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Climate
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  This is an Open Access Journal Open Access journal
ISSN (Print) 2225-1154
Published by MDPI Homepage  [249 journals]
  • Climate, Vol. 11, Pages 26: White Identity and Climate Change Skepticism:
           Assessing the Mediating Roles of Social Dominance Orientation and
           Conspiratorial Ideation

    • Authors: Matthew Grindal, Dilshani Sarathchandra, Kristin Haltinner
      First page: 26
      Abstract: Prior research has found that white people are more likely to be climate change skeptics. In much of this prior work, white identity is treated as a categorical label, limiting the theoretical and empirical understanding of this relationship. Drawing on survey data from a US national sample of 933 white young adults, we theorize that white identity is a developmental process where people explore the meanings of their racial identity and commit to a white identity marked by enhanced levels of social dominance orientation and conspiratorial ideation, two social-psychological constructs consistently associated with climate change skepticism. Using regression analyses, we tested a mediation model that a strong white identity would increase climate change skepticism by enhancing one’s social dominance orientation and conspiratorial ideation. We found partial support for our model. While a strong white identity was positively associated with social dominance orientation and conspiratorial ideation, only social dominance orientation increased climate change skepticism. Conspiratorial ideation reduced climate change skepticism. We discuss the implications of our findings for the climate change literature as well as how our findings can inform policies that could reduce climate change skepticism among white people.
      Citation: Climate
      PubDate: 2023-01-17
      DOI: 10.3390/cli11020026
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 27: Precipitation Variability for Protected Areas
           of Primary Forest and Pastureland in Southwestern Amazônia

    • Authors: Rodrigo Martins Moreira, Bruno César dos Santos, Rafael Grecco Sanches, Vandoir Bourscheidt, Fernando de Sales, Stefan Sieber, Paulo Henrique de Souza
      First page: 27
      Abstract: Daily and monthly rainfall data provided by surface rain gauges in the Amazon Basin are sparse and defective, making it difficult to monitor rainfall patterns for certain portions of its territory, in this sense, estimations of precipitation from remote sensing calibrated with rain gauge data are key to overcome this problem. This paper presents a spatiotemporal analysis of the precipitation distribution for Rondônia State, in southwestern Amazonia. Data from Climate Hazards Group InfraRed Precipitation and Station (CHIRPS) were analyzed, using a pooled time analysis of a forty-year period (1981–2020). Data obtained from remote sensing were validated by rain gauges distributed over the study region. Pixel-by-pixel trend analyzes were developed by applying the Mann-Kendall test and Sen’s slope test to study the magnitude of the trend. The analysis revealed that CHIRPS presents a tendency to underestimate precipitation values in most cases. Among the metrics, mean values between very good (<±15%) and good (±15–±35%) were observed using PBIAS; mean RMSE values range from 57.8 mm to 107.9 mm; an average agreement level of 0.9 and an average SES of 0.5; and good fit for the linear regression model (average R2 > 0.70) for about 64.7% of the stations. Sen’ slope spatialization results show a reduction of approximately −15 mm year−1, with decrease mainly in the Northern Region of Rondônia, which has extensive areas where the native forest has been replaced by pasture.
      Citation: Climate
      PubDate: 2023-01-17
      DOI: 10.3390/cli11020027
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 28: Impact of Blue Space Geometry on Urban Heat
           Island Mitigation

    • Authors: Petros Ampatzidis, Carlo Cintolesi, Tristan Kershaw
      First page: 28
      Abstract: A growing body of literature recognises the importance of nature-based solutions in providing resilience to the effects of climate change by mitigating urban heat islands. However, a knowledge gap exists regarding the contribution of blue spaces to the urban environment. Recent evidence suggests that blue spaces within urban canyons can promote pollutant removal via the vertical transport of air under certain conditions, but this is inconclusive. Using a numerical solver that accounts for evaporation effects, we investigate the influence of blue space size and shape on the in-canyon flow structure, temperature and water vapour distribution. Simulations were performed for water bodies of varying size and shape at different temperatures compared to the surrounding air. Results suggest that inadequately sized warmer water bodies are unable to promote sufficient vertical transport for pollutant removal, leading to overturning and increased temperature and humidity levels at the pedestrian level, thereby worsening environmental conditions and increasing the risk of heat-related illness and mortality. Hence, larger water bodies are better suited to nocturnal transport of pollutants and accumulated warm air away from the urban surface, while smaller water bodies are better suited to providing localised evaporative cooling. Lastly, irregular water bodies may have a greater cooling effect across a larger area.
      Citation: Climate
      PubDate: 2023-01-19
      DOI: 10.3390/cli11020028
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 29: Opportunities for Post−COP26 Governance
           to Facilitate the Deployment of Low−Carbon Energy Infrastructure: An
           Open Door Policy

    • Authors: Muhammad Imran, Shiraz Khan, Khalid Zaman, Muhammad Siddique, Haroon ur Rashid Khan
      First page: 29
      Abstract: Temperatures worldwide continue to climb, while carbon emissions have exceeded previous records. To achieve environmental sustainability, countries with the Kyoto Protocol and Paris Agreement (COP26) demonstrate sophisticated technical expertise and deploy environmentally driven technologies, such as greenfield investment and renewable energy infrastructure. This proposal presents an intriguing opportunity for policymakers to identify the distinct characteristics of institutional reforms and green energy sources that may be used to mitigate carbon emissions. Governance regulatory factors, foreign direct investment (FDI), renewable energy consumption (REC), research and development expenditures, urbanization, and carbon emissions are examined in Pakistan. The study estimated the short- and long-run association between the variables using the ARDL bounds testing method for 1996Q1 to 2020Q4. In the short run, in terms of carbon emissions and economic output, the country has an upturned cord environmental Kuznets curve (EKC). The race-to-the-bottom concept holds for countries with U-shaped EKCs in the long term. The negative correlation between overseas investment and environmental damage supports the environmental halo hypothesis. Investment in research and technology may reduce emissions, even though urbanization increases them. Future and present REC are often intertwined with carbon footprints. Carbon emissions are also strongly connected with indicators of institutional quality (IQ), such as procedural efficiency, administrative effectiveness, and political unrest. The research findings demonstrated unidirectional Granger causality running from urbanization, government effectiveness, economic growth, and R&D expenditures to carbon emissions to validate urban-led emissions, institutional-led emissions, growth-led emissions, and innovation-led emissions in a country. Furthermore, R&D expenditure Granger causality was linked to inbound FDI, while government effectiveness Granger causality was linked to REC and R&D expenditures. Following the COP26 guidelines for achieving shared prosperity, the study concluded that good governance reforms, R&D expenditures, greenfield investment, and REC promote environmental sustainability and maintain air quality.
      Citation: Climate
      PubDate: 2023-01-19
      DOI: 10.3390/cli11020029
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 30: Apparent Temperature Modifies the Effects of
           Air Pollution on Cardiovascular Disease Mortality in Cape Town, South
           Africa

    • Authors: Bukola G. Olutola, Nandi S. Mwase, Joyce Shirinde, Janine Wichmann
      First page: 30
      Abstract: Cardiovascular disease (CVD) is the top cause of mortality and a main contributor to disability globally. The evidence so far is varied on whether cold or heat modifies the CVD effects of air pollution. Weather conditions and air pollution sources and levels are different in different countries. Studies in low-and middle-income countries are lacking. Mortality data were obtained from Statistics South Africa. Air pollution and meteorological data were obtained from the South African Weather Service. A time-stratified case–crossover epidemiological design was applied. The association between air pollutants (PM10, NO2 and SO2) and CVD mortality was investigated using conditional logistic regression models. Susceptibility by sex and age groups was investigated. In total, 54,356 CVD deaths were included in the 10-year study. The daily PM10, NO2 and SO2 levels exceeded the daily WHO guidelines on 463, 421 and 8 days of the 3652 days, respectively. Higher air pollution risks were observed in this study compared to those reported in meta-analyses. In general, the elderly and females seemed to be vulnerable to air pollutants, especially at high and moderate apparent temperature levels. Harvesting effects were observed at longer lags. The results can be used to develop an early warning system for the city.
      Citation: Climate
      PubDate: 2023-01-19
      DOI: 10.3390/cli11020030
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 31: Evaluation of the Impact of Seasonal
           Agroclimatic Information Used for Early Warning and Farmer
           Communities’ Vulnerability Reduction in Southwestern Niger

    • Authors: Tinni Halidou Seydou, Alhassane Agali, Sita Aissatou, Traore B. Seydou, Lona Issaka, Bouzou Moussa Ibrahim
      First page: 31
      Abstract: In Niger (a fully Sahelian country), the use of climate information is one of the early warning strategies (EWSs) for reducing socio-economic vulnerabilities in farmer communities. It helps farmers to better anticipate risks and choose timely alternative options that can allow them to generate more profit. This study assesses the impacts of the use of climate information and services that benefit end-users. Individual surveys and focus groups were conducted with a sample of 368 people in eight communes in Southwestern Niger. The survey was conducted within the framework of the ANADIA project implemented by the National Meteorological Direction (NMD) of Niger. The survey aims to identify different types of climate services received by communities and evaluates the major benefits gained from their use. Mostly, the communities received climate (73.6%) and weather (99%) information on rainfall, temperature, dust, wind, clouds, and air humidity. Few producers in the area (10%) received information on seasonal forecasts of the agrometeorological characteristics of the rainy season. The information is not widely disseminated in the villages during the roving seminars conducted by the NMD. For most people, this information is highly relevant to their needs because of its practical advice for options to be deployed to mitigate disasters for agriculture, livestock, health, water resources, and food security. In those communities, 82% of farmers have (at least once) changed their routine practices as a result of the advice and awareness received according to the climate information. The information received enables farmers (64.4%) to adjust their investments according to the profile of the upcoming rainfall season. The use of climate information and related advice led to an increase of about 64 bunches (equivalent to 10 bags of 100 kg) in annual millet production, representing an income increase of about 73,000 FCFA from an average farmland of 3 ha per farmer. In addition, the use of climate information helps to reduce the risks of floods and droughts, which often cause massive losses to crop production, animal and human life, infrastructure, materials, and goods. It has also enabled communities to effectively manage seeds and animal foods and to plan social events, departures and returns to rural exodus. These analyses confirm that the use of climate information serves as an EWS that contributes to increasing the resilience of local populations in the Sahel.
      Citation: Climate
      PubDate: 2023-01-20
      DOI: 10.3390/cli11020031
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 32: The Changing Nature of Hazardous Weather and
           Implications for Transportation: Example from Oklahoma, USA

    • Authors: Esther Mullens, Renee McPherson
      First page: 32
      Abstract: Central Oklahoma is undergoing investment in new intermodal transportation and rehabilitation of its infrastructure. Despite a highly variable historical climate, future changes resulting from anthropogenic climate change may be outside of the range for which infrastructure was designed. We examined 21st century trends, focusing on weather and climate extremes of demonstrated importance to transportation professionals as identified through expert input. We assessed trends from a suite of 15 global climate models (GCMs) using two emissions scenarios and two high-resolution statistically downscaled datasets. This ensemble provided a quantitative range for potential future climate conditions whilst revealing uncertainties associated with different models and downscaling methods. Our results support the general consensus of a reduction in the frequency of cold temperatures, freeze–thaw cycles, and winter weather; however, for the latter, there is not necessarily a reduction in intensity. Extreme heat days (e.g., days ≥100 °F) increased by factors of 3–6, with this upper range associated with high greenhouse gas emissions, while the seasonal duration of extreme heat extended by 4–10 weeks. Projected return intervals for heavy rainfall increased in frequency and magnitude in the mid and late 21st century. Although the contribution of the emissions pathway to these changes is evident, different extreme value distributions and the varying simulations of precipitation from the GCMs have a large effect on magnitudes, leading to a range of possible futures to consider in infrastructure design. Precipitation metrics, particularly at the extremes, were more sensitive to the selection of downscaled data, as compared with temperature metrics. Our approach represents a resource for transportation professionals seeking to identify changing risk probabilities at regional to local scales, as a precursor to planning and adaptation.
      Citation: Climate
      PubDate: 2023-01-20
      DOI: 10.3390/cli11020032
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 33: An Assessment of the Present Trends in
           Temperature and Precipitation Extremes in Kazakhstan

    • Authors: Vitaliy Salnikov, Yevgeniy Talanov, Svetlana Polyakova, Aizhan Assylbekova, Azamat Kauazov, Nurken Bultekov, Gulnur Musralinova, Daulet Kissebayev, Yerkebulan Beldeubayev
      First page: 33
      Abstract: The article presents the results of a study on the assessment of modern space–time trends of extreme values of air temperature and precipitation in 42 meteorological stations throughout Kazakhstan for the period from 1971 to 2020. Spatial and temporal analysis of the distribution of specialized climatic indices was recommended by the WMO climatology commission and an assessment of their trends was carried out. Spatial heterogeneity was revealed in terms of the degree of manifestation of changes and trends. Temperature indices are shown to confirm the overall warming trend. The division of the territory of Kazakhstan by the degree of manifestation of climate change into the southwestern and northeastern half was revealed. Extreme trends are most pronounced in the southwestern half, where a significant trend has been identified both for an increase in extremely high daytime and extremely low night temperatures. The calculated trends in temperature indices are generally significant, but the significance is mainly not ubiquitous; the trends are significant only in certain parts of Kazakhstan. WSDI and CSDI trends were found to confirm a widespread increase in the overall duration of heat waves and a reduction in the overall duration of cold waves. No significant extreme effects were found in the sediments. It is confirmed that Kazakhstan has weak, statistically insignificant, positive and negative trends in the maximum duration of the non-traveling period. Precipitation index trends, unlike temperature ones, are statistically insignificant in most of the country.
      Citation: Climate
      PubDate: 2023-01-23
      DOI: 10.3390/cli11020033
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 34: Efficiency of the NWC SAF Version 2021 CRRPh
           Precipitation Product: Comparison against Previous NWC SAF Precipitation
           Products and the Influence of Topography

    • Authors: Athanasios Karagiannidis, José Alberto Lahuerta, Xavier Calbet, Llorenç Lliso, Konstantinos Lagouvardos, Vassiliki Kotroni, Pilar Ripodas
      First page: 34
      Abstract: The algorithm of the Convective Rainfall Rate with Microphysical Properties (CRRPh) product of the 2021 version of the Nowcasting and Very Short Range Forecasting Satellite Application Facility (NWC SAF) presents innovative characteristics. It was developed employing principal components analysis to reduce the number of utilized parameters and uses the same mathematical scheme for day and night, simulating the missing visual channels and satellite-derived cloud water path information that is unavailable during nighttime. Applying adequate statistical methodologies and scores and using rain gauge data as ground truth, it is shown that the new algorithm appears to be significantly improved compared to its predecessors in regard to the delineation of the precipitation areas. In addition, it minimizes the day–night difference in the estimation efficiency, which is a remarkable achievement. The new product suffers from slightly higher errors in the precipitation accumulations. Finally, it is shown that topography does not seem to affect the estimation efficiency of the product. In light of these results, it is argued that, overall, the new algorithm outperforms its predecessors and, possibly after adequate adaptations, can be used as a real-time total precipitation product.
      Citation: Climate
      PubDate: 2023-01-25
      DOI: 10.3390/cli11020034
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 35: Recent Warming Trends in the Arabian Sea:
           Causative Factors and Physical Mechanisms

    • Authors: Jiya Albert, Venkata Sai Gulakaram, Naresh Krishna Vissa, Prasad K. Bhaskaran, Mihir K. Dash
      First page: 35
      Abstract: In recent years, and particularly from 2000 onwards, the North Indian Ocean (NIO) has been acting as a major sink of ocean heat that is clearly visible in the sub-surface warming trend. Interestingly, a part of the NIO—the Arabian Sea (AS) sector—witnessed dramatic variations in recent sub-surface warming that has direct repercussion on intense Tropical Cyclone (TC) activity. This study investigated the possible causative factors and physical mechanisms towards the multi-decadal warming trends in surface and sub-surface waters over the AS region. Responsible factors towards warming are examined using altimetric observations and reanalysis products. This study used ORAS5 OHC (Ocean Heat Content), derived meridional and zonal heat transport, currents, temperature, salinity, Outgoing Longwave Radiation (OLR), and air-sea fluxes to quantify the OHC build-up and its variability at water depths of 700 m (D700) and 300 m (D300) during the past four decades. The highest variability in deeper and upper OHC is noticed for the western and southern regions of the Indian Ocean. The warming trend is significantly higher in the deeper regions of AS compared to the upper waters, and relatively higher compared to the Bay of Bengal (BoB). Increased OHC in AS show good correlation with decreased OLR in the past 20 years. An analysis of altimetric observations revealed strengthening of downwelling Kelvin wave propagation leading to warming in eastern AS, mainly attributed due to intrusion of low saline water from BoB leading to stratification. Rossby wave associated with deepening of thermocline warmed the southern AS during its propagation. Heat budget analysis reveals that surface heat fluxes play a dominant role in warming AS during the pre-monsoon season. Increasing (decreasing) trend of surface heat fluxes (vertical entrainment) during 2000–2018 played a significant role in warming the southeastern sector of AS.
      Citation: Climate
      PubDate: 2023-01-29
      DOI: 10.3390/cli11020035
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 36: Hydrometeorological Conditions of the Volga
           Flow Generation into the Caspian Sea during the Last Glacial Maximum

    • Authors: Andrey Kalugin, Polina Morozova
      First page: 36
      Abstract: The goal of this study is to evaluate annual and seasonal inflow from the Volga catchment area to the Caspian Sea during the Last Glacial Maximum (LGM ~21,000 years ago) using paleoclimate modeling data. The first approach is based on the LGM simulation by the general circulation models (GCMs) in the framework of the Paleoclimate Modelling Intercomparison Project (PMIP4) and the Coupled Modelling Intercomparison Project (CMIP6). We used four GCMs: INM-CM4-8, MIROC-ES2L, AWI-ESM1-1-LR, and MPI-ESM1-2-LR. The second approach is based on the spatially distributed process-based runoff generation model using PMIP4-CMIP6 model data as boundary conditions. The use of the hydrological ECOMAG model allows us to refine estimates of the Volga runoff in comparison to GCM calculations by considering seasonal features of runoff generation related to periglacial vegetation distribution, permafrost, and streamflow transformation along the channel network. The LGM is characterized by a high uncertainty in meteorological values calculated for the Volga basin using various GCMs. The share of runoff from the three most flooded months from the annual calculated in the LGM was 95%, according to INM-CM4-8, while other GCMs ranged from 69–78%. Three GCMs (MIROC-ES2L, AWI-ESM1-1-LR, and MPI-ESM1-2-LR) showed 83–88% of the present-day value of precipitation in the Volga basin during cooling for more than 10 °C, while INM-CM4-8 showed a two-fold decrease. According to hydrological modeling results using data from three models, the annual Volga runoff was significantly higher than the present-day value, and, when using data from INM-CM4-8, it was lower.
      Citation: Climate
      PubDate: 2023-02-02
      DOI: 10.3390/cli11020036
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 37: Macro-Regional Strategies, Climate Policies
           and Regional Climatic Governance in the Alps

    • Authors: Valentina Cattivelli
      First page: 37
      Abstract: This paper describes the macro-regional governance framework behind the climate adaptation policies that are currently in place in the Alpine area. Through this discussion, it specifically considers the implications of the regional governance of South Tyrol and Lombardy as case studies. Despite rising concern at the European level, there are still no specific guidelines in place for climate change governance at the macro-regional level. Macro-regions encompass multiple regions that have certain shared morphological characteristics. To address climate changes that occur here, they adopt optional larger-scale strategies without adequately considering territorial and governmental specificities at the regional level. Each individual region adopts specific climate adaptation strategies to deal with the challenges of the territories they govern, without considering the effects on their neighbours, decentralises climate policies to the lowest tiers of government, and encourages participation from individuals and non-governmental organisations. The Alpine macro-region is governed by three separate international/transnational institutions at the macro-regional level and is subject to different regulations from each of the 48 regions/autonomous provinces. One of these regions is Lombardy, which is particularly exposed to the effects of climate change due to having the highest values for land consumption and pollution in Italy. From the administrative point of view, it is an ordinary region, which means that it has the same legislative competences of the other Italian regions. South Tyrol is entirely mountainous. Being an autonomous province, it benefits from greater legislative autonomy than ordinary regions. Based on documental analysis of climate adaptation strategies, findings demonstrate that the preferred governance structure involves the presence of a coordinating institution (such as the province in South Tyrol or the region in Lombardy) that decides climate action, along with several other local institutions and stakeholders that have less decision-making power. Its preferred mechanism for addressing specific climate challenges is the definition of specific regulations and the draft of regional and mono-sectoral plans. These regulations do not relate strongly to wider-scale strategies at the macro-regional level, but are inspired by their principles and priorities. At both definition and implementation levels, the participation of local organisations is limited and not incentivised. Administratively, South Tyrol enjoys greater autonomy, whereas Lombardy must comply more closely with state regulations that limit its decision-making freedom.
      Citation: Climate
      PubDate: 2023-02-03
      DOI: 10.3390/cli11020037
      Issue No: Vol. 11, No. 2 (2023)
       
  • Climate, Vol. 11, Pages 12: Atmospheric and Oceanic Patterns Associated
           with Extreme Drought Events over the Paraná Hydrographic Region,
           Brazil

    • Authors: Aline Araújo de Freitas, Michelle Simões Reboita, Vanessa Silveira Barreto Carvalho, Anita Drumond, Simone Erotildes Teleginski Ferraz, Benedito Cláudio da Silva, Rosmeri Porfírio da Rocha
      First page: 12
      Abstract: The Paraná Hydrographic Region (PHR) is one of the main hydrographic basins in Brazil, standing out for its energy generation and consumption, among other ecosystem services. Thus, it is important to identify hydrological drought events and the driest periods inside of these droughts to understand the anomalous atmospheric circulation patterns associated with them (a multiscale study). This study used the standardized precipitation index (SPI) for the 12-month scale to identify hydrological drought episodes in the PHR from 1979 to 2021. For these episodes, the severity, duration, intensity, and peak were obtained, and the SPI-6 was applied to the longest and most severe drought to identify periods with dry conditions during the wet season. Anomalous atmospheric and oceanic patterns associated with such episodes were also analyzed. The results reveal that the longest and most severe hydrological drought on the PHR started in 2016. The end of this episode was not identified by the end of the analyzed period. The SPI-6 revealed three rainy seasons during this drought event marked by anomalous dry conditions: 2016/2017, 2019/2020, and 2020/2021. In general, the circulation patterns identified differ in each period, for example, in 2016/2017, an El Niño event was dominant, in 2019/2020, the tropical Pacific Ocean showed neutral conditions, and in 2020/2021, a La Niña episode was registered. Despite that, in the three periods, the anomalous atmospheric patterns contributed to the weakening of the low-level jet east of the Andes and, consequently, to the decreasing of the moisture transport to the PHR, then leading to dry conditions over the basin.
      Citation: Climate
      PubDate: 2023-01-02
      DOI: 10.3390/cli11010012
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 13: Assessing the Effects of Drought on Rice
           Yields in the Mekong Delta

    • Authors: Kim Lavane, Pankaj Kumar, Gowhar Meraj, Tran Gia Han, Luong Hong Boi Ngan, Bui Thi Bich Lien, Tran Van Ty, Nguyen Truong Thanh, Nigel K. Downes, Nguyen Dinh Giang Nam, Huynh Vuong Thu Minh, Suraj Kumar Singh, Shruti Kanga
      First page: 13
      Abstract: In contrast to other natural disasters, droughts may develop gradually and last for extended periods of time. The World Meteorological Organization advises using the Standardized Precipitation Index (SPI) for the early identification of drought and understanding of its characteristics over various geographical areas. In this study, we use long-term rainfall data from 14 rain gauge stations in the Vietnamese Mekong Delta (1979–2020) to examine correlations with changes in rice yields. Results indicate that in the winter–spring rice cropping season in both 2016 and 2017, yields declined, corresponding with high humidity levels. Excessive rainfall during these years may have contributed to waterlogging, which in turn adversely affected yields. The results highlight that not only drought, but also humidity has the potential to adversely affect rice yield.
      Citation: Climate
      PubDate: 2023-01-03
      DOI: 10.3390/cli11010013
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 14: The Role of Instability Indices in Forecasting
           Thunderstorm and Non-Thunderstorm Days across Six Cities in India

    • Authors: Kopal Arora, Kamaljit Ray, Suresh Ram, Rajeev Mehajan
      First page: 14
      Abstract: Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm prediction
      Citation: Climate
      PubDate: 2023-01-04
      DOI: 10.3390/cli11010014
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 15: Assessment of the Spatial Variation in the
           Occurrence and Intensity of Major Hurricanes in the Western Hemisphere

    • Authors: Luis-Carlos Martinez, David Romero, Eric J. Alfaro
      First page: 15
      Abstract: Major hurricanes are a critical hazard for North and Central America. The present study investigated the trends of occurrence, affectation, and intensity of major hurricanes in the North Atlantic and Northeast Pacific Oceans using GIS applications to the IBTrACS database. The study period ranged from 1970 to 2021. Tropical cyclones were sampled using a grid composed of 3.5° hexagonal cells; in addition, trends were obtained to assess the effect of long-term variability from natural phenomena and climate change. Critical factors influencing these trends at the oceanic scale and for each hexagon were determined using multivariate and multiscale analysis by the application of stepwise analysis and the related ANOVA. The integrated variables related to atmospheric and oceanographic oscillations and patterns, i.e., spatial variables resampled with the same analysis unit and climate indices. Our results indicated marked spatial areas with significant trends in occurrence and intensity. Additionally, there was evidence of linear changes in the number of major hurricanes and an increase in the maximum annual speed of +1.61 m s−1 in the North Atlantic basin and +1.75 m·s−1 in the Northeast Pacific, reported for a 10-year period. In terms of occurrence, there were increases of 19% and 5%, respectively, which may be related to ocean warming and natural variability associated with oceanic and atmospheric circulation.
      Citation: Climate
      PubDate: 2023-01-04
      DOI: 10.3390/cli11010015
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 16: The Variability of Hailfall in Catalonia and
           Its Climatic Implications

    • Authors: Tomeu Rigo, Carme Farnell
      First page: 16
      Abstract: In recent years, some works have forecasted the future scenario of severe weather phenomena, which include large hail. In the present manuscript, the authors focus on a region, Catalonia (NE of the Iberian Peninsula), influenced by complex topography, the Mediterranean Sea, and different air masses. These components are a complicated formula in determining the behavior of the hailfall in the Catalan territory. The events of recent years have shown that expectations and the historical context are not always the best indicators for the future, implying the necessity of the further study of hail events. Using radar fields combined with ground registers and a topographic model permits the characterization of the events in the territory. There is high seasonal and annual variability, with reduced hit areas and small vertical developments in non-summer cases. All these factors are not well solved by the spatial resolution of the current climatic models.
      Citation: Climate
      PubDate: 2023-01-04
      DOI: 10.3390/cli11010016
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 17: Thirty-Five Years of Aerosol–PBAP in
           situ Research in Brazil: The Need to Think outside the Amazonian Box

    • Authors: Maurício C. Mantoani, Jorge A. Martins, Leila Droprinchinski Martins, Federico Carotenuto, Tina Šantl-Temkiv, Cindy E. Morris, Fábio Rodrigues, Fábio L. T. Gonçalves
      First page: 17
      Abstract: Aerosols and primary biological aerosol particles (PBAPs) play an important role in regulating the global climate, but information summarizing the available knowledge is limited. Here, we present a systematic review of in situ studies performed in the last 35 years on aerosols–PBAPs in Brazil, with 212 studies encompassing 474 cases. The Amazon rainforest was the most studied biome, represented by 72% of cases, followed by the Atlantic Forest with 18%. Studies focusing the Amazon mostly investigated climate-related issues and aerosol physics, with less than 5% examining the biological identity of aerosols, whereas outside the Amazon, this number reached 16%. Whilst more than half of the cases within Amazon (55%) were held at seven sampling sites only, conclusions were mainly extrapolated to the entire biome. Contrarily, research beyond the Amazon has mostly addressed the temporal and biological characterisation of PBAPs, and not only is it scattered, but also scarce. Regarding sampling efforts, most cases (72%) had fewer than 100 days of sampling, and 60% of them spanned less than half a year of study. We argue that scientists should produce more detailed/complete assessments of aerosols–PBAPs in Brazil as a whole, particularly considering their biological identity, given their importance to global climate regulation.
      Citation: Climate
      PubDate: 2023-01-05
      DOI: 10.3390/cli11010017
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 18: Climate Change Impacts on the Hydrology of the
           Brahmaputra River Basin

    • Authors: Wahid Palash, Sagar Ratna Bajracharya, Arun Bhakta Shrestha, Shahriar Wahid, Md. Shahadat Hossain, Tarun Kanti Mogumder, Liton Chandra Mazumder
      First page: 18
      Abstract: Climate change (CC) is impacting the hydrology in the basins of the Himalayan region. Thus, this could have significant implications for people who rely on basin water for their lives and livelihoods. However, there are very few studies on the Himalayan river basins. This study aims to fill this gap by presenting a water balance for the Brahmaputra River Basin using the Soil and Water Assessment Tool (SWAT). Results show that snowmelt contributed about 6% of the total annual flow of the whole Brahmaputra, 21% of the upper Brahmaputra, and 5% of the middle Brahmaputra. The basin-wide average annual water yield (AWY) is projected to increase by 8%, with the maximum percentage increase in the pre-monsoon season. The annual snowmelt is projected to decrease by 17%, with a marked decrease during the monsoon but an increase in other seasons and the greatest percentage reduction in the upper Brahmaputra (22%). The contribution of snowmelt to AWY is projected to decrease while rain runoff will increase across the entire Brahmaputra and also in the upper and middle Brahmaputra. The impact assessment suggests that the upper Brahmaputra will be most affected by CC, followed by the middle Brahmaputra. The results can be used to support future water management planning in the basin taking into account the potential impact of CC.
      Citation: Climate
      PubDate: 2023-01-05
      DOI: 10.3390/cli11010018
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 19: The Arctic Winter Seasons 2016 and 2017:
           Climatological Context and Analysis

    • Authors: Monica Ionita
      First page: 19
      Abstract: In this study, we show that the extreme Arctic winter 2015/16 can be partially explained by the superposition of different atmospheric teleconnection patterns, such as the Arctic Oscillation, the Pacific-North American teleconnection, and El Niño—Southern Oscillation, whereas winter 2016/17 had different trigger mechanisms. While the temperature anomalies for winter 2015/16 were mainly driven by the large-scale atmospheric circulation, the temperature anomalies throughout winter 2016/17 may possibly reflect a response to the extremely wet and warm autumn of 2016. The atmospheric circulation anomalies in winter 2016/17 were not as “spectacular” as the ones in the previous winter, but autumn 2016 was one of the most exceptional autumns in the observational record so far and it features some remarkable records: the lowest temperature gradient between the Arctic and the mid-latitudes over the last 70 years, the lowest autumn sea ice extent over the last 40 years, and the warmest and wettest autumn over the last 37 years over most of the Arctic basin. Moreover, we demonstrate that although the background conditions were similar for winters 2015/2016 and 2016/2017 (e.g., reduced sea ice cover, a reduced temperature gradient between the Arctic and the mid-latitudes, and a very warm Barents Sea and Kara Sea in the previous autumn), the response of the atmospheric circulation and the regions affected by extremes (e.g., cold spells and snow cover) were rather different during these two winters.
      Citation: Climate
      PubDate: 2023-01-06
      DOI: 10.3390/cli11010019
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 20: Flash Flood Reconstruction and
           Analysis—A Case Study Using Social Data

    • Authors: Lenise Farias Martins, Ticiana Marinho de Carvalho Studart, João Dehon Pontes Filho, Victor Costa Porto, Francisco de Assis de Souza Filho, Francisco Railson da Silva Costa
      First page: 20
      Abstract: This work proposes a methodology for post-flood analysis in ungauged basins with low data availability located in semi-arid regions. The methodology combines social perception with recorded data. Social perception can be a useful tool to enhance the modeling process in cases where official records are nonexistent or unsatisfactory. For this aim, we structured a four-step methodology. First, we create a repository with the information that reconstructs the analyzed event. Photos and news of the flood event are collected from social media platforms. The next step is to consult official government agencies to obtain documented information about the disaster. Then, semi-structured interviews are carried out with residents to obtain the extension and depth of the flooded spot. This social information creates an overview of the flood event that can be used to evaluate the hydraulic/hydrological modeling of the flood event and the quality of the recorded data. We analyzed a flood event in a city in semi-arid Brazil. The event caused several damages such as the breaking of dams and about 40% of the population was somehow impacted although the official rain data pointed to non-extreme precipitation.
      Citation: Climate
      PubDate: 2023-01-07
      DOI: 10.3390/cli11010020
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 21: Spatiotemporal Kriging for Days without
           Rainfall in a Region of Northeastern Brazil

    • Authors: Elias Silva de Medeiros, Renato Ribeiro de Lima, Carlos Antonio Costa dos Santos
      First page: 21
      Abstract: Climate change has had several negative effects, including more severe storms, warmer oceans, high temperatures and, in particular, increased drought, directly affecting the water availability in a region. The Northeast Region of Brazil (NEB) is known to have scarce rainfall, especially in the northeastern semiarid region. Droughts and high temperatures in the NEB negatively affect water resources in the region, resulting in a gradual decrease in the storage volume in the reservoirs and contributing to unprecedented water scarcity. The objective of this research was to investigate the spatiotemporal behavior of the number of days without rain (DWR) in a region of northeastern Brazil, making use of the spatiotemporal geostatistical methodology. Cross-validation resulted in an R2 of 71%, indicating a good performance of spatiotemporal kriging for predicting DWRs. The results indicate a spatial dependence for a radius of up to 39 km and that the DWR observations in a certain location influence its estimates in the next 2.8 years. The projection maps from 2021 to 2030 identified a growing trend in the DWRs. With the results presented in our study, it is expected that they can be used by government agencies for the adoption of public policies aiming to minimize the possible damage caused by long periods of drought.
      Citation: Climate
      PubDate: 2023-01-09
      DOI: 10.3390/cli11010021
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 22: Conservation and Management of Protected Areas
           in China and India: A Literature Review (1990–2021)

    • Authors: Wen Gao, Jiefan Huang, Quan Qiu, Anil Shrestha, Changyan Yuan, Subhash Anand, Guangyu Wang, Guibin Wang
      First page: 22
      Abstract: Protected areas (PAs) are key to biodiversity conservation. As two highly populous and biodiverse countries, China and India are facing similar socioenvironmental pressures in the management of PAs. A comparative analysis of studies of PA policies in these two countries provides an objective assessment of policy concerns. This study involved a bibliometric analysis of studies of PA policies in China and India. Relevant publications were retrieved from the Web of Science and Scopus. The analysis was carried out using the Bibliometrix R Package, CiteSpace, and VOSviewer. The results indicate that PA policies studies in China are growing at an exponential rate, while Indian studies were cited significantly more often. “Environmental protection” was the main focus of the Chinese studies, with top keywords including “forest ecosystem” and “strategic approach”. In India, research was mainly focused on “wildlife management”, and the top keywords were “climate change” and “ecosystem service”. Studies from both countries were concerned with natural resource conservation and endangered species. Studies in India began relatively earlier and were more developed. India focused on people-related themes, while China emphasized strategic approaches. China is improving its system of PA and should learn from India to consider the relationship between environmental protection and people.
      Citation: Climate
      PubDate: 2023-01-12
      DOI: 10.3390/cli11010022
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 23: Acknowledgment to the Reviewers of Climate in
           2022

    • Authors: Climate Editorial Office Climate Editorial Office
      First page: 23
      Abstract: High-quality academic publishing is built on rigorous peer review [...]
      Citation: Climate
      PubDate: 2023-01-12
      DOI: 10.3390/cli11010023
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 24: Forecasting Impacts on Vulnerable Shorelines:
           Vulnerability Assessment along the Coastal Zone of Messolonghi
           Area—Western Greece

    • Authors: Eleni Filippaki, Evangelos Tsakalos, Maria Kazantzaki, Yannis Bassiakos
      First page: 24
      Abstract: The coastal areas of the Mediterranean have been extensively affected by the transgressive event that followed the Last Glacial Maximum, with many studies conducted regarding the stratigraphic configuration of coastal sediments around the Mediterranean. The coastal zone of the Messolonghi area, western Greece, consists of low-relief beaches, containing low cliffs and eroded dunes, a fact that, in combination with the rising sea levels and tectonic subsidence of the area, has led to substantial coastal erosion. Coastal vulnerability assessment is a useful means of identifying areas of coastline that are vulnerable to impacts of climate change and coastal processes, highlighting potential problem areas. Commonly, coastal vulnerability assessment takes the form of an “index” that quantifies the relative vulnerability along a coastline. Here, the Coastal Vulnerability Index (CVI) methodology by Thieler and Hammar-Klose was employed, by considering geological features, coastal slope, relative sea-level change, shoreline erosion/accretion rates, and mean significant wave height as well as mean tide range, to assess the present-day vulnerability of the coastal zone of the Messolonghi area. In light of this, an impact assessment is performed under three different sea-level-rise scenarios. This study contributes toward coastal zone management practices in low-lying coastal areas that have little data information, assisting decision-makers in adopting best adaptation options to overcome the impact of sea-level rise on vulnerable areas, similar to the coastal zone of Messolonghi.
      Citation: Climate
      PubDate: 2023-01-14
      DOI: 10.3390/cli11010024
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 25: Towards a Safe Hydrogen Economy: An Absolute
           Climate Sustainability Assessment of Hydrogen Production

    • Authors: Kevin Dillman, Jukka Heinonen
      First page: 25
      Abstract: Policymakers and global energy models are increasingly looking towards hydrogen as an enabling energy carrier to decarbonize hard-to-abate sectors (projecting growth in hydrogen consumption in the magnitude of hundreds of megatons). Combining scenarios from global energy models and life cycle impacts of different hydrogen production technologies, the results of this work show that the life cycle emissions from proposed configurations of the hydrogen economy would lead to climate overshoot of at least 5.4–8.1x of the defined “safe” space for greenhouse gas emissions by 2050 and the cumulative consumption of 8–12% of the remaining carbon budget. This work suggests a need for a science-based definition of “clean” hydrogen, agnostic of technology and compatible with a “safe” development of the hydrogen economy. Such a definition would deem blue hydrogen environmentally unviable by 2025–2035. The prolific use of green hydrogen is also problematic however, due to the requirement of a significant amount of renewable energy, and the associated embedded energy, land, and material impacts. These results suggest that demand-side solutions should be further considered, as the large-scale transition to hydrogen, which represents a “clean” energy shift, may still not be sufficient to lead humanity into a “safe” space.
      Citation: Climate
      PubDate: 2023-01-15
      DOI: 10.3390/cli11010025
      Issue No: Vol. 11, No. 1 (2023)
       
  • Climate, Vol. 11, Pages 1: Wetland Water Level Prediction Using Artificial
           Neural Networks—A Case Study in the Colombo Flood Detention Area,
           Sri Lanka

    • Authors: Tharaka Jayathilake, Ranjan Sarukkalige, Yukinobu Hoshino, Upaka Rathnayake
      First page: 1
      Abstract: Historically, wetlands have not been given much attention in terms of their value due to the general public being unaware. Nevertheless, wetlands are still threatened by many anthropogenic activities, in addition to ongoing climate change. With these recent developments, water level prediction of wetlands has become an important task in order to identify potential environmental damage and for the sustainable management of wetlands. Therefore, this study identified a reliable neural network model by which to predict wetland water levels over the Colombo flood detention area, Sri Lanka. This is the first study conducted using machine learning techniques in wetland water level predictions in Sri Lanka. The model was developed with independent meteorological variables, including rainfall, evaporation, temperature, relative humidity, and wind speed. The water levels measurements of previous years were used as dependent variables, and the analysis was based on a seasonal timescale. Two neural network training algorithms, the Levenberg Marquardt algorithm (LM) and the Scaled Conjugate algorithm (SG), were used to model the nonlinear relationship, while the Mean Squared Error (MSE) and Coefficient of Correlation (CC) were used as the performance indices by which to understand the robustness of the model. In addition, uncertainty analysis was carried out using d-factor simulations. The performance indicators showed that the LM algorithm produced better results by which to model the wetland water level ahead of the SC algorithm, with a mean squared error of 0.0002 and a coefficient of correlation of 0.99. In addition, the computational efficiencies were excellent in the LM algorithm compared to the SC algorithm in terms of the prediction of water levels. LM showcased 3–5 epochs, whereas SC showcased 34–50 epochs of computational efficiencies for all four seasonal predictions. However, the d-factor showcased that the results were not within the cluster of uncertainty. Therefore, the overall results suggest that the Artificial Neural Network can be successfully used to predict the wetland water levels, which is immensely important in the management and conservation of the wetlands.
      Citation: Climate
      PubDate: 2022-12-21
      DOI: 10.3390/cli11010001
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 2: A Southeastern United States Warm Season
           Precipitation Climatology Using Unsupervised Learning

    • Authors: Andrew Mercer, Jamie Dyer
      First page: 2
      Abstract: Agriculture in the southeastern United States (SEUS) is heavily reliant upon water resources provided by precipitation during the warm season (June–August). The convective and stochastic nature of SEUS warm season precipitation introduces challenges in terms of water availability in the region by creating localized maxima and minima. Clearly, a detailed and updated warm season precipitation climatology for the SEUS is important for end users reliant on these water resources. As such, a nonlinear unsupervised learning method (kernel principal component analysis blended with cluster analysis) was used to develop a NARR-derived SEUS warm season precipitation climatology. Three clusters resulted from the analysis, all of which strongly resembled the mean spatially (r > 0.9) but had widely variable precipitation magnitude, as one cluster denoted a mean pattern, one a dry pattern, and one a wet pattern. The clusters were related back to major SEUS warm season precipitation moderators (tropical cyclone landfall and the El Niño–southern oscillation (ENSO)) and revealed a clearer ENSO relationship when discriminating among the cluster patterns. Ultimately, these updated SEUS precipitation patterns can help end users identify areas of notable sensitivity to different climate phenomena, helping to optimize the economic use of these critical water resources.
      Citation: Climate
      PubDate: 2022-12-23
      DOI: 10.3390/cli11010002
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 3: A Novel Bias Correction Method for Extreme
           Events

    • Authors: Laura Trentini, Sara Dal Gesso, Marco Venturini, Federica Guerrini, Sandro Calmanti, Marcello Petitta
      First page: 3
      Abstract: When one is using climate simulation outputs, one critical issue to consider is the systematic bias affecting the modelled data. The bias correction of modelled data is often used when one is using impact models to assess the effect of climate events on human activities. However, the efficacy of most of the currently available methods is reduced in the case of extreme events because of the limited number of data for these low probability and high impact events. In this study, a novel bias correction methodology is proposed, which corrects the bias of extreme events. To do so, we extended one of the most popular bias correction techniques, i.e., quantile mapping (QM), by improving the description of extremes through a generalised extreme value distribution (GEV) fitting. The technique was applied to the daily mean temperature and total precipitation data from three seasonal forecasting systems: SEAS5, System7 and GCFS2.1. The bias correction efficiency was tested over the Southern African Development Community (SADC) region, which includes 15 Southern African countries. The performance was verified by comparing each of the three models with a reference dataset, the ECMWF reanalysis ERA5. The results reveal that this novel technique significantly reduces the systematic biases in the forecasting models, yielding further improvements over the classic QM. For both the mean temperature and total precipitation, the bias correction produces a decrease in the Root Mean Squared Error (RMSE) and in the bias between the simulated and the reference data. After bias correcting the data, the ensemble forecasts members that correctly predict the temperature extreme increases. On the other hand, the number of members identifying precipitation extremes decreases after the bias correction.
      Citation: Climate
      PubDate: 2022-12-23
      DOI: 10.3390/cli11010003
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 4: Climate Patterns Affecting Cold Season Air
           Pollution of Ulaanbaatar City, Mongolia

    • Authors: Erdenesukh Sumiya, Sandelger Dorligjav, Myagmartseren Purevtseren, Gantulga Gombodorj, Munkhbat Byamba-Ochir, Oyunchimeg Dugerjav, Munkhnaran Sugar, Bolormaa Batsuuri, Bazarkhand Tsegmid
      First page: 4
      Abstract: Many studies have been conducted on air pollution in Ulaanbaatar city. However, most have focused on the sources of pollutants and their characteristics and distribution. Although the location of the city subjects it to unavoidable natural conditions where air pollution accumulates during the cold season, nature-based solutions have not yet been considered in the projects implemented to mitigate air pollution levels. Therefore, this study aims to determine the combined influence of geography and atmospheric factors on cold season air pollution. The spatiotemporal variations in the variables were investigated using meteorological observation data from 1991 to 2020 in the different land-use areas. Then, atmospheric stagnation conditions and air pollution potential parameters were estimated from daily radiosonde data. Subsequently, the temporal variations in air pollutants were studied and correlated with estimates of the above parameters. In the Ulaanbaatar depression, the stable cold air lake (colder than −13.5 °C), windless (34–66% of all observations), and poor turbulent mixing conditions were formed under the near-surface temperature inversion layer in the cold season. Moreover, due to the mountain topography, the winds toward the city center from all sides cause polluted air to accumulate in the city center for long periods. Air pollution potential was categorized as very high and high (<4000 m2·s−1), in the city in winter, indicating the worst air quality. Thus, further urban planning policy should consider these nature factors.
      Citation: Climate
      PubDate: 2022-12-24
      DOI: 10.3390/cli11010004
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 5: Spatio-Temporal Analysis of Heatwaves
           Characteristics in Greece from 1950 to 2020

    • Authors: Elissavet Galanaki, Chris Giannaros, Vassiliki Kotroni, Kostas Lagouvardos, Georgios Papavasileiou
      First page: 5
      Abstract: Heatwave events are of major concern in the global context, since they can significantly impact ecosystems, economies and societies. For this reason, more detailed analyses of the characteristics and trends of heatwaves represent a priority that cannot be neglected. In this study, the interannual and decadal variability of seven indices of heatwaves were investigated during the warmest period of the year (June–August) by using an enhanced resolution reanalysis model (ERA5-Land) over a 71-year period (1950–2020) for the area of Greece. Heatwaves were defined as periods where two thresholds, based on a modified version of the Excess Heat Factor index (EHF) and the 95th percentile of the maximum daily temperature, were exceeded for at least three consecutive days. Greece experiences almost yearly 0.7 heatwaves on average during the whole period of study, while this value has increased by ~80% since 1990. Trend analysis revealed that heatwaves have become more frequent, longer, and more intense since 1950. The percentage of the land area that experiences at least one heatwave per year was almost doubled in the examined period. An increasing trend in the number of heatwaves that occurred in June was identified.
      Citation: Climate
      PubDate: 2022-12-25
      DOI: 10.3390/cli11010005
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 6: Extreme Coastal Water Levels Evolution at Dakar
           (Senegal, West Africa)

    • Authors: Cheikh Omar Tidjani Cisse, Rafael Almar, Jean Paul Marcel Youm, Serge Jolicoeur, Adelaide Taveneau, Boubou Aldiouma Sy, Issa Sakho, Bamol Ali Sow, Habib Dieng
      First page: 6
      Abstract: Increasingly, it is reported that the coastline of the Dakar region is affected by coastal flooding due to extreme water levels during wave events. Here, we quantify the extreme coastal water levels as well as the different factors contributing to coastal flooding during the period 1994–2015. Severe water levels reach values of 1.78 m and increase by 8.4 mm/year. The time spent above this threshold has already increased by 1.7 over the study period and will increase by 2100 to 8 times with 0.4 m mean sea level rise and up to 20 times with 0.8 m in the IPCC low and high greenhouse gas emission scenarios, respectively. Tide is the main contributor to the extremes when combined with large wave runup, due to wave breaking which contributes to 38% of the increase in extreme events while sea level rises to 44%. Our results show that because of its prominent location, Dakar region is affected by waves coming from the Northern and Southern Hemispheres with contrasted evolutions: wave runup events increase faster (7 mm/year) during austral winter due to a maximum of the South Atlantic storm activity, and have a decreasing trend (−3 mm/year) during boreal winter (December, January, February) driven by the evolution of corresponding climate modes.
      Citation: Climate
      PubDate: 2022-12-26
      DOI: 10.3390/cli11010006
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 7: Impact of Climate Information Services on Crop
           Yield in Ebonyi State, Nigeria

    • Authors: Chinenye Judith Onyeneke, Gibson Nwabueze Umeh, Robert Ugochukwu Onyeneke
      First page: 7
      Abstract: This paper assessed crop farmers’ access and utilization of climate information services (CIS) and impact of CIS use on crop yields in Ebonyi State, Nigeria. The multi-stage sampling procedure was used to select 405 farmers from the State, and data were collected through a survey of the farmers using a questionnaire. We employed descriptive statistics, endogenous treatment effect, and Heckman probit selection model to analyze the data collected. The result indicates that a majority (89%) of the farmers accessed climate information and that the common sources of climate information include agricultural extension officers, fellow farmers, and radio. This study shows that 88% of the farmers used climate information services in making farming decisions. Farmers’ age, household size, marital status, farming experience, income extension contact, ownership of television, ownership of radio, ownership of mobile phone, proximity to the market, workshop/training participation, climate events experienced, and knowledge of appropriate application of fertilizer significantly influenced both access and utilization of CIS. The use of CIS in planning for farming activities significantly increased rice, maize, and cassava yields. The study demonstrates the important contribution of climate information services in crop production. We therefore recommend that access and use of climate information services in agricultural communities should be increased.
      Citation: Climate
      PubDate: 2022-12-26
      DOI: 10.3390/cli11010007
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 8: Evaluation of WRF Microphysics Schemes
           Performance Forced by Reanalysis and Satellite-Based Precipitation
           Datasets for Early Warning System of Extreme Storms in Hyper Arid
           Environment

    • Authors: Mohamed Mekawy, Mohamed Saber, Sayed A. Mekhaimar, Ashraf Saber Zakey, Sayed Robaa, Magdy Abdel Wahab
      First page: 8
      Abstract: In this paper, we will investigate the influence of the microphysics schemes on the rainfall pattern of the extreme storm that impacted Egypt on 12 March 2020. The aim is to improve rainfall forecasting using the numerical Weather Research and Forecasting (WRF) model for an effective Early Warning System (EWS). The performance of six microphysics schemes were evaluated using the Model Object-based Evaluation analysis tool (MODE) forced by three selected satellite-based datasets (CMORPH, PERSIANN, PERSIANN-CCS, etc.) and one reanalysis dataset (ERA5). Six numerical simulations were performed using the WRF model, considering the following microphysics schemes: Lin, WSM6, Goddard, Thompson, Morrison, and NSSL2C. The models were evaluated using both conventional statistical indices and MODE, which is much more suitable in such studies. The results showed that the Lin scheme outperformed the other schemes such as WSM6, Goddard, Thompson, Morrison, and NSSL2C, in rainfall forecasting. The Thompson scheme was found to be the least reliable scheme. An extension for this study is recommended in other regions where the observational rain gauges data are available.
      Citation: Climate
      PubDate: 2022-12-27
      DOI: 10.3390/cli11010008
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 9: Identifying Common Trees and Herbaceous Plants
           to Mitigate Particulate Matter Pollution in a Semi-Arid Mining Region of
           South Africa

    • Authors: Sutapa Adhikari, Madeleen Struwig, Stefan John Siebert
      First page: 9
      Abstract: Plants provide long-term and sustainable solutions to mitigate particulate matter (PM) pollution in urban environments. We evaluated total, fine, coarse and large particle trapping abilities of an equal number of common trees (Carica papaya, Citrus limon, Moringa oleifera, Ozoroa paniculosa, Peltophorum africanum, Psidium guajava) and herbaceous species (Argemone ochroleuca, Catharanthus roseus, Gomphocarpus fruticosus, Ipomoea batatas, Senna italica, Tribulus terrestris) to identify dust accumulators for Sekhukhuneland, a mining–smelting region of South Africa where desertification is becoming problematic. Scanning electron microscopy techniques were used to count and measure particles and relate leaf surface micromorphology to dust accumulation. Three tree and three herbaceous species showed superior dust collection capacity (G. fruticosus > P. guajava > I. batatas > O. paniculosa > C. roseus > M. oleifera). Variations in accumulation of PM sizes were noted among these six species and between adaxial and abaxial leaf surfaces. Compared with large PM, all plants accumulated more fine and coarse fractions which are respirable and thus hazardous to human health. Leaf surface roughness, epicuticular wax and epidermal glands improved dust accumulation. The six preferred plants may serve as forerunner species to abate PM pollution in Sekhukhuneland and other arid regions facing similar climate change and pollution challenges.
      Citation: Climate
      PubDate: 2022-12-28
      DOI: 10.3390/cli11010009
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 10: Growth Response of Red Oaks to Climatic
           Conditions in the Lower Mississippi Alluvial Valley: Implications for
           Bottomland Hardwood Restoration with a Changing Climate

    • Authors: Junyeong Choi, Nana Tian, Jianbang Gan, Matthew Pelkki, Ouname Mhotsha
      First page: 10
      Abstract: Bottomland hardwood forests (BHFs) offer a wide range of ecosystem services that are of high environmental and socioeconomic value. Yet, nearly 70% of BHFs in the southern United States have been lost during the past 100 years primarily due to land use change including agricultural expansion, calling for restoration efforts. We estimated the statistical relationship of the annual radial growth rate of three red oak species with climatic conditions and tree age using the tree ring data collected from a BHF plantation in the Arkansas Delta region. These species were Cherry bark oak (Quercus pagoda), Shumard oak (Quercus shumardii), and Nuttall oak (Quercus texana). The destructive sampling method was employed to obtain tree growth data and the cross-dating method was used for tree age determination. A log-linear regression model was estimated to uncover the statistical relationship between annual tree ring growth rate and climatic conditions. We identified the most critical time windows of climate variables that affect the growth of these trees. We found that the average temperature in October of the previous year and the minimum temperature between December of the previous year and January of the current year were positively associated with the radial growth rate in the current year although the maximum temperature from January to August and total precipitation from April to July of the current year were negatively correlated with the growth rate. Compared to Cherry bark and Shumard oaks, Nuttall oak was less sensitive to a rise in the minimum temperature between December and January. The projected climate change is likely to create slightly more favorable overall climatic conditions for these oak species in the region. Our findings suggest that these three red oak species are well suited for the study region for restoring BHFs, especially with a changing climate.
      Citation: Climate
      PubDate: 2022-12-30
      DOI: 10.3390/cli11010010
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 11, Pages 11: Climate Change Impacts and Adaptation in a
           Hill Farming System of the Himalayan Region: Climatic Trends,
           Farmers’ Perceptions and Practices

    • Authors: Khem Raj Dahal, Piyush Dahal, Raj Kumar Adhikari, Veera Naukkarinen, Dinesh Panday, Niranjan Bista, Juha Helenius, Buddhi Marambe
      First page: 11
      Abstract: Farming communities in the hills and mountains of the Himalayan region are some of the most vulnerable to the changing climate, owing to their specific biophysical and socioeconomic conditions. Understanding the observed parameters of the changing climate and the farmers’ perceptions of it, together with their coping approaches, is an important asset to making farming communities resilient. Therefore, this study aimed to explore the observed change in climatic variables; understand farmers’ perceptions of the changing climate; and document their adaptation approaches in farming systems in the mid-hills of the central Himalayas. Data on the observed change in climatic variables were obtained from the nearby meteorological stations and gridded regional products, and farmers’ perceptions and their adaptation practices were collected from household surveys and from the interviews of key informants. The analysis of temperature data revealed that there has been a clear warming trend. Winter temperatures are increasing faster than summer and annual temperatures, indicating a narrowing temperature range. Results on precipitation did not show a clear trend but exhibited large inter-annual variability. The standardized precipitation index (SPI) showed an increased frequency of droughts in recent years. Farmers’ perceptions of the changing climate are coherent with the observed changes in climatic parameters. These changes may have a substantial impact on agriculture and the livelihood of the people in the study area. The farmers are adapting to climate change by altering their farming systems and practices. Location-specific adaptation approaches used by farmers are valuable assets for community resilience.
      Citation: Climate
      PubDate: 2022-12-30
      DOI: 10.3390/cli11010011
      Issue No: Vol. 11, No. 1 (2022)
       
  • Climate, Vol. 10, Pages 185: Understanding Future Climate in the Upper
           Awash Basin (UASB) with Selected Climate Model Outputs under CMIP6

    • Authors: Yonas Abebe Balcha, Andreas Malcherek, Tena Alamirew
      First page: 185
      Abstract: Climate change makes the climate system of a given region unpredictable and increases the risk of water-related problems. GCMs (global climate models) help in understanding future climate conditions over a given region. In this study, 12 GCMs from the CMIP6 (coupled model intercomparison project six) were evaluated and ranked based on their abilities to describe the historical observed series. The ensemble mean of bias-adjusted best five models of average annual precipitation showed an increment with an uncertainty range of (2.0–11.9) and change in the mean of 6.4% for SSP2-4.5 and (6.1–16.1) 10.6% for SSP5-8.5 in 2040–2069 relative to the historical period. Similarly, for 2070–2099, increments of (2.2–15.0) 7.9% and (11.8–29.4) 19.7% were predicted for the two scenarios, respectively. The average annual maximum temperature series showed increments of (1.3–2.0) 1.6 ∘C for SSP2-4.5 and (1.7–2.3) 2.0 ∘C for SSP5-8.5 in 2040–2069. At the same time, increments of (1.7–2.3) 2.0 ∘C and (2.8–3.2) 3.0 ∘C were predicted for 2070–2099. Furthermore, it was predicted that the average annual minimum temperature series will have increments of (1.6–2.3) 2.0 ∘C and (2.2–2.9) 2.5 ∘C for 2040–2069 and (2.1–2.7) 2.4 ∘C and (3.7–4.2) 4.0 ∘C for 2070–2099 for the two scenarios, respectively. An increase in precipitation with increased land degradation in the sub-basin results in a higher risk of flood events in the future. Improved soil and water conservation practices may minimize the adverse impacts of future climate change on the loss of agricultural productivity.
      Citation: Climate
      PubDate: 2022-11-22
      DOI: 10.3390/cli10120185
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 186: Mapping Open Data and Big Data to Address
           Climate Resilience of Urban Informal Settlements in Sub-Saharan Africa

    • Authors: Banzhaf, Bulley, Inkoom, Elze
      First page: 186
      Abstract: This perspective paper highlights the potentials, limitations, and combinations of openly available Earth observation (EO) data and big data in the context of environmental research in urban areas. The aim is to build the resilience of informal settlements to climate change impacts. In particular, it highlights the types, categories, spatial and temporal scales of publicly available big data. The benefits of publicly available big data become clear when looking at issues such as the development and quality of life in informal settlements within and around major African cities. Sub-Saharan African (SSA) cities are among the fastest growing urban areas in the world. However, they lack spatial information to guide urban planning towards climate-adapted cities and fair living conditions for disadvantaged residents who mostly reside in informal settlements. Therefore, this study collected key information on freely available data such as data on land cover, land use, and environmental hazards and pressures, demographic and socio-economic indicators for urban areas. They serve as a vital resource for success of many other related local studies, such as the transdisciplinary research project “DREAMS—Developing REsilient African cities and their urban environMent facing the provision of essential urban SDGs”. In the era of exponential growth of big data analytics, especially geospatial data, their utility in SSA is hampered by the disparate nature of these datasets due to the lack of a comprehensive overview of where and how to access them. This paper aims to provide transparency in this regard as well as a resource to access such datasets. Although the limitations of such big data are also discussed, their usefulness in assessing environmental hazards and human exposure, especially to climate change impacts, are emphasised.
      Citation: Climate
      PubDate: 2022-11-22
      DOI: 10.3390/cli10120186
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 187: Climate Change-Related Hazards and Livestock
           Industry Performance in (Peri-)Urban Areas: A Case of the City of
           Masvingo, Zimbabwe

    • Authors: Felix Chari, Bethuel Sibongiseni Ngcamu
      First page: 187
      Abstract: In an effort to improve their quality of life and battle poverty, many urban residents are turning to agriculture as an alternative source of income, employment, and food security. However, climate-related hazards such as heatwaves, floods, and droughts have had an effect on urban agriculture. The purpose of this study was to determine how climate change-related hazards affected the urban livestock industry in Masvingo City. These researchers administered a structured questionnaire on urban livestock farmers, the results of which were triangulated with in-depth interviews with livestock stakeholders. The results show that the urban livestock industry is significantly impacted by climate-related hazards. Farmers lose livestock to diseases, poor pastures, and extreme weather conditions. Furthermore, the hazards badly affect the storage and distribution of livestock products, the labour supply and productivity, and the profitability of livestock enterprises. This study contributes to the body of knowledge on the urban livestock industry and climate change-related hazards. The results are significant to policy makers and livestock stakeholders to understand climate change effects on the urban livestock sector so as to formulate mitigation, adaptation, and coping strategies against any adverse effects. This paper is a foundation for future studies and these researchers suggest that future studies be on location-specific adaptation strategies.
      Citation: Climate
      PubDate: 2022-11-25
      DOI: 10.3390/cli10120187
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 188: Air Quality in a Changing World

    • Authors: Qirui Zhong, Huizhong Shen
      First page: 188
      Abstract: Air pollution is one of the most concerning environmental threats to human health [...]
      Citation: Climate
      PubDate: 2022-11-27
      DOI: 10.3390/cli10120188
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 189: Mapping and Managing Livelihoods
           Vulnerability to Drought: A Case Study of Chivi District in Zimbabwe

    • Authors: Raymond Mugandani, Tavagwisa Muziri, Cyril Tapiwa Farai Murewi, Amanda Mugadza, Tavengwa Chitata, Marvelous Sungirai, Farai Solomon Zirebwa, Petronella Manhondo, Elvis Tawanda Mupfiga, Charles Nyamutowa, Bester Tawona Mudereri, Zvenyika Eckson Mugari, Liboster Mwadzingeni, Paramu Mafongoya
      First page: 189
      Abstract: The assessment of the vulnerability to drought hazards in smallholder farming systems dependent on rain-fed agriculture has recently gained global popularity, given the need to identify and prioritize climate hotspots for climate adaptation. Over the past decade, numerous studies have focused on vulnerability assessments with respect to drought and other meteorological hazards. Nonetheless, less research has focused on applying common measurement frameworks to compare vulnerability in different communities and the sources of such vulnerability. Yet, the crucial question remains: who is more vulnerable and what contributes to this vulnerability' This article is a case study for assessing the vulnerability to drought of smallholder farmers in two wards in Chivi district, Masvingo Province, Zimbabwe. This study is timely, as climate change is increasingly affecting populations dependent on rainfed agriculture. This assessment has been conducted by calculating the Livelihood Vulnerability Index (LVI) and Livelihood Vulnerability Index of the Intergovernmental Panel on Climate Change (LVI-IPCC). This empirical study used data from 258 households from the two wards and triangulated it through Key Informant Interviews and Focus Group Discussions. To calculate the LVI, twenty-six subcomponents made up of seven major components, including socio-demographic variables; livelihood strategies; social capital; access to food, health, and water; and exposure to drought, were considered. To calculate the LVI-IPCC, we combined the three contributing factors of vulnerability (exposure, sensitivity, and adaptive capacity). Our results indicate that the LVI forward 14 is statistically higher than for ward 19 (F = 21.960; p ≤ 0.01) due to high exposure to drought, food insecurity, and compromised social networks. Concerning the LVI-IPCC, ward 14 was significantly more vulnerable to the impacts of drought than ward 19 (F = 7.718; p ≤ 0.01). Thus, reducing exposure to drought through early warning systems, building diversified agricultural systems, and social networks are of high priority to reduce the vulnerability of the farmers.
      Citation: Climate
      PubDate: 2022-11-29
      DOI: 10.3390/cli10120189
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 190: Climate Change Impacts on Streamflow in the
           Krishna River Basin, India: Uncertainty and Multi-Site Analysis

    • Authors: Ponguru Naga Sowjanya, Venkata Reddy Keesara, Shashi Mesapam, Jew Das, Venkataramana Sridhar
      First page: 190
      Abstract: In Peninsular India, the Krishna River basin is the second largest river basin that is overutilized and more vulnerable to climate change. The main aim of this study is to determine the future projection of monthly streamflows in the Krishna River basin for Historic (1980–2004) and Future (2020–2044, 2045–2069, 2070–2094) climate scenarios (RCP 4.5 and 8.5, respectively), with the help of the Soil Water and Assessment Tool (SWAT). SWAT model parameters are optimized using SWAT-CUP during calibration (1975 to 1990) and validation (1991–2003) periods using observed discharge data at 5 gauging stations. The Cordinated Regional Downscaling EXperiment (CORDEX) provides the future projections for meteorological variables with different high-resolution Global Climate Models (GCM). Reliability Ensemble Averaging (REA) is used to analyze the uncertainty of meteorological variables associated within the multiple GCMs for simulating streamflow. REA-projected climate parameters are validated with IMD-simulated data. The results indicate that REA performs well throughout the basin, with the exception of the area near the Krishna River’s headwaters. For the RCP 4.5 scenario, the simulated monsoon streamflow values at Mantralayam gauge station are 716.3 m3/s per month for the historic period (1980–2004), 615.6 m3/s per month for the future1 period (2020–2044), 658.4 m3/s per month for the future2 period (2045–2069), and 748.9 m3/s per month for the future3 period (2070–2094). Under the RCP 4.5 scenario, lower values of about 50% are simulated during the winter. Future streamflow projections at Mantralayam and Pondhugala gauge stations are lower by 30 to 50% when compared to historic streamflow under RCP 4.5. When compared to the other two future periods, trends in streamflow throughout the basin show a decreasing trend in the first future period. Water managers in developing water management can use the recommendations made in this study as preliminary information and adaptation practices for the Krishna River basin.
      Citation: Climate
      PubDate: 2022-12-01
      DOI: 10.3390/cli10120190
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 191: Water Asset Transition through Treating Water
           as a New Asset Class for Paradigm Shift for Climate–Water Resilience
           

    • Authors: Amgad Elmahdi, Lixiang Wang
      First page: 191
      Abstract: Climate change is evident around the globe, which requires bold actions now to achieve UN-SDGs and Paris Agreement. The water sector is dominated by public finance and is almost subsidised. In addition, there is an increased risk perception surrounding climate investments in developing countries. Pricing climate risks is a daunting challenge for investors and the private sector, who must estimate the likelihood of various climate scenarios and their implications for physical, liability and transition risks at the firm, project, national, and regional scales. In addition, there is a building momentum to scale up global climate response. To translate this momentum into action will require significantly greater investments, investments in a different set of inclusive assets that address water security, mobilise the private sector and provides sector-based or economy-wide co-benefits to direct and indirect beneficiaries, e.g., job creation, health benefits, improved resilience and scaling knowledge and harmonise data and methodologies. Notably, climate–water finance is facing a dual challenge. It will have to both reduce the present water infrastructure financing gap and ensure that this new infrastructure/asset is low-carbon, resilient to climate change, and meets the goals of the UNFCCC and the Paris Agreement. Therefore, there is a need for a paradigm shift in the way how water asset is defined, developed, and financed. This paper presents this novel approach concept and its content and financial structure that enable treating water as a new asset class to enable private sector investment and ensure providing water for domestic, municipal, and industrial purposes and allows municipalities to scale their water reuse, sanitation, and desalination projects in partnership with the private sector and/or governments. It is increasingly important to treat water as a new asset class, particularly as nations around the world (particularly developing countries) are set to experience an anticipated 40% shortfall in water by 2030 due to climate change, economic recovery and growth, population growth and resource competition. Investment in water could be one of the ways of tackling this deficit by treating water as a new asset class.
      Citation: Climate
      PubDate: 2022-12-01
      DOI: 10.3390/cli10120191
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 192: Observations from Personal Weather
           Stations—EUMETNET Interests and Experience

    • Authors: Claudia Hahn, Irene Garcia-Marti, Jacqueline Sugier, Fiona Emsley, Anne-Lise Beaulant, Louise Oram, Eva Strandberg, Elisa Lindgren, Martyn Sunter, Franziska Ziska
      First page: 192
      Abstract: The number of people owning a private weather station (PWS) and sharing their meteorological measurements online is growing worldwide. This leads to an unprecedented high density of weather observations, which could help monitor and understand small-scale weather phenomena. However, good data quality cannot be assured and thorough quality control is crucial before the data can be utilized. Nevertheless, this type of data can potentially be used to supplement conventional weather station networks operated by National Meteorological & Hydrological Services (NMHS), since the demand for high-resolution meteorological applications is growing. This is why EUMETNET, a community of European NMHS, decided to enhance knowledge exchange about PWS between NMHSs. Within these efforts, we have collected information about the current interest in PWS across NMHSs and their experiences so far. In addition, this paper provides an overview about the data quality challenges of PWS data, the developed quality control (QC) approaches and openly available QC tools. Some NMHS experimented with PWS data, others have already incorporated PWS measurements into their operational workflows. The growing number of studies with promising results and the ongoing development of quality control procedures and software packages increases the interest in PWS data and their usage for specific applications.
      Citation: Climate
      PubDate: 2022-12-02
      DOI: 10.3390/cli10120192
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 193: Influence of Meteo-Climatic Variables and
           Fertilizer Use on Crop Yields in the Sahel: A Nonlinear Neural-Network
           Analysis

    • Authors: Antonello Pasini, Giuseppina De Felice Proia, Francesco N. Tubiello
      First page: 193
      Abstract: The Sahel is one of the regions with the highest rates of food insecurity in the world. Understanding the driving factors of agricultural productivity is, therefore, essential for increasing crop yields whilst adapting to a future that will be increasingly dominated by climate change. This paper shows how meteo-climatic variables, combined with fertilizers’ application rates, have affected the productivity of two important crops in the Sahel region, i.e. maize and millet, over the last three decades. To this end, we have applied a specifically designed neural network tool (optimised for analysis of small datasets), endowed with feed-forward networks and backpropagation training rules and characterised by generalised leave-one-out training and multiple runs of neural network models in an ensemble strategy. This tool allowed us to identify and quantify the impacts of single drivers and their linear and nonlinear role. The variables analysed included temperature, precipitation, atmospheric CO2 concentration, chemical and organic fertilizer input. They explained most of the variance in the crop data (R2 = 0.594 for maize and R2 = 0.789 for millet). Our analysis further allowed us to identify critical threshold effects affecting yields in the region, such as the number of hours with temperature higher than 30 °C during the growing season. The results identified heat waves and fertilizer application rates playing a critical role in affecting maize and millet yields in this region, while the role of increasing CO2 was less important. Our findings help identify the modalities of ongoing and future climate change impacts on maize and millet production in the Sahel.
      Citation: Climate
      PubDate: 2022-12-04
      DOI: 10.3390/cli10120193
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 194: Precipitation Trends and Flood Hazard
           Assessment in a Greek World Heritage Site

    • Authors: Elias Dimitriou
      First page: 194
      Abstract: Natural disasters have become more frequent and intense over the last decade mainly as a result of poor water and land management. Cultural sites and monuments are extremely vulnerable to natural disasters, particularly floods, while mitigation measures and protective infrastructure are difficult to construct within such areas. In the present study, the precipitation trends of the recent past and over the next 80 years were analyzed for the old town of Corfu (UNESCO World Heritage Site) in order to identify potentially significant changes that may affect the flood risk of the area. Moreover, a multi-criteria analysis using GIS software was used to identify high flood hazard zones in this living monument in order to propose specific mitigation measures that are in line with the characteristics of the site. The main effort in this study was to find a methodological approach for a fast but reliable assessment of future changes in the flood risk of historic monuments without the need for a hydrodynamic model and with a limited amount of locally based data. With the selected approach, a good indication of the potential changes in flood risk was provided, according to climate scenarios and simple, physically-based geostatistical models. The results indicate that no significant changes in the flood risk were found for the future climatic conditions, and the identified flood-prone areas will remain approximately the same as today in this particular historic monument. The uncertainty that is included in this output originates mainly from the inherent errors in climate modeling and from the non-high temporal resolution of the data.
      Citation: Climate
      PubDate: 2022-12-05
      DOI: 10.3390/cli10120194
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 195: Revealing a Tipping Point in the Climate
           System: Application of Symbolic Analysis to the World Precipitations and
           Temperatures

    • Authors: Kazuya Hayata
      First page: 195
      Abstract: Climate variabilities over the period of 80 years (1930–2010) are analyzed by the combined use of divergence measures and rank correlation. First, on the basis of a statistical linguistics procedure, the m-th order differences of the monthly mean precipitations and temperatures on the globe are symbolized according to a binary coding rule. Subsequently, the annual 12-bit binary sequence for a station is divided into twelve 6-bit sequences by scanning it over a year. Computed results indicate that there is an optimal order of differences with which one can reveal the variabilities most distinctly. Specifically, it is found that for the analysis of precipitations, the second differences (m = 2) are most useful, whereas, for the temperatures, the third differences (m = 3) are preferable. A detailed comparison between the information-theoretic and the ranking methods suggests that along with the stability and coherence, owing to its ability to make an appeal to the eyes, the latter is superior to the former.
      Citation: Climate
      PubDate: 2022-12-05
      DOI: 10.3390/cli10120195
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 196: Effect of Model Structure and Calibration
           Algorithm on Discharge Simulation in the Acısu Basin, Turkey

    • Authors: Harun Alp, Mehmet Cüneyd Demirel, Ömer Levend Aşıkoğlu
      First page: 196
      Abstract: In this study, the Acısu Basin—viz., the headwater of the Gediz Basin—in Turkey, was modelled using three types of hydrological models and three different calibration algorithms. A well-known lumped model (GR4J), a commonly used semi-distributed (SWAT+) model, and a skillful distributed (mHM) hydrological model were built and integrated with the Parameter Estimation Tool (PEST). PEST is a model-independent calibration tool including three algorithms—namely, Levenberg Marquardt (L-M), Shuffled Complex Evolution (SCE), and Covariance Matrix Adoption Evolution Strategy (CMA-ES). The calibration period was 1991–2000, and the validation results were obtained for 2002–2005. The effect of the model structure and calibration algorithm selection on the discharge simulation was evaluated via comparison of nine different model-algorithm combinations. Results have shown that mHM and CMA-ES combination performed the best discharge simulation according to NSE values (calibration: 0.67, validation: 0.60). Although statistically the model results were classified as acceptable, the models mostly missed the peak values in the hydrograph. This problem may be related to the interventions made in 2000–2001 and may be overcome by changing the calibration and validation periods, increasing the number of iterations, or using the naturalized gauge data.
      Citation: Climate
      PubDate: 2022-12-08
      DOI: 10.3390/cli10120196
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 197: Local Climate Zones, Sky View Factor and
           Magnitude of Daytime/Nighttime Urban Heat Islands in Balneário
           Camboriú, SC, Brazil

    • Authors: Ismael Luiz Hoppe, Cassio Arthur Wollmann, André Schroder Buss, João Paulo Assis Gobo, Salman Shooshtarian
      First page: 197
      Abstract: For this study on urban climatology, the study area is the city of Balneário Camboriú, belonging to the Brazilian state of Santa Catarina (SC), located at 26°59′42″ south latitude and 48°37′46″ west longitude. As it is the most vertical city in the entire Southern Hemisphere, Balneário Camboriú was selected as the study area for the development of this climate analysis.. Then, this study was concerned with analyzing the formation of urban heat islands throughout the daytime and nighttime in the city of Balneário Camboriú, Santa Catarina, Brazil, on some days in October 2020, from the perspective of the local climatic zones. Seven fixed sampling points and one official weather station were selected for this research. These points were selected in order to facilitate analysis of the climatic behaviour of the urban area throughout the day, comparing it with the other points, and also to verify possible changes in the local climate in the most diverse types of LCZ. At these same points, the Sky View Factor (SVF) measurements were taken. to elaborate the map of LCZ of Balneário Camboriú, the WUDAPT method was used. There was a great variation of the SVF between the collection points, and different LCZs were mapped, which contributed to the formation of urban heat islands whose maximum magnitude was 10.8 °C and islands with freshnesses of magnitudes of −4.5 °C.
      Citation: Climate
      PubDate: 2022-12-10
      DOI: 10.3390/cli10120197
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 198: Contemporary Climate Change and Its
           Hydrological Consequence in the Volga Federal District, European Russia

    • Authors: Yuri Perevedentsev, Artyom Gusarov, Nadezhda Mirsaeva, Boris Sherstyukov, Konstantin Shantalinsky, Vladimir Guryanov, Timur Aukhadeev
      First page: 198
      Abstract: An analysis of spatiotemporal variability of air temperature and precipitation in the Volga Federal District (European Russia) between 1966 and 2021 was carried out. Based on data from 20 meteorological stations, relatively evenly located on the territory under consideration, the spatial distribution of average monthly and average annual air temperatures and monthly and annual precipitation was assessed; some indicators of the temporal variability of these variables in the period under consideration were calculated and analyzed. It was revealed that throughout the Volga Federal District, there was a tendency of climate warming in all months, and a slight increase in annual precipitation, except for the southeast of the district, where the precipitation trend was negative. It is noted that in the period 1955–1998, the number of negative air temperature anomalies was approximately equal to the number of positive ones; however, in the later period 1999–2021, the number of positive anomalies significantly exceeded the number of negative ones. Based on reanalysis data, climatic maps of vaporization and runoff in the Volga Federal District during 1966–2021 were created. The dependence of air temperature fluctuations on the nature of atmospheric circulation was revealed using the NAO, AO, and SCAND indices. On the example of the central part of the district (Republic of Tatarstan), some increase in summer aridity of the climate was revealed by using Budyko’s dryness index, Selyaninov’s hydrothermal coefficient, and Sapozhnikov’s humidification coefficient. The indicators of runoff and evaporation were also calculated using the methods of Schreiber and Ivanov. Against the background of the positive trend in vaporization rates, favorable conditions for a decrease in runoff were noted.
      Citation: Climate
      PubDate: 2022-12-12
      DOI: 10.3390/cli10120198
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 199: Marine Heatwaves, Upwelling, and Atmospheric
           Conditions during the Monsoon Period at the Northern Coast of the Gulf of
           Guinea

    • Authors: Mamadou Koné, Sandrine Djakouré, Marcellin Adon, Samuel Ta, Yves Kouadio
      First page: 199
      Abstract: Ocean conditions influence the economies and climate of West Africa. Based on the 30-year daily Optimum Interpolation Sea Surface Temperature (OISST) dataset during May–October, upwelling surface variability and marine heatwaves (MHWs) at the northern coast of the Gulf of Guinea are investigated. The cooling surface decreases more rapidly around Cape Palmas than around Cape Three Points and extends eastward. MHWs variability exhibits a frequent occurrence of such events since 2015 that is consistent with the observed oceanic warming and the decrease in upwelling surface. The empirical orthogonal functions performed on the annual cumulated intensity of MHWs show four variability modes that include the whole northern coast, an east–west dipole between the two capes, a contrast between the northern coast at the two capes and the meridional section east of 5° E, and a north–south opposition. These patterns show 3-year, 6-year, and 8-year trends, and are related to coastal upwelling at the northern coast of the Gulf of Guinea. Similarly, surface ocean and atmospheric conditions are modified according to MHW periods. These changes take place before, during, and after MHW events. These results could be used to understand how this change influences the marine ecosystem, the local fisheries resources, and the extreme rainfall episodes in West Africa.
      Citation: Climate
      PubDate: 2022-12-14
      DOI: 10.3390/cli10120199
      Issue No: Vol. 10, No. 12 (2022)
       
  • Climate, Vol. 10, Pages 159: Flood-Related Federally Declared Disaster
           Events and Community Functioning (COPEWELL)

    • Authors: Norma F. Kanarek, Qi Wang, Tak Igusa, Tara Kirk Sell, Zachary Anthony Cox, James M. Kendra, Jonathan Links
      First page: 159
      Abstract: Objective: Understanding long-term disaster effects is key to building theories of recovery and informing policymaking. Findings regarding long-term recovery are inconsistent, with some scholars finding that disasters have little long-term impact, and others asserting otherwise. To assist in resolving this discord, we apply a conceptual framework and computational model of community resilience (“COPEWELL”) that places community functioning (CF) at the center of evaluating the effects of disaster over time. Using flooding as a disaster type, we hypothesize a change in baseline CF trend when a flood-related federally declared disaster event occurs. Methods: We used county-level flood-related federally declared disaster events (2010–2014) and selected population demographics to study their effects on annual CF trends among United States counties (N = 3141). Results: In multivariate analysis of baseline CF, we found a significant negative relationship of prior five-year flood status, federal regions relative to the Northeast (Region I), lower total earnings, and greater population size. Annual CF trend was 0.09% (95%CI: 0.01%–0.16%). In multivariate analysis, significant predictors included baseline CF (β = 0.0178, −0.0047–−0.0309), any concurrent flood-related federally declared disaster events (−0.0024, −0.0040–−0.0008), ten-year prior flood events (−0.0017, −0.0034–−0.0000) and concurrent population change (−0.0186, −0.0338–−0.0035). Conclusions: Recent floods depress baseline CF, while concurrent and ten-year-ago floods depress trend in CF. Resilience may potentially be modified by raising baseline CF and maintaining population over time.
      Citation: Climate
      PubDate: 2022-10-23
      DOI: 10.3390/cli10110159
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 160: Numerical Simulation of Winter Precipitation
           over the Western Himalayas Using a Weather Research and Forecasting Model
           during 2001–2016

    • Authors: Pravin Punde, Nischal, Raju Attada, Deepanshu Aggarwal, Chandrasekar Radhakrishnan
      First page: 160
      Abstract: In the present study, dynamically downscaled Weather Research and Forecasting (WRF) model simulations of winter (DJF) seasonal precipitation were evaluated over the Western Himalayas (WH) at grey zone configurations (at horizontal resolutions of 15 km (D01) and 5 km (D02)) and further validated using satellite-based (IMERG; 0.1°), observational (IMD; 0.25°), and reanalysis (ERA5; 0.25° and IMDAA; 0.108°) gridded datasets during 2001–2016. The findings demonstrate that both model resolutions (D01 and D02) are effective at representing precipitation characteristics over the Himalayan foothills. Precipitation features over the region, on the other hand, are much clearer and more detailed, with a significant improvement in D02, emphasizing the advantages of higher model grid resolution. Strong correlations and the lowest biases and root mean square errors indicate a closer agreement between model simulations and reanalyses IMDAA and ERA5. Vertical structures of various dynamical and thermodynamical features further confirm the improved and more realistic in WRF simulations with D02. Moreover, the seasonal patterns of upper tropospheric circulation, vertically integrated moisture transport, surface temperature and cloud cover show more realistic simulation in D02 compared to coarser domain D01. The categorical statistics reveal the efficiency of both D01 and D02 in simulating moderate and heavy precipitation events. Overall, our study emphasizes the significance of high-resolution data for simulating precipitation features specifically over complex terrains like WH.
      Citation: Climate
      PubDate: 2022-10-25
      DOI: 10.3390/cli10110160
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 161: Using High-Resolution Climate Models to
           

    • Authors: Saeed Sotoudeheian, Ehsan Jalilvand, Amirhassan Kermanshah
      First page: 161
      Abstract: The adverse effects of climate change will impact all regions around the world, especially Middle Eastern countries, which have prioritized economic growth over environmental protection. However, these impacts are not evenly distributed spatially, and some locations, namely climate change hotspots, will suffer more from climate change consequences. In this study, we identified climate change hotspots over Iran—a developing country in the Middle East that is facing dire economic situations—in order to suggest pragmatic solutions for vulnerable regions. We used a statistical index as a representative of the differences in climatic parameters for the RCP8.5 and RCP4.5 forcing pathways between historical data (1975–2005), near-future data (2030–2060) and far-future data (2070–2100). More specifically, we used downscaled high-resolution (0.25°) meteorological data from five GCMs of the CMIP5 database to calculate the statistical metric. Results indicate that for the far-future period and RCP4.5, regions stretching from the northwest to southeast of Iran, namely the Hotspot Belt, are the most vulnerable areas, while, for RCP8.5, almost the whole country is vulnerable to climate change. The highest and lowest differences in temperature for RCP8.5 in 2070–2100 are observed during summer in the northwestern and central parts and during winter in the northern and northeastern parts. Moreover, the maximum increase and decrease in precipitation are identified over the western parts of Iran during fall and winter, respectively. Overall, western provinces (e.g., Lorestan and Kermanshah), which are mostly reliant on rainfed agriculture and other climate-dependent sectors, will face the highest change in climate in the future. As these regions have less adaptive capacity, they should be prioritized through upstream policy change and special budget allocation from the government to increase their resiliency against climate change.
      Citation: Climate
      PubDate: 2022-10-27
      DOI: 10.3390/cli10110161
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 162: Flood Hazard and Management in Cambodia: A
           Review of Activities, Knowledge Gaps, and Research Direction

    • Authors: Sophea Rom Phy, Ty Sok, Sophal Try, Ratboren Chan, Sovannara Uk, Chhordaneath Hen, Chantha Oeurng
      First page: 162
      Abstract: Cambodia is located in one of the most severe flood-vulnerable zones in mainland Southeast Asia. Flooding is the country’s most recurrent and impactful hazard among other natural hazards. This hazard alone, observed in many river basins, has been inflicting huge damages on livelihoods, social infrastructure, and the country’s economy. This study aims to review the current status of flood hazards, impacts, driving factors, management capacity, and future research directions on floods in Cambodia. The findings of this study suggested that there is still a lack of flood-related studies on flood hazard mapping, risk and damage assessment, and future flood analysis in Cambodia. The existing related studies mainly focused on the Tonle Sap Basin and its tributaries, the Lower Mekong Basin, the whole Mekong River Basin, and some of the tributaries of the Mekong River in Cambodia. The fundamental driving factors of the current flooding in Cambodia are impacts of climate change, land-use change, water infrastructure development, and weather extremes. The applications of mathematical and statistical tests and indices, conceptual and physically-based modeling, artificial intelligence and machine learning, and remote sensing are recommended to focus on future research directions on flood in Cambodia in the areas of land-use change, existing and planned operation of water infrastructure, flood hazard and damage assessment, and flood forecasting. The outcomes from these studies and applications would improve the understanding of flood hazard characteristics, reinforce flood management, and achieve flood damage reduction.
      Citation: Climate
      PubDate: 2022-10-27
      DOI: 10.3390/cli10110162
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 163: Flames and Viruses: Australian and Hungarian
           Media Representation of the Australian Bushfires and the COVID-19
           Pandemic, A Case Study

    • Authors: Priszcilla Hafenscher, Ferenc Jankó
      First page: 163
      Abstract: This study addresses the difference in media coverage of the Australian bushfires and the pandemic, using an Australian and a Hungarian news site. After a frame analysis of text and imagery, a narration analysis was conducted. Our results provided evidence that crises were covered in different ways. For a distant news portal, it was an obvious option to use the bushfires in order to visualize climate change. In contrast, the bushfire–climate link has been a politicized subject in Australia for decades; hence, the exceptional bushfire season was also unable to get the issue on the agenda. Although the Australian news media in our sample strived to portray a crisis under control, when compared to the pandemic, it was not so effective. Therefore, localization is a major challenge for effective climate communication, where lessons from the pandemic, using more economic and social frames, could be helpful.
      Citation: Climate
      PubDate: 2022-10-27
      DOI: 10.3390/cli10110163
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 164: The Impacts of Urbanisation and Climate
           Change on the Urban Thermal Environment in Africa

    • Authors: Xueqin Li, Lindsay C. Stringer, Martin Dallimer
      First page: 164
      Abstract: Rapid urbanisation is affecting people in different ways, with some becoming more vulnerable to the impacts of climate change. Africa’s cities are projected to be home to nearly 60% of the continent’s population by 2050. In conjunction with climate change, these cities are experiencing critical environmental challenges, including changes in the urban thermal environment. Urban areas generally exhibit significantly higher air and surface temperatures than their surrounding rural areas, resulting in urban heat islands. However, little has been done to synthesise existing knowledge and identify the key research gaps in this area, particularly in Africa. This paper focuses on the combined effects of urbanisation and climate change on the urban thermal environment in Africa, and provides a comprehensive review of results, major advances and the dominant direction of research. Our review of 40 publications from peer-reviewed journals from 2000 to 2021 revealed that South Africa, Ethiopia and Nigeria were most frequently studied, and satellite imagery-based data and analysis were used predominantly. Results from a few studies have shown the practical implications for urban land-use planning, informal settlement management, human wellbeing and productivity, energy use, air pollution and disease spread. Integrated approaches, strengthening planning institutions, and early warning systems are proposed to address climate change. Low-income groups are emphasised in efforts to help people cope with heat stress. Solutions based on land use and land cover dynamics and blue–green infrastructure are mentioned but are in need of further research. Cities with similar patterns of urbanisation, geographies and climate conditions could benefit from multi-disciplinary research collaboration to address the combined impacts of rapid urbanisation and climate change.
      Citation: Climate
      PubDate: 2022-10-30
      DOI: 10.3390/cli10110164
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 165: Analysis of Quadratic Correlation between
           Dryness Indices and Wine Grape Yield to Estimate Future Climate Impacts in
           Hungary

    • Authors: László Lakatos, János Mika
      First page: 165
      Abstract: In many regions, water availability influences grape yield fluctuations more than thermal conditions. This study analyzes dryness indices calculated from observed and simulated RCM data to establish statistical relationships with observed yield data, considered an indicator of food safety. Five dryness indices were analyzed: the number of days without rain, the maximum number of consecutive dry days, climatic water balance, dryness index, and vineyard water indicator. These indices were analyzed for three periods: 1986–2005 (recent past), 2016–2035 (near future) and 2081–2100 (distant future). After this analysis, quadratic regression connections were established between the indices and available wine grape yields in the 22 wine regions of Hungary for 2005–2021 without information on grape varieties and for 2017–2021 with data on grape varieties. Linear agro-technological trends were extracted from these wine grape yield series, whereas the residuals exhibited significant quadratic regression in slightly over 50% of the indices and regions, according to the F-test for the 17 year series. For the short series, these proportions are 29 and 27% for the selected seven white and seven red wine grapes. According to the most significant quadratic regressions, combined with the projected dryness indices, we can expect less average yields with higher interannual variability in the future.
      Citation: Climate
      PubDate: 2022-10-31
      DOI: 10.3390/cli10110165
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 166: Energy System Transition in the Context of
           NDC and Mitigation Strategies in Tunisia

    • Authors: Panagiotis Fragkos, Eleftheria Zisarou
      First page: 166
      Abstract: The evolution of the Tunisian energy system in the next few decades will highly depend on the implementation of its Nationally Determined Contribution by 2030 and its potential long-term low-emission strategies. This study analyses the technology, emissions, energy systems and economic impacts of meeting Tunisia’s NDC targets (conditional and unconditional) and long-term transition pathways compatible with the Paris Agreement. Different climate policy targets and settings are explored using a detailed energy system model (MENA-EDS) that integrates detailed representations of energy demand and supply and their complex linkages through energy pricing. The analysis shows that in order to meet its NDC targets for 2030, current climate policies in Tunisia need substantial strengthening, based on the massive uptake of renewable energy technologies (especially solar PV and wind) and a reduction of oil and gas use. Long-term low-emission transitions leading to emission reductions of about 80% from baseline levels in 2050 is based on the further expansion of renewable energy within and beyond the electricity sector; the increased electrification of energy end-uses (especially through the uptake of electric vehicles in transport); accelerated energy efficiency improvements in transport, industries and buildings; and the emergence of low-carbon fuels. The study provides insights into the challenges to achieve the deep decarbonization of the Tunisian economy but also into the opportunities from energy sector-restructuring, including reduced energy import dependence and increased low-carbon investment.
      Citation: Climate
      PubDate: 2022-11-01
      DOI: 10.3390/cli10110166
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 167: Analyzing Sensitive Aerosol Regimes and
           Active Geolocations of Aerosol Effects on Deep Convective Clouds over the
           Global Oceans by Using Long-Term Operational Satellite Observations

    • Authors: Xuepeng Zhao, Michael J. Foster
      First page: 167
      Abstract: Long-term satellite climate data records of aerosol and cloud along with meteorological reanalysis data have been used to study the aerosol effects on deep convective clouds (DCCs) over the global oceans from a climatology perspective. Our focus is on identifying sensitive aerosol regimes and active geolocations of the aerosol effects on DCCs by using statistical analyses on long-term averaged aerosol and cloud variables. We found the aerosol effect tends to manifest relatively easily on the long-term mean values of observed cloud microphysical variables (e.g., cloud particle size and ice water amount) compared to observed cloud macrophysical variables (e.g., cloud cover and cloud top height). An increase of aerosol loading tends to increase DCC particle size and ice water amount in the tropical convergence zones but decrease them in the subtropical subsidence regions. The aerosol effect on the cloud microphysical variables is also likely to manifest over the northwestern Pacific Ocean and central and eastern subtropical Pacific Ocean. The aerosol effect manifested on the microphysical cloud variables may also propagate to cloud cover but weakly to cloud top height since the latter is more susceptible to the influence of cloud dynamical and thermodynamic processes. Our results, based on the long-term averaged operational satellite observation, are valuable for the evaluation and improvement of aerosol-cloud interactions in global climate models.
      Citation: Climate
      PubDate: 2022-11-03
      DOI: 10.3390/cli10110167
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 168: A Comparative Study on the Performances of
           Spectral Nudging and Scale-Selective Data Assimilation Techniques for
           Hurricane Track and Intensity Simulations

    • Authors: Xia Sun, Lian Xie
      First page: 168
      Abstract: It is a common practice to use a buffer zone to damp out spurious wave growth due to computational error along the lateral boundary of limited-area weather and climate models. Although it is an effective technique to maintain model stability, an unintended side effect of using such buffer zones is the distortion of the data passing through the buffer zone. Various techniques are introduced to enhance the communication between the limited-area model’s inner domain and the outer domain, which provides lateral boundary values for the inner domain. Among them, scale-selective data assimilation (SSDA) and the spectral nudging (SPNU) techniques share similar philosophy, i.e., directly injecting the large-scale components of the atmospheric circulation from the outer model domain into the interior grids of the inner model domain by-passing the lateral boundary and the buffer zone, but the two methods are taking different implementation approaches. SSDA utilizes a 3-dimensional variational data assimilation procedure to accomplish the data injection objective, whereas SPNU uses a nudging process. In the present study, the two approaches are evaluated comparatively for simulating hurricane track and intensity in a pair of cases: Jeanne (2004) and Irma (2017) using the Weather Research and Forecasting (WRF) model. The results indicate that both techniques are effective in improving tropical cyclone intensity and track simulations by reducing the errors of the large-scale circulation in the inner model domain. The SSDA runs produced better simulations of temperature and humidity fields which are not directly nudged. The SSDA runs also produced more accurate storm intensities in both cases and more realistic structure in Hurricane Jeanne’s case than those produced by the SPNU runs. It should be noted, however, that extending these case study results to more general situations requires additional studies covering a large number of additional cases.
      Citation: Climate
      PubDate: 2022-11-03
      DOI: 10.3390/cli10110168
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 169: Local Perspectives on Climate Change, Its
           

    • Authors: Deirdre Bannan, Rannveig Ólafsdóttir, Benjamin David Hennig
      First page: 169
      Abstract: Climate change is one of the most pressing issues of our time. Rising temperatures, changing precipitation and more weather extremes pose risks to local societies worldwide. Yet, climate change is most often presented and reported on a global or national scale. This paper aims to analyze the key aspects of climate change on the local scale by assessing temporal and spatial changes in temperature and precipitation in the Westfjords in north-western Iceland and evaluate their impacts on the region’s livability. Existing temperature and precipitation data were used to model trends in climate change at an unprecedented resolution. The results show that the period of 2001–2020 was warmer than the 1961–1990 reference period in almost every month of every year, and that warming was more pronounced in the winter months. Furthermore, precipitation increased during 1991–2020 period compared to 1961–1990. These detected local patterns confirm some of the major predictions about climate change on the global scale. Considering the impact of climate change at the local level is critical, as it allows the community to envisage their future and provides better possibilities to mitigate, prepare for or adapt to the predicted changes.
      Citation: Climate
      PubDate: 2022-11-04
      DOI: 10.3390/cli10110169
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 170: Annual, Seasonal, and Monthly Rainfall Trend
           Analysis through Non-Parametric Tests in the Sebou River Basin (SRB),
           Northern Morocco

    • Authors: Ridouane Kessabi, Mohamed Hanchane, Nir Y. Krakauer, Imane Aboubi, Jaafar El Kassioui, Bouchta El Khazzan
      First page: 170
      Abstract: This paper explores the temporal and spatial patterns of annual, seasonal, and monthly rainfall series during the period of 1961–2018 at 15 stations in the agriculturally important Sebou river basin, northern Morocco. Trends were investigated using the classical non-parametric Mann–Kendall test and the Theil–Sen approach at 90%, 95% and 99% confidence levels. A general decreasing trend was found at the annual scale, significant at the 95% confidence level at 8 stations out of 15 (53%). A particularly large decreasing trend between −30 mm and −50 mm per decade was found in the north and eastern parts of the basin. Autumn rainfall tended to increase, but this was not statistically significant. During the winter months, rainfall tended to decrease sharply (−27 mm and −40 mm per decade) in the northern slopes of the Rif mountains, while in spring, the mountainous area of the basin recorded decreases ranging between −12 mm and −16 mm per decade. During winter and spring, negative trends were significant at ten stations (66%). Summer rainfall tends toward a decrease, but the absolute change is small. These results help to understand the rainfall variability in the Sebou river basin and allow for improved mitigation strategies and water resource plans based on a prospective view of the impact of climate change on the river basin.
      Citation: Climate
      PubDate: 2022-11-05
      DOI: 10.3390/cli10110170
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 171: Large-Scale Effects of Aridity on Leaf
           Nitrogen and Phosphorus Concentrations of Terrestrial Plants

    • Authors: De-Juan Xie, Chun-Jing Wang, Ji-Zhong Wan
      First page: 171
      Abstract: The leaf nitrogen (N) and phosphorus (P) concentrations of terrestrial plants make large contributions to ecosystem function and dynamics. The relationship between aridity and leaf N and P has been established through experimental studies. However, few studies have focused on the large-scale effects of aridity on the leaf N and P of terrestrial plants. In this paper, we used linear regression models to test the effects of aridity on terrestrial plant leaf N and P and the N:P ratio based on global datasets. We found that aridity had significant effects on the leaf N and P and the N:P ratio of terrestrial plants. The strongest relationships were between fern leaf P, the fern N:P ratio, tree leaf P, the tree N:P ratio, vine leaf N, and the tree N:P ratio. Aridity could be used to predict the P and N:P ratio of terrestrial plants, particularly those of ferns and trees, on large scales in arid environments. Our study contributes to maintaining ecosystem functioning and services in arid environments under climate change.
      Citation: Climate
      PubDate: 2022-11-07
      DOI: 10.3390/cli10110171
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 172: Exploring Gender and Climate Change Nexus,
           and Empowering Women in the South Western Coastal Region of Bangladesh for
           Adaptation and Mitigation

    • Authors: Ashrafuzzaman Md, Carla Gomes, João Miguel Dias, Artemi Cerdà
      First page: 172
      Abstract: This study has been conducted to identify vulnerabilities and effects of climate change on women in 12 unions in Shyamnagar upazila in the Satkhira district in the Southwestern Coastal Region of Bangladesh (SWCRB). Climate vulnerability and gender inequality may increase due to climate change. Women may, thus, face specific conditions of vulnerability in society and daily livelihood. This paper focuses on investigating factors that influence women’s vulnerability from climate change, their adaptations, and the importance of women empowerment to reduce their inequality in SWCRB. This study also emphasizes gender inequality caused by climate change, and looks at accommodations for women to reduce hostile influences of climate change. From the 9 unions in SWCRB, a total of 320 household respondents were randomly selected to complete a questionnaire. The results of the statistical analysis showed that most of the survey’s perimeter has significant. Interviews, case studies, focus group discussions, workshops, and key informant interviews were also conducted from 12 unions, and it was found that climate change impacts men and women differently, with women being more vulnerable than men. Through case study this paper investigated the main factors influencing the vulnerability of women. In terms of empowerment women may also be well positioned to lead adaptation efforts alongside men, as this analysis represent that gender inequalities are leading by social norms. Women being more vulnerable both in short-term i.e., major natural disasters, cyclones, flood, and long-term i.e., sea level rise, salinity intrusion in water and soil, land erosion, droughts, climatic events, as they enhance gender inequalities. Further, gender inequality is seen in illiteracy, food shortages and poor health conditions, traditional norms, religious taboos, and patriarchy. Moreover, gender-based economic opportunities, women’s mobility, and income are changing, while household authority relations and gender-based socio-economic, cultural, and institutional constraints remain. This study examines the increased vulnerability of women in SWCRB to climate change, which can be mitigated through women empowerment; female involvement with environmentally friendly stoves, rural electrification and renewable energy development, microfinancing, and nakshikantha. (Nakshikantha is a special type of sewing art that is made by creating designs with different types of colored threads on plain stitches). Lastly, women may also lead adaptation efforts alongside men, make decisions, and promote their participation.
      Citation: Climate
      PubDate: 2022-11-07
      DOI: 10.3390/cli10110172
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 173: Climate Change Effects upon Pasture in the
           Alps: The Case of Valtellina Valley, Italy

    • Authors: Francesca Casale, Daniele Bocchiola
      First page: 173
      Abstract: In this study, we assessed the potential effects of climate change upon the productivity of mountain pastures in the Valtellina valley of Italy. Two species, Trisetum flavescens and Nardus stricta, among the most abundant in Italian pastures, were chosen for the simulation of low- and high-altitude pastures, respectively. We introduced some agroclimatic indices, related to growing season parameters, climate, and water availability, to evaluate the impacts of climate change upon pasture production. First, the dynamic of the pasture species was evaluated for the present period using the climate-driven, hydrologically based model Poli-Hydro, nesting the Poli-Pasture module simulating plants growth. Poli-Pasture was validated against yield data, at province scale, and at local scale. Then, agroclimatic indices were calculated. Subsequently, IPCC scenarios of the Fifth and Sixth Assessment Reports (AR5 and AR6) were used to project species production and agroclimatic indices until the end of the 21st century. In response to increased temperature under all scenarios, a large potential for an increased growing season length and species yield overall (between +30% and +180% for AR5 at 2100) was found. Potential for decreased yield (until −31% for AR5) is seen below 1100 m asl in response to heat stress; however, it is compensated by a large increase higher up (between +50% and +140% for AR5 above 2000 m asl). Larger evapotranspiration is foreseen and larger water demand expected. However, specific (for hectares of pasture) water use would decrease visibly, and no significant water limitations would be seen. Results provide preliminary evidence of potential livestock, and thereby economic development in the valley at higher altitudes than now.
      Citation: Climate
      PubDate: 2022-11-07
      DOI: 10.3390/cli10110173
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 174: A Visual Analytics Pipeline for the
           Identification and Exploration of Extreme Weather Events from Social Media
           Data

    • Authors: Lise Styve, Carlo Navarra, Julie Maria Petersen, Tina-Simone Neset, Katerina Vrotsou
      First page: 174
      Abstract: Extreme weather events are expected to increase in frequency and intensity due to global warming. During disaster events, up-to-date relevant information is crucial for early detection and response. Recently, Twitter emerged as a potentially important source of volunteered geographic information of key value for global monitoring systems and increasing situational awareness. While research on the use of machine learning approaches to automatically detect disaster events from social media is increasing, the visualization and exploration of the identified events and their contextual data are often neglected. In this paper, we address this gap by proposing a visual analytics pipeline for the identification and flexible exploration of extreme weather events, in particular floods, from Twitter data. The proposed pipeline consists of three main steps: (1) text classification, (2) location extraction, and (3) interactive visualization. We tested and assessed the performances of four classification algorithms for classifying relevant tweets as flood-related, applied an algorithm to assign location information, and introduced a visual interface for exploring their spatial, temporal, and attribute characteristics. To demonstrate our work, we present an example use case where two independent flooding events were identified and explored. The proposed approach has the potential to support real-time monitoring of events by providing data on local impacts collected from citizens and to facilitate the evaluation of extreme weather events to increase adaptive capacity.
      Citation: Climate
      PubDate: 2022-11-14
      DOI: 10.3390/cli10110174
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 175: Spatial and Climate Governance and Policy to
           Tackle the Challenges of the Anthropocene: A Critical Analysis Based on
           the Paradigmatic Tourism Destination of Mallorca (Spain)

    • Authors: Luis A. Escudero-Gómez, Jesús M. González-Pérez, Rubén C. Lois-González
      First page: 175
      Abstract: The Anthropocene era demands a future alternative to the current state of play. The aim of this study is to analyze spatial and climate governance and policy through a critical geographical study of the island of Mallorca (Spain), an example of the model of urban development and tourism growth that has generated acute environmental impacts. Beginning with the European Union and Spain, the work then narrows its focus to the case study of Mallorca. The study is based on a review of the academic literature, statistical sources, and an analysis of the content of spatial and climate policy in Spain and the Balearic Islands. The work reflects on the flawed spatial planning responses to climate change and outlines strategies to adopt more radical measures for effective climate action. The work identifies six main shortcomings and makes proposals to tackle the challenges of the Anthropocene in Mallorca, responding to each of the deficiencies detected. The article seeks to encourage reflection and proposes key strategies for spatial governance and climate policy to lend coherence to the fight against climate change.
      Citation: Climate
      PubDate: 2022-11-14
      DOI: 10.3390/cli10110175
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 176: A Community Capitals Assessment of Climate
           Adaptations to Traditional Milpa Farming Practices in Mayan Communities of
           Southern Belize

    • Authors: Kristin Drexler
      First page: 176
      Abstract: Climate change has exacerbated food and livelihood insecurity for Mayan milpa farmers in Central America. For centuries, milpa farming has been sustainable for subsistence; however, in the last 50 years, milpas have become less reliable due to accelerating climate change, resource degradation, declining markets, poverty, and other factors. Increasing climate-smart agriculture (CSA) practices may be needed. Using interviews with extension leaders and milpa farmers in Belize, this qualitative study examines the capacity for increasing CSA aspects of existing traditional milpa practices, specifically no-burn mulching, soil enrichment, and the use of cover plants. Applying a modified Community Capitals Framework, this study finds four key capitals were perceived by farmers and agriculture extension leaders as barriers for increasing CSA practices. Recommendations to reduce the key barriers include reinstating markets and crop-buying programs and easing border customs restrictions (Governance-Justice and Financial Capitals), improving roads and cellular access for farmers (Infrastructure Capital), and increasing budgets and resources for agriculture extension services and building farmer capacity for CSA practices of mulching, soil enrichment, and cover plants (Human-Capacity Capital). Reducing barriers to these key capitals can facilitate an increase in milpa CSA practices and crop productivity, promote food and livelihood security, and enable climate resilience of Mayan milpa communities in Belize.
      Citation: Climate
      PubDate: 2022-11-14
      DOI: 10.3390/cli10110176
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 177: Comparative Analysis and Mitigation Strategy
           for the Urban Heat Island Intensity in Bari (Italy) and in Other Six
           European Cities

    • Authors: Valentino Sangiorgio, Silvana Bruno, Francesco Fiorito
      First page: 177
      Abstract: The presence of higher air temperatures in the city in comparison with the surrounding rural areas is an alarming phenomenon named the urban heat island (UHI). In the last decade, the scientific community demonstrated the severity of the phenomenon amplified by the combination of heat waves. In southern Italy, the UHI is becoming increasingly serious due to the presence of a warming climate, extensive urbanization and an aging population. In order to extensively investigate such phenomenon in several cities, recent research calibrated quantitative indexes to forecast the maximum UHI intensity in urban districts by exploiting multicriteria approaches and open-source data. This paper proposes different mitigation strategy to mitigate the Urban Heat Island Intensity in Bari. Firstly, the research evaluates the absolute max UHI intensity of the 17 urban districts of Bari (a city in southern Italy, Puglia) by exploiting the recent index-based approach IUHII. Secondly, a comparative evaluation of seven European cities (Bari, Alicante, Madrid, Paris, Berlin, Milan and London) is achieved to point out the positives and negative aspects of the different urban districts. In total, the comparison required the analysis of 344 districts of 7 European cities: 17 districts in Bari (Italia); 9 districts in Alicante (Spain); 21 in Madrid (Spain); 80 in Paris (France); 96 in Berlin (Germany); 88 in Milan (Italy) and 33 in London (UK). Finally, the results emphasize some virtuous examples of UHII mitigation in the major European cities useful to draw inspiration for effective mitigation strategies suitable for the urban context of Bari.
      Citation: Climate
      PubDate: 2022-11-17
      DOI: 10.3390/cli10110177
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 178: Climate Change and the Caribbean: Challenges
           and Vulnerabilities in Building Resilience to Tropical Cyclones

    • Authors: Clint T. Lewis
      First page: 178
      Abstract: Caribbean Small Island Developing States (SIDS) is one of the most vulnerable regions in the world to the impacts of climate change. The region has prioritized adaptation to climate change and has implemented many adaptation actions over the past 20 years. However, the region is becoming increasingly vulnerable to the impacts of tropical cyclones (TC). This paper analyses the impacts of TC on the region between 1980 to 2019. It aims to examine the economic loss and damage sustained by the region, identify the sectors most impacted, and ascertain the perspectives of key stakeholders on the factors that hinder building resilience. Statistical analysis techniques and semi-structured interviews were to unpack and understand the dataset. The paper finds that economic loss and damage has gradually increasing between 1980 to 2009 with a drastic increase between 2010 to 2019. The paper highlights the agriculture, housing, transport, and utility sectors as the most impacted. The findings also call to attention the need for increased access to adaptation financing for SIDS, the disadvantages of the income status that hinders building resilience, and the need for increased Early Warning Systems. The paper recommends revising the per capita national income as an eligibility criterion for accessing concessional development finance assistance, a comprehensive EWS for the countries in the region, and consideration of debt relief for countries affected by TC.
      Citation: Climate
      PubDate: 2022-11-18
      DOI: 10.3390/cli10110178
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 179: Early Drought Stress Warning in Plants: Color
           Pictures of Photosystem II Photochemistry

    • Authors: Michael Moustakas, Ilektra Sperdouli, Julietta Moustaka
      First page: 179
      Abstract: Drought, the major limiting factor for plant growth and crop productivity, affecting several physiological and biochemical processes, is expected to increase in duration, intensity, and frequency as a consequence of climate change. Plants have developed several approaches to either avoid or tolerate water deficit. Plants as a response to drought stress (DS), close stomata, reducing carbon dioxide (CO2) entry in the leaf, thus decreasing photosynthesis which results in reduced synthesis of essential organic molecules that sustain the life on earth. The reduced CO2 fixation, decreases electron transport rate (ETR), while the absorbed light energy overdoes what can be used for photochemistry resulting in excess reactive oxygen species (ROS) and oxidative stress. Current imaging techniques allow non-destructive monitoring of changes in the physiological state of plants under DS. Thermographic visualization, near-infrared imaging, and chlorophyll a fluorescence imaging are the most common verified imaging techniques for detecting stress-related changes in the display of light emission from plant leaves. Chlorophyll a fluorescence analysis, by use of the pulse amplitude modulation (PAM) method, can principally calculate the amount of absorbed light energy that is directed for photochemistry in photosystem II (PSII) (ΦPSII), dissipated as heat (ΦNPQ), or dissipated by the non-radiative fluorescence processes (ΦNO). The method of chlorophyll a fluorescence imaging analysis by providing colour pictures of the whole leaf PSII photochemistry, can successfully identify the early drought stress warning signals. Its implementation allowed visualization of the leaf spatial photosynthetic heterogeneity and discrimination between mild drought stress (MiDS), moderate drought stress (MoDS), and severe drought stress (SDS). The fraction of open reaction centers of PSII (qp) is suggested as the most sensitive and suitable indicator of an early drought stress warning and also for selecting drought tolerant cultivars.
      Citation: Climate
      PubDate: 2022-11-18
      DOI: 10.3390/cli10110179
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 180: Mitigation of Climate Change for Urban
           Agriculture: Water Management of Culinary Herbs Grown in an Extensive
           Green Roof Environment

    • Authors: Stuart Alan Walters, Christina Gajewski, Amir Sadeghpour, John W. Groninger
      First page: 180
      Abstract: Extensive green roofs provide space for local agriculture in dense urban environments. However, already extreme drought and heat conditions on green roofs are likely to worsen under future climates, challenging urban crop production and impeding food security. The potential productivity of annual and perennial culinary herbs on an extensive green roof (~8 cm depth) with minimal, but consistent, water inputs was evaluated within a humid, subtropical climate (Southern Illinois University-Carbondale, Carbondale, IL, USA). Vigor, growth, and overwintering ability of four different perennial culinary herbs, namely garlic chives (Allium tuberosum), lavender (Lavandula angustifolia ‘Munstead Dwarf’), lemon balm (Melissa officinalis), and winter thyme (Thymus vulgaris ‘Winter Thyme’), as well as vigor and growth of annual ‘Italian large-leaf’ basil (Ocimum basilicum) were evaluated under twice-weekly, weekly, and fortnightly water applications of 1 L to each plant. All species of perennial herbs produced greater dry perennial biomass and overwintering potential under the two most frequent water applications. Similarly, with weekly water applications, basil proved highly suitable for production in an extensive green roof environment. Weekly watering was required to provide commercially viable plant growth, vigor, and overwinter survival for all perennial herbs. These results indicate that supplemental water is an important consideration for sustaining culinary herb production on extensive green roofs with the increasingly hot and dry conditions provided under the climate change scenarios projected for cities currently experiencing temperate climates.
      Citation: Climate
      PubDate: 2022-11-19
      DOI: 10.3390/cli10110180
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 181: Assessing the Adaptive Capacity of Slum
           Households to Flooding in the Coastline of Portee and Rokupa, Freetown,
           Sierra Leone

    • Authors: Bashiru Turay
      First page: 181
      Abstract: Frequent flooding has been a significant problem in Freetown, causing loss of lives and properties. The situation is worse for coastal residents, who are more vulnerable and exposed to the impacts. The government has made commitments to strengthen resilience and adaptive capacity by 2030. However, there is currently insufficient information to comprehend the coastal residents of Portee and Rokupa’s capacity to adapt to the yearly flooding to which they are subjected. This study aims to assess the adaptive capacity of 204 slum households selected by purposive sampling and using the local adaptive capacity framework. The results show that the widespread adaptive concerns are unflood-proofed housing; low membership in community-based organizations; and the lack of innovative, flexible and forward-looking flood management initiatives. This study argues that the inhabitants have reached their adaptation limit and are now fated to more loss and damage. The author recommends future studies to forecast the assets in the study location that will potentially be affected by different flood intensities when subjected to future climate change scenarios.
      Citation: Climate
      PubDate: 2022-11-19
      DOI: 10.3390/cli10110181
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 182: A Proposed Approach towards Quantifying the
           Resilience of Water Systems to the Potential Climate Change in the Lali
           Region, Southwest Iran

    • Authors: Nejat Zeydalinejad, Hamid Reza Nassery, Farshad Alijani, Alireza Shakiba, Babak Ghazi
      First page: 182
      Abstract: Computing the resilience of water resources, especially groundwater, has hitherto presented difficulties. This study highlights the calculation of the resilience of water resources in the small-scale Lali region, southwest Iran, to potential climate change in the base (1961–1990) and future (2021–2050) time periods under two Representative Concentration Pathways, i.e., RCP4.5 and RCP8.5. The Lali region is eminently suitable for comparing the resilience of alluvial groundwater (Pali aquifer), karst groundwater (Bibitarkhoun spring and the observation wells W1, W2 and W3) and surface water (Taraz-Harkesh stream). The log-normal distribution of the mean annual groundwater level and discharge rate of the water resources was initially calculated. Subsequently, different conditions from extremely dry to extremely wet were assigned to the different years for every water system. Finally, the resilience values of the water systems were quantified as a number between zero and one, such that they can be explicitly compared. The Pali alluvial aquifer demonstrated the maximum resilience, i.e., 1, to the future climate change. The Taraz-Harkesh stream, which is fed by the alluvial aquifer and the Bibitarkhoun karst spring, which is the largest spring of the Lali region, depicted average resilience of 0.79 and 0.59, respectively. Regarding the karstic observation wells, W1 being located in the recharge zone had the lowest resilience (i.e., 0.52), W3 being located in the discharge zone had the most resilience (i.e., 1) and W2 being located between W1 and W3 had an intermediate resilience (i.e., 0.60) to future climate change.
      Citation: Climate
      PubDate: 2022-11-19
      DOI: 10.3390/cli10110182
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 183: Phosphorous Nanofertilizers for Precise
           Application in Rice Cultivation as an Adaptation to Climate Change

    • Authors: Raquel Saraiva, Quirina Ferreira, Gonçalo C. Rodrigues, Margarida Oliveira
      First page: 183
      Abstract: Rice is the staple food of more than half of the world’s population, which is still growing. The great dependence that agriculture, and rice specially, has on fertilizers alongside extreme events that result from climatic change creates an urge for adaptation. Fertilizers are expensive, finite and a potential environmental problem. Their precise application, by the use of slow-release nanofertilizers, thus avoiding losses and consequently reducing the pressure on water resources, is one step forward in this adaptation. It can reduce costs and protect the environment while ensuring food production. Phosphorous is very important for rice, since it is involved in its flowering and root development, and its low availability to the plants constitutes a serious problem. The delivery of phosphorous through the crop cycle in the form of slow-release phosphorus nanofertilizer (Pnf) instead of the conventional annual bulk application reduces the amount of nutrients applied and increases the absorption by the crop. Combining the fertilizing effect with the use of natural stimulant compounds such as chitosan can protect the crop from diseases and increase its resilience to stress. The use of Pnf reduces the pressure on water resources and avoids imbalances in soil nutrients, thus responding to climatic change challenges and abiotic stresses.
      Citation: Climate
      PubDate: 2022-11-20
      DOI: 10.3390/cli10110183
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 184: Temporal and Spatial Distribution of
           Lightning Activity over Bulgaria during the Period 2012–2021 Based
           on ATDnet Lightning Data

    • Authors: Boryana Dimitrova Tsenova, Ilian Gospodinov
      First page: 184
      Abstract: In the present study, lightning activity based on data from ATDnet over the territory of Bulgaria for the 10-year period between 2012 and 2021 is evaluated. This analysis shows the highest lightning activity with the greatest number of thunderstorm days in June. December is the month with the lowest number of flashes and thunderstorm days. It was found that more than 30% of thunderstorm days annually are in the cold half of the year over the southern part of the considered domain. The average diurnal distribution showed a maximum of lightning activity between 12 and 15 UTC, while over some mountainous and sea regions it is between 03 and 06 UTC. The spatial distribution of flash density (fl km−2 y−1) reveals that the number of flashes and the number of thunderstorm days increase with altitude up to 1800 m and then decrease for higher altitudes.
      Citation: Climate
      PubDate: 2022-11-21
      DOI: 10.3390/cli10110184
      Issue No: Vol. 10, No. 11 (2022)
       
  • Climate, Vol. 10, Pages 137: Intensity, Duration and Spatial Coverage of
           Aridity during Meteorological Drought Years over Northeast Thailand

    • Authors: Tenanile Dlamini, Veeranun Songsom, Werapong Koedsin, Raymond J. Ritchie
      First page: 137
      Abstract: Gaps in drought monitoring result in insufficient preparation measures for vulnerable areas. This paper employed the standardized precipitation index (SPI) to identify meteorological drought years and the Thornthwaite aridity index (TAI) to evaluate aridity in three provinces of northeast Thailand growing cassava and sugarcane at massive scales. Precipitation and temperature data were sourced from Global Land Data Assimilation System-2 (GLDAS-2) Noah Model products at 0.25 degree resolution and used for calculating the drought indices. This study was conducted for the period of 2004 to 2015. The SPI was computed for 1, 3 and 6 months scales to measure short- to medium-term moisture. The results indicated major meteorological drought years as 2004, 2005, 2010, 2012, 2014 and 2015. A range of 1 to 3 months of extreme rainfall shortage was experienced during each of these years, including the growing season of 2004, 2012 and 2015. TAI-based results indicated that the area experiences an average of 7 to 8 months of aridity during drought periods, compared to the historical overall average of 6 months. The spatial TAI for the major drought years indicated delayed onset, intermittency or early cut-off of the rainy season. The year 2004 was the most intense in terms of aridity. The longest duration of aridness for some areas was between 9 and 10 months in 2012 and 2014, respectively. In terms of spatial coverage, all meteorological drought years had out-of-season aridity. Based on the region’s historical records, this highlighted an increase in the frequency of droughts and duration of aridity. A disturbance in the growing season has the potential to affect crop yields, hence, the need to improve and strengthen existing adaptive measures for agriculture as the main source of food and income in the northeast.
      Citation: Climate
      PubDate: 2022-09-23
      DOI: 10.3390/cli10100137
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 138: On the Intercontinental Transferability of
           Regional Climate Model Response to Severe Forestation

    • Authors: Olivier Asselin, Martin Leduc, Dominique Paquin, Alejandro Di Di Luca, Katja Winger, Melissa Bukovsky, Biljana Music, Michel Giguère
      First page: 138
      Abstract: The biogeophysical effects of severe forestation are quantified using a new ensemble of regional climate simulations over North America and Europe. Following the protocol outlined for the Land-Use and Climate Across Scales (LUCAS) intercomparison project, two sets of simulations are compared, FOREST and GRASS, which respectively represent worlds where all vegetation is replaced by trees and grasses. Three regional climate models were run over North America. One of them, the Canadian Regional Climate Model (CRCM5), was also run over Europe in an attempt to bridge results with the original LUCAS ensemble, which was confined to Europe. Overall, the CRCM5 response to forestation reveals strong inter-continental similarities, including a pronounced wintertime and springtime warming concentrated over snow-masking evergreen forests. Crucially, these northern evergreen needleleaf forests populate lower, hence sunnier, latitudes in North America than in Europe. Snow masking reduces albedo similarly over both continents, but stronger insolation amplifies the net shortwave radiation and hence warming simulated over North America. In the summertime, CRCM5 produces a mixed response to forestation, with warming over northern needleleaf forests and cooling over southern broadleaf forests. The partitioning of the turbulent heat fluxes plays a major role in determining this response, but it is not robust across models over North America. Implications for the inter-continental transferability of the original LUCAS results are discussed.
      Citation: Climate
      PubDate: 2022-09-23
      DOI: 10.3390/cli10100138
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 139: Potential Climate Impacts of Hydrological
           Alterations and Discharge Variabilities of the Mura, Drava, and Danube
           Rivers on the Natural Resources of the MDD UNESCO Biosphere Reserve

    • Authors: Tadić, Tamás, Mihaljević, Janjić
      First page: 139
      Abstract: This study investigated hydrological alterations in the sections of the Mura, Drava, and Danube rivers, which together form a unique river landscape proclaimed by UNESCO as the Transboundary Biosphere Reserve Mura, Drava, and Danube (TBR MDD). A coherent network of 12 major protected areas along the rivers highlights their ecological value, which could be endangered by climate change and consequent environmental changes. Statistical analyses, such as the homogeneity test, Mann–Kendall trend test of monthly and seasonal discharges, and empirical probabilities of daily discharges, were applied to discharge data series (1960–2019) from six hydrological stations prior to the calculation of indicators of hydrologic alteration (IHA). This method could be a helpful tool for recognizing the changes in hydrological regimes that can affect river ecosystems. The 33 indicators were organized into five groups. The results showed a decrease in low pulse duration and increase in rise/fall rates and the number of reversals. From an ecological perspective, the results obtained for the probabilities of long flooding periods were particularly significant. They drastically decreased for all three rivers on their stretches within the reserve. According to IHA modeling results, the river sections analyzed were moderately altered with global indicator values between 0.5 and 0.75. The most pronounced hydrological alterations were associated with the frequency and duration of low and high pulses and the rate and frequency of changes in water condition, which could have a significant impact on the ecological values of the TBR MDD. In addition, results show more pronounced climate impact versus human activities.
      Citation: Climate
      PubDate: 2022-09-25
      DOI: 10.3390/cli10100139
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 140: A New Way to Obtain Climate Files in Areas
           with the Presence of Microclimates by Applying the Sandia Method: A
           Galician Case Study

    • Authors: Antonio Couce-Casanova, Juan de Dios Rodríguez-García, María Isabel Lamas, José A. Orosa
      First page: 140
      Abstract: In order to obtain reliable energy simulation results, it is essential to have accurate climate files corresponding to specific geographical locations. The present work describes a selection process of the Typical Meteorological Months (TMM) that will generate the Typical Meteorological Years (TMY) in eight locations of the Community of Galicia for an analysis period between 2008 and 2017 (10 years). The region of Galicia, located in the northwest of the Iberian Peninsula, due to its particular orography, is prone to the generation of differentiated microclimates in relatively close locations. The process of selecting the typical meteorological months has been carried out following the Sandia Laboratories method. In the present work, data from terrestrial meteorological stations have been combined with solar radiation data obtained from satellite images. Finally, for the validation and comparative study of results, files have been generated in Energy Plus Weather (epw) format. Trends have been checked and typical statistics have been used to analyse the correlations between the files generated with the Sandia method, and the usual reference files (LT, WY, BY). It is observed that with the eight files generated, new differentiated climates are detected, which will affect the improvement of the precision of the energy simulations of buildings that are going to be carried out. For example, in the case of the Campus Lugo and Pedro Murias stations, located in the same climatic zone according to Spanish regulations, differences are observed in the annual averages: DTm (13.7%), WV (41%) or GHI (9%).
      Citation: Climate
      PubDate: 2022-09-25
      DOI: 10.3390/cli10100140
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 141: Thunderstorm Activity and Extremes in Vietnam
           for the Period 2015–2019

    • Authors: Khiem Van Mai, Terhi K. Laurila, Lam Phuc Hoang, Tien Duc Du, Antti Mäkelä, Sami Kiesiläinen
      First page: 141
      Abstract: Within a meteorological capacity building project in Vietnam, lightning location data and manual (human-observed) thunderstorm day observations were analyzed for the period 2015–2019. The lightning location dataset, based on the global lightning detection system Vaisala GLD360, consists of a total of 315,522,761 lightning strokes. The results indicate that, on average, 6.9 million lightning flashes per year occur in the land areas of Vietnam; this equals a lightning flash density of 20 flashes km−2 yr−1. The largest average annual flash density values occur in three regions in North, Central and South Vietnam. The majority of lightning occurs in the monsoon season (April–September), peaking in May, while in October–March, the lightning activity is very modest. During individual intense thunderstorm days, the flash density may exceed 12 flashes km−2 day−1. Thunderstorms in Central Vietnam are generally more intense, i.e., more lightning is expected on average per one thunderstorm day in Central Vietnam than in other regions. This study is a continuation of several years of meteorological capacity building in Vietnam, and the results suggest that large socio-economic benefits can be received by understanding the local thunderstorm climatology in high detail, especially in a country such as Vietnam, where lightning causes substantial socio-economic losses annually.
      Citation: Climate
      PubDate: 2022-09-28
      DOI: 10.3390/cli10100141
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 142: Temperature and Residential Electricity
           Demand for Heating and Cooling in G7 Economies: A Method of Moments Panel
           Quantile Regression Approach

    • Authors: Chukwuemeka Chinonso Emenekwe, Nnaemeka Vincent Emodi
      First page: 142
      Abstract: The global energy system is highly vulnerable to climate variability and change. This results in a vast range of impacts on the energy demand sector and production and supply channels. This article aims to estimate the impacts of variables such as heating and cooling temperatures, income, population, and price on residential electricity demand in G7 countries. Methodologically, this study uses the second-generation panel unit root and cointegration approaches (which are robust in the presence of cross-sectional dependence), a panel fixed effects model with Driscoll–Kraay standard errors, and a novel method of moments quantile regression (MM-QR) to determine long-run elasticities. The results suggest that the residential electricity demand of G7 countries is statistically and positively responsive to cold days rather than hot days. This study also presents some policy-relevant issues based on the results.
      Citation: Climate
      PubDate: 2022-09-29
      DOI: 10.3390/cli10100142
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 143: Contribution to the Study of Forest Fires in
           Semi-Arid Regions with the Use of Canadian Fire Weather Index Application
           in Greece

    • Authors: Nikolaos Ntinopoulos, Marios Spiliotopoulos, Lampros Vasiliades, Nikitas Mylopoulos
      First page: 143
      Abstract: Forest fires are of critical importance in the Mediterranean region. Fire weather indices are meteorological indices that produce information about the impact as well as the characteristics of a fire event in an ecosystem and have been developed for that reason. This study explores the spatiotemporal patterns of the FWI system within a study area defined by the boundaries of the Greek state. The FWI has been calculated and studied for current and future periods using data from the CFSR reanalysis model from the National Centers for Environmental Protection (NCEP) as well as data from NASA satellite programs and the European Commission for Medium-Range Weather Forecasts (ECWMF) in the form of netCDF files. The calculation and processing of the results were conducted in the Python programming language, and additional drought- and fire-related indices were calculated, such as the standardized precipitation index (SPI), number of consecutive 50-day dry periods (Dry50), the Fosberg fire weather index (FFWI), the days where the FWI exceeds values of 40 and 50 days (FWI > 40) and (days FWI > 50). Similar patterns can easily be noted for all indices that seem to have their higher values concentrated in the southeast of the country owing to the higher temperatures and more frequent drought events that affect the indices’ behavior in both the current and future periods.
      Citation: Climate
      PubDate: 2022-09-30
      DOI: 10.3390/cli10100143
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 144: Temporal and Spatial Variability of Dryness
           Conditions in Kazakhstan during 1979–2021 Based on Reanalysis Data

    • Authors: Irina Zheleznova, Daria Gushchina, Zhiger Meiramov, Alexander Olchev
      First page: 144
      Abstract: The spatial and temporal variability of dryness conditions in the territory of Kazakhstan during the period 1979–2021 was investigated using monthly and hourly ERA5 reanalysis data on air temperature and precipitation as well as various aridity indices. A large part of the territory is characterized by the air temperature increase in summer and spring, as well as precipitation reduction, especially during the summer months. It was shown that the end of the 20th century (1979–2000) and the beginning of the 21st century (2001–2021) are characterized by different trends in air temperature and precipitation. All applied indices, i.e., the Palmer Drought Severity Index (PDSI), the Keetch–Byram Drought Index (KBDI), Standardized Precipitation (SPI) and Standardized Precipitation Evapotranspiration (SPEI), showed increased dryness in most parts of the territory of Kazakhstan. KBDI indicated an increased risk of wildfires, especially in the southwestern and northwestern regions. The hottest and driest areas are situated in the regions that are simultaneously affected by rising temperatures and reduced precipitation in spring and summer. The strongest increase in aridity and fire risk in the southwest and northwest is mainly due to reduced precipitation in the summer. Minimal risks of droughts occur in the northern and central regions, where conditions in the early 21st century became even less favorable for drought formation compared to the late 20th century (increased precipitation in both spring and summer and lower summer temperatures).
      Citation: Climate
      PubDate: 2022-09-30
      DOI: 10.3390/cli10100144
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 145: Compound Risk of Air Pollution and Heat Days
           and the Influence of Wildfire by SES across California, 2018–2020:
           Implications for Environmental Justice in the Context of Climate Change

    • Authors: Shahir Masri, Yufang Jin, Jun Wu
      First page: 145
      Abstract: Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018–2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 μg/m3 showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.
      Citation: Climate
      PubDate: 2022-10-01
      DOI: 10.3390/cli10100145
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 146: Evaluation of Bioclimatic Discomfort Trend in
           a Central Area of the Mediterranean Sea

    • Authors: Monforte, Ragusa
      First page: 146
      Abstract: Effects of climate change are perceived in ever larger areas of the planet. Heat waves occur with increasing frequency, constituting a risk to the population, especially for the most sensitive subjects. Preventive information to the population on the characteristics of the phenomenon and on the behavior to be supported is the means to reduce the health risks. To monitor the intensity of heat and the physiological discomfort perceived by humans, there are indices based on the perception of meteorological parameters such as temperature and relative humidity. In this work, by applying the Thom Discomfort Index (TDI), the first bioclimatic characterization of the provinces that make up Sicily, a Mediterranean region defined as a hotspot for climate change, was performed by the authors. The nonparametric Mann–Kendall test was applied to the daily values of the TDI in all provinces in order to verify the presence of significant trends. The test results highlighted the existence of increasing trends, especially in the months of August and September, when the TDI value undergoes a significant increase due not only to high temperatures, as one might expect, but above all to a high humidity rate. When these two meteorological parameters reach certain values, the physiological discomfort from humid heat represents a risk to the population.
      Citation: Climate
      PubDate: 2022-10-05
      DOI: 10.3390/cli10100146
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 147: Comprehensive Review: Advancements in
           Rainfall-Runoff Modelling for Flood Mitigation

    • Authors: Muhammad Jehanzaib, Muhammad Ajmal, Mohammed Achite, Tae-Woong Kim
      First page: 147
      Abstract: Runoff plays an essential part in the hydrological cycle, as it regulates the quantity of water which flows into streams and returns surplus water into the oceans. Runoff modelling may assist in understanding, controlling, and monitoring the quality and amount of water resources. The aim of this article is to discuss various categories of rainfall–runoff models, recent developments, and challenges of rainfall–runoff models in flood prediction in the modern era. Rainfall–runoff models are classified into conceptual, empirical, and physical process-based models depending upon the framework and spatial processing of their algorithms. Well-known runoff models which belong to these categories include the Soil Conservation Service Curve Number (SCS-CN) model, Storm Water Management model (SWMM), Hydrologiska Byråns Vattenbalansavdelning (HBV) model, Soil and Water Assessment Tool (SWAT) model, and the Variable Infiltration Capacity (VIC) model, etc. In addition, the data-driven models such as Adaptive Neuro Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN), Deep Neural Network (DNN), and Support Vector Machine (SVM) have proven to be better performance solutions in runoff modelling and flood prediction in recent decades. The data-driven models detect the best relationship based on the input data series and the output in order to model the runoff process. Finally, the strengths and downsides of the outlined models in terms of understanding variation in runoff modelling and flood prediction were discussed. The findings of this comprehensive study suggested that hybrid models for runoff modeling and flood prediction should be developed by combining the strengths of traditional models and machine learning methods. This article suggests future research initiatives that could help with filling existing gaps in rainfall–runoff research and will also assist hydrological scientists in selecting appropriate rainfall–runoff models for flood prediction and mitigation based on their benefits and drawbacks.
      Citation: Climate
      PubDate: 2022-10-10
      DOI: 10.3390/cli10100147
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 148: Evolution and Trends of Meteorological
           Drought and Wet Events over the Republic of Djibouti from 1961 to 2021

    • Authors: Omar Assowe Dabar, Abdi-Basid Ibrahim Adan, Moussa Mahdi Ahmed, Mohamed Osman Awaleh, Moussa Mohamed Waberi, Pierre Camberlin, Benjamin Pohl, Jalludin Mohamed
      First page: 148
      Abstract: Drought is a meteorological and hydrological phenomenon affecting the environment, agriculture, and socioeconomic conditions, especially in arid and semi-arid regions. A better understanding of drought characteristics over short and long timescales is therefore crucial for drought mitigation and long-term strategies. For the first time, this study evaluates the occurrence, duration, and intensity of drought over the Republic of Djibouti by using a long-term (1961–2021) rainfall time series at Djibouti Airport, completed by the CHIRPS precipitation product and local records from 35 weather stations. The drought is examined based on the Standardized Precipitation–Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) at 3-, 6-, 9-, 12-, and 24-month timescales, so as to document short-, medium-, and long-duration events. The SPEI and SPI showed a significant drying tendency for the indices computed over 12 and 24 months at Djibouti Airport. The eastern coastal region of the Republic of Djibouti was the most affected by the increased drought incidence in recent decades, with more than 80% of the extremely and severely dry events occurring within the period 2007–2017. In contrast, the western regions recorded a positive trend in their SPIs during the period 1981–2021, due to the dominance of the June–September (JJAS) rains, which tend to increase. However, in the last few decades, the whole country experienced the droughts of 2006/2007 and 2010/2011, which were the longest and most intense on record. Large-scale climate variability in the Indo-Pacific region partially affects drought in Djibouti. The SPI and SPEI are significantly positively correlated with the Indian Ocean Dipole during October–December (OND), while for JJAS the SPI and SPEI are negatively correlated with Nino3.4. The wet event in 2019 (OND) causing devastating floods in Djibouti city was linked with a positive IOD anomaly. This study provides essential information on the characteristics of drought in the Republic of Djibouti for decision-makers to better plan appropriate strategies for early warning systems to adapt and mitigate recurrent droughts that put the country’s agro-pastoral populations in a precarious situation.
      Citation: Climate
      PubDate: 2022-10-12
      DOI: 10.3390/cli10100148
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 149: Climate Shocks and Social Networks:
           Understanding Adaptation among Rural Indian Households

    • Authors: Richard Anthony Ramsawak
      First page: 149
      Abstract: This paper seeks to uncover the impact of negative rainfall shocks on household social network relationships. I leverage the uncertainty generated from fluctuating long-term rainfall patterns across India, to estimate the impact of heightened climate risks on investments in social network relationships. In so doing, I attempt to disentangle the “direct” and “adaptive” impacts of climate shocks on social network relationships. I found that households that experience higher than average negative rainfall shocks (lower than average rainfall levels over the long term) tend to invest more in family–caste and vertical or linked network relationships. These network relationships were also found to be associated with greater access to financial credit, credit sourced specifically from family members, higher reported collaboration, more diversified businesses, and the use of private irrigation technologies, all of which are key to mitigating the negative impacts of climate shocks. Unlike past research, these results suggest that households’ decisions to invest in social networks may be an adaptive response to higher climate risk. In terms of policy implications, these results highlight the importance of strengthening and supporting family-based and linked networks (such as links to local governmental agencies and extension services) in the face of higher climate risks.
      Citation: Climate
      PubDate: 2022-10-12
      DOI: 10.3390/cli10100149
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 150: Variation Patterns of the ENSO’s
           Effects on Dust Activity in North Africa, Arabian Peninsula, and Central
           Asia of the Dust Belt

    • Authors: Zhi-Yong Yin, Anne Maytubby, Xiaodong Liu
      First page: 150
      Abstract: El Niño/Southern Oscillation (ENSO) events produce anomalous oceanographic and atmospheric conditions in regions far from the equatorial central-eastern Pacific, which modulate the atmospheric and surface processes that influence the dust emission, transport, and deposition in many places on Earth. In this study, we examined the MERRA-2 dust column mass density data in five subregions of the “dust belt”: eastern and western Arabian Peninsula, western and eastern Central Asia, and North Africa-Sahara during 1980–2021. We discovered that, while there is a common dust season from April to July, the specific dust seasons in these subregions are different with the peaks of dust activity occurring at different times of the year. In the meantime, the modulating effects of ENSO also peak at different times within the respective dust seasons. For example, ENSO has a persistent effect on dust activity during April-August in the eastern Arabian Peninsula, while its influence in eastern Central Asia lasts from February to November. For different well-recognized factors of dust activities, such as precipitation/humidity, wind, vegetation, and soil moisture, their responses to ENSO are also different in these subregions. For precipitation, humidity, and soil moisture, their responses to ENSO are mostly positive in winter and spring/early summer months during El Niño years, while mean daily maximum wind responded positively in spring, but it did so negatively in summer. During the three months when the ENSO’s effects were strongest, these factors could explain 25.1–58.6% of the variance in the dust column mass density in combination with the ENSO’s modulation effects. However, the highest model-explained variance was obtained for the North Africa–Sahara subregion where the intensity of dust activity was not statistically correlated with ENSO.
      Citation: Climate
      PubDate: 2022-10-13
      DOI: 10.3390/cli10100150
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 151: Spatiotemporal Variation of Tourism Climate
           Index for Türkiye during 1981–2020

    • Authors: Bahtiyar Efe, Edanur Gözet, Evren Özgür, Anthony R. Lupo, Ali Deniz
      First page: 151
      Abstract: Tourism activities are highly dependent on climatological conditions. The climatological suitability of tourism destinations is investigated by using a Tourism Climate Index (TCI) that is frequently used by researchers. The TCI varies between 0 and 100 and is created by using temperature, relative humidity, sunshine duration, wind and precipitation data. For TCI, 100 is for ideal and 0 is for extremely unfavorable conditions for tourism. In this study, the meteorological data covering the period of 1981–2020 for 98 stations is used to calculate the TCI of each station for all seasons and months. The Mann—Kendall trend test is used for TCI behavior of the entire country and Sen Innovative Trend Analysis method is used for four famous tourism destinations. For summer, coastal regions have smaller TCI values than inland regions due to the high amount of relative humidity. Most stations have TCI values in the “Very Good” category or better. In spring and autumn, the TCI values fall into the “Acceptable” category or better. The winter is the season with smallest TCI values. For summer, 54 of 98 stations have a decreasing trend at different levels of significance and four of them have an increasing trend. In autumn, 30 stations have an increasing trend and two stations have a decreasing trend at standard levels of significance. Similarly, for spring, 20 stations have an increasing trend and one has a decreasing trend. During winter, 14 stations have an increasing trend while one has decreasing trend. The Sen Innovative Trend test shows an increasing trend on average for four famous tourism destinations during May–September months.
      Citation: Climate
      PubDate: 2022-10-14
      DOI: 10.3390/cli10100151
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 152: The Value-Add of Tailored Seasonal Forecast
           Information for Industry Decision Making

    • Authors: Clare Mary Goodess, Alberto Troccoli, Nicholas Vasilakos, Stephen Dorling, Edward Steele, Jessica D. Amies, Hannah Brown, Katie Chowienczyk, Emma Dyer, Marco Formenton, Antonio M. Nicolosi, Elena Calcagni, Valentina Cavedon, Victor Estella Perez, Gertie Geertsema, Folmer Krikken, Kristian Lautrup Nielsen, Marcello Petitta, José Vidal, Martijn De Ruiter, Ian Savage, Jon Upton
      First page: 152
      Abstract: There is a growing need for more systematic, robust, and comprehensive information on the value-add of climate services from both the demand and supply sides. There is a shortage of published value-add assessments that focus on the decision-making context, involve participatory or co-evaluation approaches, avoid over-simplification, and address both the quantitative (e.g., economic) and qualitative (e.g., social) values of climate services. The 12 case studies that formed the basis of the European Union-funded SECLI-FIRM project were co-designed by industrial and research partners in order to address these gaps while focusing on the use of tailored sub-seasonal and seasonal forecasts in the energy and water industries. For eight of these case studies, it was possible to apply quantitative economic valuation methods: econometric modelling was used in five case studies while three case studies used a cost/loss (relative economic value) analysis and avoided costs. The case studies illustrated the challenges in attempting to produce quantitative estimates of the economic value-add of these forecasts. At the same time, many of them highlighted how practical value for users—transcending the actual economic value—can be enhanced; for example, through the provision of climate services as an extension to their current use of weather forecasts and with the visualisation tailored towards the user.
      Citation: Climate
      PubDate: 2022-10-16
      DOI: 10.3390/cli10100152
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 153: Seaside Renewable Energy Resources Literature
           Review

    • Authors: Nebiyu Wolde Girgibo
      First page: 153
      Abstract: This review paper describes seaside renewable energy resources. The motivation and need behind this work are to give background literature on the use of climate change effects as a resource support for shallow geothermal-energy (seaside energy solutions) production. This leads to combating and mitigating climate change by using its effect to our advantage. As a part of my literature review as a report series, this report gives some background about seaside energy solutions relating to water quality and climate change. This review paper addresses all aspects of renewable energy. The methodology implemented in this review paper and other series was a systematic literature review process. After searching and collecting articles from three databases, they were evaluated by title, abstract and whole article then synthesized into the literature review. The key conclusion is that seaside renewable energy is mainly shallow geothermal-energy and most of the methods use climate change effects to their advantage such as sediment heat energy production. The main recommendation is to use the effects of climate change to combat and mitigate its causes and further consequences. The overall conclusions are built on the relationships between different aspects of the topics. The paper contributes a precise current review of renewable energy. It is the last part of a series of four review papers on climate change, land uplift, water resources, and these seaside energy solutions.
      Citation: Climate
      PubDate: 2022-10-18
      DOI: 10.3390/cli10100153
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 154: Analysis of the Temporal Evolution of Climate
           Variables Such as Air Temperature and Precipitation at a Local Level:
           Impacts on the Definition of Strategies for Adaptation to Climate Change

    • Authors: Leonel J. R. Nunes
      First page: 154
      Abstract: Climate change is a global phenomenon that can affect neighbouring territories and the communities residing there in different ways. This fact, which is associated with the specificities of each of the territories, leads to the need to implement adaptive measures to address the new reality imposed by climate change and to create more resilient territories and communities capable of facing this new paradigm. The more these measures are adjusted to the specificities of the territories and their communities, the more efficient they will be. Thus, it is essential to have a thorough understanding of the evolution of the climate on the local scale and the real needs of the resident populations. To identify these needs, a survey was conducted, and it was found that the dominant opinion of all respondents, comprising citizens residing in Portugal, was that climate change can affect geographically close territories in different ways. In the present work, the municipality of Guimarães, located in the north of Portugal, was used as a case study, where a comparative analysis was carried out to assess the period between the current climate, characterized by the period of 1971–2021, and the climate of 100 years ago, characterized by the decade of 1896–1905, to determine trends for the variables of air temperature and precipitation. It was found that the temperature in the winter months increased, with less uniformity in the distribution of precipitation throughout the year. These differences in the air temperature and precipitation, as variables, lead to the need to plan adaptive measures that can be implemented so that the territory and its communities become more resilient to climate change.
      Citation: Climate
      PubDate: 2022-10-18
      DOI: 10.3390/cli10100154
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 155: Mid-XIX Century Estuary SST Time Series
           Recorded in the Venice Lagoon

    • Authors: Sara Rubinetti, Davide Zanchettin, Kevin Gazzola, Alvise Papa, Angelo Rubino
      First page: 155
      Abstract: Sea surface temperature (SST) is of paramount importance for comprehending ocean dynamics and hence the Earth’s climate system. Accordingly, it is also the most measured oceanographic parameter. However, until the end of the XIX century, no continuous time series of SST seems to exist, with most of the available data deriving from measurements on ships. Here, we present a continuous digitalized record of surface water measurements originally written in a book published in 1853. The measurements were retrieved thrice daily in the Venice lagoon, in the northeastern part of the Italian peninsula, from June to August 1851 and 1852. To the best of our knowledge, these data constitute the oldest time series of the entire world ocean. The measurements were performed by immersing a Réaumur thermometer a few meters deep in the lagoon water at 8 a.m., 12 p.m., and 8 p.m. Despite several limitations affecting these data (e.g., lacking information regarding the exact water depth where measurements were performed and instrumental metadata), they are of utmost significance, as they put many decades backward the date of the development of a fundamental aspect of oceanographic observations. Moreover, the data were collected close to the Punta della Salute site, where actual sea water temperature measurements have been performed since 2002. Therefore, a unique comparison between surface water temperatures within the Lagoon of Venice across three centuries is possible.
      Citation: Climate
      PubDate: 2022-10-20
      DOI: 10.3390/cli10100155
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 156: Appraisal of Satellite Rainfall Products for
           Malwathu, Deduru, and Kalu River Basins, Sri Lanka

    • Authors: Helani Perera, Nipuna Senaratne, Miyuru B. Gunathilake, Nitin Mutill, Upaka Rathnayake
      First page: 156
      Abstract: Satellite Rainfall Products (SRPs) are now in widespread use around the world as a better alternative for scarce observed rain gauge data. Upon proper analysis of the SRPs and observed rainfall data, SRP data can be used in many hydrological applications. This evaluation is very much necessary since, it had been found that their performances vary with different areas of interest. This research looks at the three prominent river basins; Malwathu, Deduru, and Kalu of Sri Lanka and evaluates six selected SRPs, namely, IMERG, TRMM 3B42, TRMM 3B42-RT, PERSIANN, PERSIANN-CCS, PERSIANN-CDR against 15+ years of observed rainfall data with the use of several indices. Four Continuous Evaluation Indices (CEI) such as Root Mean Square Error (RMSE), Percentage Bias (PBIAS), Pearson’s Correlation Coefficient (r), and Nash Sutcliffe Efficiency (NSE) were used to evaluate the accuracy of SRPs and four Categorical Indices (CI) namely, Probability of Detection (POD), Critical Success Index (CSI), False Alarm Ratio (FAR) and Proportion Correct (PC) was used to evaluate the detection and prediction accuracy of the SRPs. Then, the Mann–Kendall Test (MK test) was used to identify trends in the datasets and Theil’s and Sens Slope Estimator to quantify the trends observed. The study of categorical indicators yielded varying findings, with TRMM-3B42 performing well in the dry zone and IMERG doing well in the wet zone and intermediate zone of Sri Lanka. Regarding the CIs in the three basins, overall, IMERG was the most reliable. In general, all three basins had similar POD and PC findings. The SRPs, however, underperformed in the dry zone in terms of CSI and FAR. Similar findings were found in the CEI analysis, as IMERG gave top performance across the board for all four CEIs in the three basins. The three basins’ overall weakest performer was PERSIANN-CCS. The trend analysis revealed that there were very few significant trends in the observed data. Even when significant trends were apparent, the SRP projections seldom captured them. TRMM-3B42 RT had the best trend prediction performance. However, Sen’s slope analysis revealed that while the sense of the trend was properly anticipated, the amplitude of the prediction significantly differed from that of the observed data.
      Citation: Climate
      PubDate: 2022-10-20
      DOI: 10.3390/cli10100156
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 157: Quantifying Aggravated Threats to Stormwater
           Management Ponds by Tropical Cyclone Storm Surge and Inundation under
           Climate Change Scenarios

    • Authors: Hongyuan Zhang, Dongliang Shen, Shaowu Bao, Leonard Pietrafesa, Paul T. Gayes, Hamed Majidzadeh
      First page: 157
      Abstract: Stormwater management ponds (SMPs) protect coastal communities from flooding caused by heavy rainfall and runoff. If the SMPs are submerged under seawater during a tropical cyclone (TC) and its storm surge, their function will be compromised. Under climate change scenarios, this threat is exacerbated by sea level rise (SLR) and more extreme tropical cyclones. This study quantifies the impact of tropical cyclones and their storm surge and inundation on South Carolina SMPs under various SLR scenarios. A coupled hydrodynamic model calculates storm surge heights and their return periods using historical tropical cyclones. The surge decay coefficient method is used to calculate inundation areas caused by different return period storm surges under various SLR scenarios. According to the findings, stormwater management ponds will be aggravated by sea level rise and extreme storm surge. In South Carolina, the number of SMPs at risk of being inundated by tides and storm surges increases almost linearly with SLR, by 10 SMPs for every inch of SLR for TC storm surges with all return periods. Long Bay, Charleston, and Beaufort were identified as high-risk coastal areas. The findings of this study indicate where current SMPs need to be redesigned and where more SMPs are required. The modeling and analysis system used in this study can be employed to evaluate the effects of SLR and other types of climate change on SMP facilities in other regions.
      Citation: Climate
      PubDate: 2022-10-21
      DOI: 10.3390/cli10100157
      Issue No: Vol. 10, No. 10 (2022)
       
  • Climate, Vol. 10, Pages 158: Downscaled Climate Change Projections in
           Urban Centers of Southwest Ethiopia Using CORDEX Africa Simulations

    • Authors: Tesfaye Dessu Geleta, Diriba Korecha Dadi, Chris Funk, Weyessa Garedew, Damilola Eyelade, Adefires Worku
      First page: 158
      Abstract: Projections of future climate change trends in four urban centers of southwest Ethiopia were examined under a high Representative Concentration Pathways (RCP8.5) scenario for near- (2030), mid- (2050), and long-term (2080) periods based on high-resolution (0.220) Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa data. The multi-model ensemble projects annual maximum and minimum temperatures increasing by 0.047 °C per year (R2 > 0.3) and 0.038 °C per year (R2 > 0.7), respectively, with the rates increased by a factor of 10 for decadal projections between the 2030s and 2080s. The monthly maximum temperature increase is projected to be 1.41 °C and 2.82 °C by 2050 and 2080, respectively. In contrast, the monthly minimum temperature increase is projected to reach +3.2 °C in 2080. The overall seasonal multi-model ensemble average shows an increment in maximum temperature by +1.1 °C and +1.9 °C in 2050 and 2080, with the highest change in the winter, followed by spring, summer, and autumn. Similarly, the future minimum temperature is projected to increase across all seasons by 2080, with increases ranging from 0.4 °C (2030s) to 3.2 °C (2080s). All models consistently project increasing trends in maximum and minimum temperatures, while the majority of the models projected declining future precipitation compared to the base period of 1971–2005. A two-tailed T-test (alpha = 0.05) shows a significant change in future temperature patterns, but no significant changes in precipitation were identified. Changes in daily temperature extremes were found in spring, summer, and autumn, with the largest increases in extreme heat in winter. Therefore, our results support proactive urban planning that considers suitable adaptation and mitigation strategies against increasing air temperatures in urban centers in southwest Ethiopia. Future work will examine the likely changes in temperature and precipitation extremes.
      Citation: Climate
      PubDate: 2022-10-21
      DOI: 10.3390/cli10100158
      Issue No: Vol. 10, No. 10 (2022)
       
 
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