Climate

21 pages, 7053 KB

Open AccessArticle

Seasonal Regime Shifts and Warming Trends in the Universal Thermal Climate Index over the Italian and Iberian Peninsulas (1940–2024)

by Gabriel I. Cotlier and Juan Carlos Jimenez

Climate 2025, 13(9), 184; https://doi.org/10.3390/cli13090184 - 6 Sep 2025

Abstract

This study investigates long-term changes in thermal comfort across the Italian and Iberian Peninsulas from 1940 to 2024, using the Universal Thermal Climate Index (UTCI) derived from ERA5-HEAT reanalysis. We apply a dual analytical framework combining structural break detection to identify regime shifts [...] Read more.

This study investigates long-term changes in thermal comfort across the Italian and Iberian Peninsulas from 1940 to 2024, using the Universal Thermal Climate Index (UTCI) derived from ERA5-HEAT reanalysis. We apply a dual analytical framework combining structural break detection to identify regime shifts and Sen’s slope estimation with confidence intervals to quantify monotonic trends. Results reveal pronounced seasonal asymmetries. Summer exhibits abrupt regime shifts in both regions: in 1980 for Italy (slope shifting from −0.039 °C/year before 1980 to +0.06 °C/year after) and 1978 for Iberia (from −0.054 °C/year to +0.050 °C/year). Winter, by contrast, shows no structural breaks but a persistent, spatially uniform warming trend of ~0.030–0.033 °C/year across the 1940–2024 period, consistent with a gradual erosion of cold stress. Transitional seasons display more nuanced responses. Spring reveals detectable breakpoints in 1987 for Italy (shifting from −0.028 °C/year to +0.027 °C/year) and 1986 for Iberia (from −0.047 °C/year to +0.024 °C/year), indicating the early acceleration of warming. Autumn shows a breakpoint in 1970 for Italy, with trends intensifying from +0.011 °C/year before to +0.052 °C/year after, while Iberia exhibits no clear breakpoint but a consistent positive slope. These findings highlight spring as an early-warning season, where warming acceleration first emerges, and autumn as a consolidating phase that extends summer-like heat into later months. Overall, the results demonstrate that Mediterranean thermal regimes evolve through both abrupt and gradual processes, with summer defined by non-linear regime shifts, winter by steady accumulation of warming, and spring and autumn by transitional dynamics that bridge these extremes. The methodological integration of breakpoint detection with Sen’s slope estimation provides a transferable framework for detecting climate regime transitions in other vulnerable regions under accelerated global warming. Full article

(This article belongs to the Special Issue The Importance of Long Climate Records (Second Edition))

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20 pages, 6755 KB

Open AccessArticle

Future Meteorological Impact on Air Quality in the Po Valley

by Loris Colombo, Alessandro Marongiu, Giulia Malvestiti and Guido Giuseppe Lanzani

Climate 2025, 13(9), 183; https://doi.org/10.3390/cli13090183 - 5 Sep 2025

Abstract

Air quality in the Po Valley (Northern Italy), one of Europe’s most polluted regions, remains a major concern due to its unfavorable orographic setting and intense anthropogenic emissions. Climate change may further hinder progress by modifying meteorological conditions that regulate pollutant dispersion and [...] Read more.

Air quality in the Po Valley (Northern Italy), one of Europe’s most polluted regions, remains a major concern due to its unfavorable orographic setting and intense anthropogenic emissions. Climate change may further hinder progress by modifying meteorological conditions that regulate pollutant dispersion and chemistry. This study applies a modeling framework combining regional climate simulations and chemical transport models to assess the climate penalty, i.e., the adverse impact of climate-driven meteorology on air quality independent of emissions. Three scenarios were analyzed: Baseline Reference Scenario (SRB) (2011–2015), Near-Future Medium Scenario (NF) (2028–2032), and Mid-Future Medium Scenario (2048–2052), with emissions held constant. A mitigation scenario (SC_MF_2050) under the Current Legislation was also tested to accomplish the new EU Ambient Air Quality Directive. Results show that PM₁₀ and NO₂ increase under future climates, mainly due to reduced wind speed and precipitation, enhancing pollutant accumulation. Multivariate analyses confirm the strong association between stagnant conditions and higher concentrations. Even with projected emission reductions, compliance with stricter EU targets may not be achieved everywhere. Climate penalty zones, especially in lowland and transport corridors, underscore the need to integrate climate resilience into air quality planning and adopt adaptive strategies for long-term effectiveness. Full article

(This article belongs to the Special Issue Meteorological Forecasting and Modeling in Climatology)

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21 pages, 3538 KB

Open AccessArticle

Reconstruction of Water Storage Variability in the Aral Sea Region

by Nikita Murzintcev, Sahibjamal Nietullaeva, Timur Berdimbetov, Buddhi Pushpawela, Asiya Tureniyazova, Sherly Shelton, Bakbergen Aytmuratov, Khusen Gafforov, Kanat Parakhatov, Alimjan Erdashov, Abdul-Aziz Makhamatdinov and Timur Allamuratov

Climate 2025, 13(9), 182; https://doi.org/10.3390/cli13090182 - 29 Aug 2025

Abstract

The Gravity Recovery and Climate Experiment (GRACE) mission, operational from 2002 to 2017, provided critical measurements of Earth’s gravity field anomalies which have been extensively used to study groundwater and terrestrial water storage (TWS) dynamics. In this research, we utilize GRACE data to [...] Read more.

The Gravity Recovery and Climate Experiment (GRACE) mission, operational from 2002 to 2017, provided critical measurements of Earth’s gravity field anomalies which have been extensively used to study groundwater and terrestrial water storage (TWS) dynamics. In this research, we utilize GRACE data to identify, model, and analyze potential climate parameters contributing to the reconstruction of TWS variability in the Aral Sea Basin region (ASB). We assess the impact of climate change and anthropogenic nature management on TWS change using a quantitative method. Our analysis reveals a significant decline in the TWS at a rate of 0.44 cm year⁻¹ during the 2005–2009 period, primarily attributed to the prevailing drought conditions in the region. Notably, the estimated impact of anthropogenic influence on TWS during the same period of −1.39 cm year⁻¹ is higher than the influence of climatic variables, indicating that anthropogenic activity was the dominant factor in water resource depletion. In contrast, we observed an increase in TWS at a rate of 0.82 cm year⁻¹ during the 2013–2017 period, which can be attributed to the implementation of more effective water resource management practices in the ASB. Full article

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30 pages, 68660 KB

Open AccessArticle

Optimizing WRF Configurations for Improved Precipitation Forecasting in West Africa: Sensitivity to Cumulus and PBL Schemes in a Senegal Case Study

by Abdou Aziz Coly, Emmanuel Dazangwende Poan, Youssouph Sane, Habib Senghor, Semou Diouf, Ousmane Ndiaye, Abdoulaye Deme and Dame Gueye

Climate 2025, 13(9), 181; https://doi.org/10.3390/cli13090181 - 29 Aug 2025

Abstract

Despite significant progress, precipitation forecasting in West Africa remains challenging due to the complexity of atmospheric processes and the region’s climatic variability. This study aims to identify optimal configurations of the WRF model to improve precipitation forecasting. To evaluate the sensitivity of the [...] Read more.

Despite significant progress, precipitation forecasting in West Africa remains challenging due to the complexity of atmospheric processes and the region’s climatic variability. This study aims to identify optimal configurations of the WRF model to improve precipitation forecasting. To evaluate the sensitivity of the model’s physical parameterizations, 15 configurations were tested by combining various cumulus parameterization schemes (CPSs) and planetary boundary layer (PBL) schemes. The analysis examines two contrasting rainfall events in Senegal: one characterized by widespread intense precipitation and another featuring localized moderate rainfall. Simulated rainfall, temperature, and humidity were validated against rain gauges, satellite products (ENACTS, ARC, CHIRPS, and IMERG), and ERA5 reanalysis data. The results show that the WRF configurations achieve correlation coefficients (r) ranging from 0.27 to 0.62 against ENACTS and from 0.15 to 0.41 against rain gauges. The sensitivity analysis reveals that PBL schemes primarily influence temperature and humidity, while CPSs significantly affect precipitation. For the heavy rainfall event, several configurations accurately captured the observed patterns, particularly those using Tiedtke or Grell–Devenyi CPSs coupled with the Mellor–Yamada–Janjic (MYJ) PBL. However, the model showed limited skill in simulating localized convection during the moderate rainfall event. These findings highlight the importance of selecting appropriate parameterizations to enhance WRF-based precipitation forecasting, especially for extreme weather events in West Africa. Full article

(This article belongs to the Special Issue Meteorological Forecasting and Modeling in Climatology)

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21 pages, 1050 KB

Open AccessReview

The Perceptions of Rural Australians Concerning the Health Impacts of Extreme Weather Events: A Scoping Review

by Emily Vohralik, Jonathan Mond, I. Nyoman Sutarsa, Sally Hall Dykgraaf, Breanna Humber and Sari Dewi

Climate 2025, 13(9), 180; https://doi.org/10.3390/cli13090180 - 28 Aug 2025

Abstract

Understanding rural communities’ perceptions of the health impacts of extreme weather is vital for strengthening community resilience and adaptation strategies. This paper aimed to collate existing evidence on the perceptions of rural Australians regarding the health impacts of extreme weather events. A scoping [...] Read more.

Understanding rural communities’ perceptions of the health impacts of extreme weather is vital for strengthening community resilience and adaptation strategies. This paper aimed to collate existing evidence on the perceptions of rural Australians regarding the health impacts of extreme weather events. A scoping review following PRISMA-ScR guidelines was conducted. Peer-reviewed empirical articles published up to 7 May 2025 were identified from Scopus, PubMed, and Web of Science. One author undertook two-step screening and data extraction, which was checked by another author, and data were analysed using a thematic approach. Of 242 non-duplicate articles screened, 34 were included, which discussed drought (n = 14), bushfire (n = 8), flood (n = 6), extreme heat (n = 4) or a combination of events (n = 2). Two main themes arose: (1) perceived severity, frequency and duration of extreme weather events; and (2) perceptions of health impacts. The second theme comprised six subthemes: mental health risks, social disconnectedness, disrupted connection to land, distress due to uncertainties, community resilience, and disproportionate effects on vulnerable groups. Evidence gaps included a lack of perspectives separated by gender and age and a shortage of voices of socio-economically disadvantaged groups. Future research should investigate how to understand rural communities’ resilience to develop targeted adaptation and mitigation strategies. 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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20 pages, 4828 KB

Open AccessArticle

Barley, Canola and Spring Wheat Yield Throughout the Canadian Prairies Under the Effect of Climate Change

by Mohammad Zare, David Sauchyn and Zahra Noorisameleh

Climate 2025, 13(9), 179; https://doi.org/10.3390/cli13090179 - 28 Aug 2025

Abstract

Climate change is expected to have significant effects on crop yield in the Canadian Prairies. The objective of this study was to investigate these possible effects on spring wheat, barley and canola production using the Decision Support System for Agrotechnology Transfer (DSSAT) modelling [...] Read more.

Climate change is expected to have significant effects on crop yield in the Canadian Prairies. The objective of this study was to investigate these possible effects on spring wheat, barley and canola production using the Decision Support System for Agrotechnology Transfer (DSSAT) modelling platform. We applied 21 climate change scenarios from high-resolution (0.22°) regional simulations to three modules, DSSAT-CERES-Wheat, DSSAT-CERES-Barley and CSM-CROPGRO-Canola, using a historical baseline period (1985–2014) and three future periods: near (2015–2040), middle (2041–2070), and far (2071–2100). These simulations are part of CMIP6 (Coupled Model Intercomparison Project Phase 6) and have been processed using statistical downscaling and bias correction by the NASA Earth Exchange 26 Global Daily Downscaled Projections project, referred to as NEX-GDDP-CMIP6. The calibration and validation results surpassed the thresholds for a high level of accuracy. Simulated yield changes indicate that climate change has a positive effect on spring wheat and barley yields with median model increases of 7% and 11.6% in the near future, and 5.5% and 9.2% in the middle future, respectively. However, in the far future, barley production shows a modest increase of 4.4%, while spring wheat yields decline significantly by 17%. Conversely, simulated canola yields demonstrate a substantial decrease over time, with reductions of 25.9%, 46.3%, and 62.8% from the near to the far future, respectively. Agroclimatic indices, such as Number of Frost-Free Days (NFFD), Heating Degree-Days (HDD), Length of Growing Season (GSL), Crop Heat Units (CHU), and Effective Growing Degree Days (EGDD), exhibit significant correlations with spring wheat. Conversely, precipitation indices, such as very wet days and annual 5- and 10-day maximum precipitation, have a stronger correlation with canola yield changes when compared with temperature indices. The results provide key guidance for policymakers to design adaptation strategies and sustain regional food security and economic resilience, particularly for canola production, which is at significant risk under projected climate change scenarios across the Canadian Prairies. Full article

(This article belongs to the Section Climate and Environment)

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42 pages, 1695 KB

Open AccessArticle

Optimizing Policies and Regulations for Zero Routine Gas Flaring and Net Zero

by Godwin O. Aigbe, Lindsay C. Stringer and Matthew Cotton

Climate 2025, 13(9), 178; https://doi.org/10.3390/cli13090178 - 28 Aug 2025

Abstract

Global policy actions to reduce the environmental and social impacts of natural gas flaring are primarily derived from voluntary arrangements. This paper evaluates stakeholder preferences amongst competing policies and regulatory options, optimizing environmental governance to eliminate routine gas flaring by 2030 and achieve [...] Read more.

Global policy actions to reduce the environmental and social impacts of natural gas flaring are primarily derived from voluntary arrangements. This paper evaluates stakeholder preferences amongst competing policies and regulatory options, optimizing environmental governance to eliminate routine gas flaring by 2030 and achieve net-zero greenhouse emissions by 2050, whilst addressing questions of justice and fair implementation. Using a mixed-methods social scientific approach, incorporating literature and document review, interviews, expert surveys, Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (G-TOPSIS), we derive two competing perspectives on gas flaring policy strategy, with differences revealed through the AHP ranking process of individual criteria. All identified criteria and sub-criteria were integral to achieving the flaring and emissions targets, with “policy and targets” and “enabling framework” being the most important individual criteria. The “background and the role of reductions in meeting environmental and economic objectives” and ‘’nonmonetary penalties” were the key emergent sub-criteria. G-TOPSIS showed that fully implementing gas flaring policies and regulatory framework criteria to limit warming to 1.5 °C is the most effective policy alternative. Globally coordinated, uniform, and reciprocal legally binding agreements between countries to supplement national initiatives are imperative for improving the effectiveness of country-specific gas flaring policy strategies. Full article

(This article belongs to the Topic Energy, Environment and Climate Policy Analysis)

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18 pages, 4915 KB

Open AccessArticle

Snowmelt Streamflow Trends over Colorado (U.S.A.) Mountain Watersheds

by Steven R. Fassnacht and Anna K. D. Pfohl

Climate 2025, 13(9), 177; https://doi.org/10.3390/cli13090177 - 28 Aug 2025

Abstract

Streamflow generated from snowmelt is important, and changing, in snow dominated regions of the world. We used a recently developed technique to estimate the start and end of snowmelt streamflow for 39 gauging stations across Colorado and determined the 40-year trends from 1981 [...] Read more.

Streamflow generated from snowmelt is important, and changing, in snow dominated regions of the world. We used a recently developed technique to estimate the start and end of snowmelt streamflow for 39 gauging stations across Colorado and determined the 40-year trends from 1981 to 2020. Most watersheds showed a trend towards an earlier start (34 watersheds) or end (29 watersheds) of snowmelt streamflow, but the mean of the start and end dates showed mixed trends (earlier in 12 watersheds and later in 20). We determined the correlation between these streamflow snowmelt trends and terrain parameters plus trends in canopy cover, winter precipitation, peak snow water equivalent, and melt-period temperature. There were some significant correlations, primarily for total annual streamflow and the timing and volume of the end of snowmelt streamflow contribution to winter precipitation (decreasing), minimum temperature (warming), and slope (negatively). Higher elevation watersheds tend to be steeper, less snow has been observed at higher elevations, and the snowpack is melting sooner. Snowmelt streamflow trends are partially explained by climate trends and watershed characteristics. Full article

(This article belongs to the Special Issue Impacts of Climate Change on Hydrological Processes)

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52 pages, 8373 KB

Open AccessArticle

Trends in Atmospheric Emissions in Central Asian Countries Since 1990 in the Context of Regional Development

by Saken Kozhagulov, Ainagul Adambekova, Jose Carlos Quadrado, Vitaliy Salnikov, Aina Rysmagambetova and Ainur Tanybayeva

Climate 2025, 13(9), 176; https://doi.org/10.3390/cli13090176 - 27 Aug 2025

Abstract

In Central Asian countries (CACs) atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change [...] Read more.

In Central Asian countries (CACs) atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

(This article belongs to the Section Climate and Environment)

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24 pages, 4982 KB

Open AccessArticle

Climate Change in the Porto Region (Northern Portugal): A 148 Years Study of Temperature and Precipitation Trends (1863–2010)

by Leonel J. R. Nunes

Climate 2025, 13(9), 175; https://doi.org/10.3390/cli13090175 - 27 Aug 2025

Abstract

This study presents a comprehensive analysis of climate evolution in the Porto region (Northern Portugal) using 148 years (1863–2010) of continuous meteorological data from the Serra do Pilar weather station (WMO station 08546). The research employs both traditional linear statistical methods and advanced [...] Read more.

This study presents a comprehensive analysis of climate evolution in the Porto region (Northern Portugal) using 148 years (1863–2010) of continuous meteorological data from the Serra do Pilar weather station (WMO station 08546). The research employs both traditional linear statistical methods and advanced non-linear analysis techniques, including polynomial trend fitting and multidecadal oscillation analysis, to accurately characterize long-term climate patterns. Results reveal that linear trend analysis is misleading for this dataset, as both temperature and precipitation follow parabolic (U-shaped) distributions with minima around 1910–1970. The early period (1863–1900) exhibited higher values than the recent period, contradicting linear trend interpretations. Advanced analysis shows that the mean temperature follows a parabolic pattern (R² = 0.353) with the minimum around 1935, while precipitation exhibits similar behavior (R² = 0.053) with the minimum around 1936. Multidecadal oscillations are detected with dominant periods of 46.7, 15.6, and 10.0 years for temperature, and 35.0, 17.5, and 4.5 years for precipitation. Maximum temperatures show complex oscillatory behavior with a severe drop around 1890. Seasonal analysis reveals distinct patterns across all seasons: winter (+0.065 °C/decade) and autumn (+0.059 °C/decade) show warming trends in maximum temperatures, while spring (−0.080 °C/decade) and summer (−0.079 °C/decade) demonstrate cooling trends in minimum temperatures, with no significant trends in spring (+0.012 °C/decade) and summer (+0.003 °C/decade) maximum temperatures or winter (−0.021 °C/decade) and autumn (−0.035 °C/decade) minimum temperatures. The study identifies a significant change point in mean temperature around 1980, which occurs approximately one decade earlier than the global warming acceleration typically observed in the 1990s, suggesting regional Atlantic influences may precede global patterns. Extreme event analysis indicates stable frequencies of hot days (averaging 3.6 days/year above 25.0 °C) and heavy precipitation events (averaging 1.2 days/year above 234.6 mm) throughout the study period. These findings demonstrate that the Porto region’s climate is characterized by natural multidecadal variability rather than monotonic trends, with the climate system showing oscillatory behavior typical of Atlantic-influenced coastal regions. The results contribute to understanding regional climate variability and provide essential baseline data for climate change adaptation strategies in Northern Portugal. The results align with broader patterns of natural climate variability in the Iberian Peninsula while highlighting the importance of non-linear analysis for comprehensive climate assessment. Full article

(This article belongs to the Special Issue The Importance of Long Climate Records (Second Edition))

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19 pages, 1824 KB

Open AccessArticle

How Climate Ambition and Technology Choices Shape Water Use in the Power Generation Sector

by Panagiotis Fragkos, Eleftheria Zisarou and Kristina Govorukha

Climate 2025, 13(9), 174; https://doi.org/10.3390/cli13090174 - 27 Aug 2025

Abstract

The power generation sector is a major contributor to global greenhouse gas (GHG) emissions and a significant consumer of freshwater, due to the extensive water use in cooling processes of thermoelectric power plants. While net-zero strategies increasingly focus on eliminating emissions to mitigate [...] Read more.

The power generation sector is a major contributor to global greenhouse gas (GHG) emissions and a significant consumer of freshwater, due to the extensive water use in cooling processes of thermoelectric power plants. While net-zero strategies increasingly focus on eliminating emissions to mitigate climate change, the critical role of water as a key sustainability resource remains underexplored and often underrepresented in mitigation scenarios, strategies, and policy frameworks. This study examines the impact of power sector decarbonization on global and regional electricity-related water demand under two climate ambition scenarios: continuation of current climate policies (CP) and a net-zero emission (NZ) scenario where countries implement their net-zero pledges by 2050 or later. Using the PROMETHEUS energy system model, we quantify how different climate ambitions could affect global and regional water demand, considering different levels of cooling technology evolution. Results show that water demand is not only driven by how much energy is produced but by the technology mix used to generate electricity. The findings highlight the significant co-benefits of power sector decarbonization for reducing water needs and ensuring freshwater resource sustainability, underscoring the importance of integrating water management into climate policy frameworks. This integrated perspective is critical for policymakers, energy system planners, and water resource managers aiming to balance ambitious climate goals with sustainable water use amid growing climate and resource challenges. Full article

(This article belongs to the Section Climate and Environment)

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Graphical abstract

26 pages, 4753 KB

Open AccessArticle

Long-Term Climate Trends in Southern Angola and Possible Implications in Agriculture

by Carlos D. N. Correia, André Fonseca, Malik Amraoui, Carlos A. Pereira and João A. Santos

Climate 2025, 13(9), 173; https://doi.org/10.3390/cli13090173 - 26 Aug 2025

Abstract

Climate change poses a significant challenge to agriculture in southern Angola, particularly for smallholder farming systems that are highly exposed and vulnerable, lacking the resources and capacity to respond effectively. This study analyses climate trends from 1950 to 2024 in Huíla, Namibe, and [...] Read more.

Climate change poses a significant challenge to agriculture in southern Angola, particularly for smallholder farming systems that are highly exposed and vulnerable, lacking the resources and capacity to respond effectively. This study analyses climate trends from 1950 to 2024 in Huíla, Namibe, and Cunene, focusing on eight variables: Tmax, Tmin, Tmean, PRCPTOT, R95p, R95pTOT, CDD, and CWD. Due to inconsistencies in local meteorological station data, ERA5-Land reanalysis was used. Trends such as rising Tmin in Namibe (+0.32 °C/decade), Tmean in Huíla (+0.16 °C/decade), and increased precipitation in Huíla (+29.3 mm/decade), along with fewer dry days in Namibe (–2.7 days/decade), were observed. Crop–climate relationships (2000–2023) were explored using a categorical contingency analysis. Maize showed its highest yield frequency (46%) during hot years; cassava and beans were more stable under cooler, drier conditions; millet yielded above average (31%) in dry years, confirming drought resilience; potatoes performed poorly in wet years (17% above-average yields). The contingency method provided insights where linear models were insufficient, helping to understand climate–yield interactions in data-limited environments. This study offers the first long-term climate–agriculture assessment for southern Angola, providing critical evidence for climate-informed agricultural strategies in regions with scarce and unreliable observational records. The findings emphasise the urgent need for adaptation policies focused on crop-specific climate vulnerabilities. They also demonstrate the value of combining reanalysis data and categorical analysis to overcome data gaps and guide sustainable agricultural planning. Full article

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

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32 pages, 4425 KB

Open AccessArticle

Drought Monitoring to Build Climate Resilience in Pacific Island Countries

by Samuel Marcus, Andrew B. Watkins and Yuriy Kuleshov

Climate 2025, 13(9), 172; https://doi.org/10.3390/cli13090172 - 26 Aug 2025

Abstract

Drought is a complex and impactful natural hazard, with sometimes catastrophic impacts on small or subsistence agriculture and water security. In Pacific Island countries, there lacks an agreed approach for monitoring agricultural drought hazard with satellite-derived remote sensing data. This study addresses this [...] Read more.

Drought is a complex and impactful natural hazard, with sometimes catastrophic impacts on small or subsistence agriculture and water security. In Pacific Island countries, there lacks an agreed approach for monitoring agricultural drought hazard with satellite-derived remote sensing data. This study addresses this gap through a framework for agricultural drought monitoring in the Pacific using freely available space-based observations. Applying World Meteorological Organization’s (WMO) recommendations and a set of objective selection criteria, three remotely sensed drought indicators were chosen and combined using fuzzy logic to form a composite drought hazard index: the Standardised Precipitation Index, Soil Water Index, and Normalised Difference Vegetation Index. Each indicator represents a subsequential flow-on effect of drought on agriculture. The index classes geographic areas as low, medium, high, or very high levels of drought hazard. To test the drought hazard index, two case studies for drought in the western Pacific, Papua New Guinea (PNG), and Vanuatu, are assessed for the 2015–2016 El Niño-related drought. Findings showed that at the height of the drought in October 2015, 58% of PNG and 72% of Vanuatu showed very high drought hazard, compared to 6% and 40%, respectively, at the beginning of the drought. The hazard levels calculated were consistent with conditions observed and events that were reported during the emergency drought period. Application of this framework to operational drought monitoring will promote adaptive capacity and improve resilience to future droughts for Pacific communities. Full article

(This article belongs to the Special Issue Global Warming and Extreme Drought)

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34 pages, 5085 KB

Open AccessArticle

Youth Perceptions of 1.5-Degree Lifestyle to Adapt to Climate Change: A Case Analysis of Japanese University Students

by Rong Huang and Rajib Shaw

Climate 2025, 13(9), 171; https://doi.org/10.3390/cli13090171 - 22 Aug 2025

Abstract

The 1.5-degree lifestyles aim to reduce household carbon footprints across six areas (food, housing, mobility, consumer goods, leisure, and services), as identified by IGES, relying on public efforts. This study seeks to understand Japanese university students’ perceptions of 1.5-degree lifestyles, their preferred actions [...] Read more.

The 1.5-degree lifestyles aim to reduce household carbon footprints across six areas (food, housing, mobility, consumer goods, leisure, and services), as identified by IGES, relying on public efforts. This study seeks to understand Japanese university students’ perceptions of 1.5-degree lifestyles, their preferred actions for implementation at the individual, family, and community levels, and the top three enablers and barriers they face. Using a questionnaire based on the KIDA (knowledge, interest, desire, action) framework, which aligns with IGES’s six sectors, data from 244 responses collected via snowball sampling were analyzed. Results reveal low awareness of 1.5-degree lifestyles among Japanese university students, along with a moderate desire to learn more. Gender differences were significant, with females showing higher awareness, desire, and action compared to males. Three common barriers identified include challenges with work–life balance, economic concerns, and gaps between knowledge and action. Recommendations emphasize increasing youth awareness and encouraging action on 1.5-degree lifestyles through early environmental education, youth-focused communication (such as social media), and securing strong political support to help address practical challenges. Full article

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16 pages, 744 KB

Open AccessStudy Protocol

Warning System for Extreme Weather Events, Awareness Technology for Healthcare, Equitable Delivery, and Resilience (WEATHER) Project: A Mixed Methods Research Study Protocol

by Mary Lynch, Fiona Harris, Michelle Ierna, Ozayr Mahomed, Fiona Henriquez-Mui, Michael Gebreslasie, David Ndzi, Serestina Viriri, Muhammad Zeeshan Shakir, Natalie Dickinson, Caroline Miller, Andrew Hursthouse, Nisha Nadesan-Reddy, Fikile Nkwanyana, Llinos Haf Spencer and Saloshni Naidoo

Climate 2025, 13(8), 170; https://doi.org/10.3390/cli13080170 - 21 Aug 2025

Abstract

This study aims to develop, implement, and evaluate an Early Warning System (EWS) to alert communities and government agencies in KwaZulu-Natal, South Africa, about extreme weather events (EWEs) and related disease outbreaks. The project focuses on eThekwini and Ugu municipalities, using a participatory, [...] Read more.

This study aims to develop, implement, and evaluate an Early Warning System (EWS) to alert communities and government agencies in KwaZulu-Natal, South Africa, about extreme weather events (EWEs) and related disease outbreaks. The project focuses on eThekwini and Ugu municipalities, using a participatory, co-creation approach with communities and health providers. A systematic review will be undertaken to understand the impact of climate change on disease outbreaks and design an EWS that integrates data from rural and urban healthcare and environmental contexts. It will assess disease burden at primary healthcare clinics, examine health needs and community experiences during EWEs, and evaluate health system resilience. The project will also evaluate the design, development, and performance of the EWS intervention, including its implementation costs. Ethical approval will be sought, and informed consent obtained from participants. Based on the findings, recommendations will be made to the Department of Health to enhance early warning systems and health system resilience in response to EWEs and disease outbreaks. Full article

(This article belongs to the Special Issue Climate Change Responses and Mitigation at Technical, Economic, and Social Interfaces)

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17 pages, 261 KB

Open AccessArticle

Climate Change and Health: Impacts Across Social Determinants in Kenyan Agrarian Communities

by Elizabeth M. Allen, Leso Munala, Andrew J. Frederick, Cristhy Quito, Artam Enayat and Anne S. W. Ngunjiri

Climate 2025, 13(8), 169; https://doi.org/10.3390/cli13080169 - 15 Aug 2025

Abstract

Climate change is a global crisis that disproportionately affects vulnerable agrarian communities, exacerbating food insecurity and health risks. This qualitative study explored the relationship between climate change and health in the following two rural sub-counties of Kilifi County, Kenya: Ganze and Magarini. In [...] Read more.

Climate change is a global crisis that disproportionately affects vulnerable agrarian communities, exacerbating food insecurity and health risks. This qualitative study explored the relationship between climate change and health in the following two rural sub-counties of Kilifi County, Kenya: Ganze and Magarini. In fall 2023, we conducted 16 focus group discussions with adolescent girls (14–17), young adults (18–30), and older adults (31+). Thematic analysis revealed that climate change adversely affects health through key social determinants, including economic instability, environmental degradation, limited healthcare access, food insecurity, and disrupted education. Participants reported increased food scarcity, disease outbreaks, and reduced access to medical care due to droughts and floods. Economic hardship contributed to harmful survival strategies, including transactional sex and school dropout among adolescent girls. Mental health concerns, such as stress, substance use, and suicidal ideation, were prevalent. These findings highlight the wide-ranging health impacts of climate change in agrarian settings and the urgent need for comprehensive, community-informed interventions. Priorities should include improving nutrition, reproductive and mental health services, infectious disease prevention, and healthcare access. Full article

(This article belongs to the Special Issue Climate Impact on Human Health)

21 pages, 971 KB

Open AccessArticle

Lightning Nowcasting Using Dual-Polarization Weather Radar and Machine Learning Approaches: Evaluation of Feature Engineering Strategies and Operational Integration

by Marcos Antonio Alves, Rosana Alves Molina, Bruno Alberto Soares Oliveira, Daniel Calvo, Marcos Cesar Andrade Araujo Filho, Douglas Batista da Silva Ferreira, Ana Paula Paes Santos, Ivan Saraiva, Osmar Pinto, Jr. and Eugenio Lopes Daher

Climate 2025, 13(8), 168; https://doi.org/10.3390/cli13080168 - 14 Aug 2025

Abstract

Lightning nowcasting is crucial for ensuring safety and operational continuity in weather-exposed industries such as mining. This study evaluates three machine learning (ML)-based approaches for predicting lightning using dual-polarimetric weather radar data collected in the eastern Amazon, Brazil. The strategies propose advances in [...] Read more.

Lightning nowcasting is crucial for ensuring safety and operational continuity in weather-exposed industries such as mining. This study evaluates three machine learning (ML)-based approaches for predicting lightning using dual-polarimetric weather radar data collected in the eastern Amazon, Brazil. The strategies propose advances in literature in three ways by involving (i) grouping radar variables by temperature layers, (ii) statistical summaries at key altitudes, and (iii) analyzing all the 18 levels of reflectivity data combined with Principal Component Analysis (PCA) dimensionality reduction and ensemble models. For each approach, models such as Random Forest, Support Vector Machines, and XGBoost were trained and tested using data from 2021–2022 with class balancing and feature engineering techniques. Among the approaches, the PCA-based ensemble achieved the best generalization (recall = 0.89, F1 = 0.77), while the layer-based method had the highest recall (0.97), and the altitude-based strategy offered a computationally efficient alternative with competitive results. These findings confirm the predictive value of radar-derived features and emphasize the role of feature representation in model performance. Additionally, the best model was integrated into the operational LEWAIS alert system, and four integration strategies were tested. The strategy that combined alerts from both ML and LEWAIS systems reduced the failure-to-warn rate to 0.0531 and increased the lead time to 10.18 min, making it ideal for safety-critical applications. Overall, the results show that ML models based solely on radar inputs can achieve robust lightning nowcasting, supporting both scientific advancement and industrial risk mitigation. Full article

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27 pages, 1684 KB

Open AccessArticle

Comparative Study of Machine Learning-Based Rainfall Prediction in Tropical and Temperate Climates

by Ogochukwu Ejike, David Ndzi and Muhammad Zeeshan Shakir

Climate 2025, 13(8), 167; https://doi.org/10.3390/cli13080167 - 7 Aug 2025

Abstract

Reliable rainfall prediction is essential for effective climate adaptation yet remains challenging due to complex atmospheric interactions that vary across regions. This study investigates next-day rainfall predictability in tropical and temperate climates using daily atmospheric data—including pressure, temperature, dew point, relative humidity, wind [...] Read more.

Reliable rainfall prediction is essential for effective climate adaptation yet remains challenging due to complex atmospheric interactions that vary across regions. This study investigates next-day rainfall predictability in tropical and temperate climates using daily atmospheric data—including pressure, temperature, dew point, relative humidity, wind speed, and wind direction—collected from topographically similar sites in Alor Setar (tropical) and Vercelli, Williams, and Ashburton (temperate) between 2012 and 2015. Logistic regression and random forest models were used to predict rainfall occurrence as a binary outcome. Key variables were identified using Wald’s statistics and p-values in the logistic regression models, while the random forest models relied on mean decrease accuracy for ranking variable importance. The results reveal that rainfall in temperate climates is significantly more predictable than in tropical regions, with the Williams model demonstrating the highest accuracy. Atmospheric pressure consistently emerged as the dominant predictor in temperate regions but was not significant in the tropical model, reflecting the greater atmospheric variability and complexity in tropical rainfall mechanisms. Crucially, the study highlights that as global warming continues to alter temperate climate patterns—bringing increased variability and more convective rainfall—these regions may experience the same predictive uncertainties currently observed in tropical climates. These findings underscore the urgency of developing robust, climate-specific rainfall prediction models that account for changing atmospheric dynamics, with critical implications for weather forecasting, disaster preparedness, and climate resilience planning. Full article

(This article belongs to the Section Climate Dynamics and Modelling)

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14 pages, 5448 KB

Open AccessArticle

A Study of Climate-Sensitive Diseases in Climate-Stressed Areas of Bangladesh

by Ahammadul Kabir, Shahidul Alam, Nusrat Jahan Tarin, Shila Sarkar, Anthony Eshofonie, Mohammad Ferdous Rahman Sarker, Abul Kashem Shafiqur Rahman and Tahmina Shirin

Climate 2025, 13(8), 166; https://doi.org/10.3390/cli13080166 - 5 Aug 2025

Abstract

The National Adaptation Plan of Bangladesh identifies eleven climate-stressed zones, placing nearly 100 million people at high risk of climate-related hazards. Vulnerable groups such as the poor, floating populations, daily laborers, and slum dwellers are particularly affected. However, there is a lack of [...] Read more.

The National Adaptation Plan of Bangladesh identifies eleven climate-stressed zones, placing nearly 100 million people at high risk of climate-related hazards. Vulnerable groups such as the poor, floating populations, daily laborers, and slum dwellers are particularly affected. However, there is a lack of data on climate-sensitive diseases and related hospital visits in these areas. This study explored the prevalence of such diseases using the Delphi method through focus group discussions with 493 healthcare professionals from 153 hospitals in 156 upazilas across 21 districts and ten zones. Participants were selected by district Civil Surgeons. Key climate-sensitive diseases identified included malnutrition, diarrhea, pneumonia, respiratory infections, typhoid, skin diseases, hypertension, cholera, mental health disorders, hepatitis, heat stroke, and dengue. Seasonal surges in hospital visits were noted, influenced by factors like extreme heat, air pollution, floods, water contamination, poor sanitation, salinity, and disease vectors. Some diseases were zone-specific, while others were widespread. Regions with fewer hospital visits often had higher disease burdens, indicating under-reporting or lack of access. The findings highlight the need for area-specific adaptation strategies and updates to the Health National Adaptation Plan. Strengthening resilience through targeted investment and preventive measures is crucial to reducing health risks from climate change. Full article

(This article belongs to the Section Climate and Environment)

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