The Effects of Assimilating Satellite Brightness Temperature and Bogus Data on the Simulation of Typhoon Kalmaegi (2008)

Observational and bogus satellite data are directly assimilated into the Weather Research and Forecasting (WRF) model in simulations of Typhoon Kalmaegi (2008). The data assimilation is performed using the Radiative Transfer for TIROS-N Operational Vertical Sounder (RTTOV) model and the three-dimensional variational data assimilation (3DVAR) technique, with satellite observations taken from the National Oceanic and Atmospheric Administration-16 (NOAA-16) Advanced TIROS Vertical Sounder (ATOVS) system composed of the High-resolution Infrared Radiation Sounder (HIRS), the Advanced Microwave Sounding Unit-A (AMSU-A), and the Advanced Microwave Sounding Unit-B (AMSU-B). Data assimilation experiments are initialized at three different times. Improvements in the numerical simulation of the typhoon are discussed in the context of wind, temperature, pressure, and geopotential fields.The results indicate that assimilation of satellite data can improve both the representation of the initial conditions and the subsequent simulation of the typhoon. Different satellite data have different impacts on the typhoon track. In these simulations, data from AMSU-A play a greater role in improving the simulation of the typhoon than data from AMSU-B or HIRS. Assimilation of satellite data significantly affects the simulation of the subtropical high and the steering of the typhoon by the environmental flow. The subtropical high is enhanced and extends westward in the data assimilation experiments. The background flow therefore steers the typhoon more westward, improving the simulated typhoon track. Although direct assimilation of satellite brightness temperature improves the simulated environmental conditions, it does not significantly improve the simulated intensity of the typhoon. By contrast, initializing the typhoon simulation using bogus data in tandem with satellite data improves not only the environmental conditions but also the simulated inner-core structure of the typhoon. Assimilation of both types of data therefore improves the simulation of both the typhoon track and the typhoon intensity. The results of these experiments offer new insight into improving numerical simulations of typhoons.