Investigating the role of total precipitable water and leaf area index in the decoupling of passive microwave brightness temperatures over snow-covered regions of forested terrain in North America

Abstract:

Snow is a significant contributor to the Earth’s hydrologic cycle, energy cycle, and climate system due to its control of mass and energy exchanges at the land surface. In order to better protect and preserve this vital natural resource, it is essential to first quantify how much snow exists as a function of both time and space. Unfortunately, existing space-based snow mass (e.g., snow water equivalent [SWE]) estimation algorithms relying on passive microwave (PMW) brightness temperature (Tb) observations can significantly underestimate SWE, particularly in densely-forested regions since forest cover tends to modulate the snow-related portion of the Tb signal as measured from space. Both the overlying vegetation and the overlying atmosphere can attenuate surface microwave emission while simultaneously emitting its own radiation towards the satellite. A Tb decoupling process is explored here via parameterization of atmospheric and forest transmissivity as a function of satellite-derived total precipitable water (TPW) and leaf area index (LAI), respectively. This study also explores the sensitivity of the decoupled multi-frequency, multi-polarization Tb to different LAI retrieval algorithms. Preliminary results suggest the choice of LAI retrieval algorithm significantly affects the efficacy of the Tb decoupling procedure over snow-covered land, and therefore, an accurate representation of LAI as measured from space is integral for improved estimation of regional SWE using space-based passive microwave radiometers.