# Application of HY-2B Satellite Data to Retrieve Snow Depth on Antarctic Sea Ice  
Qing Ji  
1 School of Geography and Tourism  
sea ice thickness from a satellite altimeter, impacting the accuracy of sea ice thickness and volume retrieval [9; 10; 11]. Consequently, understanding the mechanisms governing sea ice variation and the associated climate implications necessitates the investigation of snow depth on sea ice. However, the harsh climatic conditions prevailing in Antarctica, combined with the scarce field measurements, emphasize the urgent need to enhance research on large-scale variations in snow depth on Antarctic sea ice. Field observations and airborne snow radar measurements are employed for investigating snow depth on sea ice. Notable data sources include in situ snow depth observations hosted by the Australian Antarctic Data Centre (AADC), ship-based observations from the Antarctic Sea Ice Processes and Climate (ASPeCt) initiative, and airborne measurements collected during Operation IceBridge (OIB) [12; 13; 14]. However, these data provide localized and time-specific information on snow depth. Hence, passive microwave remote sensing, with the advantages of being low-cost and having daylight and weather-independent observations, has become a preferred method for obtaining long-term, large-scale snow depth variations on Antarctic sea ice [15; 16]. [PERSON] and [PERSON] (1998) first constructed a regression model using the gradient ratio (GR) of the vertically polarized brightness temperature at 19 and 37 GHz measured from the Special Sensor Microwave Imager (SSM/I) sensor with ship-based snow depth observational data [15]. [PERSON] et al. (2003) subsequently adapted the algorithm to passive microwave remote sensing data from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) [17]. [PERSON] et al. (2006) identified a robust correlation between surface roughness of sea ice and snow depth [18]. [PERSON] et al. (2008) and [PERSON] et al. (2015) validated this correlation using ice station measurements and ship-based observations, respectively, on rough sea ice in the Eastern Antarctic and the Bellinghausen Sea, respectively; the AMSR-E snow products underestimate the observed snow depth by a factor of two to four [19; 20]. [PERSON] et al. (1998) also confirmed the impact of surface roughness on snow depth retrieval using ICESat data [21]. [PERSON] et al. (2018) attempted to use lower frequencies for retrieving deep snow and making the algorithm applicable to multi-year ice in the Arctic, utilizing five years of airborne snow data from OIB [22]. [PERSON] et al. (2022) analyzed seven-year airborne measured snow depth data from OIB, deriving new coefficients of the regression model to enhance snow depth retrieval using gradient ratios calculated at 7 and 39 GHz in the vertical polarization channels of passive microwave radiometers [23]. As the research on the retrieval of snow depth from passive microwave data continues to advance, various organizations have released snow depth products. The National Aeronautics and Space Administration (NASA) released the products of snow depth on Arctic first-year sea ice, which were derived from SSM/I data spanning 1978-2007. The University of Bremen (UB) and the National Snow and Ice Data Center (NSIDC) released snow depth products for 2002-2011 derived from AMSR-E data. Subsequently, the NSIDC released snow depth products from 2011 to the present study using AMSR-2 (Advanced Microwave Scanning Radiometer 2) data. However, due to the limitations of satellite sensor lifespans, the AMSR-E and AMSR-2 snow depth products are discontinuous in time. It should be noted that there is no Antarctic snow depth product released by Chinese organizations using passive microwave data from Chinese satellite measurements.