Assessment of Greenland surface melt algorithms based on DMSP and SMOS data

Satellite-borne microwave radiometers provide essential measurements to study the surface melt state of ice sheets.Therefore,selecting suitable microwave radiometer data is critical to characterize the spatial distribution of surface melt.In this study,we investigated the Greenland Ice Sheet and evaluated the usefulness,as climate indicators,of data acquired by microwave radiometers onboard the F17 satellite of the United States of America Defense Meteorological Satellite Program(DMSP)and the Soil Moisture and Ocean Salinity(SMOS)satellite of the European Space Agency.First,surface melt was simulated using the DMSP dataset as input for a brightness temperature threshold algorithm,the Microwave Emission Model of Layered Snowpacks(MEMLS2),and the SMOS dataset as input for the L-band Specific MEMLS(LS-MEMLS).For accuracy evaluation,the simulation results were then compared with surface melt estimates derived from air temperature measurements at Automatic Weather Stations and from ice surface temperature measurements from the Moderate Resolution Imaging Spectroradiometer(MODIS)satellite-borne instrument.Our results show that global(over Greenland)MEMLS2 simulation performance(overall accuracy 83%)was higher than that of LS-MEMLS(overall accuracy 78%).However,in southeastern Greenland,MEMLS2 omission error was markedly higher than that of LS-MEMLS,whereas LS-MEMLS could detect longer-lasting surface melt than MEMLS2.This analysis showed that DMSP-based surface melt simulations are more accurate than SMOS-based simulations,thereby providing a data selection reference for surface melt studies of the Greenland Ice Sheet.