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Dropwindsonde, Geostationary Operational Environmental Satellite-11 (GOES-11) rapid-scan atmo- spheric motion vectors, and NASA Quick Scatterometer (QuikSCAT) near-surface wind data collected during NASA's Tropical Cloud Systems and Processes (TCSP) field experiment in July 2005 were assimi- lated into an advanced research version of the Weather Research and Forecasting (WRF) model using its three-dimensional variational data assimilation (3DVAR) system. The impacts of the mesoscale data as- similation on WRF numerical simulation of Tropical Storms Cindy and Gert (2005) near landfall are examined. Sensitivity of the forecasts to the assimilation of each single data type is investigated. Specifically, different 3DVAR strategies with different analysis update cycles and resolutions are compared in order to identify the better methodology for assimilating the data from research aircraft and satellite for tropical cyclone study. The results presented herein indicate the following. 1) Assimilation of dropwindsonde and satellite wind data into the WRF model improves the forecasts of the two tropical storms up to the landfall time. The QuikSCAT wind information is very important for improving the storm track forecast, whereas the drop- windsonde and GOES-11 wind data are also necessary for improved forecasts of intensity and precipitation. 2) Data assimilation also improves the quantitative precipitation forecasts (QPFs) near landfall of the tropical storms. 3) A 1-h rapid-update analysis cycle at high resolution (9 km) provides more accurate tropical cyclone forecasts than a regular 6-h analysis cycle at coarse (27 km) resolution. The high-resolution rapidly updated 3DVAR analysis cycle might be a practical way to assimilate the data collected from tropical cyclone field experiments.

weather and forecasting

The Impact of Aircraft Dropsonde and Satellite Wind Data on Numerical Simulations of Two Landfalling Tropical Storms during the Tropical Cloud Systems and Processes Experiment