Multi-model ensemble bias-corrected precipitation dataset and its application in identification of drought-flood abrupt alternation in China

Atmospheric Research, Год журнала: 2024, Номер 307, С. 107481 - 107481

Опубликована: Май 21, 2024

Язык: Английский

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Projected changes in daily temperature extremes for selected locations over South Africa

Weather and Climate Extremes, Год журнала: 2025, Номер unknown, С. 100753 - 100753

Опубликована: Фев. 1, 2025

Язык: Английский

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Improving Daily CMIP6 Precipitation in Southern Africa Through Bias Correction— Part 2: Representation of Extreme Precipitation

Climate, Год журнала: 2025, Номер 13(5), С. 93 - 93

Опубликована: Май 2, 2025

Accurate simulation of extreme precipitation events is crucial for managing climate-vulnerable sectors in Southern Africa, as such 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 three bias correction techniques—scaled distribution mapping (SDM), quantile (QDM), QDM with a focus on above below 95th percentile (QDM95)—and daily outputs from 11 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The Climate Hazards Group Infrared Precipitation Stations (CHIRPS) dataset was served reference. bias-corrected native were evaluated against observational datasets—the CHIRPS, Multi-Source Weighted Ensemble (MSWEP), Global Climatology Center (GPCC) datasets—for period 1982–2014, focusing December-January-February season. ability generate eight indices developed by Expert Team Change Detection Indices (ETCCDI) evaluated. results show that captured similar spatial patterns precipitation, but there significant changes amount episodes. While generally improved representation its varied depending reference used, particularly maximum one-day (Rx1day), consecutive wet days (CWD), dry (CDD), extremely (R95p), simple intensity index (SDII). In contrast, total rain (RR1), heavy (R10mm), (R20mm) showed consistent improvement across all observations. All techniques enhanced accuracy indices, demonstrated higher pattern correlation coefficients, Taylor skill scores (TSSs), reduced root mean square errors, fewer biases. ranking using comprehensive rating (CRI) indicates no single model consistently outperformed others relative GPCC, MSWEP datasets. Among methods, SDM QDM95 variety criteria. strategies, best-performing EC-Earth3-Veg, EC-Earth3, MRI-ESM2, multi-model ensemble (MME). These findings demonstrate efficiency improving modeling extremes ultimately boosting assessments.

Язык: Английский

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Projected changes in rainfall over Uganda based on CMIP6 models

Theoretical and Applied Climatology, Год журнала: 2022, Номер 149(3-4), С. 1117 - 1134

Опубликована: Май 28, 2022

Язык: Английский

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Evaluation and projection of precipitation extremes under 1.5°C and 2.0°C GWLs over China using bias-corrected CMIP6 models

iScience, Год журнала: 2023, Номер 26(4), С. 106179 - 106179

Опубликована: Фев. 14, 2023

China is facing an increasing challenge from severe precipitation-related extremes with accelerating global warming. In this study, using a bias-corrected CMIP6 ensemble, future responses of precipitation extreme indices at 1.5°C and 2.0°C warming levels (GWLs) under the SSP245, SSP370 SSP585 scenarios are investigated. Despite different change magnitudes, events will be more frequent intense over as whole higher emissions GWLs. The increase in annual total could attribute to sharp intensity days very heavy scenarios. Limiting low emission pathways (i.e., SSP245) instead 2°C high SSP585) would have substantial benefits for terms reducing occurrences events.

Язык: Английский

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Dominant modes of precipitation over Africa, and their associated atmospheric circulations from observations

International Journal of Climatology, Год журнала: 2023, Номер 43(10), С. 4603 - 4618

Опубликована: Май 14, 2023

Abstract This study uses the empirical orthogonal function (EOF) analysis to identify and describe continental‐scale seasonal (MAM, JJA, SON DJF) precipitation modes over Africa based on observation (Global Precipitation Climatology Centre; GPCC) reanalysis (ERA5) data from 1982 2014. Using composite analysis, we attempt atmospheric circulations (wind relative humidity) associated with each mode. ERA5 has a good agreement that of GPCC, as observed in spatial congruence EOF composites. The results for season show loading patterns Mode 1 (variance >20% all seasons) match long‐term mean distribution. Atmospheric conditions across continent are primarily driven by four main high‐pressure systems (Azores, St. Helena, Arabian Mascarene High) influence moisture distribution subsequently modulate rain belt Modes 2 >11% 3 >10% deviations leading mode smaller‐scale systems. However, large‐scale factors still dominate overall pattern modulating energy transfer between hemispheres. provide comprehensive understanding continental‐wide African circulation observations. findings can be used reference future work using model historical projection studies.

Язык: Английский

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Bias-Corrected CMIP5 Projections for Climate Change and Assessments of Impact on Malaria in Senegal under the VECTRI Model

Tropical Medicine and Infectious Disease, Год журнала: 2023, Номер 8(6), С. 310 - 310

Опубликована: Июнь 6, 2023

On the climate-health issue, studies have already attempted to understand influence of climate change on transmission malaria. Extreme weather events such as floods, droughts, or heat waves can alter course and distribution This study aims impact future malaria using, for first time in Senegal, ICTP's community-based vector-borne disease model, TRIeste (VECTRI). biological model is a dynamic mathematical that considers population variability. A new approach VECTRI input parameters was also used. bias correction technique, cumulative function transform (CDF-t) method, applied simulations remove systematic biases Coupled Model Intercomparison Project Phase 5 (CMIP5) global models (GCMs) could predictions. Beforehand, we use reference data validation CPC unified gauge-based analysis daily precipitation (CPC Climate Prediction Center), ERA5-land reanalysis, Hazards InfraRed Precipitation with Station (CHIRPS), African Rainfall Climatology 2.0 (ARC2). The results were analyzed two CMIP5 scenarios different periods: assessment: 1983-2005; near future: 2006-2028; medium term: 2030-2052; far 2077-2099). show reproduce annual cycle well. Except IPSL-CM5B which gives peak August, all other (ACCESS1-3, CanESM2, CSIRO, CMCC-CM, CMCC-CMS, CNRM-CM5, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, inmcm4, IPSL-CM5B) agree maximum September period strong August-October. With spatial variation, more difference number cases between south north. Malaria much higher than However, predicted by occurrence 2100 differences RCP8.5 scenario, considered high emission RCP4.5 an intermediate mitigation scenario. predict decreases ACCESS1-3, NRCM-CM5, GFDL-ESM2M increases under (RCP4.5 RCP8.5). projected decrease these visible this are paramount importance field. These will assist decision-making allow establishment preventive surveillance systems local climate-sensitive diseases, including malaria, targeted regions Senegal.

Язык: Английский

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Meteorological Drought Variability over Africa from Multisource Datasets

Atmosphere, Год журнала: 2023, Номер 14(6), С. 1052 - 1052

Опубликована: Июнь 19, 2023

This study analyses the spatiotemporal variability of meteorological drought over Africa and its nine climate subregions from an ensemble 19 multisource datasets (gauge-based, satellite-based reanalysis) period 1983–2014. The standardized precipitation index (SPI) is used to represent on a 3-month scale. We analyse various characteristics (duration, events, frequency, intensity, severity) for all months, moderate, severe, extreme conditions. results show that occurs across continent, with equatorial regions displaying more negative SPI values, especially moderate severe droughts. On other hand, Eastern Sahara Western Southern portray less values. also reveals months have largest interannual variability, followed by months. trend analysis shows significantly increasing in episodes most Africa, tropical areas. Drought vary greatly different some areas experiencing longer droughts than others. region has highest number durations low events but leading overall higher severity area. In contrast, Madagascar display consistently categories. demonstrates importance conducting levels instead using management adaptation strategies need enhance community resilience changing situations consider order mitigate impacts continent.

Язык: Английский

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Spatiotemporal projections of extreme precipitation over Algeria based on CMIP6 global climate models

Modeling Earth Systems and Environment, Год журнала: 2023, Номер 9(3), С. 3011 - 3028

Опубликована: Янв. 31, 2023

Язык: Английский

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Performance evaluation of CMIP6 in simulating extreme precipitation in Madagascar

Theoretical and Applied Climatology, Год журнала: 2024, Номер 155(5), С. 4089 - 4100

Опубликована: Фев. 1, 2024

Язык: Английский

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