IMPACTS OF ASSIMILATION FY2G AND FY4A ATMOSPHERIC MOTION VECTORS ON TYPHOON PREDICTION

Atmospheric motion vectors (AMVs) have produced positive impacts on global weather forecasts, but few studies have evaluated the impacts of AMVs data from Fengyun (FY) geostationary satellite series, especially from FY-2G and FY-4A, on typhoon forecasts in a regional model. In this study, the AMVs data of FY-2G and FY-4A were compared and evaluated by pre-processing methods such as height assignment, quality control, channel combination and thinning. Typhoon Haishen (No.10 super typhoon in 2020) was taken as an example. The AMVs data of the two satellites were assimilated by using 3DVAR provided by WRFDA and simulated by the WRF model to evaluate the forecast results of the two satellites, respectively. The results show that the AMV data from FY-4A are better overall than those from FY-2G, with smaller RMSEs and biases for full wind speeds. On the other hand, assimilation of AMVs data improves the forecasts of environmental fields, resulting in the simulated track closer to the best track. Another experiment shows that the assimilation of AMVs data has a good impact on precipitation prediction In general, the assimilation of FY-2G and FY-4A AMV data has a relatively positive impact on typhoon prediction, and the AMVs data combined with multiple channels can provide better prediction.