Review of Assimilating Spaceborne Global Navigation Satellite System Remote Sensing Data for Tropical Cyclone Forecasting  
[PERSON]  
1 National Space Science Center, Chinese Academy of Sciences (NSSC/CAS), Beijing 100190, China; [EMAIL_ADDRESS] (W.B. ); [EMAIL_ADDRESS] (G.W. ); [EMAIL_ADDRESS] (Y.S. ); [EMAIL_ADDRESS] (Q.D. ); [EMAIL_ADDRESS] (J.X. ); [EMAIL_ADDRESS] (X.W. ); xanganggngngngngngngngngngngngngngngngngngngngngngngngngn  
false alarm means that a TC forecast is made, but the time and track are incorrect. They investigated the prediction results of TCs using global NWP models, including the Global Environmental Multiscale Model of Environment and Climate Change Canada (CMC), the European Centre for Medium-Range Weather Forecasts global model (ECMWF), the Environmental Prediction Global Forecast System (GFS) of the American National Centers, and the Met Office Global Model (UKMET) [4]. Most predictions fell into the false alarm and miss categories as shown in Figure 1.  
The accurate forecast of a TC relies on a forecast model and an accurate initial guess of all atmospheric parameters, i.e., the model state. The initial guess is usually generated by a series, combining the forecast of the model and actual observations called data assimilation. The data assimilation utilizes actual observations with errors from different platforms and techniques to correct the model forecast and produce the best estimations of the model state. Therefore, observations with a large quantity and high accuracy are crucial to weather forecasts. In the mesoscale and global weather forecast, over 90% of observations are from satellite platforms. Satellites can provide a large number of observations on a global scale especially over the ocean using different remote sensing techniques. However, for the observations of TCs, many optical and microwave remote sensing technique observations cannot penetrate the cloud and heavy rains near the center of TCs, limiting the forecasting of the TC track and intensity. GNSS (Global Navigation Satellite System) remote sensing (GNSS-RS) is a new technique that has been developed in recent decades. Currently acknowledged GNSS systems include US GPS, European GALILEO, Russian GLONASS, and Chinese BeiDou, which  
Figure 1: Mean forecast performance for each model over the North Atlantic (circle) and eastern North Pacific (triangle) basins [5]. provide real-time, all-weather, anytime, anywhere, and high-precision observations by transmitting L band signals continuously. They have been broadly applied for positioning, navigation, and timing [6]. Based on the application and propagation of GNSS signals, there are mainly two branches of GNSS-RS: GNSS Radio Occultation (RO) and GNSS Reflectometry (GNSS-R). The former uses the GNSS signals refraction when they pass through the atmosphere, while the latter utilizes the reflection of the signals on the Earth's surface [7]. GNSS RO observations have many advantages, including global coverage, high accuracy, high vertical resolution, and insensitivity to clouds and precipitation, allowing for all-weather observations. For the troposphere, the departure of temperature, pressure, and potential temperature measured using RO is 0.7 K, 0.15%, and 1.4 K, and also the vertical resolution can reach 1.5 km [8]. With the development of background information, the departure becomes smaller as it gets closer to the lower troposphere [9]. For the troposphere and near the surface, the vertical resolution can reach 0.2 km or even 0.1 km [10]. As long as there are enough satellites equipped with RO receivers, RO data can achieve denser global coverage, especially in areas where conventional observation methods are lacking, such as the poles and oceans. Additionally, RO is a self-calibrating remote sensing technique and can be regarded as a calibration standard for other observation methods [11; 12]. Self-calibrating measures the change in the signal's properties, such as the phase delay. Therefore, RO data are traceable to GNSS atomic clocks and have a low bias.