Climate Dynamics, Год журнала: 2023, Номер 61(7-8), С. 3911 - 3933
Опубликована: Апрель 13, 2023
Язык: Английский
Water, Год журнала: 2024, Номер 16(3), С. 474 - 474
Опубликована: Янв. 31, 2024
Fitting probability distribution functions to observed data is the standard way compute future design floods, but may not accurately reflect projected pattern of extreme events related climate change. In applying latest coupled model intercomparison project (CMIP5 and CMIP6), this research investigates how likely it that precipitation changes in CMIP5 CMIP6 will affect both magnitude frequency flood analysis. GCM output from four modelling institutes CMIP5, with representative pathway concentration (RCP8.5) corresponding shared socioeconomic pathways (SSP585), were selected for historical periods, before was statistically downscaled cities by using delta, quantile mapping (QM), empirical (EQM). On basis performance evaluation, a rainfall-runoff hydrological developed stormwater management (SWMM) CMIPs CMIP6) horizons. The results reveal an unprecedented increase events, (historical) (future) projections. years 2070–2080 identified as experiencing most severe flooding.
Язык: Английский
Процитировано
8
European Journal of Agronomy, Год журнала: 2025, Номер 166, С. 127560 - 127560
Опубликована: Фев. 22, 2025
Язык: Английский
Процитировано
1
Earth Systems and Environment, Год журнала: 2021, Номер 5(4), С. 849 - 859
Опубликована: Сен. 9, 2021
Abstract Nepal is located on the southern slope of Central Himalayas and has experienced frequent droughts in past. In this study, we used an ensemble 13 biased corrected models from Coupled Model Intercomparison Project Phase 6 (CMIP6) to assess future drought conditions over under three shared socioeconomic pathways (SSP126, SSP245, SSP585) using Standardized Precipitation Evapotranspiration Index (SPEI) at annual timescale. The monthly correlation between observed CMIP6-simulated historical SPEI 0.23 ( p < 0.01), which indicates CMIP6 model can simulate characteristics Nepal. period (2020–2100), duration severity are projected increase with higher emission scenarios, especially for SSP585. Our results indicate enhanced intensity SSP126, whereas, frequency will be slightly higher. early (2020–2060), decreasing late (2061–2100) all SSP scenarios. further more prolonged severe SSP585 as compared SSP126 SSP245. findings present study help mitigation well long-term adaptation strategies
Язык: Английский
Процитировано
34
Climatic Change, Год журнала: 2023, Номер 176(5)
Опубликована: Май 1, 2023
Abstract This study assesses the performance of large ensembles global (CMIP5, CMIP6) and regional (CORDEX, CORE) climate models in simulating extreme precipitation over four major river basins (Limpopo, Okavango, Orange, Zambezi) southern Africa during period 1983–2005. The ability model to simulate seasonal indices is assessed using three high-resolution satellite-based datasets. results show that all overestimate annual cycle mean basins, although intermodel spread large, with CORDEX being closest observed values. Generally, interannual variability rainy days (RR1), maximum consecutive wet (CWD), heavy very (R10mm R20mm, respectively) seasons. Simple daily rainfall intensity (SDII) number dry (CDD) are generally underestimated. lowest Taylor skill scores (TSS) spatial correlation coefficients (SCC) depicted for CDD Limpopo compared other respectively. Additionally, exhibit highest normalized standard deviations (NSD) CWD indices. RCM lower better, respectively, than those GCM (except CDD). In particular, performs better CORE basins. Although ensemble biases often within range observations, statistically significant shown by underline need bias correction when these impact assessments.
Язык: Английский
Процитировано
15
Climate Dynamics, Год журнала: 2023, Номер 61(7-8), С. 3911 - 3933
Опубликована: Апрель 13, 2023
Язык: Английский
Процитировано
14