Evaluation of Simulated Active Layer Depths in the Regional Arctic System Model
The active layer is the seasonally frozen soil layer between the ground surface and the permafrost. The seasonal thickness and spatial extent of the active layer play import roles in high-latitude thermodynamic, hydrologic, and biogeochecmical processes. Coupled land-atmosphere climate models have historically struggled to accurately reproduce the active layer thickness or extent. The Regional Arctic System Model (RASM) is a high-resolution fully-coupled regional earth system model applied over the Pan-Arctic domain. RASM has been developed to improve the representation and understanding of key high-latitude physical processes, and to advance multi-decadal climate prediction capabilities in the region. RASM is composed of the Weather Research and Forecasting (WRF) atmospheric model, the Variable Infiltration Capacity (VIC) hydrology model, the RVIC streamflow routing model, the Parallel Ocean Program (POP) model and the Los Alamos Sea Ice model (CICE). The individual component models are coupled using the Community Earth System Model (CESM) coupling infrastructure (CPL7). The current version of RASM is configured with a 1/48˚ ice-ocean grid and 25km land-atmosphere grid. Recent RASM development has included the coupling of VIC version 5.0, which includes a much more sophisticated frozen soils scheme. The improved soil thermal scheme includes an explicit coupling of the soil thermal and moisture fluxes, resolving the changes in soil column properties during periods melt and freeze. This work evaluates the performance of RASM land surface model and the land-atmosphere coupling in terms of the simulated behavior of frozen soils and the active layer. We compare results from fully-coupled RASM simulations, run between 1979 and 2015, to observations from the Circumpolar Active Layer Monitoring Network (CALM) and the FLUXNET datasets. We further compare RASM simulations to global modeling results from reanalysis and CMIP 5 datasets to put the performance of RASM in perspective with the current state of coupled land-atmosphere modeling.