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This is a real-data Four Dimensional Data Assimilation (FDDA) study using MM5 in conjunction with West
Texas Mesonet surface observations and ACARS (Aircraft Communications Addressing and Reporting System) profile
data collected by commercial aircraft during both en route and ascent/descent phases of their flights. The high-frequency
mesonet data and ACARS wind and temperature profiles are ideal for testing the effects of FDDA on short-term mesoscale
numerical weather prediction. The mesonet experiments involved 35 sites with an average horizontal spacing of about
30 km, while in the ACARS case ninety five profiles were used. Results indicated that nudging the MM5 model with the
surface-based data over the relatively small area of the mesonet domain had limited impact on the model’s performance.
In the ACARS runs, FDDA had long-lasting impact throughout the entire model atmosphere. FDDA appeared to improve
the quantitative precipitation forecasting skill of MM5 and reduce slightly the model’s warm bias at the surface. The study
suggests that ACARS has potential to significantly enhance our expertise in short-term mesoscale modeling and to support
the need to rapidly and accurately adjust high-resolution meteorological model forecasts to real-time observations.