Research On Microwave Data Assimilation Of Geostationary Orbit Meteorological Satellite Based On WRFDA

As the climate warms,the intensity and frequency of convective weather increases greatly,such as typhoons and heavy rains.Strong convective weather is often unable to produce more accurate forecasts in the meteorological field due to the lack of more accurate initial values.At present,the most effective way to improve the initial value is the data assimilation algorithm,which can improve the forecast field data by applying the observation data to the numerical forecast.Finally,we will get the initial value closer to the real field.For assimilation systems,satellite data has become an indispensable observation data,and its proportion in actual business is also growing.At present,in the assimilation test of the microwave band,the observation data are provided by the polar-orbiting satellite microwave load,but the traditional polar-orbit satellite microwave load has the disadvantages of long revisit time and small observation coverage,When we observe the weather with complex and variable temperature and humidity fields,high-frequency observations of their evolution cannot be performed,such as the typhoon,heavy rain,hail.The geostationary orbit meteorological satellite can perfectly avoid these shortcomings,which is why the international attention to geostationary orbit microwave detection is increasing.At present,China is carrying out research on geostationary orbit microwave load ground prototypes and key technologies,and has planned microwave detection satellites in China’s new generation of geostationary orbit meteorological satellite "FY4".Therefore,it is very necessary to carry out the static orbit microwave assimilation simulation test in advance.First,it is to accumulate experience for the future assimilation of geostationary orbit microwave data,because the geostationary orbit microwave load and the polar-orbit microwave load are different in the observation mode;the second is to evaluate the GEO microwave data.The performance of the typhoon forecast is improved after adding the assimilation system.In this paper,the WRF numerical prediction model and its integrated WRFDA-3DVAR will be used as research tools.Based on the observation system simulation experiment(OSSE),the assimilation experiment of static orbit simulation microwave observation data is carried out.The assimilated data bands include 50 GHz to 60 GHz oxygen absorption and 183 GHz water vapor absorption,the two important frequency bands for atmospheric detection.The experiment uses DOTLRT and CRTM radiation transmission modes to generate simulated observation brightness temperature data,and uses this as input to study the effects of cold and hot start,radiation transmission mode error,boundary conditions and other factors on assimilation results.The test scenario selected two typhoon cases,“Sura” in 2015 and “Aolu” in 2017,and used different assimilation schemes to compare and analyze the influence of data assimilation on the trajectory of typhoon and the intensity prediction performance of typhoon.In the simulation assimilation experiment,by assimilation of different simulation observations according to different schemes,we found that the assimilation of the typhoon trajectory and the prediction of typhoon intensity can be significantly improved after the assimilation of the static orbit simulation microwave load observation data,in the 72-hour forecast,the average error of the typhoon path relative to the forecast field is about 88 km,which is more than 40% better than the forecast field..Through the study of the hot and cold start assimilation experiment,we found that the hot start has obvious improvement on the atmospheric data such as cloud rain and water vapor in the analysis field.