Assessment of ERA-Interim-driven RCM simulations in reproducing the link between ENSO and Climate Extreme Indices

Theoretical and Applied Climatology, Год журнала: 2025, Номер 156(2)

Опубликована: Янв. 18, 2025

Язык: Английский

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Analysis of crop suitability index for current and future climates using statistically downscaled CMIP6 outputs over Africa

Meteorological Applications, Год журнала: 2025, Номер 32(1)

Опубликована: Янв. 1, 2025

Abstract The study aimed to assess the impact of climate change on crop suitability index (CSI) selected staple crops for current (1981–2010) and future (2021–2050 2051–2080) climates across Africa. Precipitation mean temperature data from gridded observations, 10 Global Climate Models (GCMs) were utilized calculate CSI maize, soybean, wheat, plantain, cassava, rice, millet, sorghum, yam. Ecocrop model implemented in R, utilizing FAO‐Ecocrop database alongside climatic variables different zones continent, was employed compute CSI. results indicate that all crops, except rain‐fed are suitable parts West Central African regions, with wheat being inclusive some Guinea Coast. northern, eastern, southern regions identified as least any production based balance between base parameters over historical period. Analysis this period reveals an increasing trend major most production, which demonstrates a decreasing areas. Projection analysis Sahel region is expected be affected by change, significant reduction crops. Conversely, Southeastern Africa Coast likely affected, increases considered This provides crucial information effective agricultural planning resource allocation, optimizing land use identifying aligned prevailing environmental conditions, including soil type, climate, water availability. Such enhances understanding suitability, contributing improved productivity sustainability.

Язык: Английский

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Climate model downscaling in central Asia: a dynamical and a neural network approach

Geoscientific model development, Год журнала: 2025, Номер 18(1), С. 161 - 180

Опубликована: Янв. 15, 2025

Abstract. High-resolution climate projections are essential for estimating future change impacts. Statistical and dynamical downscaling methods, or a hybrid of both, commonly employed to generate input datasets impact modelling. In this study, we employ COSMO-CLM (CCLM) version 6.0, regional model, explore the benefits dynamically general circulation model (GCM) from Coupled Model Intercomparison Project Phase 6 (CMIP6), focusing on central Asia (CA). The CCLM, at 0.22° horizontal resolution, is driven by MPI-ESM1-2-HR GCM (at 1° spatial resolution) historical period 1985–2014 projection 2019–2100 under three Shared Socioeconomic Pathways (SSPs), namely SSP1-2.6, SSP3-7.0, SSP5-8.5 scenarios. Using Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) gridded observation dataset as reference, evaluate performance CCLM ERA-Interim reanalysis over period. added value compared its driving GCM, evident mountainous areas in CA, which higher risk extreme precipitation events. mean absolute error bias climatological (mm d−1) reduced 5 mm d−1 summer 3 annual values. For winter, there was no reduction achieved. However, frequency values improved simulations. Additionally, refine projections. We present high-resolution maps heavy changes based compare them CMIP6 ensemble. Our analysis indicates an increase intensity events CA already climatic end century. number days exceeding 20 increases more than 90 century, reference period, SSP3-7.0 99th percentile total 9 relative Finally, train convolutional neural network (CNN) map simulation downscaled counterpart. CNN successfully emulates GCM–CCLM chain large but shows skill when applied different chain. scientific community interested models could use our data, architecture offers alternative traditional statistical methods.

Язык: Английский

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Assessment of Regional Climate Model simulations at reproducing the link between PDO and Climate Extreme Precipitation indices in Mexico

Theoretical and Applied Climatology, Год журнала: 2025, Номер 156(2)

Опубликована: Янв. 22, 2025

Язык: Английский

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Leveraging the GEV Model to Estimate Flood Due to Extreme Rainfall in Ungauged Dry Catchments of the Gobi Region

Sustainability, Год журнала: 2025, Номер 17(6), С. 2500 - 2500

Опубликована: Март 12, 2025

Extreme high flows can have negative economic, social, and ecological effects are expected to become more severe in many regions due climate change. Knowledge of maximum flow regimes estimation extreme rainfall is important, especially ungauged dry regions, for planning infrastructure development. In this study, we propose a regional method estimating modeled using the value theory, with examples from Gobi region Mongolia. The first step apply Generalized Value (GEV) theory data 44-year observational covering period 1978–2022. Then, estimated 100-year return used empirical equation flood calculation. As result, most stations’ follows Fréchet distribution values that range between 27.8–130.6 mm. local reference defined as 90 mm whole region. Our results show extremely has changed −7% 16%, leading higher events. These findings further provide evidence calculation, change impact assessment, water resource planning, management studies.

Язык: Английский

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Advancing high-resolution modeling to unravel the interplay between extreme weather events and air pollution under global warming

Frontiers of Environmental Science & Engineering, Год журнала: 2025, Номер 19(7)

Опубликована: Май 19, 2025

Язык: Английский

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Surge Mechanisms of Garmo Glacier: Integrating Multi-Source Data for Insights into Acceleration and Hydrological Control

Remote Sensing, Год журнала: 2024, Номер 16(24), С. 4619 - 4619

Опубликована: Дек. 10, 2024

Understanding the mechanisms of glacial surging is crucial, as surges can lead to severe hazards and significantly impact a glacier’s mass balance. We used various remote sensing data investigate surge Garmo Glacier in western Pamir. Our findings indicate that glacier surged between 27 April 30 September 2022, with peak speeds reaching 8.3 ± 0.03 m d−1. During 2020 receiving zone thickened by 37.9 0.55 m, while reservoir decreased 35.2 on average. The velocity decomposition suggests this meltwater gradually warmed bed, accelerating during pre-surge phase. surge, substantial drainage events coincided sharp deceleration, ultimately halting suggesting hydrological control. Extreme climate may not immediately trigger surges; they substantially processes over an extended period.

Язык: Английский

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