Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

• Main Authors: Heinrichs, T., Stevens, E., Zhu, Jiang, Zhang, X., Broderson, D., Zavodsky, B. T.
• Format: Other/Unknown Material
• Language: unknown
• Published: 2014
• Subjects: Meteorology and Climatology; Alaska; Cris
• Online Access: http://hdl.handle.net/2060/20140008767

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.