Correcting Multivariate Biases in Regional Climate Model Boundaries: How Are Synoptic Systems Impacted Over the Australian Region?

Abstract

Synoptic climatology, which connects atmospheric circulation with regional environmental conditions, is pivotal to understanding climate dynamics. While regional climate models (RCMs) can reproduce key mesoscale precipitation patterns, biases related to synoptic circulation from the driving model, typically global climate models (GCMs), often remain unaddressed. This study examines the influence of correcting systematic bias in RCM boundaries on the representation of Australian synoptic systems. We utilize a structural self-organizing map to evaluate the frequency, persistence, and transitions of daily synoptic systems. Our findings reveal that an RCM with multivariate bias-corrected boundaries improves the representation of synoptic systems compared to the driving GCM, or an RCM with uncorrected or simply bias-corrected boundaries, particularly in reference to the frequency of systems identified. This demonstrates that appropriately correcting RCM boundary conditions helps correct many of the circulation errors inherited from the driving GCM but not all.