Application of Direct Assimilation of ATOVS Microwave Radiances to Typhoon Track Prediction

In order to solve the difficult problem of typhoon track prediction due to the sparsity of conventional data over the tropical ocean, in this paper, the No. 0205 typhoon Rammasun of 4-6 July 2002 is studied and an experiment of the typhoon track prediction is made with the direct use of the Advanced TIROS-N Operational Vertical Sounder (ATOVS) microwave radiance data in three-dimensional variational data assimilation. The prediction result shows that the experiment with the ATOVS microwave radiance data can not only successfully predict the observed fact that typhoon Rammasun moves northward and turns right, but can also simulate the action of the fast movement of the typhoon, which cannot be simulated with only conventional radiosonde data. The skill of the typhoon track prediction with the ATOVS microwave radiance data is much better than that without the ATOVS data. The typhoon track prediction of the former scheme is consistent in time and in location with the observation. The direct assimilation of ATOVS microwave radiance data is an available way to solve the problem of the sparse observation data over the tropical ocean, and has great potential in being applied to typhoon track prediction.

Direct assimilation of simulated radar reflectivity for typhoon In-fa using EnKF:Issue with state variables updating

Using a convective scale WRF-GSI system and a reflectivity observation operator based on the double-moment microphysics(Thompson)scheme,simulated radar reflectivity data are produced and then directly assimilated with EnKF through Observing System Simulation Experi-ments(OSSEs)for the case of typhoon In-Fa(2021).We examined the ability of the EnKF to simultaneously estimate state variables and conducted sensitivity tests to evaluate the impact of updating different state variables.The results show that updating a full set of analysis variables can help obtain highly precise initialfields in the model and improve typhoon forecast skills.Excluding the horizontal wind update will affect the adjustment of the temperaturefield and the sea level pressurefield during the cyclic assimilation process.Updating the variables directly related to the reflectivity operator alone could adjust hydrometers well,but the positive impact arising from the assimilation quickly vanishes during the forecast.In addition,this study also includes a quantitative RMSE analysis for each variable during the assimilation cycle and compares the effect of each schemes on different variables.

Application of ATOVS Microwave Radiance Assimilation to Rainfall Prediction in Summer 2004

Experiments are performed in this paper to understand the influence of satellite radiance data on the initial field of a numerical prediction system and rainfall prediction. First, Advanced Microwave Sounder Unit A （AMSU-A） and Unit B （AMSU-B） radiance data are directly used by three-dimensional variational data assimilation to improve the background field of the numerical model. Then, the detailed effect of the radiance data on the background field is analyzed. Secondly, the background field, which is formed by application of Advanced Television and Infrared Observation Satellite Operational Vertical Sounder （ATOVS） microwave radiance assimilation, is employed to simulate some heavy rainfall cases. The experiment results show that the assimilation of AMSU-A （B） microwave radiance data has a certain impact on the geopotential height, temperature, relative humidity and flow fields. And the impacts on the background field are mostly similar in the different months in summer. The heavy rainfall experiments reveal that the application of AMSU-A （B） microwave radiance data can improve the rainfall prediction significantly. In particular, the AMSU-A radiance data can significantly enhance the prediction of rainfall above 10 mm within 48 h, and the AMSU-B radiance data can improve the prediction of rainfall above 50 mm within 24 h. The present study confirms that the direct assimilation of satellite radiance data is an effective way to improve the prediction of heavy rainfall in the summer in China.

An experimenal analysis for the impact of 2D variation assimilation of satellite data on typhoon track simulation

A series of test simulations are performed to evaluate the impact of satellite-derived meteorological data on numerical typhoon track prediction. Geostationary meteorological satellite (GMS-5) and NOAA's TIROS operational vertical sounder (TOVS) observations are used in the experiments. A two-dimensional variation assimilation scheme is developed to assimilate the satellite data directly into the Penn State-NCAR nonhydrostatic meteorological model (MM5). Three-dimensional objective analyses fields based on T213 results and routine observations are employed as the background fields of the initialization. The comparisons of the simulated typhoon tracks are also carried out, which correspond respectively to the initialization scheme with two-dimensional variation (2D - Var), three-dimensional observational nudging and direct assimilation of satellite data. It is found that, comparing with the experiments without satellite data assimilation, the first two assimilation schemes lead to significant improvements on typhoon track prediction. Track errors reduce by 18 % at 12 h for 2D - Var and from about 16 % at 24 h to about 35 % at 48 h for observational nudging. The simulated results based on assimilating different kinds of satellite data are also compared.