Impact of Wind Profiler Data Assimilation on Wind Field Assessment over Coastal Areas

Precise analysis of local winds for the prediction of atmospheric phenomena in the planetary boundary layer is extremely important. In this study, wind profiler data with fine time resolution and density in the lower troposphere were used to improve the performance of a numerical atmospheric model of a complex coastal area. Three-dimensional variational data assimilation (3DVAR) was used to assimilate profiler data. Two experiments were conducted to determine the effects of the profiler data on model results. First, we performed an observing system experiment. Second, we implemented a sensitivity test of data assimilation intervals to extend the advantages of the profiler to data assimilation. The lowest errors were observed when using both radio sonde and profiler data to interpret vertical and surface observation data. The sensitivity to the assimilation interval differed according to the synoptic conditions when the focus was on the surface results. The sensitivity to the weak synoptic effect was much larger than to the strong synoptic effect. The hourly-assimilated case showed the lowest root mean square error (RMSE, 1.62 m/s) and highest index of agreement (IOA, 0.82) under weak synoptic conditions, whereas the statistics in the 1, 3, and 6 hourly-assimilated cases were similar under strong synoptic conditions. This indicates that the profiler data better represent complex local circulation in the model with high time and vertical resolution, particularly when the synoptic effect is weak.