Quantitative assessment of the parameterization sensitivity of the WRF/Noah-MP model of snow dynamics in the Tianshan Mountains, Central Asia

Abstract

The study of parameterization schemes is important for land surface models (LSMs) due to the uncertainties existed in simulating snow. However, previous studies have mainly assessed the qualitative sensitivity of parameterization combinations on snow simulations in LSMs. To better understand the parameterization schemes and reduce the model uncertainties in simulating snow depth, 24 ensemble experiments were conducted in this study using the Weather Research and Forecasting (WRF) model coupled with the Noah land surface model with multiparameterization options (WRF/Noah-MP) model based on four physical subprocesses: snow surface albedo (ALB); precipitation partitioning between rain and snowfall (SNF); snow/soil temperature time (STC); surface layer turbulence (SFC) schemes. Additionally, the sensitivities of the four parameterizations in simulating the snow depth were quantitatively assessed. The results showed that the WRF/Noah-MP model underestimated snow depth, with underestimation in the snow accumulation season and overestimation in the early snow accumulation and snow ablation seasons. The Sobol sensitivity revealed the dominant role of the ALB and STC subprocesses in the simulation of the snow depth. The sensitivities of the four physical subprocesses varied in the different snow seasons and at different altitudes. Additionally, all the subprocesses exhibited interactions when simulating the snow depth in the Tianshan Mountains in this study, except for the ALB in the snow ablation season and the STC at >1000 m. Distinct differences existed in the snow depth simulations using the different selected schemes with the ALB, STC, and SFC subprocess parameterization. Comparison of the parameterization schemes of the four subprocesses revealed that the ALB, STC, and SFC subprocess parameterizations mainly affected the snow depth simulation through the heat fluxes, while the SNF affected it through the air temperature.