Climate

22 pages, 5652 KiB

Open AccessArticle

Spatiotemporal Analysis of Urban Heat Islands in Kisangani City Using MODIS Imagery: Exploring Interactions with Urban–Rural Gradient, Building Volume Density, and Vegetation Effects

by Julien Bwazani Balandi, Trésor Mbavumoja Selemani, Jean-Pierre Pitchou Meniko To Hulu, Kouagou Raoul Sambieni, Yannick Useni Sikuzani, Jean-François Bastin, Prisca Tshomba Wola, Jacques Elangilangi Molo, Joël Mobunda Tiko, Bill Mahougnon Agassounon and Jan Bogaert

Climate 2025, 13(5), 89; https://doi.org/10.3390/cli13050089 (registering DOI) - 29 Apr 2025

Abstract

The urban heat island (UHI) effect has emerged in the literature as a major challenge to urban well-being, primarily driven by increasing urbanization. To address this challenge, this study investigates the spatiotemporal pattern of the UHI in the fast-growing city of Kisangani and [...] Read more.

The urban heat island (UHI) effect has emerged in the literature as a major challenge to urban well-being, primarily driven by increasing urbanization. To address this challenge, this study investigates the spatiotemporal pattern of the UHI in the fast-growing city of Kisangani and within its urban–rural gradient from 2000 to 2024 using land surface temperature (LST) data from the MODIS 11A2 V6.1 product. Inferential and descriptive statistics were applied to examine the patterns of UHI and the relationships between the LST, building volume density (BVD), and vegetation density expressed by the Normalized Difference Vegetation Index (NDVI). The results showed that the spatial extent of the moderate UHI gradually increased from 16 km² to 38 km², while the high UHI increased from 9 km² to 19 km². Furthermore, although high UHI values (0.2 < UHI ≤ 0.3) are observed in urban areas and significant differences in UHI variations are detected across urban, peri-urban, and rural zones, the results indicate that the mean UHI in Kisangani’s urban areas remains below 0.2. Therefore, based on average UHI variations, Kisangani’s urban zones exhibit moderate disparities in LST compared to rural areas. Moreover, the LST variations significantly correlate with the building volume and vegetation densities. However, the influence of vegetation density as a predictor of LST gradually decreases while the influence of building volume density increases over time, suggesting the need to implement a synergistic development pathway to manage the interactions between urbanization, landscape change, and ecosystem service provision. This integrated approach may represent a crucial solution for mitigating the UHI effect in regions categorized as high-temperature zones. Full article

(This article belongs to the Special Issue Climate Change—Achieving the UN Sustainable Development Goals in Urban Contexts)

36 pages, 375 KiB

Open AccessReview

Barriers, Opportunities, and Best Practices for Corporate Climate Transition Plans: A Literature Review

by Daniel Kouloukoui, Nathalie de Marcellis-Warin and Thierry Warin

Climate 2025, 13(5), 88; https://doi.org/10.3390/cli13050088 (registering DOI) - 29 Apr 2025

Abstract

Corporate climate transition is one of the greatest challenges and opportunities of the 21st century, shaping the future of business sustainability and aligning economic growth with global environmental goals. This article aims to identify the main barriers, opportunities, and best practices associated with [...] Read more.

Corporate climate transition is one of the greatest challenges and opportunities of the 21st century, shaping the future of business sustainability and aligning economic growth with global environmental goals. This article aims to identify the main barriers, opportunities, and best practices associated with the implementation of corporate climate transition plans. Based on a review of studies from leading databases—Scopus, Web of Science, ScienceDirect, and Google Scholar—the research categorizes barriers into economic, financial, political, regulatory, cultural, organizational, and technological dimensions. Opportunities are grouped into areas like sustainable finance, technological innovation, and resilience building. Best practices are organized into clusters, notably governance, energy efficiency, social equity, and just transition frameworks. In addition to advancing academic understanding, this study offers practical implications for key stakeholders. Financial institutions can use these findings to develop climate-aligned financial products tailored to corporate realities. Policymakers can improve regulatory frameworks to foster sustainable business practices and remove legislative barriers. Companies are empowered to refine their climate strategies, address operational constraints, and explore new sustainability-driven opportunities. By integrating scientific insights with real-world applicability, this review contributes to a more holistic understanding of corporate climate transition, bridging academic research with actionable pathways for businesses, financial actors, and public decision-makers. Full article

(This article belongs to the Section Climate Adaptation and Mitigation)

24 pages, 4408 KiB

Open AccessArticle

Impacts of Urban Morphology on Micrometeorological Parameters and Cyclonic Phenomena in Northern Colombian Caribbean

by Raúl Pérez-Arévalo, Juan E. Jiménez-Caldera, José Luis Serrano-Montes, Jesús Rodrigo-Comino, Juan Carlos Ortiz Royero and Andrés Caballero-Calvo

Climate 2025, 13(5), 87; https://doi.org/10.3390/cli13050087 (registering DOI) - 29 Apr 2025

Abstract

The rapid urbanization processes across the world can be considered one of the most influential factors in climate change, particularly in metropolitan areas. In South America, the growing population and recurrent non-sustainable or controlled urban land management plans are even increasing the negative [...] Read more.

The rapid urbanization processes across the world can be considered one of the most influential factors in climate change, particularly in metropolitan areas. In South America, the growing population and recurrent non-sustainable or controlled urban land management plans are even increasing the negative consequences of urban heat islands. As a representative case study, Soledad in northern Colombia is an area with recurrent strong wind events, which have caused significant damage to property and human lives, conditioning urban plans. This research aimed to assess the micrometeorological conditions in areas of Soledad, where cyclonic events are highly frequent, to gather essential data on urban planning to understand microclimate changes. We conducted in situ measurements of air temperature, surface temperature, wind speed, relative humidity, and atmospheric pressure across different Local Climate Zones (LCZs). Data were analyzed to assess the impact of urban form, vegetation, and sky openness on microclimatic variations. Our results demonstrated that urban morphology, vegetation cover, and sky openness significantly influenced local microclimates, with lower Sky View Factor (SVF) and higher Leaf Area Index (LAI) values contributing to reduced temperatures and improved airflow. Areas with denser urban canyons exhibited higher temperatures and lower wind speeds, emphasizing the need for strategic urban planning to mitigate heat stress and enhance ventilation. Full article

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15 pages, 3465 KiB

Open AccessArticle

Wind and Humidity Nexus over Uganda in the Context of Past and Future Climate Volatility

by Ronald Ssembajwe, Amina Twah, Rhoda Nakabugo, Sharif Katende, Catherine Mulinde, Saul D. Ddumba, Yazidhi Bamutaze and Mihai Voda

Climate 2025, 13(5), 86; https://doi.org/10.3390/cli13050086 (registering DOI) - 29 Apr 2025

Abstract

Wind and humidity are two very vital climate variables that have received little attention by researchers regarding Uganda. This study sought to close this knowledge gap by exposing the dynamics and relationship of windspeed and humidity in Uganda from 1980 to 2023 as [...] Read more.

Wind and humidity are two very vital climate variables that have received little attention by researchers regarding Uganda. This study sought to close this knowledge gap by exposing the dynamics and relationship of windspeed and humidity in Uganda from 1980 to 2023 as well as predicting the future trends from 2025 to 2040. Using high-resolution gridded windspeed and relative humidity (RH) data for the past and seven downscaled and bias-adjusted global climate models within the coupled model intercomparison project phase 6 framework under two shared socioeconomic pathways (SSPs), SPP245 and SSP585, we employed variability, trend, and correlational analyses to expose the wind–humidity nexus at a monthly scale. The results showed a domination of winds of the calm to gentle breeze category across the country, with a maximum magnitude of 6 knots centered over eastern Lake Victoria and eastern Uganda over the historical period. RH was characterized by high to very high magnitudes, except the northern tips of the country, where RH was low for the historical period. Seasonally, both windspeed and RH demonstrated modest variations, with June–July–August (JJA) and September–October–November (SON) having the highest magnitudes, respectively. Similarly, both variables are forecasted to have significant distribution and magnitude changes. For example, windspeeds will be dominated by decreasing trends, while RH will be dominated by increasing trends. Finally, the correlation analysis revealed a strong negative correlation between windspeeds and RH for both the past and future periods, except for the March–April–May (MAM) and September–October–November (SON) seasons, where positive correlations were observed. These findings have practical applications in agriculture, hydrology, thermal comfort, disaster management, and forecasting, especially in the northern, eastern, and Lake Victoria basin regions. The study recommends further finer-scale research at various atmospheric levels and for prolonged future periods and scenarios. Full article

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

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36 pages, 5902 KiB

Open AccessReview

Arctic Warming: Cascading Climate Impacts and Global Consequences

by Ishfaq Hussain Malik, Rayees Ahmed, James D. Ford and Abdur Rahim Hamidi

Climate 2025, 13(5), 85; https://doi.org/10.3390/cli13050085 (registering DOI) - 27 Apr 2025

Abstract

The Arctic is undergoing unprecedented transformations with implications for regional ecosystems, Indigenous communities, and global climate systems. Ocean heat transport, permafrost thawing, and ice–albedo interactions are some of the feedback mechanisms that contribute to the increase in average temperatures in the Arctic. These [...] Read more.

The Arctic is undergoing unprecedented transformations with implications for regional ecosystems, Indigenous communities, and global climate systems. Ocean heat transport, permafrost thawing, and ice–albedo interactions are some of the feedback mechanisms that contribute to the increase in average temperatures in the Arctic. These processes increase the risks associated with climate change globally by speeding up the loss of sea ice, changes in biodiversity, and greenhouse gas emissions. This review synthesises recent advances in Arctic climate science, focusing on the drivers and feedback mechanisms of Arctic amplification, its cascading impacts on ecosystems and socioeconomic systems, and emerging governance challenges. It highlights critical knowledge gaps, specifically regarding the importance of Indigenous knowledge and interdisciplinary approaches in climate adaptation strategies. This study emphasises the need for inclusive, transformative, and collaborative approaches by analysing governance frameworks, climate policies, and community resilience initiatives. Innovative adaptation strategies are suggested, such as ecosystem-based adaptations, climate-resilient infrastructure, and the switch to renewable energy to address these issues. Arctic-specific governance recommendations are proposed to develop sustainable solutions that preserve its ecology while reducing its global effects by filling research gaps and promoting international collaboration. The future of the Arctic is not merely a regional issue but also a global one, requiring swift and coordinated action to address climate challenges. Full article

(This article belongs to the Special Issue Climate, Climate Change and the Arctic: Environment, Infrastructure, Health and Well-Being)

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11 pages, 16684 KiB

Open AccessArticle

Tropical Sea Surface Temperature and Sea Level as Candidate Predictors for Long-Range Weather and Climate Forecasting in Mid-to-High Latitudes

by Genrikh Alekseev, Sergei Soldatenko, Natalia Glok, Natalia Kharlanenkova, Yaromir Angudovich and Maksim Smirnov

Climate 2025, 13(5), 84; https://doi.org/10.3390/cli13050084 (registering DOI) - 27 Apr 2025

Abstract

Sea surface temperature (SST) is considered a strong indicator of climate change, being an essential parameter for long-range weather and climate forecasting. Another important indicator of climate change is sea level (SL), which has a longer history of systematic instrumental observations. This paper [...] Read more.

Sea surface temperature (SST) is considered a strong indicator of climate change, being an essential parameter for long-range weather and climate forecasting. Another important indicator of climate change is sea level (SL), which has a longer history of systematic instrumental observations. This paper aims to examine the relationships between low-latitude variations in ocean characteristics (SST and SL) and surface air temperature (SAT) anomalies in the Arctic and mid-latitudes, and discuss the possibility of using SST and SL as predictors to forecast seasonal SAT anomalies. Archives of meteorological observations, atmospheric and oceanic reanalyses, and long-term series of tide gauge data on SL were used in this study. An analysis of relationships between seasonal SAT in different mid-to-high latitude regions and SST made it possible to identify areas in the ocean that have the greatest influence on SAT patterns. The most commonly identified area is located in the tropical North Atlantic. Another area was found in the Indo-Pacific warm pool. The predictive potential of the relationships identified between ocean characteristics (SST and SL) and SAT will be used to build deep learning models aimed at predicting climate variability in mid-to-high latitudes. Full article

(This article belongs to the Special Issue Climate, Climate Change and the Arctic: Environment, Infrastructure, Health and Well-Being)

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21 pages, 16156 KiB

Open AccessArticle

Beneficial Analysis of the Effect of Precipitation Enhancement on Highland Barley Production on the Tibetan Plateau Under Different Climate Conditions

by Jiandong Liu, Fei Wang, De Li Liu, Jun Du, Rihan Wu, Han Ding, Fengbin Sun and Qiang Yu

Climate 2025, 13(5), 83; https://doi.org/10.3390/cli13050083 (registering DOI) - 26 Apr 2025

Abstract

While highland barley on the Tibetan Plateau is adversely affected by water stress during its growth period, precipitation enhancement could potentially mitigate this issue. Accurate assessment of the benefits obtained through precipitation enhancement is crucial for local governments to develop policies for sustainable [...] Read more.

While highland barley on the Tibetan Plateau is adversely affected by water stress during its growth period, precipitation enhancement could potentially mitigate this issue. Accurate assessment of the benefits obtained through precipitation enhancement is crucial for local governments to develop policies for sustainable agriculture. To quantify these benefits, the WOFOST model was employed to evaluate the effects under four different precipitation enhancement scenarios. The model demonstrated strong performance, with a Nash–Sutcliffe Efficiency (NSE) of 0.93 and a root mean square error (RMSE) of 3.66. Using the calibrated WOFOST model, yield increases were simulated under three meteorological drought conditions classified by the Standardized Precipitation Evapotranspiration Index (SPEI). The results showed that yield increases were minimal during years with less rainfall, primarily due to a lower leaf area index under extreme meteorological drought conditions. Additionally, the impact of precipitation enhancement on yield increases was nonlinear. An enhancement of 5% had negligible effects, while enhancements greater than 10% led to significant increases. Specifically, precipitation enhancement during the reproductive stage resulted in regional yield increases of 170.7, 325.5, 465.9, and 580.5 kg/ha for enhancements of 5%, 10%, 15%, and 20%, respectively, surpassing yield increases from enhancements during the vegetative stage. This greater yield increase is attributed to highland barley’s sensitivity to water stress at critical growth stages and the unique climate conditions of the Tibetan Plateau. For Longzi—the largest base for highland barley production, with a planting area of 3440 ha in 2024—a 10% enhancement at the reproductive stage could yield an economic benefit of CNY 9.8 million. Under climate change scenarios, the decreasing trends in highland barley yields could be effectively offset by precipitation enhancement, highlighting the applicability of precipitation enhancement as an effective tool for mitigating climate change in Tibet. Future studies should integrate crop models with weather numerical models to better address uncertainties. Full article

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22 pages, 11091 KiB

Open AccessArticle

Assessing Climate Change Impacts on Combined Sewer Overflows: A Modelling Perspective

by Panagiota Galiatsatou, Iraklis Nikoletos, Dimitrios Malamataris, Antigoni Zafirakou, Philippos Jacob Ganoulis, Argyro Gkatzioura, Maria Kapouniari and Anastasia Katsoulea

Climate 2025, 13(5), 82; https://doi.org/10.3390/cli13050082 - 22 Apr 2025

Abstract

The study examines the impacts of climate change on the operation and capacity of the combined sewer network in the historic center of Thessaloniki, Greece. Rainfall data from three high-resolution Regional Climate Models (RCMs), namely (a) the Cosmo climate model (CCLM), (b) the [...] Read more.

The study examines the impacts of climate change on the operation and capacity of the combined sewer network in the historic center of Thessaloniki, Greece. Rainfall data from three high-resolution Regional Climate Models (RCMs), namely (a) the Cosmo climate model (CCLM), (b) the regional atmospheric climate model (RACMO) and (c) the regional model (REMO), from the MED-CORDEX initiative with future estimations based on Representative Concentration Pathway (RCP) 4.5, are first corrected for bias based on existing measurements in the study area. Intensity–duration–frequency (IDF) curves are then constructed for future data using a temporal downscaling approach based on the scaling of the Generalized Extreme Value (GEV) distribution to derive the relationships between daily and sub-daily precipitation. Projected rainfall events associated with various return periods are subsequently developed and utilized as input parameters for the hydrologic–hydraulic model. The simulation results for each return period are compared with those of the current climate, and the projections from various RCMs are ranked according to their impact on the combined sewer network and overflow volumes. In the short term (2020–2060), the CCLM and REMO project a decrease in CSO volumes compared to current conditions, while the RACMO predicts an increase, highlighting uncertainties in short-term climate projections. In the long term (2060–2100), all models indicate a rise in combined sewer overflow volumes, with CCLM showing the most significant increase, suggesting escalating pressure on urban drainage systems due to more intense rainfall events. Based on these findings, it is essential to adopt mitigation strategies, such as nature-based solutions, to reduce peak flows within the network and alleviate the risk of flooding. Full article

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

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14 pages, 1383 KiB

Open AccessSystematic Review

Climate-Induced Migration in India and Bangladesh: A Systematic Review of Drivers, Impacts, and Adaptation Mechanisms

by Devangana Gupta, Pankaj Kumar, Naoyuki Okano and Manish Sharma

Climate 2025, 13(4), 81; https://doi.org/10.3390/cli13040081 - 21 Apr 2025

Abstract

Climate-induced migration has emerged as a major concern in India and Bangladesh, due to their geographical vulnerability and socioeconomic conditions. Coastal areas, such as the Sundarbans and the Ganges–Brahmaputra Delta, face relentless threats due to rising sea levels, cyclones, and floods. These factors [...] Read more.

Climate-induced migration has emerged as a major concern in India and Bangladesh, due to their geographical vulnerability and socioeconomic conditions. Coastal areas, such as the Sundarbans and the Ganges–Brahmaputra Delta, face relentless threats due to rising sea levels, cyclones, and floods. These factors force millions to relocate, resulting in rural–urban transitions and cross-border movements that worsen urban challenges and socioeconomic vulnerabilities. For this, a systematic literature review of the Scopus database was undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A detailed review analysis of 65 papers was carried out. The study highlighted key climatic and non-climatic drivers of migration, including natural disasters, resource depletion, poverty, and poor governance. Despite existing adaptation strategies, such as early warning systems, micro-insurance, and climate-resilient practices, gaps remain in addressing long-term resilience and legal recognition for climate migrants. The research emphasizes the need for a holistic, multi-stakeholder approach, integrating adaptive infrastructure, sustainable livelihoods, and international cooperation. Recommendations include bridging research gaps, increasing community participation, and implementing global frameworks, like the Fund for Responding to Loss and Damage. Addressing climate migration through fair, inclusive measures is essential for building resilience and ensuring long-term development in the region. Full article

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30 pages, 8572 KiB

Open AccessArticle

Flood Damage Risk Mapping Along the River Niger: Ten Benefits of a Participated Approach

by Maurizio Tiepolo, Muhammad Abraiz, Maurizio Bacci, Ousman Baoua, Elena Belcore, Giorgio Cannella, Edoardo Fiorillo, Daniele Ganora, Mohammed Ibrahim Housseini, Gaptia Lawan Katiellou, Marco Piras, Francesco Saretto and Vieri Tarchiani

Climate 2025, 13(4), 80; https://doi.org/10.3390/cli13040080 - 14 Apr 2025

Abstract

Flood risk mapping is spreading in the Global South due to the availability of high-resolution/high-frequency satellite imagery, volunteered geographic information, and hydraulic models. However, these maps are increasingly generated without the participation of exposed communities, contrary to the Sendai Framework for Disaster Risk [...] Read more.

Flood risk mapping is spreading in the Global South due to the availability of high-resolution/high-frequency satellite imagery, volunteered geographic information, and hydraulic models. However, these maps are increasingly generated without the participation of exposed communities, contrary to the Sendai Framework for Disaster Risk Reduction 2015–2030 priorities. As a result, the understanding of risk is limited. This study aims to map flood risk with citizen science complemented by hydrology, geomatics, and spatial planning. The Niger River floods of 2024–2025 on a 113 km² area upstream of Niamey are investigated. The novelty of the work is the integration of local and technical knowledge in the micro-mapping of risk in a large area. We consider risk the product of a hazard and damage in monetary terms. Focus groups in flooded municipalities, interviews with irrigation perimeter managers, and statistical river flow and rainfall analysis identified the hazard. The flood plain was extracted from Sentinel-2 images using MNDWI and validated with ground control points. Six classes of assets were identified by visual photo interpretation of very high-resolution satellite imagery. Damage was ascertained through interviews with a sample of farmers. The floods of 2024–2025 may occur again in the next 12–19 years. Farmers cannot crop safer sites, raising significant environmental justice issues. Damage depends on the strength of the levees, the crop, and the season. From January to February, horticulture is at a higher risk. Flooding does not bring benefits. Risk maps highlight hot spots, are validated, and can be linked to observed flood levels. Full article

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

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20 pages, 12012 KiB

Open AccessArticle

Multiscale Modeling Framework for Urban Climate Heat Resilience—A Case Study of the City of Split

by Tea Duplančić Leder, Samanta Bačić, Josip Peroš and Martina Baučić

Climate 2025, 13(4), 79; https://doi.org/10.3390/cli13040079 - 14 Apr 2025

Abstract

This study presents a comprehensive framework for evaluating urban heat resilience, incorporating urban climatology models, their characteristics, and simulation programs. Utilizing the local climate zone (LCZ) classification method, this research explores how urban geomorphology influences the thermal characteristics of the area. This study [...] Read more.

This study presents a comprehensive framework for evaluating urban heat resilience, incorporating urban climatology models, their characteristics, and simulation programs. Utilizing the local climate zone (LCZ) classification method, this research explores how urban geomorphology influences the thermal characteristics of the area. This study integrates spatial data at different “levels of detail” (LOD), from the meso- to building scales, emphasizing the significance of detailed LOD 3 models acquired through 3D laser scanning. The results demonstrate the ability of these models to identify urban heat islands (UHIs) and to simulate urban planning scenarios, such as increasing green spaces and optimizing building density, to mitigate the UHI effect. The ST3D 3D model of the city of Split, represented using an LOD 2 object model, is utilized for meso- and local-scale analyses, while LOD 3 models derived from laser scanning provided in-depth insights at the building scale. The case studies included the Faculty of Civil Engineering, Architecture, and Geodesy building on the University of Split campus and the old town hall in the densely built city center. This framework highlights the advantages of integrating GIS and BIM technology with urban climate analyses, offering tools for data-driven decision-making and fostering sustainable, climate-resilient urban planning. Full article

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20 pages, 5204 KiB

Open AccessArticle

A Methodological Approach (TOPSIS) to Water Management in Water-Scarce Areas Under Climate Variability Conditions

by Efthymia Stathi, Aristeidis Kastridis and Dimitrios Myronidis

Climate 2025, 13(4), 78; https://doi.org/10.3390/cli13040078 - 10 Apr 2025

Abstract

Efficient and sustainable water management measures are required on Mediterranean islands due to water shortages, which are exacerbated by climatic variability and increased tourist traffic. This study uses a multi-criteria decision analysis (MCDA) approach, specifically Technique for Order of Preference by Similarity to [...] Read more.

Efficient and sustainable water management measures are required on Mediterranean islands due to water shortages, which are exacerbated by climatic variability and increased tourist traffic. This study uses a multi-criteria decision analysis (MCDA) approach, specifically Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), to examine and rate water management strategies for three Aegean islands that face significant water shortage: Mykonos, Naxos, and Kos. Three main factors were taken into account in the analysis: preventing groundwater depletion, reducing groundwater deterioration, and managing long-term water demands. Expert questionnaires were used to evaluate eight different alternatives, which included reservoir construction, desalination plants, conserving water in agriculture, and reducing network losses. The results for Mykonos showed specific preferred alternatives, such as desalination plants (R2) and agricultural water conservation (R3), which reflect the island’s low capacity for natural water storage. Constructing reservoirs (R1) and conserving agricultural water (R3) were prioritized in Naxos, showing the significance of storage infrastructure for the island’s large agriculture sector. Kos also supported reservoir construction (R1) and agricultural water conservation (R3), displaying the need for both storage and conservation practices. The least sustainable alternative option on all islands was determined to be water transportation by ship (R8). The present study emphasized the significance of localized projects, the construction of water storage infrastructures, and stakeholder involvement in a comprehensive approach to managing water resources. The results indicate an integrated approach that takes into account infrastructure, conservation, and policy, and they are consistent with previous studies on water management in the Mediterranean. This study highlights the need for adapted combined strategies to achieve sustainable water resource management under climatic variability and offers a framework for managing water shortages in similar regions. Full article

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35 pages, 12088 KiB

Open AccessArticle

Are Climate Geoengineering Technologies Being Patented? An Overview

by Yvette Ramos and Filipe Duarte Santos

Climate 2025, 13(4), 77; https://doi.org/10.3390/cli13040077 - 7 Apr 2025

Abstract

Efforts to address anthropogenic climate change have been focused sensibly on mitigation and adaptation. However, given the difficulties in the implementation of a rapid global mitigation process, increasing attention is being given to geoengineering as a way to countervail some of the climate [...] Read more.

Efforts to address anthropogenic climate change have been focused sensibly on mitigation and adaptation. However, given the difficulties in the implementation of a rapid global mitigation process, increasing attention is being given to geoengineering as a way to countervail some of the climate change impacts. This development has increased the private investment in geoengineering research in the last few years, leading to patent filing. The article examines the recent evolution of patents in the emerging field of geoengineering technologies. Despite the secrecy surrounding the field of geoengineering, especially solar radiation management at the state level, patent databases provide transparency, offering technical details, market insights, and information about the key players. Patents, published 18 months after filing, reveal valuable data about geoengineering technologies, the targeted markets, and involved stakeholders. The databases of the International Patent Classification (IPC) and Cooperative Patent Classification (CPC) are used. The focus of the present analysis is on patents in the sub-domains of carbon dioxide removal and solar radiation management and on those held by the large oil producer corporations. The results highlight the patents filed in the controversial area of SRM. The growing economic significance of geoengineering requires the protection of innovations through patents coupled with the implementation of a global governance system based on climate justice and ethical responsibility. Full article

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19 pages, 1385 KiB

Open AccessArticle

Climate Change, Heat-Related Health Risks, and Stroke: Perceptions and Adaptations Among Older Israeli Adults

by Tehila Yoeli, Maya Negev, Shlomit Paz and Galit Weinstein

Climate 2025, 13(4), 76; https://doi.org/10.3390/cli13040076 - 7 Apr 2025

Abstract

Extreme heat, a leading cause of weather-related morbidity and mortality, particularly affects vulnerable populations such as older people, increasing their risk of stroke. There is a gap between scientific knowledge and policy implementation, particularly regarding climatic risk factors for stroke. This study aims [...] Read more.

Extreme heat, a leading cause of weather-related morbidity and mortality, particularly affects vulnerable populations such as older people, increasing their risk of stroke. There is a gap between scientific knowledge and policy implementation, particularly regarding climatic risk factors for stroke. This study aims to identify knowledge barriers and enablers and formulate recommendations. We held eight focus groups of participants aged ≥ 60 years (N = 56), a workshop with 36 public health policy experts and stakeholders, and six in-depth interviews with experts. Three main themes emerged: (1) risk perception and responsibility attribution, revealing varying awareness of climate change risk for stroke and complex personal, cultural, and institutional responsibilities; (2) barriers to climate change adaptation, including knowledge gaps, environmental maladaptation, and insufficient governmental resources; and (3) enabling factors and adaptive solutions, highlighting individual coping strategies, education, and collaborative policy interventions. Focus group participants demonstrated diverse adaptive behaviors, while policymakers emphasized interagency collaboration and targeted knowledge dissemination. Older individuals demonstrated limited knowledge about climate change and its health risks. National policies lack effective communication. There is a critical need for knowledge dissemination, coping tools, and solutions for healthcare providers and at-risk groups, particularly regarding the health implications of climate change. Full article

(This article belongs to the Section Climate Adaptation and Mitigation)

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21 pages, 3798 KiB

Open AccessArticle

Cyclic Interannual Variation in Monsoon Onset and Rainfall in South Central Arizona, USA

by Frank W. Reichenbacher and William D. Peachey

Climate 2025, 13(4), 75; https://doi.org/10.3390/cli13040075 - 6 Apr 2025

Abstract

The North American Monsoon (NAM) in southern Arizona continues to be a topic of interest to many ecologists studying the triggers and characteristics of plant growth and reproduction in relation to the onset of the monsoon. The purpose of this article is to [...] Read more.

The North American Monsoon (NAM) in southern Arizona continues to be a topic of interest to many ecologists studying the triggers and characteristics of plant growth and reproduction in relation to the onset of the monsoon. The purpose of this article is to report interannual variation in the timing of NAM onset found while researching the phenology of Saguaro cactus (Carnegiea gigantea). Using a daily rainfall dataset from 33 stations located in Pima and Pinal Counties, Arizona, from 1990–2022, we analyzed monsoon onset, monsoon precipitation, annual precipitation, and the proportion of annual station precipitation received during the monsoon season. Onset was measured by the first day from 1 June to 30 September with precipitation ≥ 10 mm counted from the day of the vernal equinox of the year. Generalized Additive Models (GAMs) identified sinusoidal waves with a period of 8.6 years and amplitudes of 14–29 days, providing frequency and amplitude estimates for Sinusoidal Regression Models (SRMs). Sinusoidal wave patterns found in the monsoon onset dataset are suggested in monsoon, annual, and proportion of monsoon in station-averaged annual precipitation although in and approximately mirror-image. These unexpected findings may have important implications for forecasters as well as ecologists interested in plant phenology. Full article

(This article belongs to the Special Issue Evolving Plant Phenology Responses and Resilience in a Changing Climate)

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20 pages, 7325 KiB

Open AccessArticle

Trends in Extreme Precipitation and Associated Natural Disasters in China, 1961–2021

by Xinlei Han, Qixiang Chen and Disong Fu

Climate 2025, 13(4), 74; https://doi.org/10.3390/cli13040074 - 4 Apr 2025

Abstract

Natural disaster events caused by extreme precipitation have far-reaching and widespread impacts on society, the economy, and ecosystems. However, understanding the long-term trends of extreme precipitation indices and their spatiotemporal correlations with disaster events remains limited. This is especially true given the diverse [...] Read more.

Natural disaster events caused by extreme precipitation have far-reaching and widespread impacts on society, the economy, and ecosystems. However, understanding the long-term trends of extreme precipitation indices and their spatiotemporal correlations with disaster events remains limited. This is especially true given the diverse factors influencing their relationship in China, which makes their spatial linkage highly complex. This study aims to detect recent spatial trends in extreme precipitation indices in China and link them with related natural disaster events, as well as with the spatial evolution of land use and land cover and Gross Domestic Product (GDP). Daily precipitation data from 1274 rain gauge stations spanning the period from 1961 to 2021 were used to analyze the spatial distribution characteristics of extreme precipitation index climate trends in China. The results revealed a significant increasing trend of the intensity of extreme precipitation in eastern China, but a decreasing trend of amount, frequency, and duration of extreme precipitation in southwest China, accompanied by a significant increase in consecutive dry days. Natural disaster records related to extreme precipitation trends indicated a significant increase at an annual rate of 1.3 times in the frequency of flood, storm, drought, and landslide occurrences nationwide, with substantial regional dependence in disaster types. Furthermore, the spatial evolution of land use and GDP levels showed a close association with the spatial distribution of natural disaster events induced by extreme precipitation. Although the number of deaths caused by extreme precipitation-related disasters in China is decreasing (by 51 people per year), the economic losses are increasing annually at an annual rate of USD 530,991, particularly due to floods and storms. This study holds the potential to inform decision-making processes, facilitate the implementation of mitigation and adaptation measures, and contribute to reducing the impacts of natural disasters across diverse regions worldwide. Full article

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38 pages, 34979 KiB

Open AccessArticle

Recovery of the Long Series of Precipitation in Pisa, Italy: Trend, Anomaly and Extreme Events

by Dario Camuffo, Francesca Becherini and Antonio della Valle

Climate 2025, 13(4), 73; https://doi.org/10.3390/cli13040073 - 2 Apr 2025

Abstract

The long instrumental series of precipitation in Pisa, the earliest one in Italy, has been reconstructed after the careful recovery and critical analysis of its history, data, and metadata. Precipitation amounts have been recovered from May 1707 to December 2024, but there are [...] Read more.

The long instrumental series of precipitation in Pisa, the earliest one in Italy, has been reconstructed after the careful recovery and critical analysis of its history, data, and metadata. Precipitation amounts have been recovered from May 1707 to December 2024, but there are gaps due to lost data. The recovered dataset includes 47.4% of the total daily, 65.0% of monthly, and 77.4% of yearly values. Original observation registers and metadata are scarce or even missing, so a thorough investigation of contemporary sources has been performed to recover as much information as possible concerning observers, instruments, locations, exposures, measuring protocols, and ancient local units. The main features of the precipitation regime in Pisa have been investigated, and the variability in the amount and frequency at different time scales, as well as extreme events, have been analysed. Pisa is characterized by intense precipitation in autumn due to the penetration of Atlantic perturbations, and the most extreme daily events occur mainly in the transition period between the end of summer and the onset of autumn. A small decreasing trend has been found in the anomaly of the yearly amount in the 1867–2024 unbroken period, with the most remarkable month anomalies in summer. The time series of the Standard Precipitation Index indicates that the period around 1945 was particularly dry, and also indicates a slight increase in arid conditions over time, mainly in spring. The most extreme yearly amounts were found in the 18th century, and the series of the daily 90th and 95th percentiles show a small decreasing trend in the 1884–2004 period. The comparison with other contemporary Italian series made it possible to identify the peculiarity of the precipitation regime in Pisa, adding an important piece to the historical research on the climate of the Italian peninsula from a long-term perspective. Full article

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

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17 pages, 3364 KiB

Open AccessArticle

Development of Prediction Model for Damage Costs of Heavy Rainfall Disasters Using Machine Learning in the Republic of Korea

by Youngseok Song, Yang Ho Song, Moojong Park and Sang Yeob Kim

Climate 2025, 13(4), 72; https://doi.org/10.3390/cli13040072 - 1 Apr 2025

Abstract

In this study, a prediction model was developed that considers the rainfall characteristics and damage characteristics of heavy rainfall disasters in Korea using machine learning models. Considering the damage characteristics of heavy rainfall disasters that occurred from 1999 to 2019 in 228 administrative [...] Read more.

In this study, a prediction model was developed that considers the rainfall characteristics and damage characteristics of heavy rainfall disasters in Korea using machine learning models. Considering the damage characteristics of heavy rainfall disasters that occurred from 1999 to 2019 in 228 administrative districts in Korea, four types of total rainfall and five types of damage costs were selected to predict the total damage cost. The machine learning models selected for this study were Random Forest, K-Nearest Neighbors, Decision Tree, and eXtreme Gradient Boosting, and their accuracy was evaluated using

R^{2}

, EVS, and MAPE. The training period spanned from 1999 to 2015, while the evaluation period extended from 2016 to 2019. The Random Forest model emerged as the most effective model for predicting the total damage costs associated with heavy rainfall disasters, exhibiting an accuracy of 0.95 for

R^{2}

, 0.95 for EVS, and 0.05 for MAPE. It was observed that when the total damage costs are minimal, all models demonstrate high prediction capability. However, as the damage costs escalate, the prediction power experiences a decline due to the presence of errors. The machine learning prediction model for heavy rainfall disasters developed in this study has the potential to contribute to national efforts aimed at preventing and preparing for heavy rainfall disasters. Full article

(This article belongs to the Special Issue Hydro-Meteorological Hazards: Causes, Impacts, and Mitigation Strategies)

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15 pages, 939 KiB

Open AccessArticle

A Pilot Study with Low-Cost Sensors: Seasonal Variation of Particulate Matter Ratios and Their Relationship with Meteorological Conditions in Rio Grande, Brazil

by Gustavo de Oliveira Silveira, Gabriella Mello Gomes Vieira de Azevedo, Ronan Adler Tavella, Paula Florencio Ramires, Rodrigo de Lima Brum, Alicia da Silva Bonifácio, Ricardo Arend Machado, Letícia Willrich Brum, Romina Buffarini, Diana Francisca Adamatti and Flavio Manoel Rodrigues da Silva Júnior

Climate 2025, 13(4), 71; https://doi.org/10.3390/cli13040071 - 30 Mar 2025

Abstract

(1) Background: This study investigated seasonal variations in particulate matter (PM) ratios (PM₁/PM_2.5, PM_2.5/PM₁₀, and PM₁/PM₁₀) and their relationship with the meteorological conditions in Rio Grande, Brazil. (2) Methods: PM₁ [...] Read more.

(1) Background: This study investigated seasonal variations in particulate matter (PM) ratios (PM₁/PM_2.5, PM_2.5/PM₁₀, and PM₁/PM₁₀) and their relationship with the meteorological conditions in Rio Grande, Brazil. (2) Methods: PM₁, PM_2.5, and PM₁₀ levels were collected using low-cost Gaia Air Quality Monitors, which measured PM concentrations at high temporal resolution. Meteorological variables, including atmospheric pressure, temperature, relative humidity, wind speed, and precipitation, were obtained from the National Institute of Meteorology (INMET). The data were analyzed through multiple linear regression to assess the influence of meteorological factors on PM ratios. (3) Results: The results show that the highest PM ratios occurred in winter, indicating a predominance of fine and ultrafine particles, while the lowest ratios were observed in spring and summer. Multiple linear regression analysis identified atmospheric pressure, wind speed, and maximum temperature as the key drivers of PM distribution. (4) Conclusions: This study highlights the importance of continuous monitoring of PM ratios, particularly PM₁, which remains underexplored in Brazil. The findings underscore the need for targeted air quality policies emphasizing seasonal mitigation strategies and improved pollution control to minimize the health risks associated with fine and ultrafine PM exposure. Full article

(This article belongs to the Special Issue New Perspectives in Air Pollution, Climate, and Public Health)

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