Examination of the impact of variable terrains on surface data assimilation
Zhaoxia Pu, University of Utah, Salt Lake City, UT
Due to limited model resolution in both horizontal and vertical, it is always a problem for numerical model to appropriately represent terrain features and subgrid scale unresolved variability (such as curvature, slope and aspects etc.). This causes difficulties in assimilating near surface observations into the numerical weather prediction model. In this study, a set of data assimilation experiments (3DVAR, EnKF) is conducted to detect the fundamental problems in assimilating the near surface observations over the complex terrains. Specifically, both terrain effects and misrepresentation impacts in surface data assimilation are investigated. Sensitivity study is also performed to identify the most sensitive atmospheric variables to the effect of complex terrains in the analysis. Results will be discussed in the presentation.
Session 17, Mesoscale predictability and data assimilation I
Thursday, 20 August 2009, 1:45 PM-3:15 PM, The Canyons
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