Here we present a global dataset of the future projection of dry-bulb, wet-bulb and wet-bulb globe temperature under 1–4°C of global warming levels compared with the preindustrial era using output from 16 CMIP6 global climate models (GCMs). The dataset was bias-corrected against ERA5 ...
Bangladesh, a low-lying subtropical monsoon-dominated region, relies heavily on agriculture and is extremely vulnerable to the impacts of climate change. This research assesses the performance of 27 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in ...
Our evaluation suggests that the bias-corrected data are of better quality than the individual CMIP6 models in terms of the climatological mean, interannual variance and extreme events. This dataset will be useful for dynamical downscaling projections of the Earth's future climate, atmospheric ...
We estimated the multimodel ensemble mean bias in precipitation, maximum and minimum temperatures from the 13 CMIP6-GCMs (Fig.3). The bias in mean annual precipitation, maximum and minimum temperatures was estimated against the observations from IMD (for the Indian domain) and Sheffieldet al.48o...
This study has focused on the performance of three bias correction methods, Delta, Quantile Mapping (QM) and Empirical Quantile Mapping (EQM) with two reference data sets (ERA and station-based observations) of precipitation for 5 single CMIP6 GCM models (ACCESS-CM2, CNRM-CM6-1-HR, GFDL-...
doi:10.1007/s00704-013-1034-6 Article Google Scholar Moise A et al. (2015) Evaluation of CMIP3 and CMIP5 models over the Australian region to inform confidence in projections. Aust. Meteorol. Oceanogr. J. 65:19–53 Article Google Scholar Olson R, Evans JP, Di Luca A, and Argueso...
www.nature.com/scientificdata OPEN Bias-corrected CMIP6 global Data Descriptor dataset for dynamical downscaling of the historical and future climate (1979–2100) Zhongfeng Xu 1 ✉,Ying Han1, Chi-Yung Tam 2, Zong-Liang Yang 3 & Congb...
Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100)doi:10.21203/rs.3.rs-424811/v1Zhongfeng XuYing HanChi Yung TamCongbin FuSpringer Science and Business Media LLC
implementations of DC (e.g. using different interpolation methods), especially as CMIP6 model outputs become available to the public, as different methods can produce varying results and thus add to the ‘uncertainty cascade’ in impacts modeling16,72. ...
The present study quantitatively assessed the thirteen (13) state-of-the-art statistically downscaled, bias-corrected, and high-resolution climate model datasets derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the extreme precipitation indices (rainfall, SDII, ...