Microwave remote sensing of rain-on-snow events in the subarctic with AMSR2 and GPM observations

Abstract:

Climate change in high northern latitudes is predicted to be greater in winter than in summer, and to have increasing, widespread impacts in northern ecosystems. Some of the resulting unknowns are the effects of an increasing frequency of sudden, short-lasting winter warming events, which can lead to rain on snow (ROS). Very little is known about ROS in northern regions, and even less about its cumulative impact on surface energy balance, permafrost, snow melt, and hydrological processes. Since, wintertime warming events have become more frequent in sub-Arctic regions, ROS event characteristics (frequency, extent, and duration) may represent new and relevant climate indicators. However, ROS event detection is challenging.

In this presentation, we propose new approaches to monitor the occurrence of ROS events using satellite passive and active microwave sensors. Specifically, we utilize observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), Global Precipitation Measurements (GPM) Microwave Imager (GMI), and GPM Dual-frequency Precipitation Radar (DPR). GPM was launched in February, 2014. It operates multiple radiometers (in the frequency range 10 – 183 GHz), and two radars (Ku and Ka bands). GPM observations are used to quantify rainfall or snowfall rates and are thus appropriate to monitor ROS events up to 66° North.

Our satellite monitoring of the ROS event is based on both temporal and spectral variations in the satellite observations. We discuss the observed ROS radiometric signatures using a Multi-Layer microwave emission model based on the Dense Media Radiative Transfer theory (DMRT-ML). In addition, our monitoring is evaluated against atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim, and NASA Modern-Era Retrospective analysis for Research and Applications (MERRA). This initial evaluation in winter months shows that the proposed ROS detection using microwave sensors occur in areas that are shown by the reanalysis data to be experiencing liquid precipitation while there is snow on the ground.