Research On Spaceborne GNSS-R Monitoring Of Typhoon Change Process

Typhoon is one of the most serious natural disasters and the changes in sea surface wind fields are closely related to the development process of typhoons.Therefore,monitoring sea surface wind field plays an important role in typhoon monitoring and early warning.Traditional observations of sea surface wind field mostly use buoy site measurements and marine meteorological satellite observations,but there are still problems such as insufficient temporal and spatial resolution,single observation methods and high costs.The satellite-borne global navigation satellite system reflectometry(GNSS-R)has the advantages with near real-time,allweather and extremely wide coverage,which provides a new observation method for sea surface wind field observation,and improves monitoring accuracy of tropical cyclones.This paper uses space-borne GNSS-R technology to invert the sea surface wind speed changes throughout the life cycle of a super typhoon for the first time,constructs a geophysical model(GMF)through high wind speed and low wind speed,and evaluates the performance of the model and the accuracy of wind speed inversion.Furthermore combining with the soil moisture active and passive detection program satellite(SMAP)satellite data,the development process of typhoons and the characteristics of sea surface wind speed changes are explored with the use of visual saliency and regional growth methods,which provides a reference for cyclone forecast and early warning.The main results are summarized as follows:(1)Normalized Bistatic Radar Cross Section(NBRCS)and Slope of the leading edge of the integrated delay waveform(LES)observations obtained from the Cyclone Global Navigation Satellite System(CYGNSS)are utilized.By collocating and matching with ERA-5reanalysis data,respectively,the empirical GMF formula model is established,and the performance of the empirical GMF model and the accuracy of wind velocity inversion are evaluated.The minimum variance estimation is further used to optimize the wind velocity inversion and improve the accuracy of wind velocity inversion.The results show that the overall root-mean-square Error(RMSE)of wind speed inversion for NBRCS is 2.26 m/s,and the average deviation is 1.30 m/s.However,the RMSE of wind speed inversion of LES is 2.54 m/s,and the average deviation is 1.39 m/s.Combining the two observations based on the minimum variance,the overall RMSE of the wind speed finally obtained is 1.64 m/s,and the average deviation is 0.67 m/s.(2)The empirical GMF model is used to invert the global sea surface wind speed change of super typhoon Mangkhut from September 6 to September 17,2018,from 40° south latitude to 40° north latitude,and analyze the inversion accuracy of sea surface wind speed during the typhoon period.The results show a good consistency.The error is concentrated near zero,and the larger error is concentrated in the region with higher wind speed or affected by typhoon(3)CYGNSS and Soil Moisture Active and Passive(SMAP)data are jointly used to observe the complete life cycle of No 22 Super Typhoon Mangkhut in 2018.Comparing the extracted typhoon center latitude and longitude with the tropical cyclone data provided by the China Meteorological Administration,the absolute longitude error is between 0.1° and 2.4°,the absolute error of latitude is between 0° and 0.9°,and the RMSE of longitude and latitude are0.83° and 0.44°,respectively.The joint observations are closer to typhoon reference data than a single CYGNSS or SMAP observation,which will improve temporal and spatial resolution of typhoon movement trends and wind speed changes.