Abstract
Microwave brightness temperature have widely been used for the detection of the ice sheet's surface melt conditions and understanding their spatio-temporal variability. In this study, we investigated the sensitivity of microwave brightness temperature products from three different sensors, namely, Advanced Microwave Scanning Radiometer-2 (AMSR2), Special Sensor Microwave Imager/Sounder (SSMIS) and Indian scatterometer satellite (SCATSAT-1) for surface melt detection over the Greenland ice sheet (GrIS). In-situ air temperature measurements from GC-Net AWSs were used for sensitivity and inter-comparison analysis. Our findings show that brightness temperature (Tb) from SSMIS better correlates (Pcoef = 0.81 for 19 GHz) with air temperature measurements in comparison to AMSR2 (Pcoef = 0.7 for 18 GHz) and SCATSAT-1 (Pcoef = 0.67). However, interestingly, AMSR2 and SCATSAT-1 uniquely discriminated the surface conditions during pre- and post-melt period, due to their heterogeneity in Tb values during the two period. Error analysis with respect to AWS melt days shows that SSMIS 19 GHz Tb (Tb/SSMIS/19H) products with TED method giving the most promising observations. A wide variability in Tb values is observed during the melt season across the various AWS sites depending upon the elevation, location and frequency. During our study period, using Tb/SSMIS/19H for TED method, we observed the highest melt extent area for the extreme melt event in year 2019 (∼1.12 million km2), followed by another melt event year 2021 when it went as high as ∼1.02 million km2.
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