Evaluation of the snow regime in dynamic vegetation land surface models using field measurements

Abstract

Abstract. An increasing number of studies have demonstrated significant climatic and ecological changes occurring in the northern latitudes over the past decades. As coupled Earth-system models attempt to describe and simulate the dynamics and complex feedbacks of the Arctic environment, it is important to reduce their uncertainties in short-term predictions by improving the description of both system processes and its initial state. This study focuses on snow-related variables and makes extensive use of a historical data set of field snow measurements acquired across the extent of the former Soviet Union to evaluate a range of simulated snow metrics produced by several land surface models, most of them embedded in IPCC-standard climate models. We reveal model-specific failings in simulating snowpack properties such as magnitude, inter-annual variability, timings of snow water equivalent and evolution of snow density. We develop novel and model-independent methodologies that use the field snow measurements to extract the values of fresh snow density and snowpack sublimation, and exploit them to assess model outputs. By directly forcing the surface heat exchange formulation of a land surface model with field data on snow depth and snow density, we evaluate how inaccuracies in simulating snow metrics affect soil temperature, thaw depth and soil carbon decomposition. We also show how field data can be assimilated into models using optimization techniques in order to identify model defects and improve model performance.

Temperature and Snow-Mediated Moisture Controls of Summer Photosynthetic Activity in Northern Terrestrial Ecosystems between 1982 and 2011

“…The result of the lagged coupling between vegetation and seasonal snow dynamics is consistent with the hypothesis that spring productivity gains from earlier thaw and extension of the growing season could potentially be offset by drought-induced productivity losses later in the season [4,16,21,35]. Since most Dynamic Global Vegetation Models (DGVMs) have only a limited ability to realistically simulate snowpack dynamics and feedbacks in forested regions [97,98], the sensitivity of the boreal forests to snow hydrology described in this empirical study may not be well captured in current simulations of the carbon cycle.…”

Review article: Parameterizations of snow-related physical processes in land surface models

“…Spatial variation of snow depth and temporal consistency of snow cover diversified due to snow freezing temperature, slope, aspect, and radiation. Hojatimalekshah et al (2020) examined the relationship between tree canopy and snow depth and Kantzas et al (2014) investigated the change of the snow regime according to vegetation dynamics through a ground model; these studies show that consideration of the vegetation effect is necessary for the snow parameterization method.…”