Climate

29 pages, 7437 KB

Open AccessArticle

Historical Trend and Future Projection of Extreme Seasonal Precipitation over Ethiopia, East Africa

by Daniel Berhanu, Tena Alamirew, Greg O’Donnell, Claire L. Walsh, Amare Haileslassie, Temesgen Gashaw Tarkegn, Amare Bantider, Solomon Gebrehiwot and Gete Zeleke

Climate 2026, 14(4), 88; https://doi.org/10.3390/cli14040088 - 21 Apr 2026

Cited by 2 | Viewed by 2715

Abstract

East Africa is highly vulnerable to climate change due to limited adaptive capacity and strong reliance on rain-fed agriculture. Ethiopia, in particular, experiences recurrent socio-economic losses from droughts and floods. This study presents a national-scale assessment of observed (1981–2010) and projected (2041–2100) changes [...] Read more.

East Africa is highly vulnerable to climate change due to limited adaptive capacity and strong reliance on rain-fed agriculture. Ethiopia, in particular, experiences recurrent socio-economic losses from droughts and floods. This study presents a national-scale assessment of observed (1981–2010) and projected (2041–2100) changes in extreme seasonal precipitation across Ethiopia using ten ETCCDIs. High-resolution Enhancing National Climate Services (ENACTS) observations and bias-corrected outputs from a selected ensemble of CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios are used to assess historically trends and future extreme precipitation, respectively. Historical trends show increases in extreme precipitation during the Kiremt (JJAS) season, particularly over the northwestern, western, and southwestern highlands; however, most of these increases are not statistically significant. In contrast, the Belg (FMAM) season exhibits widespread declines, which are also largely not statistically significant. Future projections suggest increases in total precipitation (PRCPTOT), heavy (R10) and very heavy rainfall days (R20), very wet days (R95p) and extremely wet days (R95p), and rainfall intensity (SDII) over northwestern, western, southwestern, and parts of northeastern Ethiopia during JJAS. During FMAM, PRCPTOT is projected to increase in the northern and northwestern regions, while decreases are expected in the northeastern and southeastern regions. The Awash and Tekeze basins emerge as key hotspots of change, indicating potential seasonal shifts and an increased likelihood of extreme weather in these regions. Despite inter-model uncertainty, the results highlight the need for flexible, uncertainty-informed adaptation strategies to enhance climate resilience in Ethiopia. Full article

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20 pages, 4249 KB

Open AccessArticle

Prognosis for Brazilian Agricultural Production: The Impact of Drought-Sensitive Crops on the Climate

by João Lucas Della-Silva, Fernando Saragosa Rossi, Damien Arvor, Gabriela Souza de Oliveira, Larissa Pereira Ribeiro Teodoro, Paulo Eduardo Teodoro, Tatiane Deoti Pelissari, Wendel Bueno Morinigo and Carlos Antonio da Silva Junior

Climate 2026, 14(4), 87; https://doi.org/10.3390/cli14040087 - 20 Apr 2026

Viewed by 2237

Abstract

The northern part of the state of Mato Grosso is located at the intersection of large-scale agricultural production and the Amazon, a tropical biome of great importance for ecosystem services and biodiversity. Agricultural production activities interact with natural capital, among other factors, in [...] Read more.

The northern part of the state of Mato Grosso is located at the intersection of large-scale agricultural production and the Amazon, a tropical biome of great importance for ecosystem services and biodiversity. Agricultural production activities interact with natural capital, among other factors, in land use and in biogeochemical cycles of water and carbon. In this study, we sought to use remote sensing at the regional level to diagnose and spatialize the contribution of agricultural activity to dry areas. Using carbon dioxide orbital models, land use classification techniques, the Standardized Precipitation Index (SPI), and Pettitt and Mann–Kendall statistics, the variables were compared spatially for the biogeographic boundary of the Amazon in Mato Grosso in two distinct time frames: (i) over the crop years of the CO₂ efflux model (2020 to 2023), and (ii) over the years 2008 to 2023, with consolidated data from the MODIS sensor system. The hot and cold spots analysis reinforces the correlation of carbon variables to land use; the drought index suggests a spatial correlation to forest loss, where more intense agricultural activity favors drought and inhibits moderate rainfall, and in turn is linked to the amount of forest in the context of intense continentality. Temporally, the statistical diagnosis highlights abrupt changes in 2011, 2013, and 2019, restate the complex relation of tropical forest and biogeochemical cycles, above all with carbon dioxide. Full article

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16 pages, 1989 KB

Open AccessArticle

Evaluating Grazing Management for Drought Reduction Under Different Climate Change Scenarios

by Mohammed Mussa Abdulahi, Pascal E. Egli, Anteneh Belayneh, Yazidhi Bamutaze, Charlotte Anne Nakakaawa and Sintayehu W. Dejene

Climate 2026, 14(4), 86; https://doi.org/10.3390/cli14040086 - 17 Apr 2026

Viewed by 1939

Abstract

Nature-based solutions (NbSs) are increasingly recognized as sustainable and cost-effective strategies for mitigating drought impacts. However, robust quantitative evidence on the effectiveness of NbSs for drought mitigation, especially under future climate change scenarios, remains limited. In particular, the extent to which grazing management [...] Read more.

Nature-based solutions (NbSs) are increasingly recognized as sustainable and cost-effective strategies for mitigating drought impacts. However, robust quantitative evidence on the effectiveness of NbSs for drought mitigation, especially under future climate change scenarios, remains limited. In particular, the extent to which grazing management can reduce agricultural and hydrological droughts over long time horizons is still poorly understood. This study examines the long-term effectiveness of grazing management as a NbS for mitigating drought under historical and future climate conditions in the Ganale Dawa River Basin, Ethiopia. We combined remote sensing, machine learning, and climate projections to simulate soil moisture and runoff using a long short-term memory (LSTM) model. Protected areas were used as proxies for light grazing, while adjacent non-protected areas represented heavy grazing. Agricultural and hydrological droughts were quantified using the standardized soil moisture index (SSMI) and standardized runoff index (SRI), respectively. The results show that light grazing consistently reduced drought severity compared to heavy grazing across all periods. Agricultural drought severity was reduced by up to ~15% under SSP2-4.5 and SSP5-8.5, while hydrological drought severity showed substantially larger reductions, exceeding ~40% in mid- and late-future periods. Differences between grazing regimes widened under stronger climate forcing, indicating that grazing management benefits become more pronounced under future climate stress. These findings demonstrate that grazing management is an effective NbS for enhancing long-term drought resilience. Scaling up sustainable grazing practices could, therefore, serve as a practical climate adaptation strategy for drought-prone basins in Ethiopia and similar regions. Full article

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19 pages, 3646 KB

Open AccessArticle

Impact of Unprotected Area (UPA) Deforestation on Amazonian Climate: Mapping Regional Shifts and Localized Risk

by Corrie Monteverde, Fernando De Sales, Trent W. Biggs, Katrina Mullan, Charles Jones and Mariana Vedoveto

Climate 2026, 14(4), 85; https://doi.org/10.3390/cli14040085 - 16 Apr 2026

Viewed by 1564

Abstract

Deforestation in unprotected areas (UPAs) within the Brazilian Amazon affects environmental sustainability and regional climate. This study quantifies shifts in near-surface air temperature, precipitation, and evapotranspiration (ET) during the dry season resulting from UPA loss. Utilizing a five-year ensemble (2015–2019) to isolate the [...] Read more.

Deforestation in unprotected areas (UPAs) within the Brazilian Amazon affects environmental sustainability and regional climate. This study quantifies shifts in near-surface air temperature, precipitation, and evapotranspiration (ET) during the dry season resulting from UPA loss. Utilizing a five-year ensemble (2015–2019) to isolate the climatic response from interannual variability, simulations indicate a warmer (+1.0 ± 0.4 °C) and drier climate, characterized by a basin-wide 12 ± 8% reduction in precipitation and a 12 ± 4% reduction in ET following UPA removal. This shifted climate state extends to Rondônia, a southwestern state where detailed risk mapping was developed by integrating changes in climate variables with socio-economic, agricultural, and demographic. UPA deforestation, largely external to Rondônia, is associated with a simulated decrease in precipitation by 20 ± 7% and ET by 11 ± 9% coupled with an increase in air temperature by 1.2 ± 0.4 °C. These shifts indicate increased vulnerability for municipalities, including the capital, potentially affecting agricultural productivity. Findings suggest that to protect remaining forests these biophysical risks must be mitigated. This study establishes a spatial framework for identifying municipalities most suceptible to the climatic shifts triggered by UPA loss. Full article

(This article belongs to the Special Issue Climate and Human-Driven Impacts on Tropical Rainforests)

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26 pages, 2596 KB

Open AccessArticle

Effect of Climate Variability on Rice Production in Liberia

by Bondo T. Simpson, Celsa Mondlane Macandza, Jone L. Medja Ussalu, Arsénio D. Ndeve and Luis Artur

Climate 2026, 14(4), 84; https://doi.org/10.3390/cli14040084 - 14 Apr 2026

Cited by 1 | Viewed by 2015

Abstract

Climate variability poses major challenges to agriculture worldwide amid an increasing world population and growing food demand. This study evaluates the impact of climate variability on rice production in Liberia. Rice yields and production data (1990–2023) were attained from the Food and Agriculture [...] Read more.

Climate variability poses major challenges to agriculture worldwide amid an increasing world population and growing food demand. This study evaluates the impact of climate variability on rice production in Liberia. Rice yields and production data (1990–2023) were attained from the Food and Agriculture Organization Statistics (FAOSTAT), while temperature and precipitation were sourced from ERA5 Agrometeorological Indicators and the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). Trends and relationships were analyzed using Mann–Kendall, Sen’s slope tests, and Spearman’s rank correlation. Multiple linear regression estimates climate variables’ impact on rice productivity. The results show that mean, minimum, and maximum temperatures increased by 0.57 °C, 0.55 °C, and 0.55 °C, respectively, with precipitation variability at 180.31 mm. Climate variables showed diverse correlations with rice production. Regression results revealed a significant negative impact of minimum temperature (p-value = 0.015) on production and a positive effect of precipitation on yields (p-value = 0.036). Farmers in Liberia recognized climate impacts and adopted adaptation strategies, but resilience is hindered by limited credit access, low technology adoption, reliance on traditional practices, and inadequate extension services. Overall, the findings highlight the sensitivity of rice production in Liberia to climate variability and underscore the need for guided adaptation and institutional support to augment farmer resilience. Full article

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

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20 pages, 887 KB

Open AccessReview

Heatwaves and Occupational Health: Emerging Risks and Adaptive Public Health Strategies Under Climate Change—A Narrative Review

by Xiaoli Wang, Lihua Hu, Siyu Zhang, Shiyi Hong, Ziqi Zhu, Guiping Hu and Guang Jia

Climate 2026, 14(4), 83; https://doi.org/10.3390/cli14040083 - 7 Apr 2026

Cited by 1 | Viewed by 3706

Abstract

Heatwaves, intensified by climate change and urbanization, pose increasing threats to human health, with occupational populations facing disproportionate risks due to prolonged exposure and high metabolic demands. Existing evidence remains fragmented, particularly regarding the integration of acute and chronic health effects in workplace [...] Read more.

Heatwaves, intensified by climate change and urbanization, pose increasing threats to human health, with occupational populations facing disproportionate risks due to prolonged exposure and high metabolic demands. Existing evidence remains fragmented, particularly regarding the integration of acute and chronic health effects in workplace settings. This narrative review synthesizes current knowledge on occupational heat exposure, highlighting emerging risks such as cumulative physiological strain, heat-related chronic diseases, and mental health impacts. We identify key occupational-specific pathways that amplify vulnerability beyond that of the general population. Despite growing awareness, substantial gaps persist in the implementation of effective adaptation strategies, especially in low- and middle-income countries, where regulatory, economic, and structural barriers limit intervention uptake. To address these challenges, we emphasize the need for adaptive work–rest scheduling, dynamic early warning systems, and cross-sectoral collaboration to enhance occupational heat resilience under a changing climate. Full article

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21 pages, 5822 KB

Open AccessArticle

Accuracy Assessment of CMORPH and GPCP Satellite Precipitation Products Across Iran

by Mohammad Ramyar Yousefnezhad, Manuchehr Farajzadeh and Yousef Ghavidel Rahimi

Climate 2026, 14(4), 82; https://doi.org/10.3390/cli14040082 - 6 Apr 2026

Cited by 1 | Viewed by 1226

Abstract

Reliable precipitation data are fundamental for climate and hydrological research, especially in regions with sparse ground-based observations. This study evaluates and compares the accuracy of two satellite-based precipitation products—CMORPH and GPCP—across daily, monthly, and annual scales over Iran. Daily, monthly, and annual precipitation [...] Read more.

Reliable precipitation data are fundamental for climate and hydrological research, especially in regions with sparse ground-based observations. This study evaluates and compares the accuracy of two satellite-based precipitation products—CMORPH and GPCP—across daily, monthly, and annual scales over Iran. Daily, monthly, and annual precipitation estimates from CMORPH and GPCP were validated against observations from 128 meteorological stations distributed throughout the country. The assessment employed two statistical indices—correlation coefficient (CC) and root mean square error (RMSE)—alongside three categorical indices: probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). At the daily scale, CMORPH outperformed GPCP in terms of CC, RMSE, POD, and CSI, while GPCP exhibited a lower FAR. At the monthly scale, correlations between satellite-derived and station-based precipitation were stronger than those at the daily scale; CMORPH achieved the highest correlation (CC = 0.84), whereas GPCP yielded a lower RMSE, with a mean value of 26.2 mm. At the annual scale, GPCP demonstrated better performance in CC, while CMORPH showed superior accuracy in RMSE. CMORPH consistently underestimated precipitation, whereas GPCP tended to overestimate rainfall across Iran. Although both datasets provided reliable precipitation estimates at the national scale, CMORPH demonstrated higher overall accuracy and efficiency. Its superior performance across most indices makes CMORPH the more suitable dataset for precipitation monitoring in Iran, despite its tendency to underestimate rainfall relative to ground observations. Full article

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23 pages, 2936 KB

Open AccessArticle

A Global Multi-Hazard Framework for Projecting Climate Migration Flows to 2100 Along Shared Socioeconomic Pathways (SSPs)

by Zachary M. Hirsch, Danielle N. Medgyesi, Jasmina M. Buresch and Jeremy R. Porter

Climate 2026, 14(4), 81; https://doi.org/10.3390/cli14040081 - 2 Apr 2026

Cited by 1 | Viewed by 1891

Abstract

Climate-induced migration is increasingly recognized as a major demographic consequence of environmental change, yet projections vary widely due to differences in spatial scale, hazard coverage, and modeling approaches. This study introduces the First Street Global Climate Migration Model (FS-GCMM), a globally consistent, multi-hazard [...] Read more.

Climate-induced migration is increasingly recognized as a major demographic consequence of environmental change, yet projections vary widely due to differences in spatial scale, hazard coverage, and modeling approaches. This study introduces the First Street Global Climate Migration Model (FS-GCMM), a globally consistent, multi-hazard framework that estimates climate-driven population redistribution at a 12.5 km resolution across all countries through 2100. The model integrates high-resolution global climate hazard datasets, including flood (GloFAS), wind (IBTrACS and ERA5), drought (ERA5), wildfire (Global Fire Atlas), and extreme heat and cold (ERA5-LAND) datasets, with gridded population data from NASA SEDAC’s Gridded Population of the World (GPWv4) and Shared Socioeconomic Pathway (SSP) projections. To identify climate-related migration effects, we applied within-country propensity score matching to construct balanced samples of exposed and unexposed grid cells with similar socioeconomic, demographic, geographic, and governance characteristics. Hazard-specific impacts on annualized population change from 2000 to 2020 were then estimated using mixed-effects ridge regression with country-level random effects to account for cross-national heterogeneity and multicollinearity. These empirically derived coefficients were applied to SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios to project future climate-driven outmigration, which was subsequently redistributed using a spatial attractiveness framework incorporating economic opportunity, population density, climate safety, and geographic proximity. Results indicate statistically significant negative effects of all modeled hazards on population retention globally, with approximately 199.5 million people projected to experience climate-driven displacement by 2055 under SSP2-4.5. Full article

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17 pages, 7238 KB

Open AccessArticle

Ethiopia Rift Valley Meso-Climate and Response to the Indian Ocean Dipole

by Mark R. Jury

Climate 2026, 14(4), 80; https://doi.org/10.3390/cli14040080 - 2 Apr 2026

Viewed by 1261

Abstract

This study of the Ethiopian Rift Valley meso-climate (5° N–9° N, 37° E–40° E) employed space–time statistical methods over the period 1981–2025. Links between weather conditions at Hawassa (7.1° N, 38.5° E, 1700 m) and the Indian Ocean Dipole (IOD) were uncovered, among [...] Read more.

This study of the Ethiopian Rift Valley meso-climate (5° N–9° N, 37° E–40° E) employed space–time statistical methods over the period 1981–2025. Links between weather conditions at Hawassa (7.1° N, 38.5° E, 1700 m) and the Indian Ocean Dipole (IOD) were uncovered, among 3–4 yr oscillations and a weak upward trend. Seasonal anomalies of local dewpoint temperature (Td) and IOD cross-correlated at R = 0.61 over the four-decade study. Mean annual cycling revealed a narrow range for Td from April to October, in contrast with bi-modal rainfall and asymmetric runoff. Diurnal cycle analysis indicated that evening rainfall was driven by midday heat (0.6 mm/h) and moisture fluxes (0.1 mm/h). A case study revealed how shallow cloud bands extend westward from cool, forested highlands to the warm Rift Valley. Composite differences between warm and cool IOD events exhibited contrasting effects for zonal and meridional airflows, which explains why the equatorial trough and its associated rainfall are confined to the southeastern escarpment of Ethiopia. While earlier studies had anticipated drying trends, wetter conditions during the warm IOD events of 2019 and 2023 resulted in rising lake levels (1.8 m) and crop yields (4 T/ha). These findings enhance our understanding of regional climate dynamics to support adaptive management. Full article

(This article belongs to the Special Issue Changing Rainfall Patterns and Food Insecurity: Vulnerable Regions and Adaptation Strategies)

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25 pages, 79340 KB

Open AccessArticle

Hydrodynamic Changes in the Gulf of California Under Different Climate Change Scenarios: 2015–2100

by Metzli Romero-Robles and David Alberto Salas-de-León

Climate 2026, 14(4), 79; https://doi.org/10.3390/cli14040079 - 31 Mar 2026

Viewed by 2473

Abstract

Ocean warming driven by climate change is altering regional circulation patterns and the balance of hydrodynamic forcings in semi-enclosed seas. Understanding how these changes affect ocean circulation and stratification is critical, as they directly influence marine productivity and ecosystem functioning in highly sensitive [...] Read more.

Ocean warming driven by climate change is altering regional circulation patterns and the balance of hydrodynamic forcings in semi-enclosed seas. Understanding how these changes affect ocean circulation and stratification is critical, as they directly influence marine productivity and ecosystem functioning in highly sensitive regions such as the Gulf of California. This study examines the hydrodynamic response of the Gulf of California under three climate change scenarios (SSP1–2.6, SSP2–4.5, SSP5–8.5) projected from 2015 to 2100 using the CNRM-CM6-1-HR global climate model. We evaluate changes in sea surface temperature, surface circulation, and the relative contributions of dominant dynamic forcing mechanisms at annual and interannual scales. Results reveal a basin-wide warming trend accompanied by an increased frequency of extreme heat events. Surface current velocities weaken throughout the Gulf, exhibiting a consistent negative trend, with the strongest decline occurring under SSP5–8.5 in the central basin (

- 5.1 \times 10^{- 4}

m s⁻¹ year⁻¹). Wind speed also shows a general decreasing tendency, contributing to reduced circulation intensity and enhanced stratification. The analysis of dimensionless numbers indicates moderate but consistent changes in the relative balance among inertial, baroclinic, and wind-driven processes. Although their proportions vary slightly across scenarios, the dominant forcing hierarchy remains largely preserved, suggesting a gradual modulation in forcing intensity rather than a fundamental reorganization of the hydrodynamic regime. These findings highlight spatial contrasts in climate sensitivity within the Gulf of California and underscore the importance of regional-scale assessments for anticipating future changes in circulation dynamics and marine ecosystem responses. Full article

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

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19 pages, 17608 KB

Open AccessArticle

Determining the Impact of Urban Vacant and Abandoned Land on Land Surface Temperatures in Socially Vulnerable Communities in Houston

by Dingding Ren, Galen Newman, Robert D. Brown, Dongying Li and Lei Zou

Climate 2026, 14(4), 78; https://doi.org/10.3390/cli14040078 - 27 Mar 2026

Viewed by 1512

Abstract

Uneven urbanization can lead to significant quantities of vacant and abandoned land while exacerbating urban heat island (UHI) effects and simultaneously adversely affecting socioeconomically disadvantaged communities. This study examines the correlation between land surface temperature (LST) and urban vacant and abandoned land in [...] Read more.

Uneven urbanization can lead to significant quantities of vacant and abandoned land while exacerbating urban heat island (UHI) effects and simultaneously adversely affecting socioeconomically disadvantaged communities. This study examines the correlation between land surface temperature (LST) and urban vacant and abandoned land in socially vulnerable neighborhoods in Houston, TX, USA, where extreme heat can present significant environmental and public health challenges. Six critical study locations exhibiting a social vulnerability index (SVI) over 0.7 and average land surface temperature (LST) values surpassing 82 °F (27.8 °C) are analyzed through spatial analytics and drone footage. Findings indicate that vegetated vacant spaces help mitigate urban heat by decreasing land surface temperature, but abandoned structures exacerbate temperatures due to heat retention from non-permeable surfaces. Findings suggest that elevated socioeconomic vulnerability correlates with increased land surface temperature, exacerbating heat-related hazards in at-risk communities. In this six-site sample, the abandonment rate exhibited a positive correlation with the site mean land surface temperature (exploratory linear fit: +2.42 °F [0.74, 4.11]/+1.35 °C [0.41, 2.28] per +1% increase in abandonment; to be interpreted as exploratory and potentially confounded). Results provide critical insights for climate resilience planning and urban heat reduction through high-resolution thermal and geographical analysis, highlighting the impact of vacant and abandoned land on LST. Such findings endorse certain urban cooling techniques, including land reutilization and green infrastructure, to enhance environmental equality and adaptation. Full article

(This article belongs to the Special Issue Multi-Physics and Chemistry of Urban Climate Modelling)

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32 pages, 2895 KB

Open AccessArticle

Assessing Crop Yield Variability Using Meteorological Drought Indices for Agricultural Drought Monitoring in Botswana

by Kgomotso Happy Keoagile, Modise Wiston and Nicholas Christopher Mbangiwa

Climate 2026, 14(4), 77; https://doi.org/10.3390/cli14040077 - 25 Mar 2026

Cited by 1 | Viewed by 1751

Abstract

Botswana’s semi-arid climate makes it vulnerable to climate change, particularly drought, which threatens agricultural productivity. This study assesses drought impact on Botswana’s agricultural sector using Climate Hazards Center Infrared Precipitation with Station (CHIRPS) rainfall data and Climate Hazards Center Infrared Temperature with Station [...] Read more.

Botswana’s semi-arid climate makes it vulnerable to climate change, particularly drought, which threatens agricultural productivity. This study assesses drought impact on Botswana’s agricultural sector using Climate Hazards Center Infrared Precipitation with Station (CHIRPS) rainfall data and Climate Hazards Center Infrared Temperature with Station (CHIRTS) temperature data (25 km) to compute the Standardized Precipitation Index (SPI), Standardized Temperature Condition Index (STCI) and Standardized Precipitation Evapotranspiration Index (SPEI) at seasonal/annual time scales (1, 3, 6 and 12 months). The indices are used to assess their ability to predict crop yields using national data during Botswana’s rainy season, while employing univariate and multivariate statistical models. Statistical models also linked historical drought patterns to yield variability with the Percentage Area Affected (PAA) by drought, identifying key predictors. A majority of the crops (sunflower, maize, sorghum and pulses) showed variability which was best explained by SPEI 6 more particularly under the PAA multivariate models, with the highest and moderate explanatory power (R²) found in sunflower (0.48) and maize (0.43). However, variability in millet was best explained by SPI-3, although the R² was low (0.26). Other crops displayed positive coefficients within the models, which may be attributed to the varieties grown being drought tolerant. Nevertheless, the impacts from drought, which resulted in low yields, were shown by the negative coefficients across most crops. For a more holistic approach, the study also employed questionnaire data to capture first-hand local knowledge. The results showed drought to be among the indicators of climate change that were mostly perceived as well as its effects, in which yield decline, crop damage and crop pests and diseases were among the most perceived effects. Overall, this highlighted the sector’s vulnerability to the changes in climate. The study therefore underscores the need for integrated drought early warning systems, adaptive agricultural/water management and insights for policymakers to enhance drought resilience in Botswana, aligning with global sustainability goals. Full article

(This article belongs to the Section Climate and Environment)

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21 pages, 1959 KB

Open AccessArticle

Understanding Trends in Near-Surface Air Temperature Lapse Rates in a Southern Mediterranean Region

by Gaetano Pellicone, Tommaso Caloiero and Ilaria Guagliardi

Climate 2026, 14(4), 76; https://doi.org/10.3390/cli14040076 - 25 Mar 2026

Cited by 1 | Viewed by 1519

Abstract

This study investigates the spatiotemporal variability of the near-surface air temperature lapse rate (NSATLR) in Calabria, a region representative of typical Mediterranean environmental and climatic conditions. Through the integration of observational datasets and model simulations, a global sensitivity analysis using the Sobol method, [...] Read more.

This study investigates the spatiotemporal variability of the near-surface air temperature lapse rate (NSATLR) in Calabria, a region representative of typical Mediterranean environmental and climatic conditions. Through the integration of observational datasets and model simulations, a global sensitivity analysis using the Sobol method, and Bayesian linear regression modelling across annual, seasonal, and monthly scales, the primary drivers of near-surface air temperature (NSAT) variability were identified. Results demonstrate that altitude is the dominant factor influencing temperature distribution, with minimal contributions from other geographical parameters such as latitude, longitude, and proximity to the sea. The Bayesian models yielded robust performance for mean and maximum temperatures, while minimum temperature proved more challenging to predict. Lapse rate analyses confirmed a consistent inverse relationship between temperature and elevation, with the steepest gradients observed for Tmin. In particular, a significant long-term decline in lapse rates over the past 70 years, especially during winter and autumn, points to accelerated warming at higher elevations, primarily driven by rising Tmin values. This trend suggests a gradual homogenization of temperature across altitudes, with important implications for ecosystem dynamics, snowpack stability, and climate-sensitive sectors such as agriculture and urban planning. Full article

(This article belongs to the Special Issue Climate Variability in the Mediterranean Region (Second Edition))

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Climate, Volume 14, Issue 4 (April 2026) – 13 articles

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