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AOSM2022: A mixed approach to bias-correct convection-permitting regional climate simualtion
Section 1: Publication
Authorship or Presenters
Zhenhua Li, Yanping Li, Lintao Li
A mixed approach to bias-correct convection-permitting regional climate simualtion
Hydrometeorology, Atmosphere and Extremes
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.
AOSM2022 GWF Modeling Core
Section 2: Abstract
Plain Language Summary
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.
Section 3: Miscellany
Global Institute for Water Security, University of Saskatchewan
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
Section 4: Download
T-2022-04-24-c1DDTtKvYPkGqy3gpc3sQ5DA Conference Publication 1.0