P3     Examination of Flow-Dependent Errors in Near-Surface Temperature and Wind from WRF Numerical Simulations over    Complex Terrain

Pu, Zhaoxia, and Hailing Zhang, University of Utah, Salt Lake City, UT

Accurate forecasting of near surface atmospheric conditions, especially those over complex terrain, presents a challenge in numerical weather prediction. This study evaluates the performance of the modern Weather Research and Forecasting (WRF) model in predicting near surface atmospheric temperature and wind conditions under various terrain and weather regimes.

Three individual cases under strong synoptic-forcings (i.e., a frontal system, a low-level jet and a persistent cold air pool) are first evaluated. The WRF model is able to reproduce reasonable simulations of these weather phenomena.  The verification for near surface conditions (i.e., temperature at 2-m of height and wind at 10-m of height) against the surface mesonet observations is then conducted. Results indicate that forecasts of near surface variables over flat terrain generally agree well with the observations while errors could also occur, depending on the modelŐs predictability in terms of the atmospheric boundary layer. Over complex terrain, the forecasts not only suffer from the modelŐs ability in reproducing accurate atmospheric conditions in lower atmosphere but also struggle with the representative issues due to mismatches between model and realistic terrain. In addition, over complex terrain, simulations at finer resolutions do not over-perform those at coarser resolutions.

A statistic analysis is also performed for 120 forecasts during one-month period to further investigate the forecasting error characteristics over complex terrain. Results illustrate that forecast errors in near surface variables remarkably depend on the diurnal cycle of surface conditions, especially when the synoptic-forcing is weak. Under the strong synoptic-forcings, the diurnal patterns in the errors are broken while the flow-dependent errors are clearly shown.