Abstract:
Vegetation plays a critical role in modulating snow accumulation processes. Snowpack, acting as an insolation layer (i.e., 'thermal blanket'), impedes heat exchange between ground and atmosphere and thus affecting subsurface thermodynamics. In this study, we use the NASA Catchment Land Surface Model (CLSM) driven by the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) land forcing fields to simulate active layer thickness (ALT) over permafrost regions in the Northern Hemisphere. We first demonstrate that most of the ALT variability can be jointly explained by accumulated air temperature and maximum snow water equivalent (SWE) in the CLSM-identified permafrost regions. Then, we discuss the impacts of vegetation and snow on ALT at several locations in high-latitude permafrost regions. At one particular site in Alaska, we show that replacing vegetation cover in the CLSM with the local vegetation type leads to improvements in the simulation results of snow depth, soil temperature profile, and ALT. Sensitivity analysis reveals that a thicker snowpack in winter season is able to facilitate a deeper ALT later in the warm season. That is, a larger snow depth could better slow down the heat release from soil to the atmosphere during the cold season, causing a warmer subsurface soil temperature and then a deeper thaw depth in summer. At last, we explore realistic methods to improve model simulation results.