Sea Surface Wind Speed Retrieval from the First Chinese GNSS-R Mission: Technique and Preliminary Results  
[PERSON]  
1 China Academy of Space Technology (Xi'an), Xi'an 710101, China; [EMAIL_ADDRESS] (C.J. ); [EMAIL_ADDRESS] (X.N. )12 State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China; [EMAIL_ADDRESS] School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China  
National Key Laboratory of Science and Technology and Space Microwaves, Xi'an 100101, China  
National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China; [EMAIL_ADDRESS]  
Xiaofeng Yang  
222212  
receiver, SGR-ReSI, collected a lot of valuable in-orbit data, including sea surface winds, sea surface height, inland soil moisture, and sea ice [16; 17; 18; 19; 20; 21]. The results of TDS-1 provide a strong support for future GNSS-R operational running of global wind speed retrieval. On 17 December 2016, NASA launched eight microsatellites to establish a constellation for observing tropical cyclones (TCs) with a high spatial-temporal resolution. The NASA Cyclone GNSS (CYGNSS) mission has demonstrated the capability of the GNSS-R technique to sense the TC eyes in high temporal resolution, optimize TC forecasts, supply monthly high-resolution soil moisture products, and map inland waterways [22; 23; 24; 25; 26]. Regarding the sea surface wind speed retrieval, approaches have experienced three stages. The first is based on the theory of the scattering model proposed by [PERSON] and [PERSON] in 2000 [3]. This theoretical model can simulate different sea state waveforms of GNSS-reflected signals so that wind speeds can be inversed by the delay waveform matching method [4; 5; 6; 7; 8]. The second stage focuses on the observables abstracted from the DDMs that are the standard product of airborne and spaceborne GNSS-R receivers. The observable DDM average (DDMA) directly relates to the sea surface roughness [27; 28; 29]. The third stage uses the normalized bistatic radar cross section (NBRCS), also known as the scattering coefficient, as an indicator to retrieve the sea surface wind speed [30]. The NBRCS calculation method has been proposed and improved in recent years [31; 32; 33; 34]. Combined with power calibration, the NBRCS can be calculated more accurately; therefore, it can agree well with the full sea surface wind speed range. The NBRCS is one of the two observables that produce the global tropical cyclone satellite product of the NASA CYGNSS constellation [23]. Typhoons are one of the most destructive natural disasters in China. Satellite remote sensing can provide near-real-time observations of typhoon tracks and intensities, which has become an indispensable part of typhoon monitoring and forecasting [35; 36; 37; 38; 39]. After recent years of research, the use of GNSS-R constellations to sense the sea surface roughness has been deemed a more effective and less costly method. On 5 June 2019, the first two Chinese GNSS-R satellites, BF-1 A/B, were launched into low Earth orbit (LEO) by the LongMarch 11 rocket at a sea launch platform as demonstration satellites for typhoon GNSS-R observations. Afterwards, following UK, US, and Japan, China became the fourth country that has GNSS-R satellites in Earth orbit. At the same time, BF-1 A/B is the only two-GNSS-R constellation in the world. The world's first spaceborne BDS DDM is also mapped in this mission. The next section provides an overview of the first Chinese GNSS-R mission, as well as a large amount of GNSS-R data collected from the global ocean surface in July and August 2019. In Section 3, new geophysical model functions (GMFs) for fully developed seas (FDSs) are proposed to derive the sea surface wind speed from the BF-1 NBRCS. Section 4 describes the preliminary retrieval and validation results for the sea surface wind speed, which are excellent for both the wind speed range and the accuracy compared with current GNSS-R missions.