Retrieval of snow depth on Antarctic sea ice from the FY-3D MWRI data
Abstract: The snow depth on sea ice is an extremely critical part of the cryosphere. Monitoring and understanding changes of snow depth on Antarctic sea ice is beneficial for research on sea ice and global climate change. The Microwave Radiation Imager (MWRI) sensor aboard the Chinese FengYun-3D (FY-3D) satellite has great potential for obtaining information of the spatial and temporal distribution of snow depth on the sea ice. By comparing in-situ snow depth measurements during the 35th Chinese Antarctic Research Expedition (CHINARE-35), we took advantage of the combination of multiple gradient ratio (GR (36V, 10V) and GR (36V, 18V)) derived from the measured brightness temperature of FY-3D MWRI to estimate the snow depth. This method could simultaneously introduce the advantages of high and low GR in the snow depth retrieval model and perform well in both deep and shallow snow layers. Based on this, we constructed a novel model to retrieve the FY-3D MWRI snow depth on Antarctic sea ice. The new model validated by the ship-based observational snow depth data from CHINARE-35 and the snow depth measured by snow buoys from the Alfred Wegener Institute (AWI) suggest that the model proposed in this study performs better than traditional models, with root mean square deviations (RMSDs) of 8.59 cm and 7.71 cm, respectively. A comparison with the snow depth measured from Operation IceBridge (OIB) project indicates that FY-3D MWRI snow depth was more accurate than the released snow depth product from the U.S. National Snow and Ice Data Center and the National Tibetan Plateau Data Center. The spatial distribution of the snow depth from FY-3D MWRI agrees basically with that from ICESat-2; this demonstrates its reliability for estimating Antarctic snow depth, and thus has great potential for understanding snow depth variations on Antarctic sea ice in the context of global climate change.
Figure 1. The distributions of ship routes during CHINARE-35 (blue line), the ship-based observational snow depth (red dots), Alfred Wegener Institute (AWI) snow buoy (orange line) and Operation IceBridge (OIB) airborne measurements (green line) (a) and snow depth estimation involving photogrammetric images (b). The long red line in b denotes the reference ball diameter, the short red lines denote snow depth on sea ice.
Figure 4. Comparisons of ship-based observational snow depth to the snow depth estimates based on the proposed model (a), Markus98 model (b) and Comiso03 model (c), and comparisons of AWI snow buoy data to the snow depth estimates based on the proposed model (d), Markus98 model (e) and Comiso03 model (f). The color bar represents the density of the points.
Figure 8. The spatial distributions of monthly snow depth (January to June 2020) derived from FY-3D MWRI (a) and ICESat-2 (b), with the probability density functions (PDFs) (c) from FY-3D MWRI (red line) and ICESat-2 (blue line) in the common area.
Figure 9. The spatial distributions of monthly snow depth (July to December 2020) derived from FY-3D MWRI (a) and ICESat-2 (b), with the probability density functions (PDFs) (c) from FY-3D MWRI (red line) and ICESat-2 (blue line) in the common area.
Table 1. Summary of snow depth from this study, NSIDC and NTPDC
Source Sensor Period Spatial resolution/km Modeling bands This study MWRI 2018–2020 12.5 10.65 GHz, 18.7 GHz, 36.5 GHz NSIDC AMSR2 2012 to now 12.5 18.7 GHz, 36.5 GHz NTPDC SSMIS, AMSR-E, AMSR2 2002–2020 25.0 6.9 GHz (19.35 GHz), 36.5 GHz
Table 2. The Correlation coefficient and RMSD between the ship-based observational snow depth and different GRs Derived from FY-3D MWRI
GR Correlation coefficient RMSD/cm GR Correlation coefficient RMSD/cm GR(18V, 10V) –0.66 9.95 GR(18H, 10H) –0.62 10.43 GR(23V, 10V) –0.63 10.34 GR(23H, 10H) –0.57 10.96 GR(36V, 10V) –0.72 9.06 GR(36H, 10H) –0.69 9.65 GR(23V, 18V) –0.49 11.60 GR(23H, 18H) –0.41 12.14 GR(36V, 18V) –0.73 8.95 GR(36H, 18H) –0.70 9.54 GR(36V, 23V) –0.70 9.50 GR(36H, 23H) –0.60 10.62 (GR(36V, 10V)+ GR(36V, 18V))/2 –0.73 8.91
Table 3. Differences between FY-3D MWRI snow depth, NSIDC-AMSR2 SD and NTPDC-AMSR2 SD in the Antarctic and five seas from 2018 to 2019
Region Dataset Comparison Bias/cm MAD/cm STD/cm Correlation coefficient Antarctic this study vs. NSIDC 4.27 5.58 6.42 0.83 this study vs. NTPDC –9.86 10.35 5.68 0.84 Weddell Sea this study vs. NSIDC 3.28 5.06 6.03 0.90 this study vs. NTPDC –9.84 10.26 5.34 0.87 Indian Ocean this study vs. NSIDC 5.92 6.36 5.79 0.52 this study vs. NTPDC –9.21 9.67 4.97 0.70 Pacific Ocean this study vs. NSIDC 5.83 6.77 7.64 0.54 this study vs NTPDC –10.05 10.81 6.81 0.74 Ross Sea this study vs. NSIDC 4.41 5.29 5.86 0.80 this study vs. NTPDC –9.81 10.25 5.38 0.80 Bellingshausen-Amundsen Sea this study vs. NSIDC 3.24 5.51 7.46 0.82 this study vs. NTPDC –10.69 11.30 6.90 0.83
Table 4. The comparisons between the OIB snow depth and FY-3D MWRI snow depth, NSIDC-AMSR2 SD, NTPDC-AMSR2 SD
Region snow depth dataset Pixel Number Bias/cm MAD/cm RMSD/cm Correlation
ALL this study 431 –4.17 11.52 15.10 0.46 NSIDC 431 –3.58 11.79 15.70 0.50 NTPDC 431 6.14 13.22 16.93 0.45 Weddell Sea this study 279 –4.76 8.24 10.78 0.65 NSIDC 279 –4.61 8.02 10.82 0.66 NTPDC 279 4.61 9.39 10.90 0.63 Bellingshausen-Amundsen Sea this study 81 12.42 14.49 17.78 0.26 NSIDC 81 15.23 16.73 20.06 0.08 NTPDC 81 25.73 27.22 30.30 0.14 East Antarctic this study 71 –20.78 21.05 23.81 0.27 NSIDC 71 –20.98 20.98 24.02 0.38 NTPDC 71 –10.18 12.29 15.02 0.39
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