GRACE and AMSR-E-based estimates of winter season solid precipitation accumulation in the Arctic drainage region

Abstract

Solid precipitation plays a major role in controlling the winter hydrological cycle and spring discharge in the Arctic region. However, it has not been well documented due to sharply decreasing numbers of precipitation gauges, gauge measurement biases, as well as limitations of conventional satellite methods in high latitudes. In this study, we document the winter season solid precipitation accumulation in the Arctic region using the latest new satellite measurements from the Gravity Recovery and Climate Experiment (GRACE) and the Advanced Microwave Scanning Radiometer?Earth Observing System (AMSR?E). GRACE measures the winter total water (mainly from snow water equivalent (SWE)) storage change through gravity changes while AMSR?E measures the winter SWE through passive microwave measurements. The GRACE and AMSR?E measurements are combined with in situ and numerical model estimates of discharge and evapotranspiration to estimate the winter season solid precipitation accumulation in the Arctic region using the water budget equation. These two satellite?based estimates are then compared to the conventional estimates from two global precipitation products, such as the Global Precipitation Climatology Project (GPCP) and Climate Prediction Center？s Merged Analysis of Precipitation (CMAP), and three reanalyses, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, the European Centre for Medium?Range Weather Forecasts？ERA?Interim, and the Japan Meteorological Agency？s Climate Data Assimilation System (JCDAS) reanalysis. The GRACE?based estimate is very close to the GPCP and ERA?Interim estimates. The AMSR?E?based estimate is the most different from the other estimates. This GRACE?based measurement of winter season solid precipitation accumulation can provide a new valuable benchmark to understand the hydrological cycle, to validate and evaluate the model simulation, a