Bias correction and projection of temperature over the altitudes of the Upper Indus Basin under CMIP6 climate scenarios from 1985 to 2100

Autor: Kashif Jamal, Xin Li, Yingying Chen, Muhammad Rizwan, Muhammad Adnan Khan, Zain Syed, Prince Mahmood
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Journal of Water and Climate Change, Vol 14, Iss 7, Pp 2490-2514 (2023)
Druh dokumentu: article
ISSN: 2040-2244
2408-9354
DOI: 10.2166/wcc.2023.180
Popis: The identification of projected changes in temperature caused by global warming at a fine-scale spatial resolution is of great importance for the high-altitude glacier and snow covered Upper Indus Basin. This study used a multimodel ensemble mean bias-correction technique which uses the ensemble empirical mode decomposition method to correct the bias of ensemble mean of seven CMIP6 GCMs outputs with reference to the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5). The bias-corrected data have a nonlinear trend of seven GCMs but interannual variance and mean climate of ERA5 dataset. The dataset spans from 1985 to 2100 for historical and future climate scenarios (SSP126, SSP245, SSP370, and SSP585) at daily time intervals with a 1 km grid resolution. The result of different scenarios indicates that the increase in maximum (Tmax) and minimum temperature (Tmin) ranging from 1.5 to 5.4 °C and 1.8 to 6.8 °C from 2015 to 2100, respectively. Similarly, elevation-dependent warming is identified in Tmin from 1.7 to 7.0 °C at elevations
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