Assessment of various microwave brightness temperature products and methods for surface melt detection over Greenland ice sheet

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 (T_b) from SSMIS better correlates (P_coef = 0.81 for 19 GHz) with air temperature measurements in comparison to AMSR2 (P_coef = 0.7 for 18 GHz) and SCATSAT-1 (P_coef = 0.67). However, interestingly, AMSR2 and SCATSAT-1 uniquely discriminated the surface conditions during pre- and post-melt period, due to their heterogeneity in T_b values during the two period. Error analysis with respect to AWS melt days shows that SSMIS 19 GHz T_b (T_b/SSMIS/19H) products with TED method giving the most promising observations. A wide variability in T_b values is observed during the melt season across the various AWS sites depending upon the elevation, location and frequency. During our study period, using T_b/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.