Extended Abstract (2.4M)P1.42
Data Assimilation using Weather Research and Forecasting Model: An Effort to Improve Fine-Scale Modeling
R. Suseela Reddy, Jackson State University, Jackson, MS; and A. Schwartz, M. A. Askelsen, and L. Osborne
Battlefield operations demand precise forecasting according to weather regime and location using fine scale modeling of 1-3km resolutions. Reliable mesoscale models provide insight on the potential effectiveness of the transport and diffusion of chemical and biological agents and support the deployment of ground and airborne assets. Data from various sources, using data assimilation techniques, fed into the atmospheric numerical model can be tuned to generate acceptable output and then incorporated into a decision support matrix. In the present study the Weather Research and Forecasting (WRF) model is used in a high performance-computing environment using non-conventional datasets.
A case study of severe weather event occurred on May 9, 2003 over the Oklahoma-Kansas region was chosen for simulations with a central latitude and longitude of approximately 37.0° N and 98.0° W. The scope of work is focused on using fine scale modeling to study the impact of initialization and assimilation techniques (such as MM5) on numerical simulation of near surface battle field conditions (such as temperature, visibility, precipitation, haze, turbulence, etc.). The results of the model simulations will be presented and discussed.
Poster Session 1, Monday Posters
Monday, 12 January 2004, 2:30 PM-4:00 PM, Room 4AB
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