Evaluation of Snow Depth and Soil Temperatures Predicted by the Hydro–Thermodynamic Soil–Vegetation Scheme Coupled with the Fifth-Generation Pennsylvania State University–NCAR Mesoscale Model

Abstract

Abstract The Hydro–Thermodynamic Soil–Vegetation Scheme (HTSVS) coupled in a two-way mode with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (NCAR) Mesoscale Meteorological Model (MM5) is evaluated for a typical snowmelt episode in the Baltic region by means of observations at 25 soil temperature, 355 snow-depth, and 344 precipitation sites that have, in total, 1000, 1775, and 1720 measurements, respectively. The performance with respect to predicted near-surface meteorological fields is evaluated using reanalysis data. Snow depth depends on snow metamorphism, sublimation, and snowfall. Because in the coupled model these processes are affected by the predicted surface radiation fluxes and cloud and precipitation processes, sensitivity studies are performed with two different cloud microphysical schemes and/or radiation schemes. Skill scores are calculated as a quality measure for the coupled model’s performance for a typical forecast range of 120 h for a typical spring (snowmelt) weather situation in the Baltic region. Discrepancies between predicted and observed snow-depth changes relate to the coupling. Enhanced water supply to the atmosphere, which results from water that was assumed to be open in MM5 but was actually ice covered in nature, finally leads to an overestimation of snowfall (input to HTSVS) and changes in snow depth (output). The resolution-dependent discrepancies between the terrain height in the model and real world also lead to snowfall where none occurred. For heavy snowfall the performance of the coupled model with respect to predicted snow-depth changes becomes nearly independent of the choice of the cloud microphysical and radiation schemes. As compared with observed changes in snow depth, the coupled model simulation using the Schultz scheme in conjunction with the radiation scheme from the Community Climate Model, version 2, (CCM2) predicts snow-depth changes of less than 2.5 mm considerably better than the other combinations that were tested. For thick snowpacks, the accuracy of the snow-depth decrease resulting from metamorphism strongly depends on the initial value of snow density. The coupled model acceptably captures the soil temperature diurnal cycles, the observed soil temperature increase with time, and the soil temperature behavior with depth. In general, discrepancies between simulated and observed soil temperatures decrease with soil depth. Simulations performed with the so-called CLOUD radiation scheme capture soil temperature minima and maxima better than do simulations performed with the CCM2 scheme.