural Disaster and
           Agricultural Production in South Africa

    • Authors: Reneilwe Maake, Johan Malherbe, Teboho Masupha, George Chirima, Philip Beukes, Sarah Roffe, Mark Thompson, Mokhele Moeletsi
      First page: 239
      Abstract: The Umlindi newsletter was developed to provide information towards climate advisories, considering, for instance, drought conditions, presented in a relevant manner for the agricultural and disaster sectors in South Africa. This newsletter, which is disseminated on a monthly basis, provides information derived from climate-related monitoring products obtained from an integration of remote sensing and in situ data from weather stations. It contains useful indicators, such as rainfall, vegetation, and fire conditions, that provide an overview of conditions across the country. The present study demonstrates how these natural resource indices are integrated and consolidated for utilization by farmers, policy-makers, private organizations, and the general public to make day-to-day decisions on the management and mitigation of natural disasters. However, there is a need to expand these baseline observation initiatives, including the following: (1) forecasting future conditions to strengthen coping mechanisms of government, farmers, and communities at large; and (2) incorporating information on other natural disasters such as floods and extreme heat. In the context of South Africa, this information is important to improve disaster preparedness and management for agricultural productivity. In a global context, the Umlindi newsletter can be insightful for developing and disseminating natural resources information on adaptation to and mitigation of climate change and variability impacts to other regions facing similar risks. Furthermore, while international organizations also provide natural resource information, the Umlindi newsletter may be distinguished by its regional focus and linkages to individual communities. It bridges the gap between global environmental data and local decision-making by illustrating how global scientific knowledge may be applied locally.
      Citation: Climate
      PubDate: 2023-12-05
      DOI: 10.3390/cli11120239
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 240: A Social Dimension of Adaptation and
           Mitigation of Climate Change: Empowering Local Rural Communities to
           Confront Extreme Poverty

    • Authors: Farshad Amiraslani, Deirdre Dragovich
      First page: 240
      Abstract: Climate change impacts occur at varying spatial scales requiring appropriately scaled responses. In impoverished rural areas, adapting to or mitigating the effects of climate change is challenging, with any short-term impairment to precarious livelihoods likely triggering negative community responses even if people are aware of long-term benefits. The paper will discuss a community-based carbon sequestration project in eastern Iran. It started in 2003 and since then has been expanded widely. It was nominated by UNDP as one of 10 transformative projects in Asia/Pacific in 2016. Over the past 20 years, the project has targeted improving the livelihood of the local communities while addressing local measures to adapt to/mitigate climate change. The paper elaborates on the formation of village development groups as pivotal drivers of success by highlighting local income-generating schemes and project documentation. Key lessons for climate change adaptation can be learnt and are applicable to other developing countries. Extreme poverty in rural areas facing climate change could be tackled through implementing bottom-up approaches in which local communities can be respected and engaged in co-leadership and planning.
      Citation: Climate
      PubDate: 2023-12-08
      DOI: 10.3390/cli11120240
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 241: Intercomparison of Different Sources of
           Precipitation Data in the Brazilian Legal Amazon

    • Authors: Fabrício Daniel dos Santos Silva, Claudia Priscila Wanzeler da Costa, Vânia dos Santos Franco, Helber Barros Gomes, Maria Cristina Lemos da Silva, Mário Henrique Guilherme dos Santos Vanderlei, Rafaela Lisboa Costa, Rodrigo Lins da Rocha Júnior, Jório Bezerra Cabral Júnior, Jean Souza dos Reis, Rosane Barbosa Lopes Cavalcante, Renata Gonçalves Tedeschi, Naurinete de Jesus da Costa Barreto, Antônio Vasconcelos Nogueira Neto, Edmir dos Santos Jesus, Douglas Batista da Silva Ferreira
      First page: 241
      Abstract: Monitoring rainfall in the Brazilian Legal Amazon (BLA), which comprises most of the largest tropical rainforest and largest river basin on the planet, is extremely important but challenging. The size of the area and land cover alone impose difficulties on the operation of a rain gauge network. Given this, we aimed to evaluate the performance of nine databases that estimate rainfall in the BLA, four from gridded analyses based on pluviometry (Xavier, CPC, GPCC and CRU), four based on remote sensing (CHIRPS, IMERG, CMORPH and PERSIANN-CDR), and one from reanalysis (ERA5Land). We found that all the bases are efficient in characterizing the average annual cycle of accumulated precipitation in the BLA, but with a predominantly negative bias. Parameters such as Pearson’s correlation (r), root-mean-square error (RMSE) and Taylor diagrams (SDE), applied in a spatial analysis for the entire BLA as well as for six pluviometrically homogeneous regions, showed that, based on a skill ranking, the data from Xavier’s grid analysis, CHIRPS, GPCC and ERA5Land best represent precipitation in the BLA at monthly, seasonal and annual levels. The PERSIANN-CDR data showed intermediate performance, while the IMERG, CMORPH, CRU and CPC data showed the lowest correlations and highest errors, characteristics also captured in the Taylor diagrams. It is hoped that this demonstration of hierarchy based on skill will subsidize climate studies in this region of great relevance in terms of biodiversity, water resources and as an important climate regulator.
      Citation: Climate
      PubDate: 2023-12-09
      DOI: 10.3390/cli11120241
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 242: Multi-Hazard Extreme Scenario Quantification
           Using Intensity, Duration, and Return Period Characteristics

    • Authors: Athanasios Sfetsos, Nadia Politi, Diamando Vlachogiannis
      First page: 242
      Abstract: Many modern frameworks for community resilience and emergency management in the face of extreme hydrometeorological and climate events rely on scenario building. These scenarios typically cover multiple hazards and assess the likelihood of their occurrence. They are quantified by their main characteristics, including likelihood of occurrence, intensity, duration, and spatial extent. However, most studies in the literature focus only on the first two characteristics, neglecting to incorporate the internal hazard dynamics and their persistence over time. In this study, we propose a multidimensional approach to construct extreme event scenarios for multiple hazards, such as heat waves, cold spells, extreme precipitation and snowfall, and wind speed. We consider the intensity, duration, and return period (IDRP) triptych for a specific location. We demonstrate the effectiveness of this approach by developing pertinent scenarios for eight locations in Greece with diverse geographical characteristics and dominant extreme hazards. We also address how climate change impacts the scenario characteristics.
      Citation: Climate
      PubDate: 2023-12-12
      DOI: 10.3390/cli11120242
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 243: Linking Climate Change Information with Crop
           Growing Seasons in the Northwest Ethiopian Highlands

    • Authors: Gashaw Bimrew Tarekegn, Addis A. Alaminie, Sisay E. Debele
      First page: 243
      Abstract: In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future.
      Citation: Climate
      PubDate: 2023-12-15
      DOI: 10.3390/cli11120243
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 244: Homogeneity Assessment and Correction
           Methodology for the 1980–2022 Daily Temperature Series in Padua,

    • Authors: Claudio Stefanini, Francesca Becherini, Antonio della Valle, Francesco Rech, Fabio Zecchini, Dario Camuffo
      First page: 244
      Abstract: Meteorological observations over the last four decades are of paramount importance to investigating ongoing climate change. An important issue is the quality and reliability of the climatic series, which are fundamental prerequisites to drawing the correct conclusions. Homogeneity tests are used to detect discontinuities whose interpretation is facilitated by metadata availability. In this work, daily minimum and maximum temperature measurements collected in Padua, Italy, between 1980 and 2022 are examined. During this period, the weather station of Padua center underwent many changes in location or instruments; therefore, some tests have been used to identify and remove their effects and obtain homogeneous series. Some well-known absolute tests have been applied to investigate the shift in the mean value: Standard Normal Homogeneity test (SNH), Buishand U and range tests, Pettitt test, F-test, and STARS. Relative tests have been applied too, using several stations nearby Padua and two reanalysis datasets (ERA5 and MERIDA) as reference series to enhance the picture of the local situation and provide more robust conclusions. The applied tests identify change-points in the years in which a change in instrument or the location of the station has occurred, confirming that these changes have compromised the homogeneity of the series. The sub-series obtained, splitting the observations in correspondence with these change-points, have been homogenized with respect to a selected period. The corrected series of the minimum and maximum temperatures are more coherent with the modern warming trend. The transfer functions to be applied to future measurements of minimum temperature have been calculated, while the series of maximum temperature measurements can be directly extended.
      Citation: Climate
      PubDate: 2023-12-15
      DOI: 10.3390/cli11120244
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 245: Precipitation Projection in Cambodia Using
           Statistically Downscaled CMIP6 Models

    • Authors: Seyhakreaksmey Duong, Layheang Song, Rattana Chhin
      First page: 245
      Abstract: The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.
      Citation: Climate
      PubDate: 2023-12-16
      DOI: 10.3390/cli11120245
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 246: Examining the Heat Health Burden in
           Australia: A Rapid Review

    • Authors: Manoj Bhatta, Emma Field, Max Cass, Kerstin Zander, Steven Guthridge, Matt Brearley, Sonia Hines, Gavin Pereira, Darfiana Nur, Anne Chang, Gurmeet Singh, Stefan Trueck, Chi Truong, John Wakerman, Supriya Mathew
      First page: 246
      Abstract: Extreme heat has been linked to increased mortality and morbidity across the globe. Increasing temperatures due to climatic change will place immense stress on healthcare systems. This review synthesises Australian literature that has examined the effect of hot weather and heatwaves on various health outcomes. Databases including Web of Science, PubMed and CINAHL were systematically searched for articles that quantitatively examined heat health effects for the Australian population. Relevant, peer-reviewed articles published between 2010 and 2023 were included. Two authors screened the abstracts. One researcher conducted the full article review and data extraction, while another researcher randomly reviewed 10% of the articles to validate decisions. Our rapid review found abundant literature indicating increased mortality and morbidity risks due to extreme temperature exposures. The effect of heat on mortality was found to be mostly immediate, with peaks in the risk of death observed on the day of exposure or the next day. Most studies in this review were concentrated on cities and mainly included health outcome data from temperate and subtropical climate zones. There was a dearth of studies that focused on tropical or arid climates and at-risk populations, including children, pregnant women, Indigenous people and rural and remote residents. The review highlights the need for more context-specific studies targeting vulnerable population groups, particularly residents of rural and remote Australia, as these regions substantially vary climatically and socio-demographically from urban Australia, and the heat health impacts are likely to be even more substantial.
      Citation: Climate
      PubDate: 2023-12-18
      DOI: 10.3390/cli11120246
      Issue No: Vol. 11, No. 12 (2023)
  • Climate, Vol. 11, Pages 213: Evaluation of Subseasonal Precipitation
           Simulations for the Sao Francisco River Basin, Brazil

    • Authors: Nicole C. R. Ferreira, Sin C. Chou, Claudine Dereczynski
      First page: 213
      Abstract: Water conflicts have been a significant issue in Brazil, especially in the Sao Francisco River basin. Subseasonal forecasts, up to a 60-day forecast range, can provide information to support decision-makers in managing water resources in the river basin, especially before drought events. This report aims to evaluate 5-year mean subseasonal simulations generated by the Eta regional model for the period from 2011 to 2016 and assess the usefulness of this information to support decision-making in water resource conflicts in the Sao Francisco River basin. The capability of the Eta model to reproduce the drought events that occurred between the years 2011 and 2016 was compared against the Climate Prediction Center Morphing (CMORPH) precipitation data. Two sets of 60-day simulations were produced: one started in September (SO) and the other in January (JF) of each year. These months were chosen to evaluate the model’s capability to reproduce the onset and the middle of the rainy seasons in central Brazil, where the upper Sao Francisco River is located. The SO simulations reproduced the observed spatial distribution of precipitation but underestimated the amounts. Precipitation errors exhibited large variability across the subbasins. The JF simulations also reproduced the observed precipitation distribution but overestimated it in the upper and lower subbasins. The JF simulations better captured the interannual variability in precipitation. The 60-day simulations were discretized into six 10-day accumulations to assess the intramonthly variability. They showed that the simulations captured the onset of the rainy season and the small periods of rainy months that occurred in these severe drought years. This research is a critical step to indicate subbasins where the model simulation needs to be improved and provide initial information to support water allocation in the region.
      Citation: Climate
      PubDate: 2023-10-28
      DOI: 10.3390/cli11110213
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 214: Tree-Regeneration Decline and Type-Conversion
           after High-Severity Fires Will Likely Cause Little Western USA Forest Loss
           from Climate Change

    • Authors: William L. Baker
      First page: 214
      Abstract: Temperate conifer forests stressed by climate change could be lost through tree regeneration decline in the interior of high-severity fires, resulting in type conversion to non-forest vegetation from seed-dispersal limitation, competition, drought stress, and reburns. However, is fire triggering this global change syndrome at a high rate' To find out, I analyzed a worst-case scenario. I calculated fire rotations (FRs, expected period to burn once across an area) across ~56 million ha of forests (~80% of total forest area) in 11 western USA states from 2000 to 2020 for total high-severity fire area, interior area (>90 m inward), and reburned area. Unexpectedly, there was no trend in area burned at high severity from 2000 to 2020 across the four forest types studied. The vulnerable interior area averaged only 21.9% of total high-severity fire area, as 78.1% of burned area was within 90 m of live seed sources where successful tree regeneration is likely. FRs averaged 453 years overall, 2089 years in interiors, and 19,514 years in reburns. Creation of vulnerable interior area in a particular location is thus, on average, a 2000+ year event, like a very rare natural disaster, and reburns that may favor type conversion to non-forest have almost no effect. This means that, from 2021 to 2050 at most, only 3.0–4.2% of total forest area may become a vulnerable interior area, based on a likely high aridity-based climate projection of future fire and a higher scenario, where rates in the exceptional 2020 fire year have become the norm. These findings show that increased management to reduce high-severity fires is not currently needed, as the risk to forests from this global change syndrome is likely quite low up to 2050. Faster and larger disturbances (e.g., severe droughts) are more likely to cause most tree mortality or forest loss that occurs by 2050.
      Citation: Climate
      PubDate: 2023-10-30
      DOI: 10.3390/cli11110214
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 215: Ninety-Nine Percent' Re-Examining the
           Consensus on the Anthropogenic Contribution to Climate Change

    • Authors: David Dentelski, Ran Damari, Yanir Marmor, Avner Niv, Mor Roses, Yonatan Dubi
      First page: 215
      Abstract: Anthropogenic activity is considered a central driver of current climate change. A recent paper, studying the consensus regarding the hypothesis that the recent increase in global temperature is predominantly human-made via the emission of greenhouse gasses (see text for reference), argued that the scientific consensus in the peer-reviewed scientific literature pertaining to this hypothesis exceeds 99%. This conclusion was reached after the authors scanned the abstracts and titles of some 3000 papers and mapped them according to their (abstract) statements regarding the above hypothesis. Here, we point out some major flaws in the methodology, analysis, and conclusions of the study. Using the data provided in the study, we show that the 99% consensus, as defined by the authors, is actually an upper limit evaluation because of the large number of “neutral” papers which were counted as pro-consensus in the paper and probably does not reflect the true situation. We further analyze these results by evaluating how so-called “skeptic” papers fit the consensus and find that biases in the literature, which were not accounted for in the aforementioned study, may place the consensus on the low side. Finally, we show that the rating method used in the study suffers from a subjective bias which is reflected in large variations between ratings of the same paper by different raters. All these lead to the conclusion that the conclusions of the study does not follow from the data.
      Citation: Climate
      PubDate: 2023-10-30
      DOI: 10.3390/cli11110215
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 216: The Role of Translocal Practices in a Natural
           Climate Solution in Ghana

    • Authors: John Narh, Stefanie Wehner, Christian Ungruhe, Andreas Eberth
      First page: 216
      Abstract: People-centred reforestation is one of the ways to achieve natural climate solutions. Ghana has established a people-centred reforestation programme known as the Modified Taunya System (MTS) where local people are assigned degraded forest reserves to practice agroforestry. Given that the MTS is a people-centred initiative, socioeconomic factors are likely to have impact on the reforestation drive. This study aims to understand the role of translocal practices of remittances and visits by migrants on the MTS. Using multi-sited, sequential explanatory mixed methods and the lens of socioecological systems, the study shows that social capital and socioeconomic obligations of cash remittances from, as well as visits by migrants to their communities of origin play positive roles on reforestation under the MTS. Specifically, translocal households have access to, and use remittances to engage relatively better in the MTS than households that do not receive remittances. This shows that translocal practices can have a positive impact on the environment at the area of origin of migrants where there are people-centred environmental policies in place.
      Citation: Climate
      PubDate: 2023-10-30
      DOI: 10.3390/cli11110216
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 217: Assessing Property Exposure to Cyclonic Winds
           under Climate Change

    • Authors: Evelyn G. Shu, Mariah Pope, Bradley Wilson, Mark Bauer, Mike Amodeo, Neil Freeman, Jeremy R. Porter
      First page: 217
      Abstract: Properties in the United States face increasing exposure to tropical storm-level winds due to climate change. Driving this increasing risk are severe hurricanes that are more likely to occur when hurricanes form in the future and the northward shift of Atlantic-formed hurricanes, increasing the estimated exposure of buildings and infrastructure to damaging winds. The wind model presented here combines open data and science by utilizing high-resolution topography, computer-modeled hurricane tracks, and property data to create hyper-local tropical cyclone wind exposure information for the Contiguous United States (CONUS) from current time to 2053 under RCP 4.5. This allows for a detailed evaluation of probable wind speeds by several return periods, probabilities of cyclonic thresholds being reached or surpassed, and a comparison of this cyclone-level wind exposure between the current year and 30 years into the future under climatic changes. The results of this research reveal extensive exposure along the Gulf and Southeastern Atlantic Coasts, with significant growing exposure in the Mid-Atlantic and Northeastern regions of the country.
      Citation: Climate
      PubDate: 2023-11-01
      DOI: 10.3390/cli11110217
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 218: Correction: Lightburn, K.D. Can a Symbolic
           Mega-Unit of Radiative Forcing (RF) Improve Understanding and Assessment
           of Global Warming and of Mitigation Methods Using Albedo Enhancement from
           Algae, Cloud, and Land (AEfACL)' Climate 2023, 11, 62

    • Authors: Kenneth D. Lightburn
      First page: 218
      Abstract: There were errors in the original publication [...]
      Citation: Climate
      PubDate: 2023-11-01
      DOI: 10.3390/cli11110218
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 219: Grassland Resilience to Woody Encroachment in
           North America and the Effectiveness of Using Fire in National Parks

    • Authors: Han Ling, Guangyu Wang, Wanli Wu, Anil Shrestha, John L. Innes
      First page: 219
      Abstract: The grasslands of North America are threatened by woody encroachment. Restoring historical fire regimes has been used to manage brush encroachment. However, fire management may be insufficient due to the nonlinear and hysteretic responses of vegetation recovery following encroachment and the social–political constraints affecting fire management. We synthesized the fire thresholds required to control woody encroachment by typical encroaching species in North America, especially the Great Plains region, and identified the social–political constraints facing fire management in selected grassland national parks. Our synthesis revealed the resistance, hysteresis, and irreversibility of encroached grasslands using fire and emphasized the need for a combination of brush management methods if the impacts of climate change are to be addressed. Frequent fires alone may maintain grassland states, reflecting resistance. However, high-intensity fires exceeding fire-mortality thresholds are required to exclude non-resprouting shrubs and trees, indicating hysteresis. Fire alone may be insufficient to reverse encroachment by resprouting species, exhibiting reversibility. In practice, appropriate fire management may restore resistant grassland states. However, social–political constraints have restricted the use of frequent and high-intensity fires, thereby reducing the effectiveness of management actions to control woody encroachment of grasslands in national parks. This research proposes a resilience-based framework to manage woody encroachment in grassland national parks and similar protected areas.
      Citation: Climate
      PubDate: 2023-11-02
      DOI: 10.3390/cli11110219
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 220: Microclimate and Vegetation Structure
           Significantly Affect Butterfly Assemblages in a Tropical Dry Forest

    • Authors: Anirban Mahata, Rajendra Mohan Panda, Padmanava Dash, Ayusmita Naik, Alok Kumar Naik, Sharat Kumar Palita
      First page: 220
      Abstract: Understanding the factors that influence the diversity and distribution of butterfly species is crucial for prioritizing conservation. The Eastern Ghats of India is an ideal site for such a study, where butterfly diversity studies have yet to receive much attention. This study emphasized the butterfly assemblages of three prominent habitats in the region: open forests, riparian forests, and dense forests. We hypothesized that riparian forests would be the most preferred habitat for the butterflies, as they provide suitable microclimatic conditions for butterflies. The study collected samples for 35 grids of 2 × 2 km2 for each habitat during the dry months (December–June). We considered the relative humidity, temperature, light intensity, elevation, and canopy cover to assess their influences on butterfly richness and abundance. We also considered the impact of disturbances on their distribution. We used structural equation modeling and canonical correspondence analysis to quantify the correlation and causation between the butterflies and their environment. The study recorded 1614 individual butterflies of 79 species from 57 genera and 6 families. During the study, we found that temperature was the most significant factor influencing butterfly richness. Relative humidity was also important and had a positive impact on butterfly richness. Riparian forests, where daytime temperatures are relatively low, were the most preferred microhabitat for butterflies. Open forests had greater species diversity, indicating the critical significance of an open canopy for butterflies. Though riparian forests need greater attention concerning butterfly distribution, maintaining open and dense forests are crucial for preserving butterfly diversity.
      Citation: Climate
      PubDate: 2023-11-02
      DOI: 10.3390/cli11110220
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 221: Climate Change Skeptics’ Environmental
           Concerns and Support for Clean Energy Policy: A Case Study of the US
           Pacific Northwest

    • Authors: Dilshani Sarathchandra, Kristin Haltinner
      First page: 221
      Abstract: Resistance to clean energy policy in the United States stems partly from public hesitancy and skepticism toward anthropogenic climate change. This article examines self-declared climate change skeptics’ views of clean energy policy along a continuum of skeptical thought, spanning from epistemic denial to attribution doubt. To perform this, we use data from an online survey administered in the US Pacific Northwest and a series of pilot interviews conducted with skeptics in the same region. Results reveal that skeptics’ support for clean energy policy is consistently linked with their environmental concern across the skepticism continuum. Conspiracy ideation and distrust in science lead to a reduction in support. However, the positive effect of environmental concern trumps the effects of these beliefs. Important and hopeful implications of these findings for climate change communication and policy are discussed.
      Citation: Climate
      PubDate: 2023-11-02
      DOI: 10.3390/cli11110221
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 222: Climate Risk and Vulnerability Assessment of
           Georgian Hydrology under Future Climate Change Scenarios

    • Authors: Aashutosh Aryal, Rieks Bosch, Venkataraman Lakshmi
      First page: 222
      Abstract: The Climate Risk and Vulnerability Assessment (CRVA) is a systematic process used to identify gaps in regional climate adaptation strategies. The CRVA method assesses regional vulnerability, adaptation capacity, exposure, and sensitivity to climate change to support improved adaptation policies. This CRVA study assesses Georgia’s climate exposure, geographic sensitivity, and socio-economic sensitivity by focusing on the impacts of climate change on regional hydrology. The projected change in climate extreme indices, defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), is assessed against the 1961–1990 baseline under future Representative Concentration Pathway (RCP) scenarios. These indices encompass various climate factors such as the maximum daily temperature, warmth duration, total precipitation, heavy and extreme precipitation, maximum 5-day precipitation, and consecutive drought duration. This evaluation helps us understand the potential climate exposure impacts on Georgia. The climate-induced geographic sensitivity is examined based on water stress, drought risk, and changes in soil productivity using the Normalized Difference Vegetation Index (NDVI). The climate-induced socio-economic sensitivity is determined using the Gross Domestic Product per capita (GDP), Human Development Index, Education Index, and population density. The highest vulnerability to climate change was found in the Kakheti and Kvemo Kartli regions, with the vulnerability index values ranging from 6 to 15, followed by Mtskheta-Mtianeti, Samtskhe–Javakheti, and Shida Kartli with vulnerability index values ranging from 2 to 8. The location of these regions upstream of the Alazani-Iori, Khrami-Debeda, and Mktvari river basins indicates that the country’s water resources are vulnerable to climate change impacts in the future under the RCP 4.5 and 8.5 scenarios.
      Citation: Climate
      PubDate: 2023-11-02
      DOI: 10.3390/cli11110222
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 223: Regional to Mesoscale Influences of Climate
           Indices on Tornado Variability

    • Authors: Cooper P. Corey, Jason C. Senkbeil
      First page: 223
      Abstract: Tornadoes present an undisputable danger to communities throughout the United States. Despite this known risk, there is a limited understanding of how tornado frequency varies spatially at the mesoscale across county or city area domains. Furthermore, while previous studies have examined the relationships between various climate indices and continental or regional tornado frequency, little research has examined their influence at a smaller scale. This study examines the relationships between various climate indices and regional tornado frequency alongside the same relationships at the mesoscale in seven cities with anomalous tornado patterns. The results of a correlation analysis and generalized linear modeling show common trends between the regions and cities. The strength of the relationships varied by region, but, overall, the ENSO had the greatest influence on tornado frequency, followed in order by the PNA, AO, NAO, MJO, and PDO. However, future research is critical for understanding how the effects of climate indices on tornado frequency vary at different spatial scales, or whether other factors are responsible for the atypical tornado rates in certain cities.
      Citation: Climate
      PubDate: 2023-11-04
      DOI: 10.3390/cli11110223
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 224: Time Series Homogenization with ACMANT:
           Comparative Testing of Two Recent Versions in Large-Size Synthetic
           Temperature Datasets

    • Authors: Peter Domonkos
      First page: 224
      Abstract: Homogenization of climatic time series aims to remove non-climatic biases which come from the technical changes in climate observations. The method comparison tests of the Spanish MULTITEST project (2015–2017) showed that ACMANT was likely the most accurate homogenization method available at that time, although the tested ACMANTv4 version gave suboptimal results when the test data included synchronous breaks for several time series. The technique of combined time series comparison was introduced to ACMANTv5 to better treat this specific problem. Recently performed tests confirm that ACMANTv5 adequately treats synchronous inhomogeneities, but the accuracy has slightly worsened in some other cases. The results for a known daily temperature test dataset for four U.S. regions show that the residual errors after homogenization may be larger with ACMANTv5 than with ACMANTv4. Further tests were performed to learn more about the efficiencies of ACMANTv4 and ACMANTv5 and to find solutions for the problems occurring with the new version. Planned changes in ACMANTv5 are presented in the paper along with related test results. The overall results indicate that the combined time series comparison can be kept in ACMANT, but smaller networks should be generated in the automatic networking process of the method. To improve further the homogenization methods and to obtain more reliable and more solid knowledge about their accuracies, more synthetic test datasets mimicking the true spatio-temporal structures of real climatic data are needed.
      Citation: Climate
      PubDate: 2023-11-06
      DOI: 10.3390/cli11110224
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 225: Examining the Spatiotemporal Changes in the
           Annual, Seasonal, and Daily Rainfall Climatology of Puerto Rico

    • Authors: José Javier Hernández Ayala, Rafael Méndez Tejeda
      First page: 225
      Abstract: This study explores spatial and temporal changes in the rainfall climatology of Puerto Rico in order to identify areas where annual, seasonal or daily precipitation is increasing, decreasing, or remaining normal. Total annual, seasonal, and daily rainfall were retrieved from 23 historical rain gauges with consistent data for the 1956–2021 period. Mann–Kendall trend tests were done on the annual and seasonal rainfall series, and percentage change differences between two different climatologies (1956–1987 and 1988–2021) were calculated. Most of the stations did not exhibit statistically significant annual or seasonal trends in average rainfall. However, of the sites that did experience changes, most of them had statistically significant decreasing trends in mean precipitation. The annual, dry, and early wet season had more sites with negative trends when compared with positive trends, especially in the northwestern and southeastern region of the island. The late wet season was the only period with more sites showing statistically significant trends when compared with negative trends, specifically in the northern region of the island. Results for daily events show that extreme rainfall occurrences have generally decreased, especially in the western region of the island. When the 1955–1987 and 1988–2022 climatologies are compared, the results for annual average rainfall show two main regions with mean precipitation reductions, and those are the northwestern and southeastern areas of the island. The dry season was the only period with more areas exhibiting percentage increases in mean rainfall when the two climatologies were analyzed. The early and late wet season months exhibited similar patterns, with more areas on the island showing negative percentage decreases in average seasonal precipitation. The best predictor for the decreasing annual and seasonal trend in the northwest was a higher sea level pressure, and the variable that best explained the increasing trend in the northeast was total precipitable water.
      Citation: Climate
      PubDate: 2023-11-06
      DOI: 10.3390/cli11110225
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 226: A GIS-Based Assessment of Flood Hazard
           through Track Records over the 1886–2022 Period in Greece

    • Authors: Niki Evelpidou, Constantinos Cartalis, Anna Karkani, Giannis Saitis, Kostas Philippopoulos, Evangelos Spyrou
      First page: 226
      Abstract: This paper addresses the riverine flood events that have occurred in Greece over the last 136 years (i.e., during the 1886–2022 period), focusing, amongst others, on the case of urban floods. The flood record of various sites of the country has been collected and analyzed to determine their spatial and temporal distribution. Greece is a country where flood data and records are very scarce. Therefore, as there is not an integrated catalog of Greek floods spanning from the 19th century to recently, this is the first attempt to create an integrated catalog for Greece. The sources used include published papers, local and regional newspapers and public bodies (mainly the Ministry of Environment and Energy and the official websites of Greek municipalities). Additionally, the main factors responsible for their occurrence have been issued, regarding the country’s climatic, geological and geomorphological setting, as well as human interventions. In addition, the atmospheric circulation driving factors of floods are assessed via an unsupervised neural network approach (i.e., Self-Organizing Maps). Based on the results of this research, an online GIS-based database has been created, depicting the areas that have been struck by riverine floods in Greece. By clicking a flood event in the online database, one can view several characteristics, depending on data availability, such as duration and height of the rainfall that caused them and number of fatalities. Long-term trends of mean and extremes seasonal precipitation also linked to the spatial distribution of floods. Our analysis shows that urban floods are a very large portion of the overall flood record, and they mainly occur in the two large urban centers, Athens and Thessaloniki, as well as near large rivers such as Pineios. Autumn months and mainly November are the periods with higher flood hazards, based on past records and cyclonic atmospheric circulation constitutes the principal driving factor. Our results indicate that a flood catalog at national level is of fundamental importance, as it can provide valuable statistical insights regarding seasonality, spatial distribution of floods, etc., while it can also be used by stakeholders and researchers for flood management and flood risk analysis and modelling.
      Citation: Climate
      PubDate: 2023-11-08
      DOI: 10.3390/cli11110226
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 227: Co-Cultivation and Matching of Early- and
           Late-Maturing Pearl Millet Varieties to Sowing Windows Can Enhance
           Climate-Change Adaptation in Semi-Arid Sub-Saharan Agroecosystems

    • Authors: Simon Kamwele Awala, Kudakwashe Hove, Johanna Shekupe Valombola, Helena Nalitende Nafuka, Evans Kamwi Simasiku, Barthlomew Chataika, Lydia Ndinelao Horn, Simon Angombe, Levi S. M. Akundabweni, Osmund D. Mwandemele
      First page: 227
      Abstract: In semi-arid regions, climate change has affected crop growing season length and sowing time, potentially causing low yield of the rainfed staple crop pearl millet (Pennisetum glaucum L.) and food insecurity among smallholder farmers. In this study, we used 1994–2023 rainfall data from Namibia’s semi-arid North-Central Region (NCR), receiving November–April summer rainfall, to analyze rainfall patterns and trends and their implications on the growing season to propose climate adaptation options for the region. The results revealed high annual and monthly rainfall variabilities, with nonsignificant negative trends for November–February rainfalls, implying a shortening growing season. Furthermore, we determined the effects of sowing date on grain yields of the early-maturing Okashana-2 and local landrace Kantana pearl millet varieties and the optimal sowing window for the region, using data from a two-year split-plot field experiment conducted at the University of Namibia—Ogongo Campus, NCR, during the rainy season. Cubic polynomial regression models were applied to grain-yield data sets to predict grain production for any sowing date between January and March. Both varieties produced the highest grain yields under January sowings, with Kantana exhibiting a higher yield potential than Okashana-2. Kantana, sown by 14 January, had a yield advantage of up to 36% over Okashana-2, but its yield gradually reduced with delays in sowing. Okashana-2 exhibited higher yield stability across January sowings, surpassing Kantana’s yields by up to 9.4% following the 14 January sowing. We determined the pearl millet optimal sowing window for the NCR to be from 1–7 and 1–21 January for Kantana and Okashana-2, respectively. These results suggest that co-cultivation of early and late pearl millet varieties and growing early-maturing varieties under delayed seasons could stabilize grain production in northern Namibia and enhance farmers’ climate adaptation. Policymakers for semi-arid agricultural regions could utilize this information to adjust local seed systems and extension strategies.
      Citation: Climate
      PubDate: 2023-11-10
      DOI: 10.3390/cli11110227
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 228: Managing Extreme Rainfall and Flooding
           Events: A Case Study of the 20 July 2021 Zhengzhou Flood in China

    • Authors: Xiaofan Zhao, Huimin Li, Qin Cai, Ye Pan, Ye Qi
      First page: 228
      Abstract: On 20 July 2021, an extreme rainstorm battered Zhengzhou in China’s Henan Province, killing 302 people, including 14 individuals who drowned in a subway tunnel and 6 who drowned in a road tunnel. As the global climate warms, extreme weather events similar to the Zhengzhou flood will become more frequent, with increasingly catastrophic consequences for society. Taking a case study-based approach by focusing on the record-breaking Zhengzhou flood, this paper examines the governance capacity of inland cities in North China for managing extreme precipitation and flooding events from the perspective of the flood risk management process. Based on in-depth case analysis, our paper hypothesizes that inland cities in North China still have low risk perceptions of extreme weather events, which was manifested in insufficient pre-disaster preparation and prevention, poor risk communication, and slow emergency response. Accordingly, it is recommended that inland cities update their risk perceptions of extreme rainfall and flooding events, which are no longer low-probability, high-impact “black swans”, but turning into high-probability, high-impact “gray rhinos.” In particular, cities must make sufficient preparation for extreme weather events by revising contingency plans and strengthening their implementation, improving risk communication of meteorological warnings, and synchronizing emergency response with meteorological warnings.
      Citation: Climate
      PubDate: 2023-11-12
      DOI: 10.3390/cli11110228
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 229: Flood Hazard Assessment in Australian
           Tropical Cyclone-Prone Regions

    • Authors: Michael Kaspi, Yuriy Kuleshov
      First page: 229
      Abstract: This study investigated tropical cyclone (TC)-induced flooding in coastal regions of Australia due to the impact of TC Debbie in 2017 utilising a differential evolution-optimised random forest to model flood susceptibility in the region of Bowen, Airlie Beach, and Mackay in North Queensland. Model performance was evaluated using a receiver operating characteristic curve, which showed an area under the curve of 0.925 and an overall accuracy score of 80%. The important flood-influencing factors (FIFs) were investigated using both feature importance scores and the SHapely Additive exPlanations method (SHAP), creating a flood hazard map of the region and a map of SHAP contributions. It was found that the elevation, slope, and normalised difference vegetation index were the most important FIFs overall. However, in some regions, the distance to the river and the stream power index dominated for a similar flood hazard susceptibility outcome. Validation using SHAP to test the physical reasoning of the model confirmed the reliability of the flood hazard map. This study shows that explainable artificial intelligence allows for improved interpretation of model predictions, assisting decision-makers in better understanding machine learning-based flood hazard assessments and ultimately aiding in mitigating adverse impacts of flooding in coastal regions affected by TCs.
      Citation: Climate
      PubDate: 2023-11-13
      DOI: 10.3390/cli11110229
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 230: Temporal Changes in Tourists’
           Climate-Based Comfort in the Southeastern Coastal Region of Spain

    • Authors: David Espín-Sánchez, Jorge Olcina-Cantos, Carmelo Conesa-García
      First page: 230
      Abstract: In the context of climate change, where the average temperature has risen in recent decades on the Mediterranean coast of the Iberian Peninsula, bioclimatic indicators show an increase in thermal discomfort. This is especially relevant in regions with a clear focus on mass and seasonal sun and beach tourism, with a large number of tourists experiencing discomfort in hot and humid summer environments. The research analyses the temporal evolution (1967–2022) of the coasts of the provinces of Alicante and Murcia (Spain) using the Climate Comfort Index (CCI), divided into four different regions. Used are 14 coastal meteorological observatories divided into four regions. Trend analysis was performed using the Mann–Kendall (MKT) and Theil–Sen (TSE) tests. The results revealed a loss of climate comfort during the summer season (−0.3 to −0.4/decade), as well as an expansion of the warm period toward June and early September, with an increase of 38.7 days in “hot” thermal comfort. The increase in thermal discomfort in the summer is influenced by an increase in average temperature (0.5 to 0.7 °C/decade) and a reduction in the average relative humidity (−1.0 to −2.1%/decade) and wind speed (−0.2 to −0.9 km/h/decade). In the last 22 years (2000–2022), decreases (p  ≤ 0.05) have been recorded in July and September (−0.2 to −0.4/decade), reaching “excessive heat” climatic comfort thresholds for the first time. Finally, there has been an increase in thermal comfort in winter, especially during December in recent years (2000–2022).
      Citation: Climate
      PubDate: 2023-11-17
      DOI: 10.3390/cli11110230
      Issue No: Vol. 11, No. 11 (2023)
  • Climate, Vol. 11, Pages 197: Global Riverine Archaeology and Cultural
           Heritage: Flood-Risk Management and Adaptation for the Anthropogenic
           Climate Change Crisis

    • Authors: Bethune Carmichael, Cathy Daly, Sandra Fatorić, Mark Macklin, Sue McIntyre-Tamwoy, Witiya Pittungnapoo
      First page: 197
      Abstract: Significant riverine archaeological sites around the world are vulnerable to flooding associated with climate change. However, identifying sites most at risk is not straightforward. We critically review the parameters used in 22 published analyses of risk to riverine archaeology from climate change (ARRACC). Covering 17 countries globally, the ARRACC’s risk parameters are highly variable. Proximity to rivers and projected changes to extreme flood frequency are the most commonly employed. However, to be robust, future ARRACC should select from a wider range of hazard parameters, including channel mobility/type, erosion/sedimentation patterns, land use and engineering works, as well as parameters for site sensitivity to flooding and heritage significance. To assist in this, we propose a basic field survey for ARRACC, to be treated primarily as a conceptual checklist or as a starting point for a bespoke ARRACC method adapted for a particular river and the objectives of local stakeholders. The framework proposes a pathway to optimal prioritisation of sites most in need of adaptation so that scarce management resources can be targeted.
      Citation: Climate
      PubDate: 2023-09-25
      DOI: 10.3390/cli11100197
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 198: Assessing the Hydrological Impacts of Climate
           Change on the Upper Benue River Basin in Nigeria: Trends, Relationships,
           and Mitigation Strategies

    • Authors: Andrew Ezra, Kai Zhu, Lóránt Dénes Dávid, Barnabas Nuhu Yakubu, Krisztian Ritter
      First page: 198
      Abstract: The impact of climate change on river systems is a multifaceted threat to the environment, affecting various aspects of ecosystems. The Upper Benue River Basin (UBRB) in Nigeria is an area of concern, as river flow and water levels are crucial for irrigation and transportation. In this study, we investigate the impact of climate change on the hydrology of the UBRB using data on rainfall, temperature, relative humidity, wind speed, river discharge, and water level. Trend, correlation, and stepwise regression analyses were conducted using Excel and SPSS 20 to analyze the data. The results indicate that the UBRB is experiencing climate change, as evidenced by annual decreases in rainfall and relative humidity and increases in maximum and minimum temperatures. Specifically, mean annual rainfall and relative humidity exhibit a negative trend, while the maximum and minimum temperature exhibit a positive trend. Furthermore, we found that rainfall and relative humidity have a significant positive relationship with river discharge and level (p < 0.01), whereas maximum temperature and wind speed have a significant negative relationship with water discharge and level. We also identified wind speed and rainfall as the critical climatic indices influencing river discharge, accounting for 21.7% of the variation in river discharge within the basin (R2 = 21.7). Based on these findings, we conclude that increases in rainfall and relative humidity will lead to significant increases in river discharge and level, while increases in wind speed and maximum temperature will decrease river discharge and level. Moreover, wind speed and rainfall are the critical climatic indices influencing river discharge, whereas relative humidity, wind speed, and rainfall are the critical climatic indices influencing water level. Thus, we recommend constructing more reservoirs (dams) to mitigate the negative trend in rainfall and encourage climate change control, such as afforestation among the population of the region. These findings have important implications for understanding the impact of climate change on river systems and developing effective strategies to mitigate its effects.
      Citation: Climate
      PubDate: 2023-09-26
      DOI: 10.3390/cli11100198
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 199: Dynamic and Non-Linear Analysis of the Impact
           of Diurnal Temperature Range on Road Traffic Accidents

    • Authors: Yuo-Hsien Shiau, Su-Fen Yang, Rishan Adha, Giia-Sheun Peng, Syamsiyatul Muzayyanah
      First page: 199
      Abstract: The diurnal temperature range (DTR) is a significant indicator of climate change, and a previous study has shown its impact on human health. However, research investigating the influence of DTR on road traffic accidents is scarce. Thus, this study aims to evaluate the impact of changes in DTR on road traffic accidents. The present study employs two methods to address the complexities of road accidents. Firstly, panel data from 20 cities and counties in Taiwan are utilized, and the autoregressive distributed lag (ARDL) model is employed for estimation. Secondly, distributed lag non-linear models (DLNMs) are used with quasi-Poisson regression analysis to assess the DTR’s lagged and non-linear relationships with road accidents using time series data from six Taiwanese metropolitan cities. The study results indicate that a decrease of 1 °C in DTR raises long-term road traffic accidents by 17.1%. In the short term, the impact of declining DTR on road accidents is around 4%. Moreover, the effect of low DTR values differs in each city in Taiwan. Three cities had high levels of road accidents, as evidenced by an increase in the relative risk value; two cities had moderate responses; and one city had a relatively lower response compared to high DTR values. Finally, based on the cumulative relative risk estimations, the study found that a low diurnal temperature range is linked to a high road traffic accident rate, especially during the lag-specific 0–5 months. The findings of this study offer fresh evidence of the negative impact of climate factor on road traffic accidents.
      Citation: Climate
      PubDate: 2023-10-02
      DOI: 10.3390/cli11100199
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 200: Machine Learning for Simulation of Urban Heat
           Island Dynamics Based on Large-Scale Meteorological Conditions

    • Authors: Mikhail Varentsov, Mikhail Krinitskiy, Victor Stepanenko
      First page: 200
      Abstract: This study considers the problem of approximating the temporal dynamics of the urban-rural temperature difference (ΔT) in Moscow megacity using machine learning (ML) models and predictors characterizing large-scale weather conditions. We compare several ML models, including random forests, gradient boosting, support vectors, and multi-layer perceptrons. These models, trained on a 21-year (2001–2021) dataset, successfully capture the diurnal, synoptic-scale, and seasonal variations of the observed ΔT based on predictors derived from rural weather observations or ERA5 reanalysis. Evaluation scores are further improved when using both sources of predictors simultaneously and involving additional features characterizing their temporal dynamics (tendencies and moving averages). Boosting models and support vectors demonstrate the best quality, with RMSE of 0.7 K and R2 > 0.8 on average over 21 years. For three selected summer and winter months, the best ML models forced only by reanalysis outperform the comprehensive hydrodynamic mesoscale model COSMO, supplied by an urban canopy scheme with detailed city-descriptive parameters and forced by the same reanalysis. However, for a longer period (1977–2023), the ML models are not able to fully reproduce the observed trend of ΔT increase, confirming that this trend is largely (by 60–70%) driven by megacity growth. Feature importance assessment indicates the atmospheric boundary layer height as the most important control factor for the ΔT and highlights the relevance of temperature tendencies as additional predictors.
      Citation: Climate
      PubDate: 2023-10-02
      DOI: 10.3390/cli11100200
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 201: Assessment of Climate Change Impact on
           Hydropower Generation: A Case Study for Três Marias Power Plant in

    • Authors: Benedito Cláudio da da Silva, Rebeca Meloni Virgílio, Luiz Augusto Horta Nogueira, Paola do Nascimento Silva, Filipe Otávio Passos, Camila Coelho Welerson
      First page: 201
      Abstract: Study region: The Três Marias 396 MW power plant located on the São Francisco River in Brazil. Study focus: Hydropower generation is directly and indirectly affected by climate change. It is also a relevant source of energy for electricity generation in many countries. Thus, methodologies need to be developed to assess the impacts of future climate scenarios. This is essential for effective planning in the energy sector. Energy generation at the Três Marias power plant was estimated using the water balance of the reservoir and the future stream flow projections to the power plant, for three analysis periods: FUT1 (2011–2040); FUT2 (2041–2070); and FUT3 (2071–2100). The MGB-IPH hydrological model was used to assimilate precipitation and other climatic variables from the regional Eta climatic model, via global models HadGEM2-ES and MIROC5 for scenarios RCP4.5 and RCP8.5. New hydrological insights for the region: The results show considerable reductions in stream flows and consequently, energy generation simulations for the hydropower plant were also reduced. The average power variations for the Eta-MIROC5 model were the mildest, around 7% and 20%, while minimum variations for the Eta-HadGEM2-ES model were approximately 35%, and almost 65% in the worst-case scenario. These results reinforce the urgent need to consider climate change in strategic Brazilian energy planning.
      Citation: Climate
      PubDate: 2023-10-05
      DOI: 10.3390/cli11100201
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 202: Adaptation of Agriculture to Climate Change:
           A Scoping Review

    • Authors: Elena Grigorieva, Alexandra Livenets, Elena Stelmakh
      First page: 202
      Abstract: Since agricultural productivity is weather and climate-related and fundamentally depends on climate stability, climate change poses many diverse challenges to agricultural activities. The objective of this study is to review adaptation strategies and interventions in countries around the world proposed for implementation to reduce the impact of climate change on agricultural development and production at various spatial scales. A literature search was conducted in June–August 2023 using electronic databases Google Scholar and Scientific Electronic Library eLibrary.RU, seeking the key words “climate”, “climate change”, and “agriculture adaptation”. Sixty-five studies were identified and selected for the review. The negative impacts of climate change are expressed in terms of reduced crop yields and crop area, impacts on biotic and abiotic factors, economic losses, increased labor, and equipment costs. Strategies and actions for agricultural adaptation that can be emphasized at local and regional levels are: crop varieties and management, including land use change and innovative breeding techniques; water and soil management, including agronomic practices; farmer training and knowledge transfer; at regional and national levels: financial schemes, insurance, migration, and culture; agricultural and meteorological services; and R&D, including the development of early warning systems. Adaptation strategies depend on the local context, region, or country; limiting the discussion of options and measures to only one type of approach—"top-down” or “bottom-up”—may lead to unsatisfactory solutions for those areas most affected by climate change but with few resources to adapt to it. Biodiversity-based, or “ecologically intensive” agriculture, and climate-smart agriculture are low-impact strategies with strong ecological modernization of agriculture, aiming to sustainably increase agricultural productivity and incomes while addressing the interrelated challenges of climate change and food security. Some adaptation measures taken in response to climate change may not be sufficient and may even increase vulnerability to climate change. Future research should focus on adaptation options to explore the readiness of farmers and society to adopt new adaptation strategies and the constraints they face, as well as the main factors affecting them, in order to detect maladaptation before it occurs.
      Citation: Climate
      PubDate: 2023-10-06
      DOI: 10.3390/cli11100202
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 203: Assessing the Emissions Related to European
           Households’ Expenditures and Their Impact on Achieving Carbon

    • Authors: Ilaria Perissi, Davide Natalini, Aled Jones
      First page: 203
      Abstract: The European Green Deal comprises various policy initiatives with the goal of reaching carbon neutrality by 2050. The “Fit for 55 packages” include the Social Climate Fund, which aims to help, among others, vulnerable households and transport users meet the costs of the green energy transition. Thus, analyzing households’ expenditures and the associated carbon emissions is crucial to achieving a net-zero society. In the present study, we combine scenarios of households’ expenditures according to the Classification of Individual Consumption According to Purpose with economic decoupling scenarios to assess, for the first time, the European carbon budget allocation on a consumption basis. Expenditure projections based on socioeconomic scenarios were calculated using the Bayesian structural time series, and the associated emissions were estimated through the greenhouse gas intensity of the Gross Domestic Product. The model can be used to report the carbon budget of households and monitor the effectiveness of the measures funded by the Social Climate Fund. However, the emissions burden obtained by means of averaged greenhouse gas intensity of Gross Domestic Product results in a rough approximation of outcomes, and more accurate indicators should be developed across the member states.
      Citation: Climate
      PubDate: 2023-10-10
      DOI: 10.3390/cli11100203
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 204: The Effect of Climate Variability on
           Cultivated Crops’ Yield and Farm Income in Chiang Mai Province,

    • Authors: Yadanar Kyaw, Thi Phuoc Lai Nguyen, Ekbordin Winijkul, Wenchao Xue, Salvatore G. P. Virdis
      First page: 204
      Abstract: Agriculture, entwined with climatic conditions, plays a pivotal role in Thailand’s sustenance and economy. This study aimed to examine the trends of climate variability and its correlation with crop yields and social and farm factors affecting farm net income in Chiang Mai province, Thailand. Time series climate data (2002–2020) on temperature and rainfall and yields were analyzed using the Mann–Kendall trend test and Sen’s slope estimation to investigate the trends and their changes. The Pearson correlation was used to assess the association between climate variability and cultivated crop yields, and multiple linear regression was used to detect the factors influencing the farm net income. The findings show that the total annual rainfall showed an unchanged trend, but the annual temperature increased over time. Higher temperature negatively impacted longan yield but positively affected maize, with no significant impact on rice yield. The rainfall trend had no effect on crop yields. Despite declining trends in some cultivated crops’ yield, farm net income was unaffected by individual crop types. Farm income relied on cumulative output and geographic location. This research emphasizes the need for integrating climate data and forecasting models considering agronomic and socio-economic factors and crop suitability assessments for specific regions into adaptation policies and practice.
      Citation: Climate
      PubDate: 2023-10-11
      DOI: 10.3390/cli11100204
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 205: Assessing the Reliability of Global Carbon
           Flux Dataset Compared to Existing Datasets and Their Spatiotemporal

    • Authors: Zili Xiong, Wei Shangguan, Vahid Nourani, Qingliang Li, Xingjie Lu, Lu Li, Feini Huang, Ye Zhang, Wenye Sun, Hua Yuan, Xueyan Li
      First page: 205
      Abstract: Land carbon fluxes play a critical role in ecosystems, and acquiring a comprehensive global database of carbon fluxes is essential for understanding the Earth’s carbon cycle. The primary methods of obtaining the spatial distribution of land carbon fluxes include utilizing machine learning models based on in situ measurements, estimating through satellite remote sensing, and simulating ecosystem models. Recently, an innovative machine learning product known as the Global Carbon Flux Dataset (GCFD) has been released. In this study, we assessed the reliability of the GCFD by comparing it with existing data products, including two machine learning products (FLUXCOM and NIES (National Institute for Environmental Studies)), two ecosystem model products (TRENDY and EC-LUE (eddy covariance–light use efficiency model)), and one remote sensing product (Global Land Surface Satellite), on both site and global scales. Our findings indicate that, in terms of average absolute difference, the spatial distribution of the GCFD is most similar to the NIES product, albeit with slightly larger discrepancies compared to the other two types of products. When using site observations as the benchmark, gross primary production (GPP), respiration of ecosystem (RECO), and net ecosystem exchange of machine learning products exhibit higher R2 (ranging from 0.57 to 0.85, 0.53–0.79, and 0.31–0.70, respectively) compared to model products and remote sensing products. Furthermore, we analyzed the spatial and temporal distribution characteristics of carbon fluxes in various regions. The results demonstrate an upward trend in both GPP and RECO over the past two decades, while NEE exhibits an opposite trend. This trend is particularly pronounced in tropical regions, where higher GPP is observed in tropical, subtropical, and oceanic climate zones. Additionally, two remote sensing variables that influence changes in carbon fluxes, i.e., fraction absorbed photosynthetically active radiation and leaf area index, exhibit relatively consistent spatial and temporal characteristics. Overall, our study can provide valuable insights into different types of carbon flux products and contribute to understanding the general features of global carbon fluxes.
      Citation: Climate
      PubDate: 2023-10-11
      DOI: 10.3390/cli11100205
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 206: The Response of Daily Carbon Dioxide and
           Water Vapor Fluxes to Temperature and Precipitation Extremes in Temperate
           and Boreal Forests

    • Authors: Daria Gushchina, Maria Tarasova, Elizaveta Satosina, Irina Zheleznova, Ekaterina Emelianova, Ravil Gibadullin, Alexander Osipov, Alexander Olchev
      First page: 206
      Abstract: Forest ecosystems in the mid-latitudes of the Northern Hemisphere are significantly affected by frequent extreme weather events. How different forest ecosystems respond to these changes is a major challenge. This study aims to assess differences in the response of daily net ecosystem exchange (NEE) of CO2 and latent heat flux (LE) between different boreal and temperate ecosystems and the atmosphere to extreme weather events (e.g., anomalous temperature and precipitation). In order to achieve the main objective of our study, we used available reanalysis data and existing information on turbulent atmospheric fluxes and meteorological parameters from the global and regional FLUXNET databases. The analysis of NEE and LE responses to high/low temperature and precipitation revealed a large diversity of flux responses in temperate and boreal forests, mainly related to forest type, geographic location, regional climate conditions, and plant species composition. During the warm and cold seasons, the extremely high temperatures usually lead to increased CO2 release in all forest types, with the largest response in coniferous forests. The decreasing air temperatures that occur during the warm season mostly lead to higher CO2 uptake, indicating more favorable conditions for photosynthesis at relatively low summer temperatures. The extremely low temperatures in the cold season are not accompanied by significant NEE anomalies. The response of LE to temperature variations does not change significantly throughout the year, with higher temperatures leading to LE increases and lower temperatures leading to LE reductions. The immediate response to heavy precipitation is an increase in CO2 release and a decrease in evaporation. The cumulative effect of heavy precipitations is opposite to the immediate effect in the warm season and results in increased CO2 uptake due to intensified photosynthesis in living plants under sufficient soil moisture conditions.
      Citation: Climate
      PubDate: 2023-10-12
      DOI: 10.3390/cli11100206
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 207: Autumn Surface Wind Trends over California
           during 1979–2020

    • Authors: Callum F. Thompson, Charles Jones, Leila Carvalho, Anna T. Trugman, Donald D. Lucas, Daisuke Seto, Kevin Varga
      First page: 207
      Abstract: Surface winds over California can compound fire risk during autumn, yet their long-term trends in the face of decadal warming are less clear compared to other climate variables like temperature, drought, and snowmelt. To determine where and how surface winds are changing most, this article uses multiple reanalyses and Remote Automated Weather Stations (RAWS) to calculate autumn 10 m wind speed trends during 1979–2020. Reanalysis trends show statistically significant increases in autumn night-time easterlies on the western slopes of the Sierra Nevada. Although downslope windstorms are frequent to this region, trends instead appear to result from elevated gradients in warming between California and the interior continent. The result is a sharper horizontal temperature gradient over the Sierra crest and adjacent free atmosphere above the foothills, strengthening the climatological nocturnal katabatic wind. While RAWS records show broad agreement, their trend is likely influenced by year-to-year changes in the number of observations.
      Citation: Climate
      PubDate: 2023-10-12
      DOI: 10.3390/cli11100207
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 208: Modeling the Effects of Local Atmospheric
           Conditions on the Thermodynamics of Sobradinho Lake, Northeast Brazil

    • Authors: Eliseu Oliveira Afonso, Sin Chan Chou
      First page: 208
      Abstract: The objective of this work was to study climate variability and its impacts on the temperature of Sobradinho Lake in Northeast Brazil. Surface weather station data and lake measurements were used in this study. The model applied in this work is FLake, which is a one-dimensional model used to simulate the vertical temperature profile of freshwater lakes. First, the climate variability around Sobradinho Lake was analyzed. Observations showed a reduction in precipitation during 1991–2020 compared to 1981–2010. To study climate variability impacts on Sobradinho Lake, the years 2013, 2015, and 2020 were selected to characterize normal, dry, and rainy years, respectively. In addition, the months of January, April, July, and October were analyzed for rainy months, rainy–dry transitions, dry months, and dry–rainy transitions. Dry years showed higher incoming solar radiation at the surface and, consequently, higher 2 m air temperatures. A characteristic of the normal years was more intense surface winds. October presented the highest incoming solar radiation, the highest air temperature, and the most intense winds at the surface. The lowest incoming solar radiation at the surface was observed in January, and the lightest wind was observed in April. To assess the effects of these atmospheric conditions on the thermodynamics of Sobradinho Lake, the FLake model was forced using station observation data. The thermal amplitude of the lake surface temperature (LST) varied by less than 1 °C during the four months. This result was validated against surface lake observations. FLake was able to accurately reproduce the diurnal cycle variation in sensible heat fluxes (H), latent heat fluxes, and momentum fluxes. The sensible heat flux depends directly on the difference between the LST and the air temperature. During daytime, however, Flake simulated negative values of H, and during nighttime, positive values. The highest values of latent heat flux were simulated during the day, with the maximum value was simulated at 12:00 noon. The momentum flux simulated a similar pattern, with the maximum values simulated during the day and the minimum values during the night. The FLake model also simulated the deepest mixing layer in the months of July and October. However, our results have limitations due to the lack of observed data to validate the simulations.
      Citation: Climate
      PubDate: 2023-10-17
      DOI: 10.3390/cli11100208
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 209: Analysis of the Gálvez–Davison
           Index for the Forecasting Formation and Evolution of Convective Clouds in
           the Tropics: Western Cuba

    • Authors: Tahimy Fuentes-Alvarez, Pedro M. González-Jardines, José C. Fernández-Alvarez, Laura de la Torre, Juan A. Añel
      First page: 209
      Abstract: The Gálvez–Davison Index (GDI) is an atmospheric stability index recently developed to improve the prediction of thunderstorms and shallower types of moist convection in the tropics. Because of its novelty, its use for tropical regions remains largely unexplored. Cuba is a region that suffers extreme weather events, such as tropical storms and hurricanes, some of them worsened by climate change. This research analyzes the effectiveness of the GDI in detecting the potential for convective cloud development, using forecast data from the Weather Research and Forecasting (WRF) model for Western Cuba. To accomplish this, here, we evaluated the performance of the GDI in ten study cases from the dry and wet seasons. As part of our study, we researched how GDI correlates with brightness temperatures (BTs) measured using GOES-16. In addition, the GDI results with the WRF model are compared with results using the Global Forecast System (GFS). Our results show a high correlation between the GDI and BT, concluding that the GDI is a robust tool for forecasting both synoptic and mesoscale convective phenomena over the region studied. In addition, the GDI is able to adequately forecast stability conditions. Finally, the GDI values computed from the WRF model perform much better than those from the GFS, probably because of the greater horizontal resolution in the WRF model.
      Citation: Climate
      PubDate: 2023-10-18
      DOI: 10.3390/cli11100209
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 210: Changing Climatic Conditions in Czechia
           Require Adaptation Measures in Agriculture

    • Authors: Martin Mozny, Lenka Hajkova, Vojtech Vlach, Veronika Ouskova, Adela Musilova
      First page: 210
      Abstract: Changes in climatic conditions increase risks associated with crop production in certain regions. Early detection of these changes enables the implementation of suitable adaptation measures in the local area, thereby stabilising agricultural production. Our analysis shows a significant shift in climatic conditions in Czechia between 1961 and 2020. We examined the changes in observed temperature conditions, precipitation distribution, drought occurrences, and frost incidents at a high resolution (0.5 × 0.5 km). The outputs show a significant increase in air temperatures and drought occurrence. Temperature totals above 5 °C in 1991–2020 were 15% higher than in 1961–1990. Furthermore, the relative change in totals above 10 °C was 26% after 1991. Over the last 30 years, drought incidence was four times more frequent than in 1961–1990, particularly in spring. In contrast, no significant changes in the distribution of precipitation occurred, and there was a slight decrease in the probability of frost during the growing season. Ongoing climate change brings warmer and drier conditions to higher-altitude regions in Czechia. Assessing climatic conditions on a global scale is less precise for relatively small and topographically diverse countries like Czechia due to coarse resolution. Therefore, a high-resolution analysis is more appropriate for these countries.
      Citation: Climate
      PubDate: 2023-10-20
      DOI: 10.3390/cli11100210
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 211: Proposal of an Agricultural Vulnerability
           Stochastic Model for the Rural Population of the Northeastern Region of

    • Authors: Bruce Kelly da Nóbrega Silva, Rafaela Lisboa Costa, Fabrício Daniel dos Santos Silva, Mário Henrique Guilherme dos Santos Vanderlei, Helder José Farias da Silva, Jório Bezerra Cabral Júnior, Djailson Silva da Costa Júnior, George Ulguim Pedra, Aldrin Martin Pérez-Marin, Cláudio Moisés Santos e Silva
      First page: 211
      Abstract: Agriculture is the world’s main economic activity. According to the Intergovernmental Panel on Climate Change, this activity is expected to be impacted by drought. In the Northeast region of Brazil (NEB), most agricultural activity is carried out by small rural communities. Local socio-economic data were analyzed using multivariate statistical techniques in this study to determine agricultural sensitivity to drought events (SeA) and agricultural vulnerability to drought extremes (VaED). The climate data used to develop the risk factor (Rdrought) were the drought indicator with the Standard Precipitation Index (SPI) and the average number of drought disasters from 1991 to 2012. Conditional probability theory was applied to determine agricultural vulnerability to drought extremes (VaED). Characterization of the risk of agricultural drought using the proposed methodology showed that the rainy season presents high risk values in the central region, covering areas of the states of Ceará, Piauí, Pernambuco and Rio Grande do Norte, as well as all areas of the semi-arid region. The risk ranged from high to medium. The results also indicated that part of the south of Bahia and the west of Pernambuco have areas of extreme agro-climatic sensitivity. Consequently, these states have an extreme degree of climate vulnerability during the region’s rainy season.
      Citation: Climate
      PubDate: 2023-10-20
      DOI: 10.3390/cli11100211
      Issue No: Vol. 11, No. 10 (2023)
  • Climate, Vol. 11, Pages 212: Homogenous Climatic Regions for Targeting
           Green Water Management Technologies in the Abbay Basin, Ethiopia

    • Authors: Degefie Tibebe, Mekonnen Adnew Degefu, Woldeamlak Bewket, Ermias Teferi, Greg O’Donnell, Claire Walsh
      First page: 212
      Abstract: Spatiotemporal climate variability is a leading environmental constraint to the rain-fed agricultural productivity and food security of communities in the Abbay basin and elsewhere in Ethiopia. The previous one-size-fits-all approach to soil and water management technology targeting did not effectively address climate-induced risks to rain-fed agriculture. This study, therefore, delineates homogenous climatic regions and identifies climate-induced risks to rain-fed agriculture that are important to guide decisions and the selection of site-specific technologies for green water management in the Abbay basin. The k-means spatial clustering method was employed to identify homogenous climatic regions in the study area, while the Elbow method was used to determine an optimal number of climate clusters. The k-means clustering used the Enhancing National Climate Services (ENACTS) daily rainfall, minimum and maximum temperatures, and other derived climate variables that include daily rainfall amount, length of growing period (LGP), rainfall onset and cessation dates, rainfall intensity, temperature, potential evapotranspiration (PET), soil moisture, and AsterDEM to define climate regions. Accordingly, 12 climate clusters or regions were identified and mapped for the basin. Clustering a given geographic region into homogenous climate classes is useful to accurately identify and target locally relevant green water management technologies to effectively address local-scale climate-induced risks. This study also provided a methodological framework that can be used in the other river basins of Ethiopia and, indeed, elsewhere.
      Citation: Climate
      PubDate: 2023-10-23
      DOI: 10.3390/cli11100212
      Issue No: Vol. 11, No. 10 (2023)
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School of Mathematical and Computer Sciences
Heriot-Watt University
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