Bias-corrected NESM3 global dataset for dynamical downscaling under 1.5 °C and 2 °C global warming scenarios

Abstract

Abstract Dynamical downscaling is vital for generating finer-scale climate projections. Recently, a set of simulations under four types of 1.5/2 °C global warming scenarios are available with Nanjing University of Information Science and Technology Earth System Model (NESM). However, NESM3’s bias in large-scale driving variables would degrade downscaled simulations. We corrected NESM3 bias in terms of climate mean and inter-annual variance against ERA5 using a novel bias correction method and then produced a set of bias-corrected datasets for dynamical downscaling. The bias-corrected NESM3 spans the historical period for 1979–2014 and four future scenarios (i.e., 1.5 °C overshoot for 2070–2100, stabilized 1.5/2 °C for 2070–2100, and transient 2 °C for 2031–2061) with 1.25° × 1.25° horizontal resolution at six-hourly intervals. Our evaluation suggests that bias-corrected NESM3 outperforms the original NESM3 in the climatological mean of seasonal mean and variability, as well as climate extreme events during the historical period. This bias-corrected dataset is expected to generate more reliable projections for regional climate and environment under 1.5/2 °C global warming.