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  • Climate, Vol. 10, Pages 124: Implications of Regional Droughts and
           Transboundary Drought Risks on Drought Monitoring and Early Warning: A

    • Authors: Sivapuram Venkata Rama Krishna Prabhakar
      First page: 124
      Abstract: Regional droughts are increasing in frequency and climate change projections indicate an exacerbation in the occurrence of regional droughts in the future. Droughts are complex hydrometeorological events, and the complexity of cause-and-effect relationships across administrative and political borders can make drought management a challenge. While countries are largely focused on assessing drought impacts within their borders, thereby providing focused information for the relevant administration, the impact on communities, industries, and countries that are distantly connected with the affected location must also be taken into consideration. If not considered, drought impacts can be underestimated, and adaptation actions undertaken may not completely address the drought risks. Understanding transboundary drought risks is an important and integral part of drought risk reduction and it will grow in importance as the world experiences more integration at regional and global levels on multiple fronts. To address drought risks comprehensively, the new paradigm demands that the impacts of regional droughts are fully understood, that this understanding is incorporated into drought monitoring and early warning systems, and that drought early warning information is provided to all stakeholders, including those beyond the boundaries of the affected region, thereby eliciting appropriate action.
      Citation: Climate
      PubDate: 2022-08-23
      DOI: 10.3390/cli10090124
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 125: Effectiveness of Drought Indices in the
           Assessment of Different Types of Droughts, Managing and Mitigating Their

    • Authors: Jean Marie Ndayiragije, Fan Li
      First page: 125
      Abstract: Droughts are the most destructive catastrophes in the world. The persistence of drought is considered to cause many challenges for both humans and animals and ruins the ecosystem. These challenges have encouraged scientists to search for innovative methods and models that are effective for assessing and predicting drought events. The use of drought indices has been extensively employed in many regions across the globe and their effectiveness demonstrated. This review illustrates the effectiveness of drought indices in the assessment of droughts, with a focus on drought management and mitigation measures. Additionally, several ways of managing drought risk and proactive strategies that need to be implemented to mitigate droughts have been illustrated. In conclusion, this article suggests that drought mitigation should be done more naturally, in ways that strongly protect the environment rather than involve engineering projects which might cause the degradation of rivers and land, and damage the ecosystem.
      Citation: Climate
      PubDate: 2022-08-25
      DOI: 10.3390/cli10090125
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 126: Periods and Amplitudes of Southern Pine
           Beetle Infestations under Climate Change

    • Authors: Hyunjin An, Jianbang Gan
      First page: 126
      Abstract: The southern pine beetle (SPB), Dendroctonus frontalis Zimmermann, is one of the most destructive insects to pine forests in North and Central America. Historical SPB infestations have shown strong cyclical patterns and are attributed to an array of abiotic and biotic factors with climatic conditions being the dominant. Climate change has been projected to increase SPB infestations; however, its impacts on the cyclical patterns of SPB infestations remain unknown. Here, we estimated the statistical relationship between SPB infestations and climatic and other factors using generalized linear regression modeling and historical data, analyzed the cyclical patterns of SPB infestations via periodogram analysis and explored how these patterns would evolve with the projected future climate change in 11 states of the Southern United States. We found that SPB infestations intensified with increases in seasonal average temperatures and minimum winter temperatures and decreases in spring and winter precipitations. Compared to the historical SPB infestation patterns, climate change was estimated to nearly double SPB infestation frequencies although with smaller amplitudes in the region. Our findings advance the understanding of cyclical patterns of SPB infestations, especially climate change impacts on such patterns, aiding in developing and deploying future SPB management practices and strategies.
      Citation: Climate
      PubDate: 2022-08-28
      DOI: 10.3390/cli10090126
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 127: Upscaling Gross Primary Production from Leaf
           to Canopy for Potato Crop (Solanum tuberosum L.)

    • Authors: Fabio Ernesto Martínez-Maldonado, Angela María Castaño-Marín, Gerardo Antonio Góez-Vinasco, Fabio Ricardo Marin
      First page: 127
      Abstract: Estimating gross primary production (GPP) is important to understand the land–atmosphere CO2 exchange for major agroecosystems. Eddy covariance (EC) measurements provide accurate and reliable information about GPP, but flux measurements are often not available. Upscaling strategies gain importance as an alternative to the limitations of the use of the EC. Although the potato provides an important agroecosystem for worldwide carbon balance, there are currently no studies on potato GPP upscaling processes. This study reports two GPP scaling-up approaches from the detailed leaf-level characterization of gas exchange of potatoes. Multilayer and big leaf approaches were applied for extrapolating chamber and biometric measurements from leaf to canopy. Measurements of leaf area index and photosynthesis were performed from planting to the end of the canopy life cycle using an LP-80 ceptometer and an IRGA Li-Cor 6800, respectively. The results were compared to concurrent measurements of surface–atmosphere GPP from the EC measurements. Big-leaf models were able to simulate the general trend of GPP during the growth cycle, but they overestimated the GPP during the maximum LAI phase. Multilayer models correctly reproduced the behavior of potato GPP and closely predicted both: the daily magnitude and half-hourly variation in GPP when compared to EC measurements. Upscaling is a reliable alternative, but a good treatment of LAI and the photosynthetic light-response curves are decisive factors to achieve better GPP estimates. The results improved the knowledge of the biophysical control in the carbon fluxes of the potato crop.
      Citation: Climate
      PubDate: 2022-08-29
      DOI: 10.3390/cli10090127
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 128: Evaluation of ECMWF-SEAS5 Seasonal
           Temperature and Precipitation Predictions over South America

    • Authors: Glauber W. S. Ferreira, Michelle S. Reboita, Anita Drumond
      First page: 128
      Abstract: Nowadays, a challenge in Climate Science is the seasonal forecast and knowledge of the model’s performance in different regions. The challenge in South America reflects its huge territory; some models present a good performance, and others do not. Nevertheless, reliable seasonal climate forecasts can benefit numerous decision-making processes related to agriculture, energy generation, and extreme events mitigation. Thus, given the few works assessing the ECMWF-SEAS5 performance in South America, this study investigated the quality of its seasonal temperature and precipitation predictions over the continent. For this purpose, predictions from all members of the hindcasts (1993–2016) and forecasts (2017–2021) ensemble were used, considering the four yearly seasons. The analyses included seasonal mean fields, bias correction, anomaly correlations, statistical indicators, and seasonality index. The best system’s performance occurred in regions strongly influenced by teleconnection effects, such as northern South America and northeastern Brazil, in which ECMWF-SEAS5 even reproduced the extreme precipitation anomalies that happened in recent decades. Moreover, the system indicated a moderate capability of seasonal predictions in medium and low predictability regions. In summary, the results show that ECMWF-SEAS5 climate forecasts are potentially helpful and should be considered to plan various strategic activities better.
      Citation: Climate
      PubDate: 2022-08-29
      DOI: 10.3390/cli10090128
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 129: Public Perceptions on Human Health Risks of
           Climate Change in Cyprus: 2018 and 2021 Survey Results

    • Authors: Corina Konstantinou, Christina Xeni, Eva M. van Bergen Henegouw, Nita Chaudhuri, Carijn Beumer, Konstantinos C. Makris
      First page: 129
      Abstract: Understanding public perceptions on the health impacts of climate change will help to better address planetary health challenges. This study aimed to assess differences in perceptions in the Cypriot population regarding climate-related health risks, information sources used, and self-assessed health status over a three-year period, along with the relationship between sociodemographics and perceptions on climate-related health risks. Two cross-sectional surveys on environmental health risks and climate change, information sources, and self-assessed health were conducted in July–December 2018 (n = 185) and August–September 2021 (n = 202) among adults living in Cyprus. A descriptive analysis of the survey responses was conducted. Between-survey and within-survey associations were examined among environmental and health risk perceptions and stratified by sociodemographics (age, sex, educational level) using chi-square tests. The perceived views on most questions about environmental health risks and climate change were not different between the two surveys (p > 0.05). With environmental factors in mind, such as climate change, pollution, and toxic waste, most respondents (>72%) considered that health issues such as asthma, cancer, obesity, type II diabetes, and high blood pressure would occur much more often or somewhat more often in the next 10 years. In both surveys, the most popular sources of information about environmental health risks were social media/the internet, followed by TV news and TV films and documentaries. Notable differences in several perceptions on climate-related health risks were observed between females and males, while age and educational level did not influence most perceptions. Women were more likely than men to report that environmental factors such as temperature rise, extreme weather events, and air pollution will be extremely influenced by climate change (p < 0.05). The study survey populations recognized the important linkages between climate change and human health, including their drivers. Sex was an important factor for differentiated perceptions on environmental health risks and climate change. Such survey results on perceptions about climate change and their impact on population health can be used to inform public awareness and risk communication campaigns.
      Citation: Climate
      PubDate: 2022-08-31
      DOI: 10.3390/cli10090129
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 130: Evaluating the Influence of CAM5 Aerosol
           Configuration on Simulated Tropical Cyclones in the North Atlantic

    • Authors: J. Jacob A. Huff, Kevin A. Reed, Julio T. Bacmeister, Michael F. Wehner
      First page: 130
      Abstract: This study examines the influence of prescribed and prognostic aerosol model configurations on the formation of tropical cyclones (TCs) in the North Atlantic Ocean in Community Atmosphere Model version 5 (CAM5). The impact of aerosol parameterization is examined by investigating storm track density, genesis density, potential intensity, and genesis potential index. This work shows that both CAM5 configurations simulate reduced storm frequency when compared to observations and that differences in TC climatology between the model configurations can be explained by differences in the large-scale environment. The analysis shows that simulation with the prognostic aerosol parameterization scheme reasonably captures the observed interannual variability in tropical cyclones and aerosols (i.e., dust) in the North Atlantic, while simulation with the prescribed configuration (climatology) is less favorable. The correlation between dust and TCs in observations (i.e., reanalysis and satellite datasets) is shown to be negative, and this relationship was also found for the prognostic aerosol configuration despite an overall decrease in the frequency of TCs. This indicates that, to accurately replicate certain aspects of TC interannual variability, the aerosol configuration within CAM5 needs to account for the appropriate dust variability.
      Citation: Climate
      PubDate: 2022-08-31
      DOI: 10.3390/cli10090130
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 131: New Air Temperature- and Wind Speed-Based
           Clothing Thermal Resistance Scheme—Estimations for the Carpathian

    • Authors: Ferenc Ács, Erzsébet Kristóf, Amanda Imola Szabó, Hajnalka Breuer, Zsófia Szalkai, Annamária Zsákai
      First page: 131
      Abstract: A new clothing thermal resistance scheme is presented and verified for the Carpathian region and for the time period 1971–2000. The scheme is as simple as possible by connecting operative temperature to air temperature, which allows for it to only use air temperature and wind speed data as meteorological inputs. Another strength of the scheme is that a walking person’s metabolic heat flux density is also simply simulated without having to regard any thermoregulation processes. Human thermal load in the above region is characterised by a representative adult Hungarian male and female with a body mass index of 23–27 kgm−2. Our most important findings are as follows: (1) human thermal load in the Carpathian region is relief dependent; (2) the scheme cannot be applied in the lowland areas of the region in the month of July since the energy balance is not met; (3) in the same areas but during the course of the year, clothing thermal resistance values are between 0.4 and 1 clo; (4) clothing thermal resistance can reach 1–1.2 clo in the mountains in the month of July, but during the course of the year this value is 1.8 clo; and (5) the highest clothing thermal resistance values can be found in January reaching about 2.5 clo. The scheme may be easily applied to any another region by determining new, region-specific, operative temperature–air temperature relationships.
      Citation: Climate
      PubDate: 2022-09-01
      DOI: 10.3390/cli10090131
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 132: Coastal Flood Risks and the Business
           Community: Stakeholders’ Perception in Malta

    • Authors: Daniel Spiteri, Ritienne Gauci
      First page: 132
      Abstract: Resilience of coastal communities is increasingly required to adjust to the effects of cli- mate change and its coast-related threats. Climate change is a major global threat to the environment, economy, and health of urban coastal lowlands. Flooding risks from both rising sea levels and increases in the frequency and severity of storm surges are considered to be amongst the most threatening consequences associated with climate change. The aim of this study was to assess the levels of socio-economic preparedness of low-lying urbanized towns in Malta for the impacts of coastal flooding through the triangulation of stakeholders’ participation from three sectors: the business community, local councils, and specialized experts from the governmental and private sectors. The study also included field collection of elevation data for each locality to capture the businesses’ distribution in relation to their height above sea level along the urban waterfront. One-way analysis of variance and NVivo were used to test and compare the business owners’ responses and the experts’ feedback, respectively. The main findings from the business community suggest that there are no long-term contingency plans or strategies in place to address potential flooding impacts from rising sea levels and storm surges, and that the risks of driving owners out of business is high. From the feedback received by the local councils, it was observed that all of them significantly lack the physical and financial resources to effectively manage long-term coastal flooding within their locality, forcing them to completely rely on central government for any future needs caused by the impact of coastal flooding. From a central government perspective, it seems that all interviewed experts operate within a fragmented governance model, and mainly adhere to the set of responsibilities aligned with their respective roles within such a governance model. This evidence of governance disconnect requires more horizontal and vertical integration of cross-sectoral strategies to address coastal flooding, within the broader framework of integrated coastal zone management as established by the Mediterranean ICZM protocol.
      Citation: Climate
      PubDate: 2022-09-02
      DOI: 10.3390/cli10090132
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 133: Compound Extremes of Air Temperature and
           Precipitation in Eastern Europe

    • Authors: Elena Vyshkvarkova, Olga Sukhonos
      First page: 133
      Abstract: The spatial distribution of compound extremes of air temperature and precipitation was studied over the territory of Eastern Europe for the period 1950–2018. Using daily data on air temperature and precipitation, we calculated the frequency and trends of the four indices—cold/dry (CD), cold/wet (CW), warm/dry (WD) and warm/wet (WW). The connection between these indices and large-scale patterns in the ocean–atmosphere system, such as the North Atlantic Oscillation (NAO), the East Atlantic (EA) and Scandinavia (SCAND) patterns, was also studied. The positive and statistically significant trends in the region were observed for the warm extremes (especially the WW index) in all seasons, with maximum values in the winter season, while negative trends were obtained for the cold extremes. The NAO index has a strong positive and statistically significant correlation with the warm compound indices (WD and WW) in the northern part of Eastern Europe in winter like the EA pattern, but with smaller values. The spatial distribution of the correlation coefficients between compound extremes and the SCAND index in the winter season is opposite to the correlation coefficients with the NAO index.
      Citation: Climate
      PubDate: 2022-09-05
      DOI: 10.3390/cli10090133
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 134: Spatio-Temporal Assessment of Satellite
           Estimates and Gauge-Based Rainfall Products in Northern Part of Egypt

    • Authors: Mahmoud Roushdi
      First page: 134
      Abstract: Egypt’s climate is generally dry all over the country except for the Northern Mediterranean Coast. The Egyptian Meteorological Authority (EMA) uses few meteorological stations to monitor weather events in the entire country within the area of one million square kilometers, which makes it scarce with respect to spatial distribution. The EMA data are relatively expensive to obtain. Open access rainfall products (RP) are commonly used to monitor rainfall as good alternatives, especially for data-scarce countries such as Egypt. This paper aims to evaluate the performance of 12 open access rainfall products for 8 locations in the northern part of Egypt, in order to map the rainfall spatial distribution over the northern part of Egypt based on the best RP. The evaluation process is conducted for the period 2000–2018 for seven locations (Marsa-Matrouh, Abu-Qeir, Rasheed, Port-Said, Tanta, Mansoura, and Cairo-Airport), while it is conducted for the period 1996–2008 for the Damanhour location. The selected open access rainfall products are compared with the ground stations data using annual and monthly timescales. The point-to-pixel approach is applied using four statistical indices (Pearson correlation coefficient (r), Nash–Sutcliffe efficiency (NSE), root mean square error (RMSE) and bias ratio (Pbias)). Overall, the results indicate that both the African Rainfall Estimation Algorithm (RFE) product and the Climate Prediction Center (CPC) product could be the best rainfall data sources for the Marsa-Matrouh location, with relatively higher r (0.99–0.93 for RFE and 0.99–0.89 for CPC) and NSE (0.98–0.79 for RFE and 0.98–0.75 for CPC), in addition to lower RMSE (0.94–7.78 for RFE and 0.92–12.01 for CPC) and Pbias (0.01–11.95% for RFE and −2.22–−12.15% for CPC) for annual and monthly timescales. In addition, the Global Precipitation Climatology Centre (GPCC) and CPC give the best rainfall products for the Abu-Qier and Port-Said locations. GPCC is more suitable for the Rasheed location. The most appropriate rainfall product for the Tanta location is CHIRPS. The current research confirms the benefits of using rainfall products after conducting the recommended performance assessment for each location.
      Citation: Climate
      PubDate: 2022-09-19
      DOI: 10.3390/cli10090134
      Issue No: Vol. 10, No. 9 (2022)
  • Climate, Vol. 10, Pages 112: Diagnosis of the Extreme Climate Events of

    • Authors: Lucy Giráldez, Yamina Silva, José L. Flores-Rojas, Grace Trasmonte
      First page: 112
      Abstract: The most extreme precipitation event in Metropolitan Lima (ML) occurred on 15 January 1970 (16 mm), this event caused serious damage, and the real vulnerability of this city was evidenced; the population is still not prepared to resist events of this nature. This research describes the local climate variability and extreme climate indices of temperature and precipitation. In addition, the most extreme precipitation event in ML is analyzed. Extreme climate indices were identified based on the methodology proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI). Some extreme temperature indices highlight an initial trend toward warm conditions (1965–1998); this trend has changed towards cold conditions since 1999, consistent with the thermal cooling during the last two decades in ML (−0.5 °C/decade) and other coastal areas of Peru. The variations of extreme temperature indices are mainly modulated by sea-surface temperature (SST) alterations in the Niño 1 + 2 region (moderate to strong correlations were found). Extreme precipitation indices show trends toward wet conditions after the 1980s, the influence of the Pacific Ocean SST on the extreme precipitation indices in ML is weak and variable in sign. The most extreme precipitation event in ML is associated with a convergence process between moisture fluxes from the east (Amazon region) at high and mid levels and moisture fluxes from the west (Pacific Ocean) at low levels, and near the surface.
      Citation: Climate
      PubDate: 2022-07-23
      DOI: 10.3390/cli10080112
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 113: Heat Vulnerability Index Mapping: A Case
           Study of a Medium-Sized City (Amiens)

    • Authors: Aiman Mazhar Qureshi, Ahmed Rachid
      First page: 113
      Abstract: Urbanization, anthropogenic activities, and social determinants such as poverty and literacy rate greatly contribute to heat-related mortalities. The 2003 strong heat wave (Lucifer) in France resulted in catastrophic health consequences in the region that may be attributed to urbanization and other anthropogenic activities. Amiens is a medium-sized French city, where the average temperature has increased since the year 2000. In this study, we evaluated the Heat Vulnerability Index (HVI) in Amiens for extreme heat days recorded during three years (2018–2020). We used the principal component analysis (PCA) technique for fine-scale vulnerability mapping. The main types of considered data included (a) socioeconomic and demographic data, (b) air pollution, (c) land use and cover, (d) elderly heat illness, (e) social vulnerability, and (f) remote sensing data (land surface temperature (LST), mean elevation, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI)). The output maps identified the hot zones through comprehensive GIS analysis. The resultant maps showed that high HVI exists in three typical areas: (1) areas with dense population and low vegetation, (2) areas with artificial surfaces (built-up areas), and (3) industrial zones. Low-HVI areas are in natural landscapes such as rivers and grasslands. Our analysis can be implemented in other cities to highlight areas at high risk of extreme heat and air pollution.
      Citation: Climate
      PubDate: 2022-07-24
      DOI: 10.3390/cli10080113
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 114: Identifying Western North American Tree
           Populations Vulnerable to Drought under Observed and Projected Climate

    • Authors: Kathryn Levesque, Andreas Hamann
      First page: 114
      Abstract: Global climate change has affected forest health and productivity. A highly visible, direct climate impact is dieback caused by drought periods in moisture-limited forest ecosystems. Here, we have used a climate moisture index (CMI), which has been developed in order to map forest–grassland transitions, to investigate the shifts of the zero-CMI isopleths, in order to infer drought vulnerabilities. Our main objective was to identify populations of the 24 most common western North American forest tree species that are most exposed to drought conditions by using a western North American forest inventory database with 55,700 plot locations. We have found that climate change projections primarily increase the water deficits for tree populations that are already in vulnerable positions. In order to test the realism of this vulnerability assessment, we have compared the observed population dieback with changes in index values between the 1961–1990 reference period and a recent 1991–2020 average. The drought impacts that were predicted by negative CMI values largely conformed to the observed dieback in Pinus edulis, Populus tremuloides, and Pinus ponderosa. However, there was one notable counter-example. The observed dieback in the Canadian populations of Populus tremuloides were not associated with directional trends in the drought index values but were instead caused by a rare extreme drought event that was not apparently linked to directional climate change. Nevertheless, a macro-climatic drought index approach appeared to be generally suitable to identify and forecast the drought threats to the tree populations.
      Citation: Climate
      PubDate: 2022-07-29
      DOI: 10.3390/cli10080114
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 115: Climate Risk Mitigation and Adaptation
           Concerns in Urban Areas: A Systematic Review of the Impact of IPCC
           Assessment Reports

    • Authors: Ana Monteiro, Johnson Ankrah, Helena Madureira, Maria Oliveira Pacheco
      First page: 115
      Abstract: Urban areas continue to be the center of action for many countries due to their contribution to economic development. Many urban areas, through the urbanization process, have become vulnerable to climate risk, thereby making risk mitigation and adaptation essential components in urban planning. The study assessed the impacts of IPCC Assessment Reports (ARs) on academic research on risk mitigation and adaptation concerns in urban areas. The study systematically reviewed literature through searches of the Web of Science and Scopus databases; 852 papers were retrieved and 370 were deemed eligible. The results showed that the East Asia and Pacific, and Europe and Central Asia regions were most interested in IPCC ARs, while Sub-Saharan Africa showed little interest. Several urban concerns, including socio-economic, air quality, extreme temperature, sea level rise/flooding, health, and water supply/drought, were identified. Additionally, studies on negative health outcomes due to extreme temperatures and air pollution did not appear in the first four IPCC ARs. However, significant studies appeared after the launch of the AR5. Here, we must state that climate-related problems of urbanization were known and discussed in scientific papers well before the formation of the IPCC. For instance, the works of Clarke on urban structure and heat mortality and Oke on climatic impacts of urbanization. Though the IPCC ARs show impact, their emphasis on combined mitigation and adaptation policies is limited. This study advocates more combined risk mitigation and adaptation policies in urban areas for increased resilience to climate risk.
      Citation: Climate
      PubDate: 2022-08-01
      DOI: 10.3390/cli10080115
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 116: Correction: Kumari et al. A Long-Term
           Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region
           Using Google Earth Engine. Climate 2021, 9, 109

    • Authors: Nikul Kumari, Ankur Srivastava, Umesh Chandra Dumka
      First page: 116
      Abstract: There was an error in the original publication [...]
      Citation: Climate
      PubDate: 2022-08-10
      DOI: 10.3390/cli10080116
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 117: Exploring ENSO-Induced Anomalies over North
           America in Historical and Future Climate Simulations That Use HadGEM2-ESM
           Output to Drive WRF

    • Authors: Tristan Shepherd, Jacob J. Coburn, Rebecca J. Barthelmie, Sara C. Pryor
      First page: 117
      Abstract: Projected changes to the El Niño Southern Oscillation (ENSO) climate mode have been explored using global Earth system models (ESMs). Regional expressions of such changes have yet to be fully advanced and may require the use of regional downscaling. Here, we employ regional climate modeling (RCM) using the Weather Research and Forecasting (WRF) model at convection-permitting resolution and nested in output from the HadGEM2 ESM. We quantify ENSO teleconnections to temperature and precipitation anomalies in historical and future climate scenarios over eastern North America. Two paired simulations are run, a strong El Niño (positive ENSO phase) and a weak La Niña (negative ENSO phase), for the historical and future years. The HadGEM2 direct output and HadGEM2-WRF simulation output are compared to the anomalies derived from the NOAA ENSO Climate Normals dataset. The near-surface temperature and precipitation differences by ENSO phase, as represented by the HadGEM2-WRF historical simulations, show a poor degree of association with the NOAA ENSO Climate Normals, in part because of the large biases in the HadGEM2 model. Downscaling with the WRF model does improve the agreement with the observations, and large discrepancies remain. The model chain HadGEM2-WRF reverses the sign of the ENSO phase response over eastern North America under simulations of the future climate with high greenhouse gas forcing, but due to the poor agreement with the NOAA ENSO Climate Normals it is difficult to assign confidence to this prediction.
      Citation: Climate
      PubDate: 2022-08-10
      DOI: 10.3390/cli10080117
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 118: An Analysis of the Differences in
           Vulnerability to Climate Change: A Review of Rural and Urban Areas in
           South Africa

    • Authors: Leocadia Zhou, Dumisani Shoko Kori, Melusi Sibanda, Kenneth Nhundu
      First page: 118
      Abstract: Evidence is unequivocal that rural and urban areas in South Africa are vulnerable to the impacts of climate change; however, impacts are felt disproportionately. This difference in vulnerability between rural and urban areas is presently unclear to guide context-based climate policies and frameworks to enhance adaptation processes. A clear understanding of the differences in vulnerability to climate change between rural and urban areas is pertinent. This systematic review aimed to explore how vulnerability to climate change varies between rural and urban areas and what explains these variations. The approach was guided by the Intergovernmental Panel on Climate Change vulnerability framework incorporating exposure, sensitivity, and adaptive capacity dimensions integrated into the Sustainable Livelihood Framework. The review used 30 articles based on the search criteria developed. The findings show differences in vulnerability to climate change between rural and urban areas owing to several factors that distinguish rural from urban areas, such as differences in climate change drivers, infrastructure orientation, typical livelihood, and income-generating activities. We conclude that vulnerability varies with location and requires place-based analyses. Instead of blanket policy recommendations, localized interventions that enhance adaptation in specific rural and urban areas should be promoted.
      Citation: Climate
      PubDate: 2022-08-13
      DOI: 10.3390/cli10080118
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 119: Influence of Climate on Conflicts and
           Migrations in Southern Africa in the 19th and Early 20th Centuries

    • Authors: Mphethe I. Tongwane, Teke S. Ramotubei, Mokhele E. Moeletsi
      First page: 119
      Abstract: Climate and other environmental factors continue to play important contributions on the livelihoods of communities all over the world. Their influence during historical periods and the roles they played remain under-reported. The main objective of this review is to investigate the climatological conditions during the time of the invasion of early European settlers in Southern Africa in the 19th and early 20th centuries. It establishes the possible relationships between climate variability and historical conflicts and wars, famines, disease pandemics, and the migration of African people to towns in search of sustainable and predictable livelihoods away from unreliable agriculture. A qualitative analysis of published peer reviewed literature in the form of reports, papers, and books was used in this review. At least 60 literature items were reviewed in this paper. There is a relationship between climate variability and the historical events of the 19th and early 20th centuries. Tribal conflicts and most of the wars between the settlers and the African people for land coincided with periods of droughts. Drought were key causes of famines, instabilities, and land degradation in the region. This study highlights the influence of environmental conditions on socio-economic conditions as the world enters an era of climate change and urbanization in developing countries, particularly in Africa. It shows that the hardships caused by environmental conditions have the potential to destabilize societies.
      Citation: Climate
      PubDate: 2022-08-16
      DOI: 10.3390/cli10080119
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 120: Rainy Day Prediction Model with Climate

    • Authors: Matteo Gentilucci, Gilberto Pambianchi
      First page: 120
      Abstract: The reconstruction of daily precipitation data is a much-debated topic of great practical use, especially when weather stations have missing data. Missing data are particularly numerous if rain gauges are poorly maintained by their owner institutions and if they are located in inaccessible areas.In this context, an attempt was made to assess the possibility of reconstructing daily rainfall data from other climatic variables other than the rainfall itself, namely atmospheric pressure, relative humidity and prevailing wind direction.The pilot area for the study was identified in Central Italy, especially on the Adriatic side, and 119 weather stations were considered.The parameters of atmospheric pressure, humidity and prevailing wind direction were reconstructed at all weather stations on a daily basis by means of various models, in order to obtain almost continuous values rain gauge by rain gauge. The results obtained using neural networks to reconstruct daily precipitation revealed a lack of correlation for the prevailing wind direction, while correlation is significant for humidity and atmospheric pressure, although they explain only 10–20% of the total precipitation variance. At the same time, it was verified by binary logistic regression that it is certainly easier to understand when it will or will not rain without determining the amount. In this case, in fact, the model achieves an accuracy of about 80 percent in identifying rainy and non-rainy days from the aforementioned climatic parameters. In addition, the modelling was also verified on all rain gauges at the same time and this showed reliability comparable to an arithmetic average of the individual models, thus showing that the neural network model fails to prepare a model that performs better from learning even in the case of many thousands of data (over 400,000). This shows that the relationships between precipitation, relative humidity and atmospheric pressure are predominantly local in nature without being able to give rise to broader generalisations.
      Citation: Climate
      PubDate: 2022-08-17
      DOI: 10.3390/cli10080120
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 121: An Urban Governance Framework for Including
           Environmental Migrants in Sustainable Cities

    • Authors: Ilan Kelman, Aaron Clark-Ginsberg
      First page: 121
      Abstract: This article proposes an urban governance framework for including environmental migrants in sustainable cities. It outlines the links among environmental migration, vulnerability, and sustainability, showing how vulnerability and sustainability are not about the environment or the human condition as snapshots in space and time, but rather are long-term, multi-scalar, ever-evolving processes. This theoretical baseline is followed by a description of some practical approaches already applied for including environmental migrants in sustainable cities. The wide variety and lack of cohesion justifies the need for a framework, leading to three principal characteristics of a governance framework suitable for addressing vulnerability and environmental migration for urban sustainability: horizontally and vertically networked, inclusive, and evidence-based. As the framework’s three dimensions represent principles or overarching structural solutions rather than presenting operational guidance, the concluding discussion covers the framework’s limitations and a research agenda.
      Citation: Climate
      PubDate: 2022-08-18
      DOI: 10.3390/cli10080121
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 122: Evaluation of the CMIP6 Performance in
           Simulating Precipitation in the Amazon River Basin

    • Authors: Corrie Monteverde, Fernando De Sales, Charles Jones
      First page: 122
      Abstract: The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water to the people and environment and are critical to moisture recycling and transport, and represents an important variable for climate models to simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This is done by discussing results from spatial pattern mapping, Taylor diagram analysis and Taylor skill score, annual climatology comparison, cumulative distribution analysis, and empirical orthogonal function (EOF) analysis. Precipitation analysis shows: (1) This region displays higher rainfall in the north-northwest and drier conditions in the south. Models tend to underestimate northern values or overestimate the central to northwest averages. (2) The southern Amazon has a more defined dry season (June, July, and August) and wet season (December, January, and February) and models simulate this well. The northern Amazon dry season tends to occur in August, September, and October and the wet season occurs in March, April, and May, and models are not able to capture the climatology as well. Models tend to produce too much rainfall at the start of the wet season and tend to either over- or under-estimate the dry season, although ensemble means typically display the overall pattern more precisely. (3) Models struggle to capture extreme values of precipitation except when precipitation values are close to 0. (4) EOF analysis shows that models capture the dominant mode of variability, which was the annual cycle or South American Monsoon System. (5) When all evaluation metrics are considered, the models that perform best are CESM2, MIROC6, MRIESM20, SAM0UNICON, and the ensemble mean. This paper supports research in determining the most up-to-date CMIP6 model performance of precipitation regime for 1981–2014 for the Brazilian Amazon. Results will aid in understanding future projections of precipitation for the selected subset of global climate models and allow scientists to construct reliable model ensembles, as precipitation plays a role in many sectors of the economy, including the ecosystem, agriculture, energy, and water security.
      Citation: Climate
      PubDate: 2022-08-22
      DOI: 10.3390/cli10080122
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 123: Improving Future Estimation of
           Cheliff-Mactaa-Tafna Streamflow via an Ensemble of Bias Correction

    • Authors: Mohammed Renima, Ayoub Zeroual, Yasmine Hamitouche, Ali Assani, Sara Zeroual, Ahmed Amin Soltani, Cedrick Mulowayi Mubulayi, Sabrina Taibi, Senna Bouabdelli, Sara Kabli, Allal Ghammit, Idris Bara, Abdennour Kastali, Ramdane Alkama
      First page: 123
      Abstract: The role of climate change in future streamflow is still very uncertain, especially over semi-arid regions. However, part of this uncertainty can be offset by correcting systematic climate models’ bias. This paper tries to assess how the choice of a bias correction method may impact future streamflow of the Cheliff-Mactaa-Tafna (CMT) rivers. First, three correction methods (quantile mapping (QM), quantile delta mapping (QDM), and scaled distribution mapping (SDM)) were applied to an ensemble of future precipitation and temperature coming from CORDEX-Africa, which uses two Representative Concentration Pathways: RCP4.5 and RCP8.5. Then, the Zygos model was used to convert the corrected time series into streamflow. Interestingly, the findings showed an agreement between the three methods that revealed a decline in future streamflow up to [−42 to −62%] in autumn, [+31% to −11%] in winter, [−23% to −39%] in spring, and [−23% to −41%] in summer. The rate of decrease was largest when using QM-corrected model outputs, followed by the raw model, the SDM-corrected model, and finally, the QDM-corrected model outputs. As expected, the RCP presents the largest decline especially by the end of the 21st Century.
      Citation: Climate
      PubDate: 2022-08-22
      DOI: 10.3390/cli10080123
      Issue No: Vol. 10, No. 8 (2022)
  • Climate, Vol. 10, Pages 90: Making Climate Risks Governable in Swedish
           Municipalities: Crisis Preparedness, Technical Measures, and Public

    • Authors: Rolf Lidskog, Linn Rabe
      First page: 90
      Abstract: Creating preparedness for climate change has become an increasingly important task for society. In Sweden, the responsibility for crisis preparedness rests to a large extent on the municipalities. Through an interview study of municipal officials, this paper examines municipalities’ crisis preparedness for climate change and the role they assign to citizens. The theoretical approach is that of risk governance, which adopts an inclusive approach to risk management, and that of risk sociology, which states that how a problem is defined determines how it should be handled and by whom. The empirical results show that the municipal officials mainly discuss technically defined risks, such as certain kinds of climate-related extreme events, the handling of which does not require any substantial involvement of citizens. Citizens’ responsibility is only to be individually prepared, and thereby they do not require municipal resources to protect their own properties in the case of an extreme event. The municipalities, however, feel that their citizens have not developed this individual preparedness and therefore they try to better inform them. This analysis finds five different views of citizens, all with their own problems, and to which the municipalities respond with different communicative measures. By way of conclusion, three crucial aspects are raised regarding the task of making societies better prepared for climate change.
      Citation: Climate
      PubDate: 2022-06-21
      DOI: 10.3390/cli10070090
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 91: Improving Early Warning of Drought in

    • Authors: Lellyett, Truelove, Huda
      First page: 91
      Abstract: This invited review outlines a selection of recent technical and communication advances, in certain areas of climate and weather science that could improve the capability and utility of drought early warning systems in Australia. First, a selection of current operational outputs and their significance for drought early warning is reviewed, then a selection of advancements in the Research and Development (R&D) pipeline are considered, which have potential to help enable better decision-making by stakeholders subject to drought risk. The next generation of drought early warning systems should have a focus on index- and impact-based prediction models that go beyond basic weather and climate parameters, at seasonal through to multi-year timescales. Convergence and integration of emerging research, science and technology is called for across the fields of climate, agronomy, environment, economics and social science, to improve early warning information. The enablement of more predictively based drought policy, should facilitate more proactive responses by stakeholders throughout the agricultural value chain, and should make stakeholders more drought resilient.
      Citation: Climate
      PubDate: 2022-06-21
      DOI: 10.3390/cli10070091
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 92: Correction: Kim et al. Assessing Role of
           Drought Indices in Anticipating Pine Decline in the Sierra Nevada, CA.
           Climate 2022, 10, 72

    • Authors: Yoonji Kim, Nancy E. Grulke, Andrew G. Merschel, Kellie A. Uyeda
      First page: 92
      Abstract: Author “David A [...]
      Citation: Climate
      PubDate: 2022-06-22
      DOI: 10.3390/cli10070092
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 93: Stalagmite-Inferred Climate in the Western
           Mediterranean during the Roman Warm Period

    • Authors: Hsun-Ming Hu, Véronique Michel, Patricia Valensi, Horng-Sheng Mii, Elisabetta Starnini, Marta Zunino, Chuan-Chou Shen
      First page: 93
      Abstract: The circum-Mediterranean region is the cradle of ancient civilizations that had their roots in the Holocene. Climate change has been considered a key element that contributed to their rise or fall. The Roman Warm Period (RWP), 200 B.C. to 400 A.D., was the warmest period in Europe during the last two thousand years. Hydroclimatic change at the end of the RWP has been suggested as a possible influence on the stability of the Roman political regime and the eventual collapse of the Roman Empire in 476 A.D. A lack of precise proxy records hampers our understanding of hydroclimatic variability over the RWP. Here we present a stalagmite-based climate record from 550 ± 10 B.C. to 950 ± 7 A.D. (2σ) from northern Italy, which reveals a climatic trend of warming and increased humidity throughout the RWP. By comparison with other proxy records in Europe and the circum-Mediterranean region, we argue that the warm, humid climate in southern Europe could be linked to the multi-centennial warming of the Mediterranean Sea. Our record further suggests a century-long rapid drying trend from the early-4th to early-5th century, followed by a 100-year-long drought event, which could have influenced the fall of the Roman Empire.
      Citation: Climate
      PubDate: 2022-06-23
      DOI: 10.3390/cli10070093
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 94: The Imprint of Recent Meteorological Events on
           Boulder Deposits along the Mediterranean Rocky Coasts

    • Authors: Marco Delle Delle Rose, Paolo Martano
      First page: 94
      Abstract: In this review, the potential of an emerging field of interdisciplinary climate research, Coastal Boulder Deposits (CBDs) as natural archives for intense storms, is explored with particular reference to the Mediterranean region. First, the identification of the pertinent scientific articles was performed by the using Web of Science (WoS) engine. Thus, the selected studies have been analysed to feature CBDs produced and/or activated during the last half-century. Then, the meteorological events responsible for the literature-reported cases were analysed in some detail using the web archives of the Globo-Bolam-Moloch model cascade. The study of synoptical and local characteristics of the storms involved in the documented cases of boulder production/activation proved useful for assessing the suitability of selected sites as geomorphological storm proxies. It is argued that a close and fruitful collaboration involving several scientific disciplines is required to develop this climate research field.
      Citation: Climate
      PubDate: 2022-06-26
      DOI: 10.3390/cli10070094
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 95: Assessment of Climate Models Performance and
           Associated Uncertainties in Rainfall Projection from CORDEX over the
           Eastern Nile Basin, Ethiopia

    • Authors: Sadame M. Yimer, Abderrazak Bouanani, Navneet Kumar, Bernhard Tischbein, Christian Borgemeister
      First page: 95
      Abstract: The adverse impact of climate change on different regionally important sectors such as agriculture and hydropower is a serious concern and is currently at the epicentre of global interest. Despite the extensive efforts to project the future climate and assess its potential impact, it is surrounded by uncertainties. This study aimed to assess climate models’ performance and associated uncertainties in rainfall projection over the eastern Nile basin, Ethiopia. Seventeen climate models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and their four ensemble models were evaluated in terms of their historical prediction performance (1986–2005) and future simulation skill (2006–2016) at rainfall station (point location), grid-scale (0.44° × 0.44°) and basin scale. Station-based and spatially interpolated observed rainfall data were used as a reference during climate model performance evaluation. In addition, CRU data was used as an alternative reference data to check the effect of the reference data source on the climate models evaluation process. As the results showed, climate models have a large discrepancy in their projected rainfall and hence prior evaluation of their performance is necessary. For instance, the bias in historical mean annual rainfall averaged over the basin ranges from +760 mm (wet bias) to −582 mm (dry bias). The spatial pattern correlation (r) of climate models output and observed rainfall ranges from −0.1 to 0.7. The ensemble formed with selected (performance-based) member models outperforms the widely used multi-model ensemble in most of the evaluation metrics. This showed the need for reconsidering the widely used multi-model approach in most climate model-based studies. The use of CRU data as a reference resulted in a change in the magnitude of climate model bias. To conclude, each climate model has a certain degree of uncertainty in the rainfall projection, which potentially affects the studies on climate change and its impact (e.g., on water resources). Therefore, climate-related studies have to consider uncertainties in climate projections, which will help end-users (decision-makers) at least to be aware of the potential range of deviation in the future projected outcomes of interest.
      Citation: Climate
      PubDate: 2022-06-27
      DOI: 10.3390/cli10070095
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 96: Linking Climate-Change Impacts on Hydrological
           Processes and Water Quality to Local Watersheds

    • Authors: Ying Ouyang, Sudhanshu Sekhar Panda, Gary Feng
      First page: 96
      Abstract: Estimation of hydrological processes and water quality is central to water resource management, clean water supply, environmental protection, and ecological services [...]
      Citation: Climate
      PubDate: 2022-06-30
      DOI: 10.3390/cli10070096
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 97: Applying Machine Learning for Threshold
           Selection in Drought Early Warning System

    • Authors: Hui Luo, Jessica Bhardwaj, Suelynn Choy, Yuriy Kuleshov
      First page: 97
      Abstract: This study investigates the relationship between the Normalized Difference Vegetation Index (NDVI) and meteorological drought category to identify NDVI thresholds that correspond to varying drought categories. The gridded evaluation was performed across a 34-year period from 1982 to 2016 on a monthly time scale for Grassland and Temperate regions in Australia. To label the drought category for each grid inside the climate zone, we use the Australian Gridded Climate Dataset (AGCD) across a 120-year period from 1900 to 2020 on a monthly scale and calculate percentiles corresponding to drought categories. The drought category classification model takes NDVI data as the input and outputs of drought categories. Then, we propose a threshold selection algorithm to distinguish the NDVI threshold to indicate the boundary between two adjacent drought categories. The performance of the drought category classification model is evaluated using the accuracy metric, and visual interpretation is performed using the heat map. The drought classification model provides a concept to evaluate drought severity, as well as the relationship between NDVI data and drought severity. The results of this study demonstrate the potential application of this concept toward early drought warning systems.
      Citation: Climate
      PubDate: 2022-06-30
      DOI: 10.3390/cli10070097
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 98: Evaluation of Satellite-Based Air Temperature
           Estimates at Eight Diverse Sites in Africa

    • Authors: Danny Parsons, David Stern, Denis Ndanguza, Mouhamadou Bamba Sylla
      First page: 98
      Abstract: High resolution satellite and reanalysis-based air temperature estimates have huge potential to complement the sparse networks of air temperature measurements from ground stations in Africa. The recently released Climate Hazards Center Infrared Temperature with Stations (CHIRTS-daily) dataset provides daily minimum and maximum air temperature estimates on a near-global scale from 1983 to 2016. This study assesses the performance of CHIRTS-daily in comparison with measurements from eight ground stations in diverse locations across Africa from 1983 to 2016, benchmarked against the ERA5 and ERA5-Land reanalysis to understand its potential to provide localized temperature information. Compared to ERA5 and ERA5-Land, CHIRTS-daily maximum temperature has higher correlation and lower bias of daily, annual mean maximum and annual extreme maximum temperature. It also exhibits significant trends in annual mean maximum temperature, comparable to those from the station data. CHIRTS-daily minimum temperatures generally have higher correlation, but larger bias than ERA5 and ERA5-Land. However, the results indicate that CHIRTS-daily minimum temperature biases may be largely systematic and could potentially be corrected for. Overall, CHIRTS-daily is highly promising as it outperforms ERA5 and ERA5-Land in many areas, and exhibits good results across a small, but diverse set of sites in Africa. Further studies in specific geographic areas could help support these findings.
      Citation: Climate
      PubDate: 2022-06-30
      DOI: 10.3390/cli10070098
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 99: Studies of the Effect of Seasonal Cycle on the
           Equatorial Quasi-Biennial Oscillation with a Chemistry-Climate Model

    • Authors: Kiyotaka Shibata
      First page: 99
      Abstract: The effect of the seasonal cycle on the quasi-biennial oscillation (QBO) in the equatorial stratosphere was investigated using a chemistry-climate model (CCM) by fixing the seasonal cycle in CCM simulations. The CCM realistically reproduced the QBO in wind and ozone fields of a 30-month period in a climatological simulation (control run) under annually repeating sea surface temperature (SST) with a seasonal cycle. For the control run, four experimental simulations (perpetual runs) were made by fixing solar declination and SST on the 15th of January, April, July, and October, respectively, for about 20 years. In the three perpetual runs of January, July, and October, the QBO was maintained and persisted throughout the 20-year integration in spite of some small differences in period and amplitude among the three runs. On the other hand, the QBO in the perpetual April run began to weaken after about 15 years and the downward propagation of westerly wind stopped at about 20 hPa, resulting in the QBO’s ceasing. The cause of this QBO disappearance is related to the evolution of the background mean flow in the lower stratosphere, which filtered out the parameterized gravity waves propagating upwards farther.
      Citation: Climate
      PubDate: 2022-06-30
      DOI: 10.3390/cli10070099
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 100: Estimation of Air Emissions Externalities Due
           to Shipping: Analytical Methodological Framework

    • Authors: Emmanouil Doundoulakis, Spiros Papaefthimiou
      First page: 100
      Abstract: The main objective of this paper is to present an analytical methodological framework for the estimation of the external costs of air emissions from passenger ships. We used as a case study the two main ports of Crete (Souda and Heraklion) and studied all passenger ferries and cruise vessels that visited these ports in the last 5 years (2017–2021). A detailed inventory was created containing all technical details for 10 passenger ferries (owned by three different shipping companies) operating every day, following various itineraries all year around, and 88 different cruise vessels (which approached both ports mainly during the summer period). The estimated external costs due to air emissions cover health effects, materials and building damages, biodiversity and crop losses. Two levels of calculations for the total external costs per pollutant were implemented. At the first level, a bottom-up approach was applied to accurately calculate the total annual air emissions (CO2, SOX, NOX, PM2.5, PM10), while for the second level, the cost factors per pollutant were used as input values to estimate the annual total external costs. One of the most important findings is that externalities comprise a significant amount of shipping companies’ revenues (about 25–35%), thus, implying a substantial revenue loss in the case that they would be asked to bear these costs. Assuming that ship owners will pass these costs on to ticket fares, an attempt is made to allocate the “externalities surcharge” (i.e., the burden of external costs) to ticket fares per transportation category.
      Citation: Climate
      PubDate: 2022-07-01
      DOI: 10.3390/cli10070100
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 101: Climate Change Related Catastrophic Rainfall
           Events and Non-Communicable Respiratory Disease: A Systematic Review of
           the Literature

    • Authors: Alexandra M. Peirce, Leon M. Espira, Peter S. Larson
      First page: 101
      Abstract: Climate change is increasing the frequency and intensity of extreme precipitation events, the impacts of which disproportionately impact urban populations. Pluvial flooding and flooding related sewer backups are thought to result in an increase in potentially hazardous human-pathogen encounters. However, the extent and nature of associations between flooding events and non-communicable respiratory diseases such as chronic bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) are not well understood. This research seeks to characterize the state of research on flooding and NCRDs through a systematic review of the scientific literature. We conducted a systematic search of PubMed, Web of Science, and Scopus for published scholarly research papers using the terms flooding, monsoon, and tropical storm with terms for common NCRDs such as asthma, COPD, and chronic bronchitis. Papers were included if they covered research studies on individuals with defined outcomes of flooding events. We excluded review papers, case studies, and opinion pieces. We retrieved 200 articles from PubMed, 268 from Web of Science and 203 from Scopus which comprised 345 unique papers. An initial review of abstracts yielded 38 candidate papers. A full text review of each left 16 papers which were included for the review. All papers except for one found a significant association between a severe weather event and increased risk for at least one of the NCRDs included in this research. Our findings further suggest that extreme weather events may worsen pre-existing respiratory conditions and increase the risk of development of asthma. Future work should focus on more precisely defining measure of health outcomes using validated tools to describe asthma and COPD exacerbations. Research efforts should also work to collect granular data on patients’ health status and family history and assess possible confounding and mediating factors such as neighborhood water mitigation infrastructure, housing conditions, pollen counts, and other environmental variables.
      Citation: Climate
      PubDate: 2022-07-04
      DOI: 10.3390/cli10070101
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 102: Upscaling Local Adaptive Heritage Practices
           to Internationally Designated Heritage Sites

    • Authors: Sarah Kerr, Felix Riede
      First page: 102
      Abstract: World Heritage Sites can face an onslaught of risks from high tourist numbers, climate changes, the impacts of conflict and war, and static management practices. These sites have been ascribed a value that is considered both outstanding and universal (OUV) and as such they are placed at a higher prioritisation than all other heritage sites. The aim of this listing is to ensure their protection for future generations. Yet, the management practices enacted under this preservation mandate can be reactive rather than proactive and reflective, overly concerned with maintaining the status quo, and restricted by a complexity of national and international regulations and stakeholders. We here introduce a local-scale, community-driven heritage project, called CHICC, that offers, we argue, a useful insight into management practices that may be upscaled to internationally designated sites. Although this is not a blueprint to fit all heritage needs, some of the fundamental intentions embedded within CHICC can and perhaps should be adopted in the approaches to internationally designated site management. These include inclusivity with the local community as a priority stakeholder, a deeper understanding of the site including its future risks, consideration of the wider heritage landscape, and greater incorporation of heritage dynamism. Through analysing and evaluating the case study project, this conceptual chapter argues that adaptive heritage practices are underway in some local-scale contexts, and this can be a useful template for advancing the management of World Heritage Sites.
      Citation: Climate
      PubDate: 2022-07-05
      DOI: 10.3390/cli10070102
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 103: Climate Change and Its Effects on Indoor
           Pests (Insect and Fungi) in Museums

    • Authors: Pascal Querner, Katja Sterflinger, Katharina Derksen, Johanna Leissner, Bill Landsberger, Astrid Hammer, Peter Brimblecombe
      First page: 103
      Abstract: Climate change not only affects the biodiversity of natural habitats, but also the flora and fauna within cities. An increase in average temperature and changing precipitation, but additionally extreme weather events with heat waves and flooding, are forecast. The climate in our cities and, thus, also inside buildings is influenced by the changing outdoor climate and urban heat islands. A further challenge to ecosystems is the introduction of new species (neobiota). If these species are pests, they can cause damage to stored products and materials. Much cultural heritage is within buildings, so changes in the indoor climate also affect pests (insect and fungi) within the museums, storage depositories, libraries, and historic properties. This paper reviews the literature and presents an overview of these complex interactions between the outdoor climate, indoor climate, and pests in museums. Recent studies have examined the direct impact of climate on buildings and collections. The warming of indoor climates and an increased frequency or intensity of extreme weather events are two important drivers affecting indoor pests such as insects and fungi, which can severely damage collections. Increases in activity and new species are found, e.g., the tropical grey silverfish Ctenolepisma longicaudatum has been present in many museums in recent years benefitting from increased indoor temperatures.
      Citation: Climate
      PubDate: 2022-07-05
      DOI: 10.3390/cli10070103
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 104: Climate Security and Its Implications for
           East Asia

    • Authors: Takashi Sekiyama
      First page: 104
      Abstract: This study investigated the scientific progress of climate security studies through a literature review and discussed its risks in East Asia. Climate security refers to the protection of countries and societies from conflicts and riots caused by climate change. As climate change becomes more apparent, climate security has been vigorously debated in the international community. Climate security risks in East Asia, however, are not yet widely discussed. This literature review identified that climate change increases the risk of conflict not only through direct threats to people and societies from extreme weather events and natural disasters, but also indirectly through various pathways, such as shortages of water and other resources, outbreaks of climate migration, disruptions in food production, economic and social disturbances, and geopolitical changes. Considering the climate-conflict pathways identified by the literature review, East Asia may face (1) tensions caused by climate emigrants, (2) conflicts over loss of territories and fishery areas, (3) conflicts caused by water shortage, (4) instability caused by heavy rain and floods, and (5) geopolitical risks of rare earth sourcing, green industrial policies, and the Arctic. East Asian countries need to lower climate security risks in the region through cooperative international measures such as climate change mitigation, vulnerability reduction, and policy dialogue.
      Citation: Climate
      PubDate: 2022-07-06
      DOI: 10.3390/cli10070104
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 105: Local Officials’ Perceptions of Climate
           Victim Management Challenges on Bangladesh’s Southeast Coast

    • Authors: Kisinger Chakma, Kenichi Matsui
      First page: 105
      Abstract: In Bangladesh, extreme weather events displace about one million people each year. The national government resettles these climate victims by allocating houses in so-called cluster villages. This paper examines how local disaster management officials manage the resettlement of climate victims in Bangladesh’s coastal areas. For this paper, we conducted a preliminary field work, questionnaire survey, and informal phone interviews. The questionnaire survey was conducted from March to July 2020 among 70 central government civil servants who worked as disaster management officials and played a pivotal role in local decision making for climate victim resettlement. This paper first examines how national disaster response policies were implemented in local areas before, during, and after disasters. Our questionnaire survey results show five management challenges local officials faced in managing displaced people: (1) local officials’ limited onsite experience, (2) varied impacts of natural disasters on islands and the mainland, (3) arbitrary engagement in disaster response actions, (4) lack of evacuation drills, and (5) weak coordination skills among relevant stakeholders. In particular, these challenges were acute among island officials. Our multiple regression analyses show that the respondents’ age and onsite work experience (p < 0.05) significantly affected their perceptions. Overall, these findings suggest a need to drastically improve local disaster governance capacity. This study offers insights into how countries with similar challenges may respond to climate-induced displacement in the future.
      Citation: Climate
      PubDate: 2022-07-06
      DOI: 10.3390/cli10070105
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 106: A Methodology for Bridging the Gap between
           Regional- and City-Scale Climate Simulations for the Urban Thermal

    • Authors: Konstantina Koutroumanou-Kontosi, Constantinos Cartalis, Kostas Philippopoulos, Ilias Agathangelidis, Anastasios Polydoros
      First page: 106
      Abstract: The main objective of this study is to bridge the gap between regional- and city-scale climate simulations, with the focus given to the thermal environment. A dynamic-statistical downscaling methodology for defining daily maximum (Tmax) and minimum (Tmin) temperatures is developed based on artificial neural networks (ANNs) and multiple linear regression models (MLRs). The approach involves the use of simulations from two EURO-CORDEX regional climate models (RCMs) (at approximately 12 km × 12 km) that are further downscaled to a finer resolution (1 km × 1 km). A feature selection methodology is applied to select the optimum subset of parameters for training the machine learning models. The downscaling methodology is initially applied to two RCMs, driven by the ERA-Interim reanalysis (2008–2011) and high-resolution urban climate model simulations (UrbClims). The performance of the relationships is validated and found to successfully simulate the spatiotemporal distribution of Tmax and Tmin over Athens. Finally, the relationships that were extracted by the models are further used to quantify changes for Tmax and Tmin in high resolution, between the historical period (1971–2000) and mid-century (2041–2071) climate projections for two different representative concentration pathways (RCP4.5 and RCP8.5). Based on the results, both mean Tmax and Tmin are estimated to increase by 1.7 °C and 1.5 °C for RCP4.5 and 2.3 °C and 2.1 °C for RCP8.5, respectively, with distinct spatiotemporal patterns over the study area.
      Citation: Climate
      PubDate: 2022-07-13
      DOI: 10.3390/cli10070106
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 107: Hydrological and Meteorological Variability
           in the Volga River Basin under Global Warming by 1.5 and 2 Degrees

    • Authors: Andrey Kalugin
      First page: 107
      Abstract: The idea of the research to assess the impact of 1.5 °C and 2 °C global warming in the 21st century on the runoff formation in the Volga basin corresponds to the Paris agreement on climate change 2016 with the main goal to keep the global air temperature rise to below 2 °C relative to the pre-industrial level and to take measures to limit warming to 1.5 °C by the end of the 21st century. The purpose of this study was to obtain physically based results of changes in the water regime of the Volga basin rivers under global warming by 1.5 °C and 2 °C relative to pre-industrial values. The physical and mathematical model of runoff generation ECOMAG (ECOlogical Model for Applied Geophysics) was applied in calculations using data from global climate models (GCMs). The estimation of flow anomalies of the Volga River and its major tributaries showed a decrease in annual runoff by 10–11% relative to the period from 1970 to 1999. The largest relative decrease in runoff by 17–20% was noted for the Oka and Upper Volga rivers, while the Kama River had only a 1–5% decrease. The Volga winter runoff increased by 17% and 28% under global warming by 1.5 °C and 2 °C, respectively, and negative runoff anomalies during the spring flood and the summer–autumn period turned out to be in the range of 21 to 23%. Despite the increase in precipitation, the role of evaporation in the water balance of the Volga basin will only increase.
      Citation: Climate
      PubDate: 2022-07-15
      DOI: 10.3390/cli10070107
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 108: Regional Responses of the Northern Hemisphere
           Subtropical Jet Stream to Reduced Arctic Sea Ice Extent

    • Authors: José Luis Rodriguez Solis, Cuauhtémoc Turrent, Markus Gross
      First page: 108
      Abstract: The effect of Arctic sea ice loss on the boreal winter regional trends of wind speed and latitudinal position of the Northern Hemisphere subtropical jet stream (STJ) in 1980–2012 is investigated. Two sets of global simulations with reduced Arctic sea ice extent are analyzed: simulations that, south of 70 N, use a climatological annual cycle of the sea surface temperature (SST) and a second set that uses full SST variability. Results with the climatological SST have a significant but weak response of the STJ wind speed and latitudinal position to the warmer Arctic: the wind speed generally decreases and the jet core is displaced equatorward. However, in the realistic SST simulations, the effect of Arctic warming is only slightly evident in a small equatorward shift of the jet over the Atlantic basin. Over the Pacific basin the STJ is mostly driven by tropical and mid-latitude SST variability, with little influence from the Arctic region. A weakening and poleward shift of the STJ that is observed in the realistic SST simulations over the Pacific basin is attributed to negative SST trends in the tropical Pacific and the consequent weakening of the mid-latitude meridional gradient of geopotential height in the upper troposphere.
      Citation: Climate
      PubDate: 2022-07-16
      DOI: 10.3390/cli10070108
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 109: Exploring Methods for Developing Local
           Climate Zones to Support Climate Research

    • Authors: Laurence Sigler, Joan Gilabert, Gara Villalba
      First page: 109
      Abstract: Meteorological and climate prediction models at the urban scale increasingly require more accurate and high-resolution data. The Local Climate Zone (LCZ) system is an initiative to standardize a classification scheme of the urban landscape, based mainly on the properties of surface structure (e.g., building, tree height, density) and surface cover (pervious vs. impervious). This approach is especially useful for studying the influence of urban morphology and fabric on the surface urban heat island (SUHI) effect and to evaluate how changes in land use and structures affect thermal regulation in the city. This article will demonstrate three different methodologies of creating LCZs: first, the World Urban Database and Access Portal Tools (WUDAPT); second, using Copernicus Urban Atlas (UA) data via a geographic information system (GIS) client directly; and third via Google Earth Engine (GEE) using Oslo, Norway as the case study. The WUDAPT and GEE methods incorporate a machine learning (random forest) procedure using Landsat 8 imagery, and offer the most precision while requiring the most time and familiarity with GIS usage and satellite imagery processing. The WUDAPT method is performed principally using multiple GIS clients and image processing tools. The GEE method is somewhat quicker to perform, with work performed entirely on Google’s sites. The UA or GIS method is performed solely via a GIS client and is a conversion of pre-existing vector data to LCZ classes via scripting. This is the quickest method of the three; however, the reclassification of the vector data determines the accuracy of the LCZs produced. Finally, as an illustration of a practical use of LCZs and to further compare the results of the three methods, we map the distribution of the temperature according to the LCZs of each method, correlating to the land surface temperature (LST) from a Landsat 8 image pertaining to a heat wave episode that occurred in Oslo in 2018. These results show, in addition to a clear LCZ-LST correspondence, that the three methods produce accurate and similar results and are all viable options.
      Citation: Climate
      PubDate: 2022-07-16
      DOI: 10.3390/cli10070109
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 110: Climate-Induced Fire Hazard in Forests in the
           Volga Federal District of European Russia during 1992–2020

    • Authors: Yuri Perevedentsev, Boris Sherstyukov, Artyom Gusarov, Timur Aukhadeev, Nadezhda Mirsaeva
      First page: 110
      Abstract: This paper shows the relevance of the problem of fire hazard in the forests of the Volga Federal District (VFD) of European Russia. The Nesterov index and the Selyaninov hydrothermal coefficient (HTC) are considered as indicators of fire hazard. The changes in climatic conditions in the VFD during 1955–2018 are shown; a trend towards warming and an increase in aridity in the study region were revealed. The repeatability of various fire hazard classes from May to September was calculated using the Nesterov method. It is shown that in July, the most dangerous situation was in the south of the VFD, where the repeatability of class IV fire hazard reached 27%. Using the HTC index, the degree of aridity of the district in the summer period was estimated. The frequency of the most arid conditions (HTC < 0.5) increases from the north to the south of the district, from 6% (Kirov Region) to 47% (Orenburg Region). Using the TT index, the potential thunderstorm danger in the VFD was assessed. With the help of the constructed maps, the hotspots of the most probable occurrence of thunderstorms were detected. The use of Rosstat data on the number of forest fires from 1992 to 2020 made it possible to consider the spatiotemporal distribution of forest fires in 14 administrative regions of the VFD. The distribution of the number of fires by the regions is shown depending on their forest cover and season. The peak of the number of fires was revealed in 2010, when the entire territory of the study region was covered by a severe drought, as a result of which the area of forests covered by fire increased many times over. In recent years (since 2017), there has been an increase in the area of burned forest due to the active phase of climate warming.
      Citation: Climate
      PubDate: 2022-07-18
      DOI: 10.3390/cli10070110
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 111: Spatial and Temporal Assessment of Remotely
           Sensed Land Surface Temperature Variability in Afghanistan during

    • Authors: Ahmad Farid Nabizada, Iman Rousta, Marjan Dalvi, Haraldur Olafsson, Anna Siedliska, Piotr Baranowski, Jaromir Krzyszczak
      First page: 111
      Abstract: The dynamics of land surface temperature (LST) in Afghanistan in the period 2000–2021 were investigated, and the impact of the factors such as soil moisture, precipitation, and vegetation coverage on LST was assessed. The remotely sensed soil moisture data from Land Data Assimilation System (FLDAS), precipitation data from Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), and NDVI and LST from Moderate-Resolution Imaging Spectroradiometer (MODIS) were used. The correlations between these data were analyzed using the regression method. The result shows that the LST in Afghanistan has a slightly decreasing but insignificant trend during the study period (R = 0.2, p-value = 0.25), while vegetation coverage, precipitation, and soil moisture had an increasing trend. It was revealed that soil moisture has the highest impact on LST (R = −0.71, p-value = 0.0007), and the soil moisture, precipitation, and vegetation coverage explain almost 80% of spring (R2 = 0.73) and summer (R2 = 0.76) LST variability in Afghanistan. The LST variability analysis performed separately for Afghanistan’s river subbasins shows that the LST of the Amu Darya subbasin had an upward trend in the study period, while for the Kabul subbasin, the trend was downward.
      Citation: Climate
      PubDate: 2022-07-19
      DOI: 10.3390/cli10070111
      Issue No: Vol. 10, No. 7 (2022)
  • Climate, Vol. 10, Pages 88: Analysis of Ocean Parameters as Sources of
           Coastal Storm Damage: Regional Empirical Thresholds in Northern Spain

    • Authors: Rivas, Garmendia, Rasilla
      First page: 88
      Abstract: This contribution aims to explore the role of oceanographic parameters on the damage caused by storms at the eastern Cantabrian coast (1996–2016). All wave storms affecting the study area were characterized in terms of several oceanographic parameters; among them, damaging storms (responsible for direct and tangible loss) were identified. Cross-referencing both databases makes it possible to find some thresholds that explain storm conditions associated with property damage. Particularly relevant are those responsible for significant and widespread damage: maximum significant offshore wave height >6.5 m, maximum total water level >6 m, SPI >1700 m2h, and a storm duration >48 h. These values are exceptionally high, mostly exceeding the 95th percentile. A comparison has been made with other thresholds described in the literature. The concurrence of high wave height and high tidal level is crucial as the greatest damage is caused by the combination of wave impact and over-wash, so a long duration of the storm is necessary to coincide with high tide. An empirical Intensity-Duration threshold has also been obtained with the following function I = 248.7 D−0.45. Damage can occur with moderate storms, but with severe effects only with exceptional wave and sea-level values, during long-lasting storms.
      Citation: Climate
      PubDate: 2022-06-17
      DOI: 10.3390/cli10060088
      Issue No: Vol. 10, No. 6 (2022)
  • Climate, Vol. 10, Pages 89: Spatiotemporal Changes in Mean and Extreme
           Climate: Farmers’ Perception and Its Agricultural Implications in
           Awash River Basin, Ethiopia

    • Authors: Addisu Damtew, Ermias Teferi, Victor Ongoma, Richard Mumo, Befikadu Esayas
      First page: 89
      Abstract: The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p < 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.
      Citation: Climate
      PubDate: 2022-06-20
      DOI: 10.3390/cli10060089
      Issue No: Vol. 10, No. 6 (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 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

    • 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

    • 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 135: Embodied Carbon Emissions of the Residential
           Building Stock in the United States and the Effectiveness of Mitigation

    • Authors: Ming Hu
      First page: 135
      Abstract: According to the 2021 Global Status Report for Buildings and Construction published by the United Nations Environment Programme, global carbon emissions from the building sector in 2019 were nearly 14 gigatons (Gt), representing 38% of total global carbon emissions, including 10% from building construction. In the United States, the largest knowledge gap regarding embodied carbon in buildings exists at the whole-building level. The first step in creating informative policy to reduce embodied carbon emissions is to map the existing building stock emissions and changes over time to understand the primary contributing building types and hot spots (states), and then to compare and analyze mitigation scenarios. To fill this knowledge gap, this study first developed a bottom-up model to assess the embodied carbon of the US residential building stock by using 64 archetypes to represent the building stock. Then, the embodied carbon characteristics of the current building stock were analyzed, revealing that the primary contributor was single-family detached (SD) houses. The results indicated that the exterior wall was a major contributor, and that small multifamily housing was the most embodied carbon-intense building type. Two scenarios, the baseline scenario and progressive scenario, were formed to evaluate the effectiveness of six mitigation strategies. The progressive scenario with all mitigation strategies (M1–M6) applied produced a total reduction of 33.13 Gt CO2eq (42%) in the cumulative residential building stock related to carbon emissions during 2022–2050, and a total reduction of 88.34 Gt CO2eq (80%) during 2022–2100. The results show that with an embodied carbon emissions reduction in the progressive scenario (42% by 2100), the total embodied carbon emissions comply with the carbon budget of a 2 °C pathway, but will exceed the budget for a 1.5 °C pathway.
      Citation: Climate
      PubDate: 2022-09-20
      DOI: 10.3390/cli10100135
      Issue No: Vol. 10, No. 10 (2022)
  • Climate, Vol. 10, Pages 136: The Western Pacific North Equatorial
           Countercurrent Responses to Two Forms of El Niño During the Period
           1978 to 2017

    • Authors: Wijaya, Wisha, Hisaki
      First page: 136
      Abstract: This research aims to examine how the Western Pacific North equatorial countercurrent (NECC) flow reacts to two different forms of El Niño (EN) over a 40-year period. To establish the prevailing modes for each season, we implemented Empirical Orthogonal Function (EOF) analysis on the eastward current component of the Ocean Reanalysis System 5 (ORAS5) dataset. In comparison to the Central Pacific (CP) episode, the time series principal component of the first mode (PC1) demonstrated that the strongest NECC’s magnitude often emerged during the development period (spring to fall) of the Eastern Pacific (EP) EN event. However, in episode CP 2002/2003, we witnessed an abnormal behavior in which the stronger NECC manifested. This was due to the emergence of a strong anomalous westerly wind, which differed from other CP events and forced the NECC’s magnitude to be greater. When approaching the peak stage, on the other hand, the magnitude of the NECC during the CP episode was typically greater than that of the EP episode. The NECC’s magnitude fell greatly in the second year of the EP episode, particularly during the spring season, since most EP episodes would transition into an La Niña (LN) event in the succeeding event. During the EP EN, it was found that the strength of the westerly wind had a bigger effect on the NECC than during the CP EN.
      Citation: Climate
      PubDate: 2022-09-20
      DOI: 10.3390/cli10100136
      Issue No: Vol. 10, No. 10 (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

    • 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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