Development and Impact Study of Community Satellite Data Thinning and Representation Optimization Tool

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Monday, 5 January 2015
Tong Zhu, CIRA/NOAA/NESDIS/STAR/Joint Center for Satellite Data Assimilation, College Park, MD; and S. A. Boukabara

Handout (3.2 MB)

To optimize the thinning procedure in the satellite data assimilation for global and regional modeling systems, a new Community Satellite data Thinning and Representation Optimization Tool (CSTROT) is developed at NOAA/JCSDA recently. The main thinning strategy is based on the derived standard deviation (STDV) of the satellite data that to be thinned. There are also several other different options for thinning, representation and nesting schemes in CSTROT. The new thinning tool has been implemented into the NCEP Gridpoint Statistical Interpolation (GSI) system. The GSI analysis results with CSTROT are evaluated. It is found that high density observations can be kept within data high variational regions, such as tropical cyclone and front systems. High density data can also be selected by giving the locations of the interested regions. The impact study of the analyzed fields on Superstorm Sandy forecast using Hurricane Weather Research and Forecasting (HWRF) model will be performed.