Coupling DMRT-ML to a Multi-Scale Passive Microwave Data

Abstract:

Dense Media Radiative Transfer Theory (DMRT) for multi layered snowpack (Picard et al., 2012), a physically based numerical model for microwave emission from snow, is coupled to passive microwave brightness temperature (Tb) observations to retrieve snow depth and snow water equivalent. Passive microwave data obtained from space-based and airborne radiometry were coordinated with intense snow-survey campaigns in the sub-Arctic Eureka tundra snow cover region during April 2011. The airborne Tb observations were made across a 50 x 50 km grid using two sampling approaches: high altitude, low spatial resolution observations with footprint dimensions of ~550 x 850 m and low altitude, high spatial resolution observations at ~70 x 110m. The Tb observations from the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), covering the study area in four pixels of 25 x 25 km, were also used to compare with the airborne observations.

A preliminary step in retrieval via physical modeling is parameterizing model inputs in the forward mode to assure an inverse model will result an accurate measure of the unknown variable (snow depth). Measurements of snowpack stratigraphy from snow-pits and interpolated snow depth data from magna probe measurements are used to force the DMRT model. While the optical grain size (D₀) is used in DMRT, observed grain diameter (D_max) was measured in the field. In this study, a method based on a practical approach that classifies SSA for each type of snow layer is used and optical grain size is then calculated using reported field data. Furthermore, we report on simple approaches to parameterize stickiness factor and snowpack physical temperature. Using forward DMRT model simulations of snow from different field observations, the sensitivity of the DMRT model to snowpack properties is evaluated at two scales: airborne and spaceborne. For instance, results indicate that 1 K change in snowpack physical temperature of 265 K results in ~1 K change of Tb at 36GHz, and 100 mm change in grain size from 400 to 500 mm (in a 30 to 50 cm snowpack) causes ~8 K change in simulated Tb. The analysis explains how Tbs from the high resolution airborne measurements scale up to the satellite observation scale. It also provides insight into the appropriate retrieval scheme suitable for satellite-scale estimates.