Climate

16 pages, 237 KiB

Open AccessArticle

“Taking Action in Community Is Much, Much Preferable to Doing It Alone”: An Examination of Multi-Level Facilitators of and Barriers to Sustained Collective Climate Change Activism Among US Residents

by Lauren Dayton, Kelsie Parker, Julia Ross, Saraniya Tharmarajah and Carl Latkin

Climate 2024, 12(12), 222; https://doi.org/10.3390/cli12120222 (registering DOI) - 14 Dec 2024

Abstract

To enact climate mitigation policies, sustained collective activism is essential to create political pressure and prioritize addressing climate change. Climate change activism includes behaviors such as contacting elected officials to urge them to take action on climate change, volunteering, and signing petitions. Climate [...] Read more.

To enact climate mitigation policies, sustained collective activism is essential to create political pressure and prioritize addressing climate change. Climate change activism includes behaviors such as contacting elected officials to urge them to take action on climate change, volunteering, and signing petitions. Climate change activism is often measured as a one-time event, not sustained activism efforts, which are necessary to enact sufficiently impactful policy changes. To examine barriers to and facilitators of sustained climate change activism, 23 in-depth interviews were conducted between August and December 2023 among members of an innovative national climate change-focused organization. Eligibility included being at least 18 years of age, English-speaking, a US resident, and highly engaged in a climate change activism group. Content analysis of interview transcripts was employed, and five themes emerged as barriers, four themes as facilitators, and five themes as both facilitators of and barriers to sustained climate change activism. The study identified strategies to promote the critical behavior of sustained climate change activism, which included fostering a community of climate change activists, clear instructions on how to engage in activism behaviors for all technical abilities, supporting mental health, and creating climate change activism as a habit and identity. Full article

28 pages, 10117 KiB

Open AccessArticle

The Drought Regime in Southern Africa: Long-Term Space-Time Distribution of Main Drought Descriptors

by Fernando Maliti Chivangulula, Malik Amraoui and Mário Gonzalez Pereira

Climate 2024, 12(12), 221; https://doi.org/10.3390/cli12120221 - 13 Dec 2024

Abstract

Drought consequences depend on its type and class and on the preparedness and resistance of communities, which, in turn, depends on the knowledge and capacity to manage this climate disturbance. Therefore, this study aims to assess the drought regime in Southern Africa based [...] Read more.

Drought consequences depend on its type and class and on the preparedness and resistance of communities, which, in turn, depends on the knowledge and capacity to manage this climate disturbance. Therefore, this study aims to assess the drought regime in Southern Africa based on vegetation and meteorological indices. The SPI and SPEI were calculated at different timescales, using ERA5 data for the 1971–2020 period. The results revealed the following: (i) droughts of various classes at different timescales occurred throughout the study period and region; (ii) a greater Sum of Drought Intensity and Number, in all classes, but lower duration and severity of droughts with the SPI than with the SPEI; (iii) drought frequency varies from 1.3 droughts/decade to 4.5 droughts/decade, for the SPI at 12- to 3-month timescales; (iv) the number, duration, severity and intensity of drought present high spatial variability, which tends to decrease with the increasing timescale; (v) the area affected by drought increased, on average, 6.6%/decade with the SPI and 9.1%/decade with the SPEI; and (vi) a high spatial-temporal agreement between drought and vegetation indices that confirm the dryness of vegetation during drought. These results aim to support policymakers and managers in defining legislation and strategies to manage drought and water resources. Full article

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16 pages, 2925 KiB

Open AccessArticle

A Comprehensive AI Approach for Monitoring and Forecasting Medicanes Development

by Javier Martinez-Amaya, Veronica Nieves and Jordi Muñoz-Mari

Climate 2024, 12(12), 220; https://doi.org/10.3390/cli12120220 - 13 Dec 2024

Abstract

Medicanes are rare cyclones in the Mediterranean Sea, with intensifying trends partly attributed to climate change. Despite progress, challenges persist in understanding and predicting these storms due to limited historical tracking data and their infrequent occurrence, which make monitoring and forecasting difficult. In [...] Read more.

Medicanes are rare cyclones in the Mediterranean Sea, with intensifying trends partly attributed to climate change. Despite progress, challenges persist in understanding and predicting these storms due to limited historical tracking data and their infrequent occurrence, which make monitoring and forecasting difficult. In response to this issue, we present an AI-based system for tracking and forecasting Medicanes, employing machine learning techniques to identify cyclone positions and key evolving spatio-temporal structural features of the cloud system that are associated with their intensification and potential extreme development. While the forecasting model currently operates with limited training data, it can predict extreme Medicane events up to two days in advance, with precision rates ranging from 65% to 80%. These innovative data-driven methods for tracking and forecasting provide a foundation for refining AI models and enhancing our ability to respond effectively to such events. Full article

(This article belongs to the Special Issue Addressing Climate Change with Artificial Intelligence Methods)

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22 pages, 6758 KiB

Open AccessArticle

Analysis of the Observed Trends in Rainfall and Temperature Patterns in North-Eastern Nigeria

by Deborah Ishaku, Emmanuel Tanko Umaru, Abel Aderemi Adebayo, Ralf Löwner and Appollonia Aimiosino Okhimamhe

Climate 2024, 12(12), 219; https://doi.org/10.3390/cli12120219 - 11 Dec 2024

Abstract

The present study offers a comprehensive evaluation of the monthly rainfall and temperature patterns across nine stations and fifty-nine points in North-Eastern Nigeria using NASA’s Prediction of Worldwide Energy Resources data, spanning four decades (1981–2021). By employing the Mann–Kendall (MK) test and inverse [...] Read more.

The present study offers a comprehensive evaluation of the monthly rainfall and temperature patterns across nine stations and fifty-nine points in North-Eastern Nigeria using NASA’s Prediction of Worldwide Energy Resources data, spanning four decades (1981–2021). By employing the Mann–Kendall (MK) test and inverse distance weighting (IDW) interpolation, the researchers effectively detected and visualized trends in climate variables. The MK test results indicate contrasting rainfall trends, with notable decreases in Akko, Billiri, Maiduguri, Numan, and Yola, and increases in Gombe, Abadam, Biu, and Mubi. The trends in the maximum temperature were found to be statistically significant across all stations, showing a consistent increase, whereas the minimum temperature trends exhibited a slight but insignificant decrease. The application of the Theil–Sen slope estimator quantified these trends, providing nuanced insights into the magnitudes of changes in climate variables. The IDW results further corroborate the general trend of decreasing rainfall (z = −0.442), modest increases in the maximum temperature (z = 0.046), and a marginal decline in the minimum temperature (z = −0.005). This study makes an important contribution by advocating for the proactive dissemination of climate information. Given the evident climate shifts, particularly the increasing temperatures and fluctuating rainfall patterns, timely access to such information is crucial to enhancing climate resilience in the region. The rigorous statistical methods applied and the detailed spatial analysis strengthen the validity of these findings, making this study a valuable resource for both researchers and policymakers aiming to address climate variability in North-Eastern Nigeria. These research results may also be useful for understanding the climate variabilities in different parts of the world. Full article

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21 pages, 2159 KiB

Open AccessArticle

Multi-Secular Trend of Drought Indices in Padua, Italy

by Francesca Becherini, Claudio Stefanini, Antonio della Valle, Francesco Rech, Fabio Zecchini and Dario Camuffo

Climate 2024, 12(12), 218; https://doi.org/10.3390/cli12120218 - 10 Dec 2024

Abstract

The aim of this work is to investigate drought variability in Padua, northern Italy, over a nearly 300-year period, from 1725 to 2023. Two well-established and widely used indices are calculated, the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). [...] Read more.

The aim of this work is to investigate drought variability in Padua, northern Italy, over a nearly 300-year period, from 1725 to 2023. Two well-established and widely used indices are calculated, the standardized precipitation index (SPI) and the standardized precipitation evapotranspiration index (SPEI). They are compatible with a data series starting in the early instrumental period, as both can be estimated using only temperature and precipitation data. The Padua daily precipitation and temperature series from the early 18th century, which were recovered and homogenized with current observations, are used as datasets. The standard approach to estimate SPI and SPEI based on gamma and log-logistic probability distribution functions, respectively, is questioned, assessing the fitting performance of different distributions applied to monthly precipitation data. The best-performing distributions are identified for each index and accumulation period at annual and monthly scales, and their normality is evaluated. In general, they detect more extreme drought events than the standard functions. Moreover, the main statistical values of SPI are very similar, regardless of the approach type, as opposed to SPEI. The difference between SPI and SPEI time series calculated with the best-fit approach has increased since the mid-20th century, in particular in spring and summer, and can be related to ongoing global warming, which SPEI takes into account. The innovative trend analysis applied to SPEI12 indicates a general increasing trend in droughts, while for SPI12, it is significant only for severe events. Summer and fall are the most affected seasons. The critical drought intensity–duration–frequency curves provide an easily understandable relationship between the intensity, duration and frequency of the most severe droughts and allow for the calculation of return periods for the critical events of a certain duration. Moreover, the longest and most severe droughts over the 1725–2023 period are identified. Full article

(This article belongs to the Special Issue Climate Variability in the Mediterranean Region)

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13 pages, 769 KiB

Open AccessArticle

Factors Contributing to Effective Climate Change Adaptation Projects in Water Management: Implications from the Developing Countries

by Yuki Shiga and Rajib Shaw

Climate 2024, 12(12), 217; https://doi.org/10.3390/cli12120217 - 10 Dec 2024

Abstract

The adaptation finance gap is widening as the impact of climate change grows more disruptive around the globe. Although progress in adaptation planning and implementation has been observed across all sectors and regions, this trend of a widening resource gap calls for more [...] Read more.

The adaptation finance gap is widening as the impact of climate change grows more disruptive around the globe. Although progress in adaptation planning and implementation has been observed across all sectors and regions, this trend of a widening resource gap calls for more ‘effective’ climate adaptation projects. Therefore, the purpose of this paper is to provide a comprehensive analysis to explore potential factors contributing to the effectiveness of climate change projects in developing countries with a particular focus on water management financed under multilateral funds that have been implemented on the ground, completed and documented. Thirty-five projects from the multilateral funds were collected and analyzed for this purpose. Project evaluation documents have been studied, and the effectiveness rating at completion has been assessed against possible contributing factors through regression analysis. The results showed that the factors contributing to project effectiveness converge around several elements: (i) capacity building and education (|r| > 0.3); (ii) healthy and resilient livelihoods (|r| > 0.2); and (iii) climate data and a robust theory of change (stated by >30% of projects). The implications from this study can provide a useful quantitative ground for discussion around the effective adaptation projects in water management as well as inform relevant international processes such as the Global Goal on Adaptation and global stocktake. Full article

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11 pages, 1637 KiB

Open AccessArticle

Views of Health Professionals About Climate and Health in Sierra Leone: A Cross-Sectional Study

by Isaac S. Sesay and Konstantinos C. Makris

Climate 2024, 12(12), 216; https://doi.org/10.3390/cli12120216 - 10 Dec 2024

Abstract

Climate change presents one of the biggest global threats to society, while the impact of its manifestations on human health has been poorly characterized and quantified, especially in middle- and low-income countries. The perceptual views of health professionals about the climate and health [...] Read more.

Climate change presents one of the biggest global threats to society, while the impact of its manifestations on human health has been poorly characterized and quantified, especially in middle- and low-income countries. The perceptual views of health professionals about the climate and health nexus are critical for the effective implementation of climate policies. The Sierra Leone health professionals are no exception to this, and no such data exist for their country. To this extent, we distributed a cross-sectional survey to understand the perceptual views and beliefs of health professionals in Sierra Leone about the climate and health nexus. A validated international questionnaire on the topic was electronically administered to 265 participants. A descriptive analysis of the survey responses was conducted. Results showed that almost all of the respondents (97%) felt that climate change is an important issue; more than half (68%) of them were very worried about climate change, and 28% were somewhat worried. About half of respondents believed that human activities mostly caused climate change, while 40% of health professionals felt this was equally caused by human activities and natural changes in the environment. The need to engage health professionals with the public and policymakers to bring the health effects of climate change to their attention was particularly highlighted; however, most respondents (81%) stated that numerous barriers impede them from doing so. The most widely reported barriers and needs were the need for training to communicate effectively about climate change and health (96%) and guidance on creating sustainable workplaces (94%), followed by the need for lifelong training and education programs on climate and health, and the lack of time (73%). These survey findings would be valuable to policymakers in Sierra Leone and the broader African regions towards mitigating and adapting to climate change threats to human health. Full article

(This article belongs to the Special Issue Confronting the Climate Change and Health Nexus: Interactions, Impacts, and Adaptation Strategies)

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29 pages, 5051 KiB

Open AccessArticle

Evolution of Bioclimatic Belts in Spain and the Balearic Islands (1953–2022)

by Christian Lorente, David Corell, María José Estrela, Juan Javier Miró and David Orgambides-García

Climate 2024, 12(12), 215; https://doi.org/10.3390/cli12120215 - 10 Dec 2024

Abstract

This study examines the spatio-temporal evolution of bioclimatic belts in peninsular Spain and the Balearic Islands from 1953 to 2022 using the World Bioclimatic Classification System and data from 3668 meteorological stations. Findings indicate a shift toward warmer and more arid conditions, with [...] Read more.

This study examines the spatio-temporal evolution of bioclimatic belts in peninsular Spain and the Balearic Islands from 1953 to 2022 using the World Bioclimatic Classification System and data from 3668 meteorological stations. Findings indicate a shift toward warmer and more arid conditions, with thermotypes showing an increase in mesomediterranean and thermomediterranean types and a decrease in mesotemperate and supratemperate types. Ombrotype analysis revealed a rise in semiarid types and a decline in humid and hyperhumid types. Significant changes occurred in climate transition zones and mountainous regions, where a process of “Mediterraneanisation”—a process characterised by the expansion of warmer and drier conditions typical of Mediterranean climates into previously temperate areas and/or an altitudinal rise in thermotypes—has been observed. The spatial variability of changes in ombrotypes was greater than that in thermotypes, with regions showing opposite trends to the general one. These results highlight the need for adaptive conservation strategies, particularly in mountainous and climate transition areas, where endemic species may face increased vulnerability due to habitat loss and fragmentation. The results of this study provide insight into how climate change is affecting bioclimatological conditions in the Iberian Peninsula and the Balearic Islands. Full article

(This article belongs to the Special Issue Climate Variability in the Mediterranean Region)

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17 pages, 2031 KiB

Open AccessArticle

Resilience of Chinese Ports to Tropical Cyclones: Operational Efficiency and Strategic Importance

by Mark Ching-Pong Poo, Wen Zhang, Leila Kamalian, Tianni Wang, Yui-yip Lau and Tina Ziting Xu

Climate 2024, 12(12), 214; https://doi.org/10.3390/cli12120214 - 9 Dec 2024

Abstract

This study evaluated the resilience of five major Chinese ports—Shanghai, Tsingtao, Shenzhen, Xiamen, and Qinzhou—against the impacts of tropical cyclones. These ports, as integral global maritime supply chain nodes, face rising vulnerabilities from climate-related disruptions such as typhoons, sea-level rise, and extreme temperature [...] Read more.

This study evaluated the resilience of five major Chinese ports—Shanghai, Tsingtao, Shenzhen, Xiamen, and Qinzhou—against the impacts of tropical cyclones. These ports, as integral global maritime supply chain nodes, face rising vulnerabilities from climate-related disruptions such as typhoons, sea-level rise, and extreme temperature fluctuations. Employing a resilience assessment framework, this study integrated climate and operational data to gauge how cyclone-induced events affect port performance, infrastructure, and economic stability. Multi-centrality analysis and the Borda count method were applied to assess each port’s strategic importance and operational efficiency under cyclone exposure. The findings highlight variations in resilience across the ports, with Shanghai and Tsingtao showing heightened risk due to their critical roles within international logistics networks. This study suggests strategies like strengthening infrastructure, improving emergency responses, and adopting climate-resilient policies to make China’s ports more sustainable and resilient to climate threats. This research offers actionable insights for policymakers and port authorities, contributing to a more climate-resilient maritime logistics framework. Full article

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13 pages, 865 KiB

Open AccessArticle

The Role of Psychological Capital on Climate Change Adaptation Among Smallholder Farmers in the uMkhanyakude District of KwaZulu-Natal, South Africa

by Mbongeni Maziya, Lelethu Mdoda and Lungile Pearl Sindiswa Mvelase

Climate 2024, 12(12), 213; https://doi.org/10.3390/cli12120213 - 8 Dec 2024

Abstract

Climate change and variability pose a challenge to the livelihoods of smallholder farmers. Previous studies on climate change in the context of smallholder farming have mainly focused on the influence of socio-economic factors in understanding farmers’ responses to climate change. However, little is [...] Read more.

Climate change and variability pose a challenge to the livelihoods of smallholder farmers. Previous studies on climate change in the context of smallholder farming have mainly focused on the influence of socio-economic factors in understanding farmers’ responses to climate change. However, little is known about the effect of psychological capital on climate change adaptation. There are calls for better empirical models and transdisciplinary approaches to understand the underlying drivers of climate change adaptation in smallholder farming systems. This study draws from behavioural decision research to assess psychological factors influencing climate change adaptation in the uMkhanyakude district of KwaZulu-Natal. This study adopted the Theory of Planned Behaviour to understand the effect of psychological capital on climate change adaptation. Data were collected from a sample of 400 smallholder farmers who were randomly selected from the uMkhanyakude district. Survey data were analysed using a multivariate probit regression model. The results of the multivariate probit regression model indicated that psychological capital (attitudes towards climate change, subjective norms, and trust) played an important role in influencing climate change adaptation. Climate change adaptation is also influenced by the gender of the farmer, education level, household size, and Tropical Livestock Units. These findings underscore the role of psychological capital in shaping climate change adaptation. This study recommends using transdisciplinary approaches (i.e., combining economics and psychology) in evaluating farmers’ responses to climate change. Full article

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20 pages, 2850 KiB

Open AccessArticle

Decoding Carbon Footprints: How U.S. Climate Zones Shape Building Emissions

by Ali Nouri and Ming Hu

Climate 2024, 12(12), 212; https://doi.org/10.3390/cli12120212 - 6 Dec 2024

Abstract

The construction industry accounts for over 40% of carbon emissions in the United States, with embodied carbon—emissions associated with building materials and construction processes—remaining underexplored, particularly regarding the impact of location and climate. This study addresses this gap by investigating the influence of [...] Read more.

The construction industry accounts for over 40% of carbon emissions in the United States, with embodied carbon—emissions associated with building materials and construction processes—remaining underexplored, particularly regarding the impact of location and climate. This study addresses this gap by investigating the influence of different climate zones on the embodied carbon emissions of residential buildings. Using Building Information Modeling (BIM), 3D models were developed based on the 2021 International Energy Conservation Code (IECC) and International Residential Code (IRC). A lifecycle assessment (LCA) was conducted using Environmental Product Declarations (EPDs) to evaluate the embodied carbon of building materials during the product stage. The findings reveal that buildings in colder climates exhibit higher embodied carbon emissions, ranging from 25,768 kgCO₂e in Zone 1 to 40,129 kgCO₂e in Zone 8, due to increased insulation requirements. Exterior walls and roofs were identified as significant contributors, comprising up to 34% of total emissions. Sensitivity analysis further indicates that the window-to-wall ratio and interior wall design substantially affect embodied carbon, with baseline emissions around 170 kgCO₂e/m² in warm areas and 255 kgCO₂e/m² in cold areas. These results establish a baseline for lifecycle embodied carbon values across different climate zones in the United States and align with international standards. This study provides valuable insights for policymakers and designers, offering data to inform effective carbon reduction strategies and optimize building designs for sustainability. Full article

(This article belongs to the Section Climate and Environment)

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24 pages, 6036 KiB

Open AccessArticle

Projected Changes in Dry and Wet Spells over West Africa during Monsoon Season Using Markov Chain Approach

by Jules Basse, Moctar Camara, Ibrahima Diba and Arona Diedhiou

Climate 2024, 12(12), 211; https://doi.org/10.3390/cli12120211 - 6 Dec 2024

Abstract

This study examines projected changes in dry and wet spell probabilities in West Africa during the July–August–September monsoon season using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. [...] Read more.

This study examines projected changes in dry and wet spell probabilities in West Africa during the July–August–September monsoon season using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. The results show an increase in the probability of having a dry day, a dry day preceding a wet day, and a dry day preceding a dry day, and a decrease in the probability of wet days in the Sahel region under anthropogenic forcing scenarios RCP4.5 and RCP8.5. The decrease in wet days is stronger in the far future and under the RCP8.5 scenario (up to −30%). The study also finds that the probability of consecutive dry days (lasting at least 7 days and 10 days) is expected to increase in western Sahel, central Sahel, and the Sudanian Area under both scenarios, with stronger increases in the RCP8.5 scenario. In contrast, a decrease is expected over the Guinea Coast, with the changes being more important under the RCP4.5. Dry spell probabilities increasing in the Sahel areas and in the northern Sudanian Area is linked to the increase in the very wet days (R95P) in the daily rainfall intensity index (SDII). These changes in dry and wet spell probabilities are important for water management decisions and risk reduction in the energy and agricultural sectors. This study also highlights the need for decision-makers to implement mitigation and adaptation policies to minimize the adverse effects of climate change. Full article

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17 pages, 3385 KiB

Open AccessArticle

Climatology and Long-Term Trends in Population Exposure to Urban Heat Stress Considering Variable Demographic and Thermo–Physiological Attributes

by Christos Giannaros, Elissavet Galanaki and Ilias Agathangelidis

Climate 2024, 12(12), 210; https://doi.org/10.3390/cli12120210 - 5 Dec 2024

Abstract

Previous studies assessing population exposure to heat stress have focused primarily on environmental heat loads without accounting for variations in human thermo–physiological responses to heat. A novel 30-year (1991–2020) human thermal bioclimate dataset, consisting of hourly mPET (modified physiologically equivalent temperature) values for [...] Read more.

Previous studies assessing population exposure to heat stress have focused primarily on environmental heat loads without accounting for variations in human thermo–physiological responses to heat. A novel 30-year (1991–2020) human thermal bioclimate dataset, consisting of hourly mPET (modified physiologically equivalent temperature) values for diverse populations, was employed in the present study to assist in addressing this gap. Focusing on the Athens urban area (AUA), Greece, the climatology and long-term trends in acclimatization-based strong heat stress (accliSHS) experienced by average male and female adult and senior individuals during the warm period of the year (April–October) were investigated. Results showed that an average adult (senior) in AUA experienced, on average, approximately 13 (18) additional days with at least 1 h accliSHS in 2020 compared with 1991. The increasing rates per year were particularly pronounced for days with ≥6 h accliSHS, indicating a rise in the daily duration of heat stress in AUA from 1991 to 2020. Combining the variations in climate and demographics in AUA during the examined 30-year period, the long-term trends in ≥1 h accliSHS exposure for the study population types were further examined. This analysis revealed that seniors’ exposure to ≥1 h accliSHS in AUA increased by up to +153,000 person-days

\times

year⁻¹ from 1991 to 2020. Increasing population aging was the main driver of this outcome, highlighting the urgent need for heat–health action planning in Greece. Full article

(This article belongs to the Special Issue Confronting the Climate Change and Health Nexus: Interactions, Impacts, and Adaptation Strategies)

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19 pages, 3282 KiB

Open AccessArticle

A Novel Index for Agricultural Drought Measurement: Soil Moisture and Evapotranspiration Revealed Drought Index (SERDI)

by Hushiar Hamarash, Azad Rasul and Rahel Hamad

Climate 2024, 12(12), 209; https://doi.org/10.3390/cli12120209 - 5 Dec 2024

Abstract

Droughts are common across various climates, typically caused by prolonged decreases in rainfall. Several factors contribute to drought, including the temperature, wind speed, and relative humidity and the timing, amount, and intensity of rainfall during the growing season. This study introduces the Soil [...] Read more.

Droughts are common across various climates, typically caused by prolonged decreases in rainfall. Several factors contribute to drought, including the temperature, wind speed, and relative humidity and the timing, amount, and intensity of rainfall during the growing season. This study introduces the Soil Moisture and Evapotranspiration Revealed Drought Index (SERDI), a new index that combines soil moisture and evapotranspiration (calculated using the Penman–Monteith method) to enhance drought early warning systems. To validate the SERDI, we compared it with other established indices such as the Land Surface Temperature (LST), Vegetation Health Index (VHI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI), using metrics like the R-squared (R²), root mean square error (RMSE), mean absolute percentage error (MAPE), and p-value to assess the accuracy, data variability, and forecast conditions. The results showed a low RMSE and high R² between the SERDI and the LST and VHI, indicating a strong correlation. However, weaker correlations were observed between the SERDI and NDVI/NDWI, as shown by the lower R² and higher RMSE values in semi-arid areas. Regions across Iran, Iraq, Syria, Jordan, and Israel experienced mostly moderate to severe drought conditions, with a few areas in Iran and Syria showing normal conditions. The SERDI’s strong correlation with the LST and moderate correlation with the VHI can be attributed to the direct influence of the soil moisture and evapotranspiration on the surface temperature and vegetation health. On the other hand, the weaker correlation with the NDVI and NDWI is due to variability in the vegetation response, irrigation practices, and regional differences. This study concludes that the SERDI is an effective tool for the detection of drought based on soil moisture and evapotranspiration. Full article

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18 pages, 5713 KiB

Open AccessArticle

Comparative Trend Analysis of Precipitation Indices in Several Towns of the Sirba River Catchment (Burkina Faso) from CHIRPS and TAMSAT Rainfall Estimates

by Giorgio Cannella, Alessandro Pezzoli and Maurizio Tiepolo

Climate 2024, 12(12), 208; https://doi.org/10.3390/cli12120208 - 4 Dec 2024

Abstract

The increasingly frequent pluvial flood of West African urban settlements indicates the need to investigate the drivers of local rainfall changes. However, meteorological stations are few, unevenly distributed, and work irregularly. Daily satellite rainfall datasets can be used. Nevertheless, these products often need [...] Read more.

The increasingly frequent pluvial flood of West African urban settlements indicates the need to investigate the drivers of local rainfall changes. However, meteorological stations are few, unevenly distributed, and work irregularly. Daily satellite rainfall datasets can be used. Nevertheless, these products often need to be more accurate due to sensor errors and limitations in retrieval algorithms. The problem is, therefore, how to characterize rainfall where there is a need for ground-based rainfall records or incomplete series. This study aims to characterize urban rainfall using two satellite datasets. The analysis was carried out in the Sirba river catchment, Burkina Faso, using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and the Tropical Applications of Meteorology using SATellite and ground-based data (TAMSAT) datasets. Ten indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) of precipitation were calculated, and their statistical trends were evaluated from 1983 to 2023. The study introduces two key innovations: a comparative analysis of precipitation trends using two satellite datasets and applying this analysis to towns within a previously understudied 39,138 km² catchment area that is frequently flooded. Both datasets agree on the increase of (i) annual cumulative rainfall over all towns, (ii) five-day maximum rainfall over the town of Manni, (iii) rainfall due to very wet days in Gayéri, (iv) days of heavy rainfall in Bogandé, Manni and Yalgho, and (v) days of very heavy rainfall in Yalgho. These findings suggest the need for targeted pluvial flood prevention measures in towns with increasing trends in heavy rainfall. Full article

(This article belongs to the Special Issue Advances of Flood Risk Assessment and Management)

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18 pages, 1469 KiB

Open AccessSystematic Review

Leadership and Climate Change Mitigation: A Systematic Literature Review

by Corey McPherson and Amelia Clarke

Climate 2024, 12(12), 207; https://doi.org/10.3390/cli12120207 - 3 Dec 2024

Abstract

This systematic literature review (SLR) explores leadership and climate change mitigation in cities. In doing so, it investigates explicit meanings of leadership, enablers of leadership, and leadership similarities and differences across regions. The review utilized three databases on 8 March 2024—Scopus, ProQuest, and [...] Read more.

This systematic literature review (SLR) explores leadership and climate change mitigation in cities. In doing so, it investigates explicit meanings of leadership, enablers of leadership, and leadership similarities and differences across regions. The review utilized three databases on 8 March 2024—Scopus, ProQuest, and Web of Science—curating an initial 496 results, resulting in 30 studies in the final analysis, using a two-reviewer screening process to limit bias and ensure consistency of approach. Inclusion criteria included English-language peer-reviewed articles over a ten-year period. The timeframe used was limited to January 2014 to December 2023 (10 years) to focus on the lead up to and post-implementation of the Paris Agreement. Further, empirical and conceptual studies were included to provide readers of this review with a thorough understanding of leadership work completed since 2014. Exclusion criteria included any studies that focus on adaptation measures and forms of leadership where the focus is on the private business, state, or national level, including leadership and climate change mitigation outside the influence of the local government. The study highlights five distinct meanings of leadership using the Braun and Clarke method of thematic analysis. It found leadership themes related to people (e.g., mayors), policy (e.g., ambitious climate plans), ideas (e.g., new concepts), collective action (e.g., motivating others), and mobilizing power (e.g., through regulations). The enablers of leadership included polycentricity, social capital influences, co-creational and mayor leadership, climate governance, and multi-actor coordination. This review segments the studies based on the findings from the literature, which focus on three continents (North America, Europe, and Asia) with a distinct difference in the meaning and enablers of leadership based on region. The 30 articles shared similarities in content, such as strong mayoral influence, but also had some distinct differences, such as how leadership is enacted based on leveraging market mechanisms, policy, and horizontal and vertical coordination. Finally, research gaps were identified, such as the scant focus on leadership and climate change mitigation in the Global South, to enable future research. Limitations of this study include the utilization of three databases, a focus on only English-language peer-reviewed articles, and a strong climate change mitigation focus. Full article

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23 pages, 3843 KiB

Open AccessArticle

A Deeper Understanding of Climate Variability Improves Mitigation Efforts, Climate Services, Food Security, and Development Initiatives in Sub-Saharan Africa

by Shamseddin M. Ahmed, Hassan A. Dinnar, Adam E. Ahmed, Azharia A. Elbushra and Khalid G. Biro Turk

Climate 2024, 12(12), 206; https://doi.org/10.3390/cli12120206 - 2 Dec 2024

Abstract

This research utilized the bagging machine learning algorithm along with the Thornthwaite moisture index (TMI) to enhance the understanding of climate variability and change, with the objective of identifying the most efficient climate service pathways in Sub-Saharan Africa (SSA). Monthly datasets at a [...] Read more.

This research utilized the bagging machine learning algorithm along with the Thornthwaite moisture index (TMI) to enhance the understanding of climate variability and change, with the objective of identifying the most efficient climate service pathways in Sub-Saharan Africa (SSA). Monthly datasets at a 0.5° resolution (1960–2020) were collected and analyzed using R 4.2.2 software and spreadsheets. The results indicate significant changes in climatic conditions in Sudan, with aridity escalation at a rate of 0.37% per year. The bagging algorithm illustrated that actual water use was mainly influenced by rainfall and runoff management, showing an inverse relationship with increasing air temperatures. Consequently, sustainable strategies focusing on runoff and temperature control, such as rainwater harvesting, agroforestry and plant breeding were identified as the most effective climate services to mitigate and adapt to climate variability in SSA. The findings suggest that runoff management (e.g., rainwater harvesting) could potentially offset up to 22% of the adverse impacts of climate variability, while temperature control strategies (e.g., agroforestry) could account for the remaining 78%. Without these interventions, climate variability will continue to pose serious challenges to food security, livelihood generations, and regional stability. The research calls for further in-depth studies on the attributions of climate variability using finer datasets. Full article

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23 pages, 7393 KiB

Open AccessArticle

Methodology for Obtaining ET_o Data for Climate Change Studies: Quality Analysis and Calibration of the Hargreaves–Samani Equation

by Antónia Ferreira, Maria do Rosário Cameira and João Rolim

Climate 2024, 12(12), 205; https://doi.org/10.3390/cli12120205 - 2 Dec 2024

Abstract

Reference evapotranspiration (ET_o) is an important part of the water cycle, essential for climate studies, water resource management, and agricultural planning. However, accurate estimation of ET_o is challenging when meteorological data are insufficient or of low quality. Furthermore, in climate [...] Read more.

Reference evapotranspiration (ET_o) is an important part of the water cycle, essential for climate studies, water resource management, and agricultural planning. However, accurate estimation of ET_o is challenging when meteorological data are insufficient or of low quality. Furthermore, in climate change studies where large amounts of data need to be managed, it is important to minimize the complexity of the ET_o calculation. This study presents a comprehensive approach that integrates data quality analysis with two calibration methods—annual and cluster-based—to improve ET_o estimates based solely on temperature data from a set of weather stations (WS). First, the quality and integrity of meteorological data from several WS were analyzed to reduce uncertainty. Second, the Hargreaves–Samani equation (HS) is site calibrated using two approaches: (a) annual calibration, where the radiation coefficient (k_Rs) is adjusted using a data set covering the entire year; (b) cluster-based calibration, where independent radiation coefficients are adjusted for clusters of years and months. The methodology was evaluated for the Alentejo region in Southern Portugal, using data from 1996 to 2023. When using the original HS equation with a k_Rs = 0.17 °C^−0.5, ET_o was estimated with errors from 14.9% to 22.9% with bias ranging from −9.0% to 8.8%. The annual calibration resulted in k_Rs values between 0.157 and 0.165 °C^−0.5 with estimation errors between 13.3% and 20.6% and bias ranging from −1.5% to 1.0% across the different weather stations. Calibration based on clusters of months and years produced unclear results. Dry season months showed better results using cluster-based calibration, while wet season months performed poorly regardless of the calibration approach. The results highlight the importance of meteorological data quality and site-specific calibration for refining temperature-based ET_o estimation methods, and for the region studied, the gains do not justify the increased complexity of the cluster-based approach. Full article

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13 pages, 408 KiB

Open AccessArticle

It Is Normal: The Probability Distribution of Temperature Extremes

by Nir Y. Krakauer

Climate 2024, 12(12), 204; https://doi.org/10.3390/cli12120204 - 2 Dec 2024

Abstract

The probability of heat extremes is often estimated using the non-stationary generalized extreme value distribution (GEVD) applied to time series of annual maximum temperature. Here, this practice was assessed using a global sample of temperature time series, from reanalysis (both at the grid [...] Read more.

The probability of heat extremes is often estimated using the non-stationary generalized extreme value distribution (GEVD) applied to time series of annual maximum temperature. Here, this practice was assessed using a global sample of temperature time series, from reanalysis (both at the grid point and the region scale) as well as station observations. This assessment used forecast negative log-likelihood as the main performance measure, which is particularly sensitive to the most extreme heat waves. It was found that the computationally simpler normal distribution outperforms the GEVD in providing probabilistic year-ahead forecasts of temperature extremes. Given these findings, it is suggested to consider alternatives to the GEVD for assessing the risk of extreme heat. Full article

(This article belongs to the Special Issue Extreme Weather Detection, Attribution and Adaptation Design)

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