Session 11A.7 Evaluation of the ARW WRF Model in the Complex Terrain of Southwest Asia Part I: Objective Verification and Data Assimilation

Thursday, 28 June 2007: 5:30 PM
Summit A (The Yarrow Resort Hotel and Conference Center)
Jianjun Xu, JCSDA/NOAA & AFWA/UCAR, Camp Springs, MD

Presentation PDF (2.4 MB)

This paper firstly describes an objective verification of the National Center for Atmospheric Research (NCAR) mesoscale model (ARW WRF) used in the complex terrain of Southwest Asia from May 1 through 31 2006. The statistical evaluation is designed to assess the model's surface and upper-air forecast accuracy at nine specific locations during the transforming season (May) of Asian Monsoon. The evidence is observed that the model biases caused by inadequate parameterization of physical processes, except for the 2-m (meter) temperature forecasts, are relatively small compared to these nonsystematic errors resulted partially from uncertainty of initial condition. The model errors in surface air forecasts are closely related to the terrain configuration, but the performance of 2-m temperature forecasts is different from that for 10-m wind field. Secondly, in order to understand the role of initial condition in accuracy of the model forecasts, this study then assimilated a kind of satellite radiance data into this model through the Joint Center for Satellite Data Assimilation (JCSDA) analysis system (GSI). The results show that on average for the 24- and 48-h (hour) forecasts of one month experiments, the satellite data provides useful information for improvement of initial condition, the model errors get reduced for most of location within the 24-h forecasts. However, the improvement is mainly limited to the forecasts over lower terrain or water areas. With radiance data assimilation, the thermal and dynamics structure of upper air have been changed substantially, an extra warm anticyclone center appears over the central Southwest Asia. The satellite data assimilation produces a positive impacting to improve the forecast in the complex terrain areas.

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