Climate

21 pages, 991 KiB

Open AccessArticle

Strengthening Agricultural Drought Resilience of Commercial Livestock Farmers in South Africa: An Assessment of Factors Influencing Decisions

by Yonas T. Bahta, Frikkie Maré and Ezael Moshugi

Climate 2025, 13(8), 154; https://doi.org/10.3390/cli13080154 - 22 Jul 2025

Abstract

In order to fulfil SDG 13—taking urgent action to combat climate change and its impact—SDG 2—ending hunger and poverty—and the African Union CAADP Strategy and Action Plan: 2026–2035, which’s goal is ending hunger and intensifying sustainable food production, agro-industrialisation, and trade, the resilience [...] Read more.

In order to fulfil SDG 13—taking urgent action to combat climate change and its impact—SDG 2—ending hunger and poverty—and the African Union CAADP Strategy and Action Plan: 2026–2035, which’s goal is ending hunger and intensifying sustainable food production, agro-industrialisation, and trade, the resilience of commercial livestock farmers to agricultural droughts needs to be enhanced. Agricultural drought has affected the economies of many sub-Saharan African countries, including South Africa, and still poses a challenge to commercial livestock farming. This study identifies and determines the factors affecting commercial livestock farmers’ level of resilience to agricultural drought. Primary data from 123 commercial livestock farmers was used in a principal component analysis to estimate the agricultural drought resilience index as an outcome variable, and the probit model was used to determine the factors influencing the resilience of commercial livestock farmers in the Northern Cape Province of South Africa. This study provides a valuable contribution towards resilience-building strategies that are critical for sustaining commercial livestock farming in arid regions by developing a formula for calculating the Agricultural Drought Resilience Index for commercial livestock farmers, significantly contributing to the pool of knowledge. The results showed that 67% of commercial livestock farming households were not resilient to agricultural drought, while 33% were resilient. Reliance on sustainable natural water resources, participation in social networks, education, relative support, increasing livestock numbers, and income stability influence the resilience of commercial livestock farmers. It underscores the importance of multidimensional policy interventions to enhance farmer drought resilience through education and livelihood diversification. Full article

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21 pages, 3532 KiB

Open AccessReview

Climate Hazards Management of Historic Urban Centers: The Case of Kaštela Bay in Croatia

by Jure Margeta

Climate 2025, 13(7), 153; https://doi.org/10.3390/cli13070153 - 19 Jul 2025

Abstract

The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban [...] Read more.

The preservation and protection of historic urban centers in climate-sensitive coastal areas contributes to the promotion of culture as a driver and enabler of achieving temporal and spatial sustainability, as it is recognized that urban heritage is an integral part of the urban landscape, culture, and economy. The aim of this study was to enhance the resilience and protection of cultural heritage and historic urban centers (HUCs) in the coastal area of Kaštela, Croatia, by providing recommendations and action guidelines in response to climate change impacts, including rising temperatures, sea levels, storms, droughts, and flooding. Preserving HUCs is essential to maintain their cultural values, original structures, and appearance. Many ancient coastal Roman HUCs lie partially or entirely below mean sea level, while low-lying medieval castles, urban areas, and modern developments are increasingly at risk. Based on vulnerability assessments, targeted mitigation and adaptation measures were proposed to address HUC vulnerability sources. The Historical Urban Landscape Approach tool was used to transition and manage HUCs, linking past, present, and future hazard contexts to enable rational, comprehensive, and sustainable solutions. The effective protection of HUCs requires a deeper understanding of the evolution of urban development, climate dynamics, and the natural environments, including both tangible and intangible urban heritage elements. The “hazard-specific” vulnerability assessment framework, which incorporates hazard-relevant indicators of sensitivity and adaptive capacity, was a practical tool for risk reduction. This method relies on analyzing the historical performance and physical characteristics of the system, without necessitating additional simulations of transformation processes. Full article

(This article belongs to the Special Issue Coastal Hazards under Climate Change)

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28 pages, 2140 KiB

Open AccessArticle

Application of the GEV Distribution in Flood Frequency Analysis in Romania: An In-Depth Analysis

by Cristian Gabriel Anghel and Dan Ianculescu

Climate 2025, 13(7), 152; https://doi.org/10.3390/cli13070152 - 18 Jul 2025

Abstract

This manuscript investigates the applicability and behavior of the Generalized Extreme Value (GEV) distribution in flood frequency analysis, comparing it with the Pearson III and Wakeby distributions. Traditional approaches often rely on a limited set of statistical distributions and estimation techniques, which may [...] Read more.

This manuscript investigates the applicability and behavior of the Generalized Extreme Value (GEV) distribution in flood frequency analysis, comparing it with the Pearson III and Wakeby distributions. Traditional approaches often rely on a limited set of statistical distributions and estimation techniques, which may not adequately capture the behavior of extreme events. The study focuses on four hydrometric stations in Romania, analyzing maximum discharges associated with rare and very rare events. The research employs seven parameter estimation methods: the method of ordinary moments (MOM), the maximum likelihood estimation (MLE), the L-moments, the LH-moments, the probability-weighted moments (PWMs), the least squares method (LSM), and the weighted least squares method (WLSM). Results indicate that the GEV distribution, particularly when using L-moments, consistently provides more reliable predictions for extreme events, reducing biases compared to MOM. Compared to the Wakeby distribution for an extreme event (T = 10,000 years), the GEV distribution produced smaller deviations than the Pearson III distribution, namely +7.7% (for the Danube River, Giurgiu station), +4.9% (for the Danube River, Drobeta station), and +35.3% (for the Ialomita River). In the case of the Siret River, the Pearson III distribution generated values closer to those obtained by the Wakeby distribution, being 36.7% lower than those produced by the GEV distribution. These results support the use of L-moments in national hydrological guidelines for critical infrastructure design and highlight the need for further investigation into non-stationary models and regionalization techniques. Full article

(This article belongs to the Special Issue Hydroclimatic Extremes: Modeling, Forecasting, and Assessment)

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21 pages, 6605 KiB

Open AccessArticle

Analysis of Spatial and Temporal Dynamics of Climate Aridization in Rostov Oblast in 1951–2054 Using ERA5 and CMIP6 Data and the De Martonne Index

by Denis Krivoguz

Climate 2025, 13(7), 151; https://doi.org/10.3390/cli13070151 - 17 Jul 2025

Abstract

Rostov Oblast is one of the key grain-producing regions in Russia, accounting for 6% of the total grain production. However, it faces an increasing risk of climate aridization, which requires an accurate scientific assessment to ensure the food security of the country. The [...] Read more.

Rostov Oblast is one of the key grain-producing regions in Russia, accounting for 6% of the total grain production. However, it faces an increasing risk of climate aridization, which requires an accurate scientific assessment to ensure the food security of the country. The present study analyzes the spatial and temporal dynamics of climate aridification in the Rostov region for the period 1951–2054. This analysis is based on ERA5 reanalysis data and CMIP6 forecast models (MPI-ESM1-2-HR, CanESM5, BCC-CSM2-MR). The analysis indicates that the annual mean temperature in the region has increased by 2–3 °C since the 1950s, reaching 12 °C in 2023. At the same time, precipitation shows significant interannual variability with no detectable long-term trend. Spatial analysis reveals a stable meridional temperature gradient and zonality of precipitation distribution. The southeastern parts of the region are characterized by the highest degree of aridification. Projection models indicate further warming (+1.5–3 °C by 2054) and increasing contrasts between western (wetter) and eastern (drier) areas. Projections derived from the CMIP6 models indicate an intensification of aridification, accompanied by a decrease in the De Martonne index of 15–25% by the year 2054. The area of territories with arid climates is expected to increase from 30% to 40%. The most vulnerable regions will be in the southeast part of Rostov Oblast, where the De Martonne index values are predicted to decrease to less than 10. The potential increase in temperature and evapotranspiration, coupled with spatial differentiation, could pose significant risks to the sustainability of the agro-industrial complex, particularly in the southeastern part of the region. Full article

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17 pages, 4652 KiB

Open AccessArticle

Challenge and Bias Correction for Surface Wind Speed Prediction: A Case Study in Shanxi Province, China

by Zengyuan Guo, Zhuozhuo Lyu and Yunyun Liu

Climate 2025, 13(7), 150; https://doi.org/10.3390/cli13070150 - 17 Jul 2025

Abstract

Accurate prediction of wind speed is critical for wind power generation and bias correction serves as an effective tool to enhance the precision of climate model forecasts. This study evaluates the effectiveness of three bias correction methods—Quantile Regression at the 50th percentile (QR50), [...] Read more.

Accurate prediction of wind speed is critical for wind power generation and bias correction serves as an effective tool to enhance the precision of climate model forecasts. This study evaluates the effectiveness of three bias correction methods—Quantile Regression at the 50th percentile (QR50), Linear Regression (LR), and Optimal Threat Score (OTS)—for improving wind speed predictions at a height of 70 m from the NCEP CFSv2 model in Shanxi Province, China. Using observational data from nine wind towers (2021–2024) and corresponding model hindcasts, we analyze systematic biases across lead times of 1–45 days. Results reveal persistent model errors: overestimation of low wind speeds (<6 m/s) and underestimation of high wind speeds (>6 m/s), with the Root Mean Square Error (RMSE) exceeding 1.5 m/s across all lead times. Among the correction methods, QR50 demonstrates the most robust performance, reducing the mean RMSE by 11% in October 2023 and 10% in February 2024. Correction efficacy improves significantly at longer lead times (>10 days) and under high RMSE conditions. These findings underscore the value of regression-based approaches in complex terrain while emphasizing the need for dynamic adjustments during extreme wind events. Full article

(This article belongs to the Special Issue Wind‑Speed Variability from Tropopause to Surface)

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17 pages, 2472 KiB

Open AccessArticle

Long-Term Rainfall–Runoff Relationships During Fallow Seasons in a Humid Region

by Rui Peng, Gary Feng, Ying Ouyang, Guihong Bi and John Brooks

Climate 2025, 13(7), 149; https://doi.org/10.3390/cli13070149 - 16 Jul 2025

Abstract

The hydrological processes of agricultural fields during the fallow season in east-central Mississippi remain poorly understood, due to the region’s unique rainfall patterns. This study utilized long-term rainfall records from 1924 to 2023 to evaluate runoff characteristics and the runoff response to various [...] Read more.

The hydrological processes of agricultural fields during the fallow season in east-central Mississippi remain poorly understood, due to the region’s unique rainfall patterns. This study utilized long-term rainfall records from 1924 to 2023 to evaluate runoff characteristics and the runoff response to various rainfall events during fallow seasons in Mississippi by applying the DRAINMOD model. The analysis revealed that the average rainfall during the fallow season was 760 mm over the past 100 years, accounting for 65% of the annual total. In dry, normal, and wet fallow seasons, the average rainfall was 528, 751, and 1010 mm, respectively, corresponding to runoff of 227, 388, and 602 mm. Runoff frequency increased with wetter weather conditions, rising from 16 events in dry seasons to 23 in normal seasons and 30 in wet seasons. Over the past century, runoff dynamics were predominantly regulated by high-intensity rainfall events during the fallow season. Very heavy rainfall events (mean frequency = 11 events) generated 215 mm of runoff and accounted for 53% of the total runoff, while extreme rainfall events (mean frequency = 2 events) contributed 135 mm of runoff, making up 34% of the total runoff. Water table depth played a critical role in shaping spring runoff dynamics. As the water table decreased from 46 mm in March to 80 mm in May, the soil pore space increased from 5 mm in March to 14 mm in May. This increased soil infiltration and water storage capacity, leading to a steady decline in runoff. The study found that the mean daily runoff frequency dropped from 13.5% in March to 7.6% in May, while monthly runoff decreased from 74 to 38 mm. Increased extreme rainfall (R95p) in April contributed over 45% of the total runoff and resulted in the highest daily mean runoff of 20 mm, compared to 18 mm in March and 16 mm in May. The results from this century-long historical weather data could be used to enhance field-scale water resource management, predict potential runoff risks, and optimize planting windows in the humid east-central Mississippi. Full article

(This article belongs to the Section Weather, Events and Impacts)

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21 pages, 2800 KiB

Open AccessArticle

Integrating Socioeconomic and Community-Based Strategies for Drought Resilience in West Pokot, Kenya

by Jean-Claude Baraka Munyaka, Seyid Abdellahi Ebnou Abdem, Olivier Gallay, Jérôme Chenal, Joseph Timu Lolemtum, Milton Bwibo Adier and Rida Azmi

Climate 2025, 13(7), 148; https://doi.org/10.3390/cli13070148 - 14 Jul 2025

Abstract

This paper examines how demographic characteristics, institutional structures, and livelihood strategies shape household resilience to climate variability and drought in West Pokot County, one of Kenya’s most climate-vulnerable arid and semi-arid lands (ASALs). Using a mixed-methods approach, it combines household survey data with [...] Read more.

This paper examines how demographic characteristics, institutional structures, and livelihood strategies shape household resilience to climate variability and drought in West Pokot County, one of Kenya’s most climate-vulnerable arid and semi-arid lands (ASALs). Using a mixed-methods approach, it combines household survey data with three statistical techniques: Multinomial Logistic Regression (MLR) assesses the influence of gender, age, and education on livestock ownership and livelihood choices; Multiple Correspondence Analysis (MCA) reveals patterns in institutional access and adaptive practices; and Stepwise Linear Regression (SLR) quantifies the relationship between resilience strategies and agricultural productivity. Findings show that demographic factors, particularly gender and education, along with access to veterinary services, drought-tolerant inputs, and community-based organizations, significantly shape resilience. However, trade-offs exist: strategies improving livestock productivity may reduce crop yields due to resource and labor competition. This study recommends targeted interventions, including gender-responsive extension services, integration of indigenous and scientific knowledge, improved infrastructure, and participatory governance. These measures are vital for strengthening resilience not only in West Pokot but also in other drought-prone ASAL regions across sub-Saharan Africa. Full article

(This article belongs to the Special Issue Climate Change Impacts at Various Geographical Scales (2nd Edition))

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22 pages, 2775 KiB

Open AccessArticle

Surface Broadband Radiation Data from a Bipolar Perspective: Assessing Climate Change Through Machine Learning

by Alice Cavaliere, Claudia Frangipani, Daniele Baracchi, Maurizio Busetto, Angelo Lupi, Mauro Mazzola, Simone Pulimeno, Vito Vitale and Dasara Shullani

Climate 2025, 13(7), 147; https://doi.org/10.3390/cli13070147 - 13 Jul 2025

Abstract

Clouds modulate the net radiative flux that interacts with both shortwave (SW) and longwave (LW) radiation, but the uncertainties regarding their effect in polar regions are especially high because ground observations are lacking and evaluation through satellites is made difficult by high surface [...] Read more.

Clouds modulate the net radiative flux that interacts with both shortwave (SW) and longwave (LW) radiation, but the uncertainties regarding their effect in polar regions are especially high because ground observations are lacking and evaluation through satellites is made difficult by high surface reflectance. In this work, sky conditions for six different polar stations, two in the Arctic (Ny-Ålesund and Utqiagvik [formerly Barrow]) and four in Antarctica (Neumayer, Syowa, South Pole, and Dome C) will be presented, considering the decade between 2010 and 2020. Measurements of broadband SW and LW radiation components (both downwelling and upwelling) are collected within the frame of the Baseline Surface Radiation Network (BSRN). Sky conditions—categorized as clear sky, cloudy, or overcast—were determined using cloud fraction estimates obtained through the RADFLUX method, which integrates shortwave (SW) and longwave (LW) radiative fluxes. RADFLUX was applied with daily fitting for all BSRN stations, producing two cloud fraction values: one derived from shortwave downward (SWD) measurements and the other from longwave downward (LWD) measurements. The variation in cloud fraction used to classify conditions from clear sky to overcast appeared consistent and reasonable when compared to seasonal changes in shortwave downward (SWD) and diffuse radiation (DIF), as well as longwave downward (LWD) and longwave upward (LWU) fluxes. These classifications served as labels for a machine learning-based classification task. Three algorithms were evaluated: Random Forest, K-Nearest Neighbors (KNN), and XGBoost. Input features include downward LW radiation, solar zenith angle, surface air temperature (

T_{a}

), relative humidity, and the ratio of water vapor pressure to

T_{a}

. Among these models, XGBoost achieved the highest balanced accuracy, with the best scores of 0.78 at Ny-Ålesund (Arctic) and 0.78 at Syowa (Antarctica). The evaluation employed a leave-one-year-out approach to ensure robust temporal validation. Finally, the results from cross-station models highlighted the need for deeper investigation, particularly through clustering stations with similar environmental and climatic characteristics to improve generalization and transferability across locations. Additionally, the use of feature normalization strategies proved effective in reducing inter-station variability and promoting more stable model performance across diverse settings. Full article

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

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30 pages, 2860 KiB

Open AccessArticle

Objectifying Inland Shipping Decision Frameworks: A Case Study on the Climate Resilience of Dutch Inland Waterway Transport Policies

by Frederik Vinke, Cornelis van Dorsser and Mark van Koningsveld

Climate 2025, 13(7), 146; https://doi.org/10.3390/cli13070146 - 12 Jul 2025

Abstract

Inland waterway transport (IWT) is a key function of river systems worldwide. It is vulnerable to climate change, specifically to discharge extremes, and competes for water with multiple other functions. A clear framework describing its interests to inform decision-making during regular conditions as [...] Read more.

Inland waterway transport (IWT) is a key function of river systems worldwide. It is vulnerable to climate change, specifically to discharge extremes, and competes for water with multiple other functions. A clear framework describing its interests to inform decision-making during regular conditions as well as during climate extremes is as yet unavailable in the literature. To address this gap we examine how inland shipping is taken into account in waterway policies in the Netherlands. We apply the frame of reference method to ‘objectify’ current inland waterway transport (IWT) policies, addressing the themes of waterway capacity, safety, service level, and sustainability. By ‘objectifying’ we mean turning the implicit into an explicit ‘object’ of study on the one hand and revealing underlying ‘objectives’ on the other. We show that policies for waterway capacity and service level are well developed, while waterway safety policies are more implicit, and waterway resilience lacks a quantitative decision framework. We furthermore show that current policies mainly focus on regular conditions, leaving it unclear what changes under extreme river discharge conditions. The results provide important insights into shipping-related decision challenges during climate extremes, highlighting aspects that should be developed further to improve the climate resilience of inland shipping. While some of these implications are specific to the Dutch case, the method applied here can also be used for other river systems that support multiple functions. Full article

(This article belongs to the Section Policy, Governance, and Social Equity)

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19 pages, 2465 KiB

Open AccessArticle

Long-Term Variations in Extreme Rainfall in Japan for Predicting the Future Trend of Rain Attenuation in Radio Communication Systems

by Yoshio Karasawa

Climate 2025, 13(7), 145; https://doi.org/10.3390/cli13070145 - 9 Jul 2025

Abstract

Rain attenuation of radio waves with frequencies above 10 GHz causes a serious problem in wireless communications. For wireless systems design, highly accurate methods for estimating the magnitude of attenuation have long been studied. ITU-R recommends a calculation method for rain attenuation using [...] Read more.

Rain attenuation of radio waves with frequencies above 10 GHz causes a serious problem in wireless communications. For wireless systems design, highly accurate methods for estimating the magnitude of attenuation have long been studied. ITU-R recommends a calculation method for rain attenuation using R_0.01, the 1 min rainfall rate that is exceeded for 0.01% of an average year. Accordingly, an R_0.01 database suitable for this calculation has been constructed. In recent years, global warming has emerged as an important climatological issue. If the predicted rise in temperatures associated with global warming induces a significant effect on rainfall characteristics, the existing R_0.01 database will need to be revised. However, there is currently no information for quantitatively evaluating the likely long-term change in R_0.01. In our previous study, the long-term trend in annual maximum values for 1-day, 1 h, and 10 min rainfall in Japan was estimated from a large amount of meteorological data and a 95% confidence interval approach was used to identify an increasing trend of more than 10% over approximately 100 years. In this paper, we investigate the long-term trend in greater detail using non-linear approximations for three types of rainfall and adopt the Akaike Information Criterion to determine the optimal order of the non-linear approximation. The future trend of R_0.01 is then estimated based on the long-term change in annual maximum 1 h rainfall, exploiting the strong correlation between long-term average annual maximum 1 h rainfall and R_0.01. Full article

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15 pages, 2489 KiB

Open AccessArticle

Interannual Variability in Barotropic Sea Level Differences Across the Korea/Tsushima Strait and Its Relationship to Upper-Ocean Current Variability in the Western North Pacific

by Jihwan Kim, Hanna Na and SeungYong Lee

Climate 2025, 13(7), 144; https://doi.org/10.3390/cli13070144 - 9 Jul 2025

Abstract

The barotropic sea level difference (SLD) across the Korea/Tsushima Strait (KTS) is considered an index of the volume transport into the East/Japan Sea. This study investigates the interannual variability of the barotropic SLD (the KTS inflow) from 1985 to 2017 and its relationship [...] Read more.

The barotropic sea level difference (SLD) across the Korea/Tsushima Strait (KTS) is considered an index of the volume transport into the East/Japan Sea. This study investigates the interannual variability of the barotropic SLD (the KTS inflow) from 1985 to 2017 and its relationship to upper-ocean (<300 m) current variability in the western North Pacific. An increase in the KTS inflow is associated with a weakening of the Kuroshio current through the Tokara Strait and upper-ocean cooling in the North Pacific Subtropical Gyre, characteristic of a La Niña-like state. Diagnostic analysis reveals that the KTS inflow variability is linked to at least two statistically distinct and concurrent modes of oceanic variability. The first mode is tied to the El Niño–Southern Oscillation through large-scale changes in the Kuroshio system. The second mode, which is linearly uncorrelated with the first, is associated with regional eddy kinetic energy variability in the western North Pacific. The identification of these parallel pathways suggests a complex regulatory system for the KTS inflow. This study provides a new framework for understanding the multi-faceted connection between the KTS and upstream oceanic processes, with implications for the predictability of the ocean environmental conditions in the East/Japan Sea. Full article

(This article belongs to the Special Issue The Dynamics and Impacts of Ocean-Atmosphere Coupling on Regional and Global Climate)

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13 pages, 392 KiB

Open AccessArticle

The Range of Projected Change in Vapour Pressure Deficit Through 2100: A Seasonal and Regional Analysis of the CMIP6 Ensemble

by Jiulong Xu, Mingyang Yao, Yunjie Chen, Liuyue Jiang, Binghong Xing and Hamish Clarke

Climate 2025, 13(7), 143; https://doi.org/10.3390/cli13070143 - 9 Jul 2025

Abstract

Vapour pressure deficit (VPD) is frequently used to assess the impact of climate change on wildfires, vegetation, and other phenomena dependent on atmospheric moisture. A common aim of projection studies is to sample the full range of changes projected by climate models. Although [...] Read more.

Vapour pressure deficit (VPD) is frequently used to assess the impact of climate change on wildfires, vegetation, and other phenomena dependent on atmospheric moisture. A common aim of projection studies is to sample the full range of changes projected by climate models. Although characterization of model spread in projected temperature and rainfall is common, similar analyses are lacking for VPD. Here, we analyze the range of change in projected VPD from a 15-member CMIP6 model ensemble using the SSP-370 scenario. Projected changes are calculated for 2015–2100 relative to the historical period 1850–2014, and the resulting changes are analyzed on a seasonal and regional basis, the latter using continents based on IPCC reference regions. We find substantial regional differences including higher increases in VPD in areas towards the equatorial regions, indicating increased vulnerability to climate change in these areas. Seasonal assessments reveal that regions in the Northern Hemisphere experience peak VPD changes in summer (JJA), correlating with higher temperatures and lower relative humidity, while Southern Hemisphere areas like South America see notable increases in all seasons. We find that the mean projected change in seasonal VPD ranges from 0.02–0.23 kPa in Europe, 0.04–0.19 kPa in Asia, 0.02–0.16 kPa in North America, 0.15–0.33 kPa in South America, 0.10–0.18 kPa in Oceania, and 0.21–0.31 kPa in Africa. Our analysis suggests that for most regions, no two models span the range of projected change in VPD for all seasons. The overall projected change space for VPD identified here can be used to interpret existing studies and support model selection for future climate change impact assessments that seek to span this range. Full article

(This article belongs to the Section Weather, Events and Impacts)

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18 pages, 15684 KiB

Open AccessArticle

The Calculation and Mapping of the Moisture Indices of the East Kazakhstan Region for the Preventive Assessment of the Climate–Hydrological Background

by Dmitry Chernykh, Kamilla Rakhymbek, Roman Biryukov, Andrey Bondarovich, Lilia Lubenets and Yerzhan Baiburin

Climate 2025, 13(7), 142; https://doi.org/10.3390/cli13070142 - 8 Jul 2025

Abstract

The assessment of the hydrological functions of landscapes and the landscape–hydrological background is an important instrument for minimizing damage from rivers and preventing water conflicts under conditions of data scarcity for hydrological modeling. To assess the climate–hydrological background of the East Kazakhstan region, [...] Read more.

The assessment of the hydrological functions of landscapes and the landscape–hydrological background is an important instrument for minimizing damage from rivers and preventing water conflicts under conditions of data scarcity for hydrological modeling. To assess the climate–hydrological background of the East Kazakhstan region, the Selyaninov Hydro-thermal Coefficient and the Vysotsky–Ivanov Moisture Coefficient were used. The East Kazakhstan region is a typical continental arid and semi-arid region. The presence of mountain ranges, such as the Altai, makes the climate and environment in the region highly varied. A dataset from 30 weather stations for the period 1961–2023 was used for calculations. Three interpolation methods and landscape extrapolation were used to construct maps of the coefficients. Over the observation period, the values of the moisture indices at the weather stations in the region fluctuated within a wide range. Both coefficients are in the range from extra arid to extra humid climates. Full article

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28 pages, 7776 KiB

Open AccessArticle

Climate Risk and Vulnerability Assessment in the Province of Almeria (Spain) Under Different Climate Change Scenarios

by Sara Barilari, Yaiza Villar-Jiménez, Giusy Fedele, Alfredo Reder and Iván Ramos-Diez

Climate 2025, 13(7), 141; https://doi.org/10.3390/cli13070141 - 4 Jul 2025

Abstract

Climate change represents a major global challenge, with semi-arid regions like the province of Almería being particularly vulnerable. Almería’s dependence on climate-sensitive sectors such as agriculture and tourism, coupled with the absence of perennial rivers, increases its exposure to extreme events including heatwaves, [...] Read more.

Climate change represents a major global challenge, with semi-arid regions like the province of Almería being particularly vulnerable. Almería’s dependence on climate-sensitive sectors such as agriculture and tourism, coupled with the absence of perennial rivers, increases its exposure to extreme events including heatwaves, droughts, and extreme precipitation events like storms. This study proposes a semi-quantitative methodology to assess climate risk across different sectors at the municipal level, combining indicators of hazard, exposure and vulnerability within the framework of the IPCC AR6. Exposure and vulnerability indicators were derived from regional, national and European datasets, while hazards were characterized using downscaled Essential Climate Variables. After data collection, the indicators were normalized using a percentile-based approach to ensure their comparison and replicability, especially in data-scarce contexts. The results reveal both sectoral and spatial patterns of risk under three different climate change scenarios, highlighting municipalities with a higher level of exposure, vulnerability and risk. Although the static nature of exposure and vulnerability indicators represents a limitation in future risk quantification, the findings remain valuable for identifying priority areas for targeted adaptation and mitigation strategies. The proposed semi-quantitative risk methodology based on indicators is of great interest and relevance for understanding differences at local scales, as well as for implementing adaptation and mitigation solutions adjusted to the real needs of each municipality. Full article

(This article belongs to the Special Issue Climate Change Impacts at Various Geographical Scales (2nd Edition))

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24 pages, 4645 KiB

Open AccessArticle

The Impact of Climate Change and Water Consumption on the Inflows of Hydroelectric Power Plants in the Central Region of Brazil

by Filipe Otávio Passos, Benedito Cláudio da Silva, José Wanderley Marangon de Lima, Marina de Almeida Barbosa, Pedro Henrique Gomes Machado and Rafael Machado Martins

Climate 2025, 13(7), 140; https://doi.org/10.3390/cli13070140 - 4 Jul 2025

Abstract

There is a consensus that climate change has affected society. The increase in temperature and reduction in precipitation for some regions of the world have had implications for the intensity and frequency of extreme events. This scenario is worrying for various sectors of [...] Read more.

There is a consensus that climate change has affected society. The increase in temperature and reduction in precipitation for some regions of the world have had implications for the intensity and frequency of extreme events. This scenario is worrying for various sectors of water use, such as hydroelectric power generation and agriculture. Reduced flows in river basins, coupled with increased water consumption, can significantly affect energy generation and food production. Within this context, this paper presents an analysis of climate change impacts in a large basin of Brazil between the Amazon and Cerrado biomes, considering the effects of water demands. Inflow projections were generated for seven power plant reservoirs in the Tocantins–Araguaia river basin, using projections from five climate models. The results indicate significant reductions in flows, with decreases of more than 50% in the average flow. For minimum flows, there are indications of reductions of close to 85%. The demand for water, although growing, represents a smaller part of the effects, but should not be disregarded, since it impacts the dry periods of the rivers and can generate conflicts with energy production. Full article

(This article belongs to the Section Climate and Economics)

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29 pages, 3813 KiB

Open AccessArticle

Addressing Climate Resilience in the African Region: Prioritizing Mental Health and Psychosocial Well-Being in Disaster Preparedness and Response Planning for Mainstream Communities and Migrants

by Belayneh Fentahun Shibesh and Nidhi Nagabhatla

Climate 2025, 13(7), 139; https://doi.org/10.3390/cli13070139 - 3 Jul 2025

Abstract

Climate change represents a complex and multifaceted challenge for health systems, particularly in the African region, where the research has predominantly focused on physical health impacts while overlooking critical mental health dimensions. Our central hypothesis is that integrating culturally adapted mental health and [...] Read more.

Climate change represents a complex and multifaceted challenge for health systems, particularly in the African region, where the research has predominantly focused on physical health impacts while overlooking critical mental health dimensions. Our central hypothesis is that integrating culturally adapted mental health and psychosocial support (MHPSS) into climate resilience frameworks and disaster response planning will significantly reduce psychological distress (e.g., anxiety, depression, and trauma) and enhance adaptive capacities among both mainstream and migrant communities in disaster-prone African regions. This rapid review methodology systematically explores the intricate relationships between climate change, mental health, and migration by examining the existing literature and identifying significant information gaps. The key findings underscore the urgent need for targeted research and strategic interventions that specifically address mental health vulnerabilities in the context of climate change. This review highlights how extreme weather events, environmental disruptions, and forced migration create profound psychological stressors that extend beyond immediate physical health concerns. This research emphasizes the importance of developing comprehensive adaptation strategies integrating mental health considerations into broader climate response frameworks. Recommendations emerging from this assessment call for immediate and focused attention on developing specialized research, policies, and interventions that recognize the unique mental health challenges posed by climate change in African contexts. We also note the current limitations in the existing national adaptation plans, which frequently overlook mental health dimensions, thereby underscoring the necessity of a more holistic and nuanced approach to understanding climate change’s psychological impacts. In this exploratory study, we intended to provide a crucial preliminary assessment of the complex intersections between climate change, mental health, and migration, offering valuable insights for policymakers, researchers, and healthcare professionals seeking to develop more comprehensive and responsive strategies in an increasingly challenging environmental landscape. Full article

(This article belongs to the Special Issue Coping with Flooding and Drought)

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18 pages, 2010 KiB

Open AccessArticle

Frequency Analysis and Trend of Maximum Wind Speed for Different Return Periods in a Cold Diverse Topographical Region of Iran

by Leila Alimohamadian and Raoof Mostafazadeh

Climate 2025, 13(7), 138; https://doi.org/10.3390/cli13070138 - 2 Jul 2025

Abstract

This study examines the trends and statistical characteristics of daily maximum wind speed across various synoptic stations in Ardabil Province, Iran, with diverse topography. Using daily wind speed data from multiple synoptic stations, the research focuses on three primary objectives: assessing changes in [...] Read more.

This study examines the trends and statistical characteristics of daily maximum wind speed across various synoptic stations in Ardabil Province, Iran, with diverse topography. Using daily wind speed data from multiple synoptic stations, the research focuses on three primary objectives: assessing changes in daily maximum wind speed, fitting various statistical distributions to the data, and estimating wind speed values for different return periods. In this research, the temporal changes were evaluated while analyzing the frequency of the data, and then the maximum wind speed values were calculated and analyzed for different return periods by fitting frequency distributions. The analysis reveals notable variability in maximum wind speeds across stations. The trend analysis, conducted using the nonparametric Mann–Kendall method, reveals significant positive trends in maximum wind speed at Meshgin-Shahr and Sareyn (p < 0.05). Meanwhile, data from Khalkhal station displays a significant decreasing trend, while other stations, like Ardabil and Parsabad, show no meaningful trends. According to the statistical distributions analysis, the Fisher–Tippett T2 mirrored distribution demonstrates the best fit for Ardabil, with an absolute difference of 2.52%, while the Laplace distribution yields the lowest discrepancies for Bilesavar (3.50%) and Ardabil Airport (3.83%). This ranking indicates that, despite similar first-ranked distributions in some stations, secondary models show variability, suggesting localized influences on wind speed that modify distributional fit. As a conclusion, the Laplace (std) distribution stands out as the best-fit model for several stations, showing relative consistency across several stations. These findings demonstrate the necessity of site-specific statistical modeling to accurately represent wind speed patterns across the diverse landscapes of Ardabil Province. Based on the results, comparing the wind characteristics in the study area with those of other regions in Iran, as well as analyzing the reported trends, can be useful in determining the impact of the region’s climatic conditions and topography on wind patterns. This research offers key insights into wind speed variability and trends in Ardabil, crucial for climate adaptation and risk management of extreme wind events. Full article

(This article belongs to the Special Issue Wind‑Speed Variability from Tropopause to Surface)

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23 pages, 3151 KiB

Open AccessArticle

Should We Use Quantile-Mapping-Based Methods in a Climate Change Context? A “Perfect Model” Experiment

by Mathieu Vrac, Harilaos Loukos, Thomas Noël and Dimitri Defrance

Climate 2025, 13(7), 137; https://doi.org/10.3390/cli13070137 - 1 Jul 2025

Abstract

This study assesses the use of Quantile-Mapping methods for bias correction and downscaling in climate change studies. A “Perfect Model Experiment” is conducted using high-resolution climate simulations as pseudo-references and coarser versions as biased data. The focus is on European daily temperature and [...] Read more.

This study assesses the use of Quantile-Mapping methods for bias correction and downscaling in climate change studies. A “Perfect Model Experiment” is conducted using high-resolution climate simulations as pseudo-references and coarser versions as biased data. The focus is on European daily temperature and precipitation under the RCP 8.5 scenario. Six methods are tested: an empirical Quantile-Mapping approach, the “Cumulative Distribution Function—transform” (CDF-t) method, and four CDF-t variants with different parameters. Their performance is evaluated based on univariate and multivariate properties over the calibration period (1981–2010) and a future period (2071–2100). The results show that while Quantile Mapping and CDF-t perform similarly during calibration, significant differences arise in future projections. Quantile Mapping exhibits biases in the means, standard deviations, and extremes, failing to capture the climate change signal. CDF-t and its variants show smaller biases, with one variant proving particularly robust. The choice of discretization parameter in CDF-t is crucial, as the low number of bins increases the biases. This study concludes that Quantile Mapping is not appropriate for adjustments in a climate change context, whereas CDF-t, especially a variant that stabilizes extremes, offers a more reliable alternative. Full article

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17 pages, 897 KiB

Open AccessArticle

The Gender–Climate–Security Nexus: A Case Study of Plateau State

by T. Oluwaseyi Ishola and Isaac Luginaah

Climate 2025, 13(7), 136; https://doi.org/10.3390/cli13070136 - 30 Jun 2025

Abstract

This study investigates the gendered nexus between climate change, food insecurity, and conflict in Plateau State, Nigeria. This region in north-central Nigeria is marked by recurring farmer–herder clashes and climate-induced environmental degradation. Drawing on qualitative methods, including interviews, gender-disaggregated focus groups, and key [...] Read more.

This study investigates the gendered nexus between climate change, food insecurity, and conflict in Plateau State, Nigeria. This region in north-central Nigeria is marked by recurring farmer–herder clashes and climate-induced environmental degradation. Drawing on qualitative methods, including interviews, gender-disaggregated focus groups, and key informant discussions, the research explores how climate variability and violent conflict interact to exacerbate household food insecurity. The methodology allows the capture of nuanced perspectives and lived experiences, particularly emphasizing the differentiated impacts on women and men. The findings reveal that irregular rainfall patterns, declining agricultural yields, and escalating violence have disrupted traditional farming systems and undermined rural livelihoods. The study also shows that women, though they are responsible for household food management, face disproportionate burdens due to restricted mobility, limited access to resources, and a heightened exposure to gender-based violence. Grounded in Conflict Theory, Frustration–Aggression Theory, and Feminist Political Ecology, the analysis shows how intersecting vulnerabilities, such as gender, age, and socioeconomic status, shape experiences of food insecurity and adaptation strategies. Women often find creative and local ways to cope with challenges, including seed preservation, rationing, and informal trade. However, systemic barriers continue to hinder sustainable progress. This study emphasized the need for integrating gender-sensitive interventions into policy frameworks, such as land tenure reforms, targeted agricultural support for women, and improved security measures, to effectively mitigate food insecurity and promote sustainable livelihoods, especially in conflict-affected regions. Full article

(This article belongs to the Topic Climate Change Impacts and Adaptation: Interdisciplinary Perspectives, 2nd Edition)

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