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), GEOBASE, GeoRef, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Meteorology and Atmospheric Sciences) / CiteScore - Q1 (Atmospheric Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.5 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the first half of 2026).
- 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.
- Journal Cluster of Geospatial and Earth Sciences: Remote Sensing, Atmosphere, Geosciences, Climate, Quaternary, Earth, Geographies, Geomatics, Meteorology and Fossil Studies.
Impact Factor:
4.0 (2025);
5-Year Impact Factor:
4.1 (2025)
Latest Articles
Soil Salinization Under Climatic and Management Drivers: A Multi-Scale Comparative Synthesis of Nine Long-Term Case Studies
Climate 2026, 14(9), 184; https://doi.org/10.3390/cli14090184 - 4 Sep 2026
Abstract
Soil salinization affects more than 424 million hectares of topsoil worldwide and is associated with yield losses of 18–43% in drylands, yet its long-term dynamics have rarely been compared across regions on a common basis. This work synthesizes nine case studies from a
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Soil salinization affects more than 424 million hectares of topsoil worldwide and is associated with yield losses of 18–43% in drylands, yet its long-term dynamics have rarely been compared across regions on a common basis. This work synthesizes nine case studies from a systematic, PRISMA-guided search, selected purposively to maximize variation in climate, scale and method. ECe (dS/m) and total salt content (g/kg) have no general conversion, so the eight ECe-based studies are compared class by class using their own figures; the single g/kg study contributes direction only, and no values are pooled. The largest transfers occur between the intermediate and higher classes, while the non-saline class changes little in most settings; intensification of already salt-affected land therefore predominates over conversion of new land, though the latter also occurs (Bachu County). The drivers reported by the source studies are irrigation expansion, inadequate drainage, and shallow saline groundwater, with rising evaporative demand and reduced leaching as amplifiers; since no study partitions the change between climatic and management causes, this ordering is descriptive, not a causal attribution. The synthesis is hypothesis-generating; its main product is a direction-of-change summary table separating observed trends from projections.
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(This article belongs to the Section Climate and Environment)
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Open AccessArticle
Comparative Evaluation of Machine Learning Models for Global Horizontal Irradiance Estimation in an Arid Coastal Climate
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Jimmy Rosales-Huamaní, Odón Sánchez-Ccoyllo, María Álvarez-Paucar and Oscar Toapanta-Cunalata
Climate 2026, 14(9), 183; https://doi.org/10.3390/cli14090183 - 3 Sep 2026
Abstract
Accurate estimation of global horizontal irradiance (GHI) is relevant for characterizing solar resources in regions with limited measurement infrastructure. This study compared six machine learning models Polynomial Ridge Regression, Decision Tree, Random Forest, XGBoost, Artificial Neural Network, and K-Nearest Neighbors for the contemporaneous
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Accurate estimation of global horizontal irradiance (GHI) is relevant for characterizing solar resources in regions with limited measurement infrastructure. This study compared six machine learning models Polynomial Ridge Regression, Decision Tree, Random Forest, XGBoost, Artificial Neural Network, and K-Nearest Neighbors for the contemporaneous estimation of GHI at a five-minute resolution in an arid coastal climate. After quality control and restriction to daytime periods, 45,024 observations were analyzed using five external chronological blocks with an expanding-window scheme, generating 31,517 out-of-sample estimates. XGBoost achieved the highest and the lowest RMSE (108.01 ± 13.67 W m ), whereas Random Forest yielded lower MAE, WMAPE, and MASE values. DM–HAC sensitivity analysis favored XGBoost under squared-error loss for six of the seven evaluated bandwidths, whereas no significant difference between XGBoost and Random Forest was found under absolute-error loss. None of the models achieved the nominal conformal coverage level of 90%; XGBoost showed the highest empirical coverage and the narrowest prediction intervals (PICP = 0.791; PINAW = 0.312). Predictor-set reduction improved the performance of four of the six algorithms. Overall, XGBoost and Random Forest exhibited complementary performance profiles, indicating that model selection should jointly consider predictive accuracy, temporal stability, predictor sensitivity, and uncertainty.
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(This article belongs to the Special Issue Meteorological Forecasting and Modeling in Climatology)
Open AccessArticle
Integrating Hydro-Geomorphological Analysis into Regional Sediment Management: Insights from the Rio Geremeas Basin (Sardinia, Italy)
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Demurtas Valentino, Sulis Andrea, Azzena Costantino, Alemanni Federico, Carboni Andrea, Luise Giovanni, Manconi Veronica, Mancosu Gianluigi, Sabatini Andrea, Santona Giulio, Orrù Paolo Emanuele and Deiana Giacomo
Climate 2026, 14(9), 182; https://doi.org/10.3390/cli14090182 - 2 Sep 2026
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Mitigating flood risk and planning river corridors in Torrent-type Basins (TBs) requires integrated frameworks that link hydro-geomorphological processes with ecological quality, a combination currently lacking in regional planning. This study presents an integrated hydro-geomorphological and ecological analysis of the Rio Geremeas catchment (Sardinia,
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Mitigating flood risk and planning river corridors in Torrent-type Basins (TBs) requires integrated frameworks that link hydro-geomorphological processes with ecological quality, a combination currently lacking in regional planning. This study presents an integrated hydro-geomorphological and ecological analysis of the Rio Geremeas catchment (Sardinia, Italy), developed within the Regional Sediment Management Plan (PGS). The approach combines multi-scale geomorphological mapping, the IDRAIM eco-morphological framework, and 2D hydro-morphodynamic modelling (MIKE 21C), supported by field surveys and remote sensing of sediment source areas and biological assemblages (riparian vegetation, macroinvertebrates, and fish). Results reveal a direct link between altered sediment dynamics and ecological degradation, with confined reaches showing lower biotic diversity compared to mobile, morphologically functional reaches. 50-year flood simulations identified critical erosion/deposition zones, guiding targeted proposals: restoring sediment continuity by removing hydraulic constraints, controlling invasive species, and managing the river mouth to favour the migration of the European eel. This work provides a transferable, interdisciplinary approach for sediment- and ecosystem-informed river basin planning, directly supporting the EU Water Framework Directive and climate resilience strategies.
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Open AccessArticle
Error Variations in the Sub-Seasonal Precipitation Prediction of the BCC-CPS-S2Sv2 in Summer over China
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Yifan Wang, Ya Tuo, Qingquan Li and Guolin Feng
Climate 2026, 14(9), 181; https://doi.org/10.3390/cli14090181 - 1 Sep 2026
Abstract
The application of sub-seasonal prediction error analysis and interpretation remains a key research frontier of climate prediction. Related studies are essential for deepening the understanding of model performance, investigating error sources, and improving model prediction accuracy. Based on four perspectives—basic characteristics, spatial and
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The application of sub-seasonal prediction error analysis and interpretation remains a key research frontier of climate prediction. Related studies are essential for deepening the understanding of model performance, investigating error sources, and improving model prediction accuracy. Based on four perspectives—basic characteristics, spatial and temporal consistency, and potential causes of prediction errors—this study systematically investigates the sub-seasonal hindcast errors of summer precipitation over China from the state-of-the-art model system BCC–CPS–S2Sv2 (S2Sv2). The findings reveal that (1) S2Sv2 shows significant prediction skill in the first three pentads and shows an obvious increase in RMSE and a decrease in SCC of the precipitation prediction. This feature is quite similar to other operational models. (2) The prediction error primarily presents typical modes such as the meridional dipole, triple or consistent patterns. Prediction errors maintain spatial consistency in South China, the middle and lower reaches of the Yangtze River, and North China. Temporal consistency of the prediction errors shows a significant correlation between neighboring pentads, which diminishes as the prediction period extends, with a better correlation lasting for 2–4 pentads in some areas. (3) The prediction errors of S2Sv2 are significantly correlated with major circulation patterns in East Asia and key area sea surface temperatures (SSTs). For instance, errors are larger when the West Pacific Subtropical High is stronger, but smaller when the East Asia Trough is stronger. Errors also decrease with higher SSTs in the central equatorial Pacific and increase with higher SSTs in the tropical North Atlantic. This study provides valuable insights into the limitations of the S2Sv2 model and offers important references for error correction and model application.
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(This article belongs to the Section Climate Dynamics and Modelling)
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Open AccessArticle
Factors Contributing to the Effectiveness Ratings of the Climate Change Adaptation Projects in Agriculture: Implications from the Developing Countries
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Yuki Shiga and Rajib Shaw
Climate 2026, 14(9), 180; https://doi.org/10.3390/cli14090180 - 1 Sep 2026
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As the impact of climate change becomes increasingly disruptive worldwide, the gap in adaptation finance is widening. Despite advancements in adaptation planning and implementation in every sector and region, the growing resource gap necessitates more ‘effective’ climate adaptation projects. Against this backdrop, the
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As the impact of climate change becomes increasingly disruptive worldwide, the gap in adaptation finance is widening. Despite advancements in adaptation planning and implementation in every sector and region, the growing resource gap necessitates more ‘effective’ climate adaptation projects. Against this backdrop, the purpose of this paper is to provide an exploratory analysis to identify and examine potential factors associated with the effectiveness ratings of multilateral-funded agricultural climate adaptation projects that have been implemented on the ground, completed and documented. Forty-four projects from multilateral funds were collected and analyzed for this purpose. The study employed a two-pronged approach to cross-complement the implications—key contributing factors to the effectiveness, rated per the actual outcome of the projects, were identified from the terminal evaluation documents of the highly satisfactory and unsatisfactory projects (conventional content analysis); and, effectiveness ratings were assessed against various socio-economic indicators of the countries where the projects were executed through Spearman’s correlation analysis to identify the possible association. The results implied that the contributing factors associated with the effectiveness ratings converge around several elements: (i) capacity building and education; (ii) local engagement and social inclusion; (iii) healthy and resilient livelihood; and, (iv) governance and commitment. Additionally, social inequality indicated its relevance to the project effectiveness ratings. While effectiveness ratings were found to have a positive and moderate correlation (r: 0.274; p < 0.1) with Inequality-adjusted Human Development Index (IHDI), such a correlation was not explicit with HDI. In addition, the study found strong correlations with multiple ‘inequality’ indicators—the gender inequality index, inequality-adjusted life expectancy index and inequality-adjusted income index. These results from the various ‘inequality-adjusted’ indexes further suggest the importance of considering all levels of the community, particularly those groups in the most disadvantageous positions, often farmers, to close the inequality gap. Overall, the findings and implications from this study are expected to provide a basis for future climate adaptation investments in agriculture.
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Open AccessArticle
Basin-Scale Vegetation Sensitivity to Relative Humidity Variability Across Türkiye Under CMIP6 SSP Pathways
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Mehmet Ali Çelik, Adile Bilik, Yasin Paşa and Ishak Pacal
Climate 2026, 14(9), 179; https://doi.org/10.3390/cli14090179 - 1 Sep 2026
Abstract
Relative humidity (RH) provides complementary information on atmospheric moisture conditions that is not captured by precipitation alone. This study characterizes basin-scale RH-associated vegetation sensitivity across Türkiye’s 25 hydrographic basins using MODIS MOD13A1 NDVI observations for 2000–2024 and processed CMIP6-derived RH products for SSP1-2.6,
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Relative humidity (RH) provides complementary information on atmospheric moisture conditions that is not captured by precipitation alone. This study characterizes basin-scale RH-associated vegetation sensitivity across Türkiye’s 25 hydrographic basins using MODIS MOD13A1 NDVI observations for 2000–2024 and processed CMIP6-derived RH products for SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 at the 2040, 2060, 2080 and 2100 single-year horizons. MODIS and climate-model products are summarized independently at basin scale, avoiding pixel-level fusion across different native resolutions. The archived 25-by-4 pathway sensitivity matrix is evaluated using cross-pathway dispersion, a robust median-magnitude check, hierarchical clustering with silhouette diagnostics, and explicit percentile-based hotspot criteria. Mean absolute sensitivity is 0.0244, 0.0236, 0.0368, and 0.0386 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. Antalya, Küçük Menderes, Konya Closed, Ceyhan, and Aras satisfy the magnitude and persistence criteria, and all five also exceed the upper-quartile threshold for median absolute sensitivity. Silhouette diagnostics do not support a unique three-cluster solution, favoring explicit threshold-based response classes. The results are interpreted as comparative basin screening rather than causal attribution or validated vegetation forecasting. Because the retained processed products do not preserve model/member provenance or the horizon-level intermediate values used to generate the pathway index, model-specific and predictive interpretations are deliberately avoided.
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(This article belongs to the Special Issue Evolving Plant Phenology Responses and Resilience in a Changing Climate)
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Open AccessArticle
Response of Mesospheric Temperature and Water Vapor to Volcanic Activity
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Xia Sheng, Zheng Sheng and Shengtao Feng
Climate 2026, 14(9), 178; https://doi.org/10.3390/cli14090178 - 30 Aug 2026
Abstract
Stratospheric sulfate aerosol loading from volcanic eruptions conventionally perturbs planetary radiation budgets, inducing either global-scale cooling or regional thermal anomalies. The January 2022 eruption of Hunga Tonga–Hunga Ha’apai constituted a pronounced departure from this archetype. Here, ERA5 reanalysis products are leveraged to characterise
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Stratospheric sulfate aerosol loading from volcanic eruptions conventionally perturbs planetary radiation budgets, inducing either global-scale cooling or regional thermal anomalies. The January 2022 eruption of Hunga Tonga–Hunga Ha’apai constituted a pronounced departure from this archetype. Here, ERA5 reanalysis products are leveraged to characterise thermodynamic and moisture perturbations at 0.01 hPa (~80 km) throughout the post-eruptive interval. The submarine event delivered approximately 146 Tg of water vapour into the stratosphere, with the plume ascending to 57 km and penetrating the tropical tropopause; a substantial fraction of this anomalous moisture subsequently persisted at mesopause altitudes, forming a reservoir that dissipates only gradually and perturbs upper-atmospheric chemistry across multi-year horizons. Nonlinear interactions between radiative forcing and dynamical feedbacks, both attributable to this exceptional water vapour burden, are elucidated. These observational constraints should advance understanding of upper-atmospheric responses to major volcanic events characterised by substantial water vapour emission.
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(This article belongs to the Section Weather, Events and Impacts)
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Open AccessEssay
The Climate Bathtub at 25: Expanding a Popular Physical Metaphor to Illuminate Social Challenges of Climate Change
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Jonah Busch
Climate 2026, 14(9), 177; https://doi.org/10.3390/cli14090177 - 28 Aug 2026
Abstract
The “climate bathtub,” originated by Linda Booth Sweeney and John Sterman in 2001, has provided an elegant metaphor for the physical problem of climate change for 25 years. In this metaphor, as long as inflows of water into a bathtub from a faucet
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The “climate bathtub,” originated by Linda Booth Sweeney and John Sterman in 2001, has provided an elegant metaphor for the physical problem of climate change for 25 years. In this metaphor, as long as inflows of water into a bathtub from a faucet (greenhouse gas emissions) exceed outflows through a drain (removals), then the stock of water in the bathtub (atmospheric concentrations) will rise, with eventual consequences when the bathtub overflows. This bathtub metaphor is simple, relatable, urgent, and apt. But climate change is a social problem, not just a physical problem. By adding four new elements to the climate bathtub—multiple faucets; multiple drains; multiple damage thresholds; and multiple people—the climate bathtub metaphor can illuminate a wide range of social challenges related to climate change. This expanded climate bathtub metaphor offers insights on how individuals prioritize climate actions; why collective disagreements emerge; and hierarchical levels of climate cooperation. It suggests heuristics that policymakers, practitioners, and future climate professionals can use to evaluate potential climate actions. This more complex, but more versatile, version of the climate bathtub can supplement the original metaphor as a public communications tool and motivator for climate action.
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(This article belongs to the Section Climate and Economics)
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Open AccessPerspective
Oxygen Footprint Regulates Dryland Carbon Cycling
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Dongliang Han, Jianping Huang, Lei Ding and Guolong Zhang
Climate 2026, 14(9), 176; https://doi.org/10.3390/cli14090176 - 26 Aug 2026
Abstract
In the Anthropocene, dryland ecosystems—natural and semi-natural ecosystems—are highly sensitive to anthropogenic warming, and their carbon cycling dynamics are easily disrupted by this trend. In this perspective, we propose a novel yet long-overlooked conceptual framework. It reveals that the oxygen footprint, defined as
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In the Anthropocene, dryland ecosystems—natural and semi-natural ecosystems—are highly sensitive to anthropogenic warming, and their carbon cycling dynamics are easily disrupted by this trend. In this perspective, we propose a novel yet long-overlooked conceptual framework. It reveals that the oxygen footprint, defined as the atmospheric oxygen consumption-to-production ratio, could serve as an important diagnostic indicator for assessing the impacts of anthropogenic warming on dryland carbon cycling. This framework can be divided into three parts, including the increasing oxygen footprint, warming effects on dryland carbon cycling, and direct or indirect links between oxygen footprint and carbon-cycle responses. In short, it centers on the core logical chain: oxygen footprint-anthropogenic warming-dryland carbon cycling. This work strives to enhance dryland sustainability by filling essential knowledge gaps, combining separate research findings, and providing actionable field guidance for ecosystem management.
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(This article belongs to the Special Issue Climate-Ecosystem Feedbacks in Cold and Arid Regions)
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Open AccessArticle
Towards Integrated Climate Services: Platforms Supporting Environmental and Agricultural Resilience in Portugal
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Carlos A. Pereira, João Ferreira, Vanda C. Pires, Paula Drumond, Eduardo Castanho, Ricardo Deus, Tânia Moura and Rita M. Durão
Climate 2026, 14(9), 175; https://doi.org/10.3390/cli14090175 - 26 Aug 2026
Abstract
The Portuguese agricultural sector has suffered a profound transformation over recent decades, evolving from traditional to increasingly technology-driven systems. Throughout this transition, climate and meteorological conditions have remained key drivers of agricultural productivity. Today, Portuguese agriculture faces growing challenges associated with climate change,
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The Portuguese agricultural sector has suffered a profound transformation over recent decades, evolving from traditional to increasingly technology-driven systems. Throughout this transition, climate and meteorological conditions have remained key drivers of agricultural productivity. Today, Portuguese agriculture faces growing challenges associated with climate change, including more frequent and intense heatwaves, droughts, and floods. Consequently, reliable climate information and decision-support tools are essential for strengthening resilience and promoting sustainable management. To address these needs, the Portuguese Institute for the Sea and Atmosphere (IPMA) developed two complementary climate service platforms for mainland Portugal: AgroClima and DataClima. The first provides observations from IPMA’s meteorological network, ECMWF forecasts, and agroclimatic indicators such as temperature, precipitation, soil water, and so-called agroclimatic warnings. The second offers historical climate information including WRFv4.2 simulations dynamically downscaled from ERA5 (1981–present), in situ observations (1941–present), and climate normals. Evaluation of the WRFv4.2 regionalization against IPMA observations shows a systematic underestimation of precipitation and air temperature, while mean wind speed is generally overestimated. Despite these biases, the downscaled WRFv4.2 dataset demonstrates sufficient accuracy to support operational climate services, providing valuable help for environmental monitoring, climate adaptation, and decision-making in agriculture and water resource management across Portugal.
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(This article belongs to the Section Climate Adaptation and Mitigation)
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Open AccessArticle
An Early Documented Late-Spring Heatwave in Iberia Under Pre-Industrial Climatic Conditions
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Maite deCastro, José González-Cao, Nicolás G. deCastro, María Cruz Gallego, José M. Vaquero, Ricardo M. Trigo and Moncho Gómez-Gesteira
Climate 2026, 14(9), 174; https://doi.org/10.3390/cli14090174 - 26 Aug 2026
Abstract
Early instrumental meteorological observations are essential for identifying and characterizing extreme climate events prior to the modern observational era, particularly in regions where historical data are scarce. This study documents a remarkable late-spring heatwave using newly recovered daily temperature observations from Ferrol (northwestern
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Early instrumental meteorological observations are essential for identifying and characterizing extreme climate events prior to the modern observational era, particularly in regions where historical data are scarce. This study documents a remarkable late-spring heatwave using newly recovered daily temperature observations from Ferrol (northwestern Spain) for the period 1792–1795, retrieved from the Historical Archive of the Royal Institute and Observatory of the Spanish Navy. Despite the temporal limitations of this early dataset, its daily resolution enables a detailed analysis of short-term climatic variability and extreme temperature events. The analysis reveals an extraordinary warm episode in late May 1795, characterized by sustained positive temperature anomalies that stand out clearly against the surrounding days. Comparison with the modern climate indicates that the event was exceptional even by present-day standards, with mean temperatures approximately 2 °C above the current 95th percentile. To assess the spatial extent of the heatwave, we compared the Ferrol data with contemporaneous instrumental records from Madrid, Barcelona, and Cádiz. All three locations exhibit synchronous, pronounced positive anomalies, demonstrating that the 1795 event was a large-scale phenomenon affecting most of the Iberian Peninsula. This study highlights the critical value of historical data rescue for contextualizing modern climate extremes and extending our understanding of regional climate variability.
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(This article belongs to the Special Issue The Importance of Long Climate Records (Second Edition))
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Open AccessArticle
Impacts of Solar Radiation Modification on Extreme Climate Indices in the Philippines
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Patricia Ann A. Jaranilla-Sanchez, Hanz Lester C. Lunas, Catherine B. Gigantone, Michael Jason L. Mozo, Emmanuel Zeus S. Gapan, Keane Carlo G. Lomibao, Allan T. Tejada, Jr. and Rodel D. Lasco
Climate 2026, 14(9), 173; https://doi.org/10.3390/cli14090173 - 24 Aug 2026
Abstract
The rising global temperature and changing climate patterns have increased the frequency and intensity of extreme heat events, droughts, and heavy precipitation, significantly affecting agriculture, water resources, and ecosystems. Solar radiation management (SRM) has been proposed as a geoengineering strategy to mitigate these
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The rising global temperature and changing climate patterns have increased the frequency and intensity of extreme heat events, droughts, and heavy precipitation, significantly affecting agriculture, water resources, and ecosystems. Solar radiation management (SRM) has been proposed as a geoengineering strategy to mitigate these effects by reducing incoming solar radiation. This study evaluated future trends and variability in rainfall and temperature extremes in the Philippines under GeoMIP (G6Solar and G6Sulfur) and ScenarioMIP (SSP2-4.5 and SSP5-8.5) projections. Using five General Circulation Models (GCMs) and a suite of 10 climate indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), changes in extreme precipitation and temperature across different climate zones in the Philippines were assessed. Climate projections for the future (2041–2070) scenario were analyzed using bias correction, downscaling, and spatial interpolation techniques. Trend analysis was evaluated using the Mann–Kendall test and Sen’s slope estimator, while variability was assessed through statistical methods. The results show widespread warming and increased extreme precipitation, but these trends vary significantly across regions. Non-uniform responses emerge across scenarios, with some northern regions experiencing decreases in specific precipitation indices despite the broader warming trend under SRM and non-SRM conditions. These findings provide critical insights into the potential impacts of SRM on future climate extremes in the Philippines and guidance on climate policy recommendations for decision-makers and stakeholders.
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(This article belongs to the Section Climate Adaptation and Mitigation)
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Open AccessArticle
Observed and Simulated Decadal Variability of Precipitation in North Africa and the Mediterranean: Insights from ERA5 Reanalysis and CORDEX-CORE Simulations
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Faustin Katchele Ogou, Khadija Arjdal and Fatima Driouech
Climate 2026, 14(9), 172; https://doi.org/10.3390/cli14090172 - 24 Aug 2026
Abstract
Climate change and variability pose serious threats to natural and human systems. The Mediterranean and North Africa (MNA) are among the world’s climate change hotspots. An in-depth understanding of the decadal climate variability in this region is critical to support planning and management,
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Climate change and variability pose serious threats to natural and human systems. The Mediterranean and North Africa (MNA) are among the world’s climate change hotspots. An in-depth understanding of the decadal climate variability in this region is critical to support planning and management, as well as adaptation in important sectors such as water resources. Therefore, in this study, fifth-generation ECMWF atmospheric reanalysis (ERA5) precipitation data and the outputs of the Coordinated Regional Downscaling Experiment-COmmon Regional Experiment (CORDEX-CORE) regional models were used to characterize the decadal precipitation variability in MNA and its sub-regions (Western North Africa: WNA, Sahara: SAH, southern Mediterranean: SMED, and northern Mediterranean: NMED). The models showed overestimation in most areas and underestimation in a few areas relative to the ERA5 data, with the magnitude varying by region and season. The positive biases obtained from the regional climate models (RCMs) were higher than the positive biases obtained from the general circulation models (GCMs). The wet biases were dominant during the annual, summer, and autumn seasons over MNA and its sub-regions. Negative biases were mostly associated with GCMs, mainly HadGEM2-ES and/or NorESM1-M; meanwhile, they were linked with RCMs such as CCLM5-0-15 and/or RegCM4_v7 and were mostly obtained in winter and spring. The multi-model mean (MME) was better at reproducing the decadal precipitation patterns over MNA, SMED, and NMED at all time scales, while REMO2015-NorESM1-M and the MME performed better than the remaining models at the annual time scale over WNA and SAH. These findings are useful for improving climate modeling, the water resources management and related sectors, and climate adaptation strategies in the region, especially in North Africa. The short-period coverage of the simulated data available for this study constitutes a limitation to the findings.
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(This article belongs to the Special Issue The Dynamics and Impacts of Ocean-Atmosphere Coupling on Regional and Global Climate)
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Open AccessArticle
Climate Change and Poverty in the MENA Region: Evidence from a Panel ARDL Model Using Household Consumption and Infant Mortality
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Aziz Razzouki, Mounsif Ridaoui, Fadma Razzouki, Mohamed Oudgou, Mustapha Ouatmane and Abdeslam Boudhar
Climate 2026, 14(9), 171; https://doi.org/10.3390/cli14090171 - 23 Aug 2026
Abstract
Climate change is becoming an increasingly important source of economic and health vulnerability in developing countries. This study examines the dynamic relationship between climate change and poverty across 22 countries in the Middle East and North Africa (MENA) region from 2000 to 2023.
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Climate change is becoming an increasingly important source of economic and health vulnerability in developing countries. This study examines the dynamic relationship between climate change and poverty across 22 countries in the Middle East and North Africa (MENA) region from 2000 to 2023. Poverty is captured through two indicators: household consumption expenditure, the monetary dimension, and infant mortality, the non-monetary dimension. Methodologically, the analysis relies on a panel autoregressive distributed lag (panel ARDL) model, estimated using the Pooled Mean Group (PMG) and Mean Group (MG) approaches. The results reveal a long-run relationship among climatic variables, macroeconomic factors, and poverty-related indicators. In the long run, precipitation is associated with a decline in household consumption expenditure, while temperature is associated with higher infant mortality, indicating a deterioration in both monetary and health-related well-being under changing climatic conditions. In the short run, rising temperatures are also associated with lower household consumption expenditure, revealing the immediate vulnerability of living standards to climate shocks. In addition, GDP per capita is associated with higher household consumption and lower infant mortality, while education is associated with lower health-related poverty. Inflation appears to exacerbate poverty, whereas the positive association between health expenditure and infant mortality suggests reverse causality or inefficiencies in the allocation of health resources. These findings highlight the need to articulate climate adaptation strategy, macroeconomic stability, education investment, and improved efficiency of health spending in order to achieve sustainable reduction in poverty in the MENA region.
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(This article belongs to the Special Issue Climate Adaptation and Resilience Economics)
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Open AccessArticle
Determinants of Drought Adaptation Under Climate Change Among Rice-Farming Households in the Northernmost Region of Thailand
by
Pussadee Laor, Wanvisa Saisanan Na Ayudhaya, Sirinthip Rakjun, Pannipha Dokmaingam, Vivat Keawdounglek, Anuttara Hongtong, Weerayuth Siriratruengsuk, Krailak Fakkaew, Thitipong Sukdee and Rohmatul Fajriyah
Climate 2026, 14(8), 170; https://doi.org/10.3390/cli14080170 - 20 Aug 2026
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Rice farmers in Chiang Rai are increasingly exposed to recurrent drought under climate change. Although previous studies have applied Knowledge–Attitude–Practice (KAP) frameworks to drought adaptation, evidence on ageing farming populations and the interaction between behavioral and institutional factors remains limited. This study aimed
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Rice farmers in Chiang Rai are increasingly exposed to recurrent drought under climate change. Although previous studies have applied Knowledge–Attitude–Practice (KAP) frameworks to drought adaptation, evidence on ageing farming populations and the interaction between behavioral and institutional factors remains limited. This study aimed to identify behavioral and institutional factors associated with drought adaptation practices among rice-farming households. A cross-sectional study was conducted among 180 rice-farming households. Quantitative data were collected using a structured questionnaire validated through expert review (IOC) and pilot testing to assess socio-demographic characteristics and drought-related perception, knowledge, attitudes, and practices (KAP). Pearson correlation and binary logistic regression were applied to examine relationships and factors associated with higher drought adaptation practices. Qualitative data from open-ended questionnaire responses regarding government support and drought management recommendations were analyzed thematically to provide contextual insights into farmers’ experiences and adaptation challenges. Farmers demonstrated high drought perception (M = 4.86 ± 1.05/5) but only moderate knowledge (16.75 ± 3.36/25), attitudes (2.77 ± 1.33/5), and practices (22.57 ± 6.04/35). Knowledge was positively associated with adaptation practices (r = 0.224, p < 0.01), whereas perception showed no significant direct association, indicating a gap between awareness and adaptive action. Regression analysis showed that higher drought-related knowledge (aOR = 4.60, p = 0.003) and prior water scarcity experience (aOR = 4.45, p = 0.002) were significantly associated with higher drought adaptation practices. In contrast, older age, male gender, and off-farm employment were significant constraints. Qualitative findings highlighted persistent concerns regarding the adequacy, timeliness, and equity of government support, suggesting that institutional barriers limited farmers’ ability to translate awareness into adaptive action. These findings indicate that both behavioral and structural factors shape drought adaptation practices. While drought-related knowledge represents an important component of adaptive capacity, effective adaptation also depends on institutional support and resource accessibility. Strengthening agricultural extension services and improving the responsiveness and equity of government support may enhance the adaptive capacity and resilience of smallholder rice farmers in drought-prone regions.
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Open AccessArticle
Between Individual Belief and National Context: Relative Positioning and Expectations of Collective Climate Action in Europe
by
João Carlos de Sousa and Luísa Schmidt
Climate 2026, 14(8), 169; https://doi.org/10.3390/cli14080169 - 18 Aug 2026
Abstract
Expectations regarding collective climate action are multidimensional and should be understood in relation to the social contexts in which they are embedded. This study examines whether these expectations are associated with the country-level average belief in the anthropogenic origin of climate change and
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Expectations regarding collective climate action are multidimensional and should be understood in relation to the social contexts in which they are embedded. This study examines whether these expectations are associated with the country-level average belief in the anthropogenic origin of climate change and with individuals’ deviation from that average. Drawing on Round 10 of the European Social Survey, the analysis utilizes 24,014 valid cases from 29 European countries. It estimates Complex Samples General Linear Models (CSGLM) to account for the complex sampling design. The results show that the country-level average belief in the anthropogenic origin of climate change is positively associated with expectations of collective climate action; that is, countries with a higher average belief exhibit higher expectations of collective climate action. Conversely, individuals whose belief in the anthropogenic origin of climate change exceeds the respective country-level average tend to express lower expectations of collective climate action. This negative association becomes stronger at higher levels of climate worry and is attenuated as ideological positioning moves towards the right; in contrast, trust in scientists does not have a significant moderating effect. Overall, the findings support a socially contextualized understanding of expectations of collective climate action, in which both national belief contexts and individuals’ relative positioning within those contexts are relevant.
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(This article belongs to the Section Policy, Governance, and Social Equity)
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Open AccessArticle
Climate Change Impacts on Agroforestry Suitability in the Amazon: CMIP6-Based Projections for Theobroma grandiflorum
by
Waléria Pereira Monteiro Corrêa, Leonardo de Sousa Miranda, Luciano Jorge Serejo dos Anjos, Thaiane Soeiro da Silva Dias, José Felipe Gazel Menezes and Everaldo Barreiros de Souza
Climate 2026, 14(8), 168; https://doi.org/10.3390/cli14080168 - 18 Aug 2026
Abstract
Climate change is expected to significantly alter surface air temperature and precipitation regimes across the Amazon Basin, with direct implications for agroforestry systems and climate-sensitive perennial crops. This study projects the impacts of anthropogenic global warming on the habitat suitability of Theobroma grandiflorum
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Climate change is expected to significantly alter surface air temperature and precipitation regimes across the Amazon Basin, with direct implications for agroforestry systems and climate-sensitive perennial crops. This study projects the impacts of anthropogenic global warming on the habitat suitability of Theobroma grandiflorum (cupuaçu), a keystone species for Amazonian agroforestry, local livelihoods, and the bioeconomy. Using an ensemble species distribution modeling (SDM) framework, we applied multiple algorithms and two CMIP6 global climate models (BCC-CSM2-MR and MIROC6) under the SSP3-7.0 and SSP5-8.5 scenarios for the near-future (2021–2040) and far-future (2061–2080). Contrary to the range contractions projected for many Amazonian endemics, our ensemble projections reveal a consistent trend of expanding climatically suitable area, primarily into adjacent ecological transition zones. This expansion is driven largely by basin-wide increases in mean annual temperature, the most influential predictor in our modeling study. Quantitatively, we project a net habitat expansion of 32.2% (415,114 km2) under high-concordance future scenarios. A core climate refuge of 955,570 km2, representing 74.2% of the current suitable range, is identified as a high priority for in situ conservation. Conversely, approximately 25.8% of the current range (331,919 km2) may become climatically unsuitable, particularly in parts of the western Amazon. These findings suggest that reducing thermal constraints in currently marginal areas could open opportunities for integrating cupuaçu into climate-resilient agroforestry systems beyond its present distribution. Such heterogeneous responses of Amazonian agroforestry species to climate change highlight the importance of incorporating species-specific climate sensitivities into adaptation planning, land-use strategies, and climate-resilient bioeconomy policies under future warming scenarios.
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(This article belongs to the Special Issue Climate Risk in Agriculture, Analysis, Modeling and Applications)
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Open AccessReview
Mediterranean Ornamental Horticulture Under Climate Change: Impacts and Adaptation Strategies—A Systematic Review
by
Emmanouela Kamperi, Apostolos-Emmanouil Bazanis and Konstantinos Bertsouklis
Climate 2026, 14(8), 167; https://doi.org/10.3390/cli14080167 - 18 Aug 2026
Cited by 1
Abstract
Climate change increasingly threatens Mediterranean ornamental horticulture and green infrastructure through elevated temperatures, prolonged drought conditions, soil salinity, and more frequent extreme weather events. As a result, plant growth, phenology and landscape sustainability are significantly affected. This systematic review aimed to identify and
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Climate change increasingly threatens Mediterranean ornamental horticulture and green infrastructure through elevated temperatures, prolonged drought conditions, soil salinity, and more frequent extreme weather events. As a result, plant growth, phenology and landscape sustainability are significantly affected. This systematic review aimed to identify and qualitatively synthesize the available evidence on the responses of ornamental plants and their production and end use systems to climate-related stress, with emphasis on Mediterranean native species and their potential contribution to climate-resilient landscaping. The review was conducted and reported in accordance with PRISMA 2020. An adapted Population–Exposure–Outcome framework was used to operationalize the overarching review question and guide eligibility assessment. Scopus and the Web of Science Core Collection were systematically searched for peer-reviewed English-language articles published between 1 January 2001 and 31 May 2026. Eligible publications examined ornamental plants, floricultural species, or native and endemic taxa with potential ornamental or landscape use and addressed climate-related stressors, plant resilience, adaptation strategies, cultivation or propagation practices, green-infrastructure applications, or related ecological trade-offs in Mediterranean-relevant contexts. Two reviewers independently assessed titles, abstracts, and full texts using predefined eligibility criteria. The review used a structured qualitative narrative synthesis organized into thematic domains to systematically identify, select, and synthesize the available evidence. Meta-analysis was not undertaken because of substantial heterogeneity in plant material, environmental stressors, study designs, and reported outcomes. A total of ninety studies were included and organized into five domains: climate stress and plant responses (n = 14), native Mediterranean ornamental species (n = 21), adaptation and resilience strategies (n = 16), urban landscaping and green infrastructure (n = 25), and ecological risks and invasive species (n = 14). The review revealed that several native Mediterranean plants possess morphological, physiological, or ecological characteristics associated with tolerance to drought, salinity, and other climate-related stresses, supporting their potential use in sustainable ornamental horticulture. Water-efficient irrigation, alternative water sources and substrates, nursery preconditioning, non-microbial biostimulants, and genotype or physiological screening showed adaptation potential, but their effectiveness depended on species, genotype, intervention intensity, and application context. Evidence remained limited for compound stresses, combined interventions, nursery-to-landscape transfer, long-term field performance, commercial scalability, and environmental trade-offs. Overall, climate-resilient ornamental horticulture requires the integration of plant selection, propagation, production, controlled stress screening, landscape validation, and ecological-risk assessment. This review proposes an evidence-to-application framework to support research, nursery production, landscape planning, and the responsible deployment of climate-adapted ornamental plants.
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(This article belongs to the Special Issue Climate Variability in the Mediterranean Region (Second Edition))
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Open AccessArticle
Long-Term Changes in Thickness Temperature of the Lower Atmosphere Calculated from Air Pressure Data in the Central Mountain Region, Japan
by
Fumiaki Fujibe
Climate 2026, 14(8), 166; https://doi.org/10.3390/cli14080166 - 18 Aug 2026
Abstract
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Changes in the thickness temperature (TT) of the lower atmosphere from 1961 to 2025 were investigated using air pressure data from eight stations in the Central Mountain region of Japan. The stations were located at elevations ranging from 400 m to 1300 m
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Changes in the thickness temperature (TT) of the lower atmosphere from 1961 to 2025 were investigated using air pressure data from eight stations in the Central Mountain region of Japan. The stations were located at elevations ranging from 400 m to 1300 m above sea level. The average linear trend in TT at these stations was 0.25 °C per decade, which was close to the air temperature trend at non-urban stations in the surrounding coastal areas. Despite the presence of some divergence in TT trends across the stations, TT is expected to serve as a complementary index for climate change research, since concerns about spatial representativeness and temporal homogeneity exist in air temperature data.
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Open AccessArticle
Performance of CMIP6 GCMs in Representing Extreme Precipitation in Peru (1981–2014)
by
Gustavo De la Cruz, Eduardo Chávarri-Velarde and Waldo Lavado-Casimiro
Climate 2026, 14(8), 165; https://doi.org/10.3390/cli14080165 - 18 Aug 2026
Abstract
Extreme climate events, particularly precipitation extremes, pose significant risks to ecosystems, infrastructure, and socio-economic systems globally. In Peru, the diversity of its climate, driven by its complex topography, makes it highly vulnerable to such events, especially in the Andes and Amazon regions. This
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Extreme climate events, particularly precipitation extremes, pose significant risks to ecosystems, infrastructure, and socio-economic systems globally. In Peru, the diversity of its climate, driven by its complex topography, makes it highly vulnerable to such events, especially in the Andes and Amazon regions. This study evaluates the performance of 25 CMIP6 GCMs in simulating extreme precipitation events during both the wet and dry seasons at the national level. Gridded precipitation data from the PISCO product and CMIP6 model simulations for the period 1981–2014 were used to estimate extreme precipitation indices, including Rx1day, Rx5day, SDII, CDD, CWD, R10mm, and PRCPTOT. Performance was assessed using statistical metrics such as PBIAS, NRMSE, and the Pattern Correlation Coefficient (PCC), integrated through a TOPSIS ranking. Results indicate that NorESM2-MM, MPI-ESM1-2-LR, and CESM2 exhibit the best performance, achieving TOPSIS scores above 0.8. These models show high spatial correlation (PCC frequently >0.8) and relatively low biases. In contrast, models like FGOALS-g3 and CanESM5 show significant limitations, with PBIAS exceeding 80% in Rx1day and Rx5day and TOPSIS scores below 0.5. The ensemble reveals a persistent ‘drizzle bias,’ with wet day frequency (R1mm) generally overestimated by 20–40% in the wet season and by 40–80% during the dry season across most CMIP6 models. Furthermore, indices of temporal persistence (CWD and CDD) remain the most challenging, with CWD overestimations often exceeding 100–200%. These findings highlight the critical need for statistical or dynamical downscaling, together with bias correction, before using CMIP6 projections for local adaptation strategies in the Andes and Amazon regions.
Full article
(This article belongs to the Section Climate Dynamics and Modelling)
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