Application Of GOES-16 Atmospheric Temperature Product Data Assimilation In A Hurricane Forecast

This article selects a case of Atlantic hurricane "Michael" in 2018.Based on the WRF model,three-dimensional variation(3DVar)and hybrid variational-ensemble(Hybrid)assimilation methods are used to achieve the assimilation of GOES-16 temperature profile products.The effects of different data thinning scale settings and different cycle assimilation intervals on hurricane forecasting based on the 3DVar assimilation method were studied.The single-point characteristics of different mixing coefficients and horizontal localization scales were analyzed when using the Hybrid assimilation method.Developed a sensitivity test on the effects of assimilation effects.The effects of assimilation increment,path intensity and precipitation prediction,root mean square error with height,and time over the two assimilation methods are comprehensively compared,and the impact of assimilation of GOES-16 temperature profile product data on hurricane forecast is evaluated.In addition,accuracy verification was performed for the FY-4 temperature profile data in China,and Typhoon Maria was selected as an example for assimilation experiments to analyze the effect of this data on the typhoon forecast effect.The research found that during hurricane "Michael",the root mean square error of GOES-16 temperature profile products at heights of 200 h Pa-1000 h Pa was within 2K,and the quality of the data was generally good.In the 3DVar assimilation scheme,when the GOES-16 temperature profile product is thinned to 60 km and the cycle assimilation interval is 6h,assimilating this data has a better enhancement of the temperature increment structure,the simulation of the wind field structure is conducive to the development of the hurricane,and the increase in the height of the potential can effectively correct the position of the hurricane,and it has a better prediction effect on the path and intensity.At the same time,both the24-hour cumulative precipitation structure and the ETS score are better.Different from the static background error covariance of the traditional 3DVar assimilation method,the hybrid has a "flow dependence" characteristic,and the single-point assimilation increment is irregularly distributed depending on the characteristics of the weather system.In view of the actual hurricane "Michael",in the hybrid assimilation scheme,when the mixing coefficient is0.5 and the horizontal localization scale is 200 km,the effect of path,intensity forecast and precipitation simulation is the best.A comprehensive comparison of the 3DVar and Hybridassimilation schemes,combined with a control test that not assimilate any observational data,proving that assimilation of GOES-16 temperature profile data can indeed effectively improve hurricane analysis and forecast fields.And the results of two different assimilation methods prove that the "flow dependence" characteristic of the assimilation increment obtained by hybrid method is more obvious,and it has a reasonable improvement on the initial field of the model.The temperature increase has a clear spiral structure,which is consistent with the characteristics of hurricanes,and the adjustment of the wind field and the geopotential height field is more conducive to the development of the hurricane.The effect of forecasting the path intensity and precipitation is also significantly better.With the height error and its change with time,the performance of Hybrid scheme is better than 3DVar scheme.In addition,during Typhoon Maria,assimilating the FY-4 temperature profile data improved the root mean square error of the analysis and forecast fields.