Zhenhua Li, Yanping Li, Lintao Li (2022). A mixed approach to bias-correct convection-permitting regional climate simualtion. Proceedings of the GWF Annual Open Science Meeting, May 16-18, 2022.

Convection-permitting regional climate models can provide better representations of physical processes, especially convection and underlying surface heterogeneity, in the climate system and provide more detailed climate projections at higher temporal and spatial resolution. However, biases still exist in high-resolution RCM simulations due to their deficiency in representations of sub-grid processes and unavoidable parameterization schemes. The RCM dynamical downscaling of future climate projection, therefore, needs bias-correction before their application. We present a new method to bias-correct the dynamically downscaled climate projection by convection-permitting WRF. The method, based on MBCn and machine learning,preserves the large-scale features of observed patterns in reanalysis with added detail from the RCM simulations. It also maintains the climate change signals between the future projection and the historical simulation.

AOSM2022 GWF Modeling Core First Author: Zhenhua Li, Global Institute for Water Security Additional Authors: Yanping Li, Global Institute for Water Security; Lintao Li, Global Institute for Water Security