P30 Dynamic origins of WRF bias in simulating southeastern United States summer precipitation

Li, Laifang, Wenhong Li, Duke University, and Jiming Jin, Utah State University

Weather Research and Forecasting (WRF) model simulation participated in North American Regional Climate Change Assessment Program (NARCCAP) shows a significant dry bias in Southeastern (SE) United States (US) summer precipitation, which hampers the skill of seasonal prediction. This study addresses the possible causes of the dry biases in the simulations. Our analysis shows that the bias mainly comes from northwestward (NW) misrepresentation of North Atlantic Subtropical High (NASH) western ridge that is related to a dry condition over the SE US. The distortion of the NASH western ridge may result from an anomalously strong super-geostrophic Great Plain low-level jet whose maintenance requires a high pressure over the SE US. Such a high pressure causes NASH western ridge to extend northwestward and dynamically induces the SE US dry bias. The analytical results were further verified through Four-Dimensional Data Assimilation (FDDA) experiments: thermodynamic and dynamic FDDA. In the thermodynamic (dynamic) FDDA, only temperature and specific humidity (wind) is nudged towards reanalysis. The dynamic FDDA is able to successfully correct the dry bias, whereas the thermodynamic FDDA is not. Our analysis shows that an improved representation of large-scale dynamics advances WRF simulation skill in SE US summer precipitation simulations.