Abstract
Accurately simulating snow-cover dynamics and the snow-atmosphere coupling is of major importance for topics as wide-ranging as water resources, natural hazards and climate change impacts with consequences for sea-level rise. We present a new modelling framework for atmospheric flow simulations for cryospheric regions called CRYOWRF. CRYOWRF couples the state-of-the-art and widely used atmospheric model WRF, with the detailed snow-cover model SNOWPACK. CRYOWRF makes it feasible to simulate dynamics of a large number of snow layers governed by grain-scale prognostic variables with online coupling to the atmosphere for multiscale simulations from the synoptic to the turbulent scales. Additionally, a new blowing snow scheme is introduced in CRYOWRF and is discussed in detail. CRYOWRF's technical design goals and model capabilities are described and performance costs are shown to compare favourably with existing land surface schemes. Three case studies showcasing envisaged use-cases for CRYOWRF for polar ice sheets and alpine snowpacks are provided to equip potential users with templates for their research. Finally, the future road-map for CRYOWRF's development and usage is discussed.
Highlights
The cryosphere consists of regions of the Earth where snow and ice cover the surface for some reasonable period during the 15 course of the year
This article describes the first version of CRYOWRF, a new modelling framework to simulate atmospheric flows and snowpack dynamics in cryospheric environments
CRYOWRF is an extension of the widely-used atmospheric model, Weather Research and Forecasting Model (WRF), with an advanced complexity snow model, SNOWPACK acting as the land-surface model
Summary
The cryosphere consists of regions of the Earth where snow and ice cover the surface for some reasonable period during the 15 course of the year. From the perspective of land-atmosphere interaction, there is a stark contrast between snow-free and snow-covered regions in terms of mass and energy fluxes. These differences emerge due to the defining material properties of snow: high albedo, 25 low thermal conductivity, large latent heat for phase change and low mechanical roughness (Arduini et al, 2019). There is a vast area of the planet where accurately modelling the dynamics of snow-cover and its special interaction with the atmosphere is of primary importance
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