-
Enhancing Agricultural Soil Carbon Sequestration: A Review with Some Research Needs
-
Combining Multi-Source Satellite Data with a Microclimate Model to Analyze the Microclimate of an Urban Park
-
Application of Machine Learning and Hydrological Models for Drought Evaluation in Ungauged Basins Using Satellite-Derived Precipitation Data
Journal Description
Climate
Climate
is a scientific, peer-reviewed, open access journal of climate science published online monthly by MDPI. The American Society of Adaptation Professionals (ASAP) is affiliated with Climate and its members receive discounts on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), GeoRef, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Meteorology and Atmospheric Sciences) / CiteScore - Q2 (Atmospheric Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 19.7 days after submission; acceptance to publication is undertaken in 2.9 days (median values for papers published in this journal in the second half of 2024).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.0 (2023);
5-Year Impact Factor:
3.3 (2023)
Latest Articles
Developing Low-Carbon Pathways for the Transport Sector in Ethiopia
Climate 2025, 13(5), 96; https://doi.org/10.3390/cli13050096 - 6 May 2025
Abstract
This paper discusses the development of baseline and mitigation scenarios to guide the creation of a long-term plan supporting low-carbon transport in Ethiopia. Developing this method involved comprehensively reviewing policy documents, collecting historical activity data, and modelling the baseline and mitigation scenarios. The
[...] Read more.
This paper discusses the development of baseline and mitigation scenarios to guide the creation of a long-term plan supporting low-carbon transport in Ethiopia. Developing this method involved comprehensively reviewing policy documents, collecting historical activity data, and modelling the baseline and mitigation scenarios. The paper emphasises the importance of stakeholder engagement, which is instrumental in validating the model inputs, policy targets, and results at each stage, ensuring the credibility and robustness of our findings. The scenario development and analysis are based on the IPCC guidelines, informed by the policies of the Government of Ethiopia, and implemented with the Low-Energy Analysis Platform (LEAP). Three net-zero scenarios are assessed for the time horizon between 2020 to 2050. The so-called maximum ambition, NDC-aligned, and late action scenarios reflect the energy requirements and emissions contribution for varying levels of government ambition towards low-carbon interventions in the transport sector. In the baseline scenario, the total amount of carbon emissions is estimated at 4.81 million tonnes of CO2e in 2020, which is projected to increase to over 15 million tonnes by 2050. Under the mitigation scenarios, significant reductions are projected, with specific interventions like electrification in road freight reducing emissions by 9.68 MtCO2e and expanding rail transport reducing 9.95 MtCO2e by 2050 compared to the baseline. Other strategies identified for mitigating transport sector emissions, like improving energy efficiency, encouraging mass transit and non-motorised transport, show good potential for achieving a greener future. With the transport sector in Ethiopia identified as a major contributor to GHG emissions and climate change, this paper underscores the government’s efforts to ensure the long-term sustainability of its transport sector.
Full article
(This article belongs to the Special Issue Climate Change and Transport)
►
Show Figures
Open AccessArticle
Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction—Part 1: Spatiotemporal Characteristics
by
Amarech Alebie Addisuu, Gizaw Mengistu Tsidu and Lenyeletse Vincent Basupi
Climate 2025, 13(5), 95; https://doi.org/10.3390/cli13050095 - 4 May 2025
Abstract
►▼
Show Figures
Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these models emphasize the distribution of precipitation within a month or season rather than the overall amount. To meet this requirement, a study applied three
[...] Read more.
Impact models used in water, ecology, and agriculture require accurate climatic data to simulate observed impacts. Some of these models emphasize the distribution of precipitation within a month or season rather than the overall amount. To meet this requirement, a study applied three bias correction techniques—scaled distribution mapping (SDM), quantile distribution mapping (QDM), and QDM with a separate treatment for precipitation below and above the 95th percentile threshold (QDM95)—to daily precipitation data from eleven Coupled Model Intercomparison Project Phase 6 (CMIP6) models, using the Climate Hazards Group Infrared Precipitation with Station version 2 (CHIRPS) as a reference. This study evaluated the performance of all bias-corrected CMIP6 models over Southern Africa from 1982 to 2014 in replicating the spatial and temporal patterns of precipitation across the region against three observational datasets, CHIRPS, the Climatic Research Unit (CRU), and the Global Precipitation Climatology Centre (GPCC), using standard statistical metrics. The results indicate that all bias-corrected precipitation generally performs better than native model precipitation in replicating the observed December–February (DJF) mean and seasonal cycle. The probability density function (PDF) of the bias-corrected regional precipitation indicates that bias correction enhances model performance, particularly for precipitation in the range of 3–35 mm/day. However, both corrected and uncorrected models underestimate higher extremes. The pattern correlations of the bias-corrected precipitation with CHIRPS, the GPCC, and the CRU, as compared to the correlations of native precipitation with the three datasets, have improved from 0.76–0.89 to 0.97–0.99, 0.73–0.87 to 0.94–0.97, and 0.74–0.89 to 0.97–0.99, respectively. Additionally, the Taylor skill scores of the models for replicating the CHIRPS, GPCC, and CRU precipitation spatial patterns over Southern Africa have improved from 0.57–0.80 to 0.79–0.95, 0.55–0.76 to 0.80–0.91, and 0.54–0.75 to 0.81–0.91, respectively. Overall, among the three bias correction techniques, QDM consistently demonstrated better performance than both QDM95 and SDM across various metrics. The implementation of distribution-based bias correction resulted in a significant reduction in bias and improved the spatial consistency between models and observations over the region.
Full article

Figure 1
Open AccessArticle
Extreme Weather Shocks and Crime: Empirical Evidence from China and Policy Recommendations
by
Huaxing Lin and Ping Jiang
Climate 2025, 13(5), 94; https://doi.org/10.3390/cli13050094 - 3 May 2025
Abstract
►▼
Show Figures
Rising global temperatures and increasing extreme weather events pose challenges to social stability and public security. This study examines the relationship between extreme weather and crime in China using fixed-effects quasi-Poisson and negative binomial regression models, along with a generalized additive model to
[...] Read more.
Rising global temperatures and increasing extreme weather events pose challenges to social stability and public security. This study examines the relationship between extreme weather and crime in China using fixed-effects quasi-Poisson and negative binomial regression models, along with a generalized additive model to explore nonlinear effects. The results show that extreme heat significantly increases crime, following an “S” shaped pattern. This intense heat heightens emotional instability and impulsivity, leading to a crime surge. While moderate heat reduces crime, extreme cold and heavy rainfall have no significant effects. These findings highlight the need for stratified policy interventions. Based on empirical evidence, this study proposes three key recommendations: (1) developing a weather warning and public security risk coordination system, (2) promoting community-based crime prevention through mutual assistance networks and infrastructure improvements, and (3) enhancing psychological interventions to mitigate mental health challenges linked to extreme weather. Integrating meteorological data, law enforcement, and interventions to help potential perpetrators can strengthen urban resilience and public safety against climate-induced crime risks.
Full article

Figure 1
Open AccessArticle
Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction— Part 2: Representation of Extreme Precipitation
by
Amarech Alebie Addisuu, Gizaw Mengistu Tsidu and Lenyeletse Vincent Basupi
Climate 2025, 13(5), 93; https://doi.org/10.3390/cli13050093 - 2 May 2025
Abstract
►▼
Show Figures
Accurate simulation of extreme precipitation events is crucial for managing climate-vulnerable sectors in Southern Africa, as such events directly impact agriculture, water resources, and disaster preparedness. However, global climate models frequently struggle to capture these phenomena, which limits their practical applicability. This study
[...] Read more.
Accurate simulation of extreme precipitation events is crucial for managing climate-vulnerable sectors in Southern Africa, as such events directly impact agriculture, water resources, and disaster preparedness. However, global climate models frequently struggle to capture these phenomena, which limits their practical applicability. This study investigates the effectiveness of three bias correction techniques—scaled distribution mapping (SDM), quantile distribution mapping (QDM), and QDM with a focus on precipitation above and below the 95th percentile (QDM95)—and the daily precipitation outputs from 11 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset was served as a reference. The bias-corrected and native models were evaluated against three observational datasets—the CHIRPS, Multi-Source Weighted Ensemble Precipitation (MSWEP), and Global Precipitation Climatology Center (GPCC) datasets—for the period of 1982–2014, focusing on the December-January-February season. The ability of the models to generate eight extreme precipitation indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) was evaluated. The results show that the native and bias-corrected models captured similar spatial patterns of extreme precipitation, but there were significant changes in the amount of extreme precipitation episodes. While bias correction generally improved the spatial representation of extreme precipitation, its effectiveness varied depending on the reference dataset used, particularly for the maximum one-day precipitation (Rx1day), consecutive wet days (CWD), consecutive dry days (CDD), extremely wet days (R95p), and simple daily intensity index (SDII). In contrast, the total rain days (RR1), heavy precipitation days (R10mm), and extremely heavy precipitation days (R20mm) showed consistent improvement across all observations. All three bias correction techniques enhanced the accuracy of the models across all extreme indices, as demonstrated by higher pattern correlation coefficients, improved Taylor skill scores (TSSs), reduced root mean square errors, and fewer biases. The ranking of models using the comprehensive rating index (CRI) indicates that no single model consistently outperformed the others across all bias-corrected techniques relative to the CHIRPS, GPCC, and MSWEP datasets. Among the three bias correction methods, SDM and QDM95 outperformed QDM for a variety of criteria. Among the bias-corrected strategies, the best-performing models were EC-Earth3-Veg, EC-Earth3, MRI-ESM2, and the multi-model ensemble (MME). These findings demonstrate the efficiency of bias correction in improving the modeling of precipitation extremes in Southern Africa, ultimately boosting climate impact assessments.
Full article

Figure 1
Open AccessArticle
Exploring Socio-Spatial Inequalities in Flood Response Using Flood Simulation and Social Media Data: A Case Study of 2020 Flood in Nanjing, China
by
Yi Chen, Yang Zhang, Dekai Tao, Wenjie Zhang, Jingxian You, Yuan Li, Yong Lei and Yao Meng
Climate 2025, 13(5), 92; https://doi.org/10.3390/cli13050092 - 30 Apr 2025
Abstract
►▼
Show Figures
Identifying socio-spatial inequalities in flood resilience is crucial for effective disaster risk management. This study integrates flood susceptibility simulations and Weibo activity data to construct a flood susceptibility index and incorporates socio-spatial differentiation to represent residents’ coping capacities. By combining flood risk awareness
[...] Read more.
Identifying socio-spatial inequalities in flood resilience is crucial for effective disaster risk management. This study integrates flood susceptibility simulations and Weibo activity data to construct a flood susceptibility index and incorporates socio-spatial differentiation to represent residents’ coping capacities. By combining flood risk awareness and coping capacity, we develop a comprehensive flood response capability model to examine the spatial patterns of flood resilience inequality. The findings reveal that (1) high flood risk awareness is concentrated near the Yangtze River and major lakes based on social media data and simulations; (2) coping capacity to floods exhibits a central–periphery pattern, with higher resilience in urban centers and gradually decreases gradually to the suburban and exurban areas; (3) communities are classified into four types based on the combination of flood risk awareness and coping capacities. Multiple linear regression analysis indicates that both natural and social factors significantly influence flood response capacity. This research provides critical insights into the spatial patterns of flood resilience, offering valuable guidance for formulating targeted adaptation strategies.
Full article

Figure 1
Open AccessArticle
The Impact of Beach Wrack on Greenhouse Gas Emissions from Coastal Soils
by
Olga Nesterova, Mariia Bovsun, Andrei Egorin, Andrey Yatsuk, Dmitry Kravchenko, Irina Lisina, Igor Stepochkin and Anastasia Brikmans
Climate 2025, 13(5), 91; https://doi.org/10.3390/cli13050091 - 30 Apr 2025
Abstract
The existing management strategies of macrophyte beach wrack are not always environmentally sound. In this study, we tried to assess the impact of the presence or absence of macrophyte beach wrack on the CO2 flux and the possibility of creating an environmentally
[...] Read more.
The existing management strategies of macrophyte beach wrack are not always environmentally sound. In this study, we tried to assess the impact of the presence or absence of macrophyte beach wrack on the CO2 flux and the possibility of creating an environmentally sound recycling of macrophyte beach wrack based on their removal from the beach and processing into biochar. The study was conducted on the coast of the Sea of Japan in the bay of Kievka. The Picarro G4301 portable laser gas analyzer was used to measure CO2 fluxes in areas with and without macrophyte beach wrack. The CO2 flux was 23 times higher at plots with macrophyte beach wrack, compared with plots without macrophyte beach wrack. In the plots after manual removal of the macrophyte beach wrack, on average, there was a 1.6-fold decrease in flow values compared to the plots with the macrophyte beach wrack. Considering the frequency of emissions in the study area, which is associated with frequent cyclones and storms, it is possible to organize the systematic cleaning of macrophyte beach wrack for the production of biochar. Creating projects based on the conversion of macrophyte beach wrack into biochar can have both environmental and economic benefits. The environmental benefits include the reduction of CO2 flux at plots after manual removal of macrophyte beach wrack; the long-term storage of carbon from macrophyte beach wrack biomass in the form of biochar; and the reduction of CO2 flux from soils (carbon sequestration) with the correct technology of introducing biochar into the soil. However, for a more accurate assessment, monitoring seasonal measurements and economic calculations of the entire technological chain of production, risks, and footprint are necessary.
Full article
(This article belongs to the Special Issue Coastal Hazards under Climate Change)
►▼
Show Figures

Figure 1
Open AccessArticle
Socio-Economic Determinants of Climate Change Adaptation Strategies Among Smallholder Farmers in Mbombela: A Binary Logistic Regression Analysis
by
Thando Dyanty, Isaac Azikiwe Agholor, Tapelo Blessing Nkambule, Andries Agrippa Nkuna, Mzwakhe Nkosi, Shalia Matilda Ndlovu, Jabulani Johannes Mokoena, Pretty Nombulelo Nkosi, Nombuso Precious Nkosi and Thulasizwe Hopewell Makhubu
Climate 2025, 13(5), 90; https://doi.org/10.3390/cli13050090 - 29 Apr 2025
Abstract
Climate change poses significant challenges to smallholder farmers, particularly in sub-Saharan Africa, where agriculture is highly vulnerable to changing climatic conditions. This study examines the socioeconomic determinants influencing the adoption of strategies for adapting to climate change among smallholder farmers in Mbombela, South
[...] Read more.
Climate change poses significant challenges to smallholder farmers, particularly in sub-Saharan Africa, where agriculture is highly vulnerable to changing climatic conditions. This study examines the socioeconomic determinants influencing the adoption of strategies for adapting to climate change among smallholder farmers in Mbombela, South Africa. A quantitative research approach was employed, using structured questionnaires to collect data from 308 randomly selected smallholder farmers. Furthermore, the study utilised binary logistic regression to analyse the relationship between socioeconomic factors and the adoption of adaptation strategies. The results revealed that gender, age, income sources, access to climate information, and cooperative membership significantly influenced farmers’ adoption of adaptation strategies. Findings further showed that female farmers, older farmers, and those relying solely on farming income were less likely to adopt adaptation strategies, while younger farmers and those with diversified income sources were more likely to embrace adaptation strategies. Moreover, the study found that access to climate information and cooperative membership were negatively associated with the adoption of adaptation strategies. This negative association may be attributed to inefficiencies in current information dissemination, where climate-related information may not be tailored to the specific needs of farmers, or to cooperative structures that may not effectively facilitate knowledge sharing or collective action. The study concludes that targeted interventions, such as gender-sensitive policies, livelihood diversification, improved extension services, and strengthened cooperative structures, are essential to enhance smallholder farmers’ adaptive capacity.
Full article
(This article belongs to the Section Climate Adaptation and Mitigation)
►▼
Show Figures

Figure 1
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 - 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)
►▼
Show Figures

Figure 1
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 - 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)
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 - 29 Apr 2025
Abstract
►▼
Show Figures
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

Figure 1
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 - 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)
►▼
Show Figures

Figure 1
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 - 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)
►▼
Show Figures

Figure 1
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 - 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)
►▼
Show Figures

Figure 1
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 - 26 Apr 2025
Abstract
►▼
Show Figures
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

Figure 1
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)
►▼
Show Figures

Figure 1
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
►▼
Show Figures
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

Figure 1
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)
►▼
Show Figures

Figure 1
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
►▼
Show Figures
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

Figure 1
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
►▼
Show Figures
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

Figure 1
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
►▼
Show Figures
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

Figure 1

Journal Menu
► ▼ Journal Menu-
- Climate Home
- Aims & Scope
- Editorial Board
- Reviewer Board
- Topical Advisory Panel
- Instructions for Authors
- Special Issues
- Topics
- Sections & Collections
- Article Processing Charge
- Indexing & Archiving
- Editor’s Choice Articles
- Most Cited & Viewed
- Journal Statistics
- Journal History
- Journal Awards
- Society Collaborations
- Editorial Office
Journal Browser
► ▼ Journal BrowserHighly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Sustainability, Buildings, Sensors, Remote Sensing, Land, Climate, Atmosphere
Advances in Low-Carbon, Climate-Resilient, and Sustainable Built Environment
Topic Editors: Baojie He, Stephen Siu Yu Lau, Deshun Zhang, Andreas Matzarakis, Fei GuoDeadline: 31 May 2025
Topic in
Agronomy, Climate, Earth, Remote Sensing, Water
Advances in Crop Simulation Modelling
Topic Editors: Mavromatis Theodoros, Thomas Alexandridis, Vassilis AschonitisDeadline: 15 July 2025
Topic in
Hydrology, Water, Climate, Atmosphere, Agriculture, Geosciences
Advances in Hydro-Geological Research in Arid and Semi-Arid Areas
Topic Editors: Ahmed Elbeltagi, Quanhua Hou, Bin HeDeadline: 31 July 2025
Topic in
Climate, Diversity, Forests, Plants, Sustainability, Earth
Responses of Trees and Forests to Climate Change
Topic Editors: Qinglai Dang, Ilona Mészáros, Lei WangDeadline: 30 August 2025

Conferences
Special Issues
Special Issue in
Climate
Climate Change—Achieving the UN Sustainable Development Goals in Urban Contexts
Guest Editors: Christine Fürst, Muhammad Mushahid Anwar, Yazidhi Bamutaze, Ellen Banzhaf, Bolormaa Batsuuri, Henry Bulley, Paula Kapstein, Daniele La Rosa, Purevtseren Myagmartseren, Appollonia Okhimamhe, Malte SteinbrinkDeadline: 31 May 2025
Special Issue in
Climate
Climate Impact on Human Health
Guest Editors: Zhiming Yang, Yunquan Zhang, Zheming Yan, Ang LiDeadline: 31 May 2025
Special Issue in
Climate
Climate Change Impacts on Hydrologic Variables across Timescales and Spatial Scale
Guest Editors: Yang Zhou, Jiabao WangDeadline: 31 May 2025
Special Issue in
Climate
Recent Climate Change Impacts in Australia
Guest Editors: Milton S. Speer, Lance LeslieDeadline: 31 May 2025
Topical Collections
Topical Collection in
Climate
Adaptation and Mitigation Practices and Frameworks
Collection Editor: Rajib Shaw