Numerical Simulation of A Prognostic Meteorological Model Using Four-Dimensional Observational Data Assimilation in Ohio

Title:	Numerical Simulation of A Prognostic Meteorological Model Using Four-Dimensional Observational Data Assimilation in Ohio
Author:	Lin, Peng
Description:	The Fifth Generation Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model system (MM5) was applied to simulate precipitation in the Ohio region for summer season in 2004. Observational data were nudged in MM5 model using four-dimensional data assimilation (FDDA). Eight sensitivity runs were tested. The model results were compared with observational data in the fields of precipitation, temperature, wind and humidity. The combinations of the physics schemes and FDDA that most improved precipitation modeling performance among the sensitivity runs were applied to the rest episodes of the related month. The model results were compared against observed precipitation data retrieved from National Oceanic and Atmospheric Administration/National Climatic Data Center and gridded precipitation analysis. The results showed that the model performance was significantly enhanced by introducing FDDA and that the combination of Kain-Fritsch cumulus parameterization scheme and Pleim-Xiu land-surface scheme provided the most improvement in precipitation prediction among all sensitivity runs.
Permanent Link:	http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1195160699 http://hdl.handle.net/2374.OX/13931
Date:	2007

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