Dr. Emily Collier
Institut für Geographie
The Weather Research and Forecasting (WRF) model is an open-source, community-developed mesoscale atmospheric model that is widely used for both research and forecasting applications around the world, with more than 48,000 registered users in 160 countries. Researchers at Friedrich-Alexander University (FAU) Erlangen-Nürnberg have recently used WRF as a tool for investigating atmospheric impacts on the cryosphere around the world, including on Kilimanjaro, High Mountain Asia, Patagonia, and Greenland. Although these studies have yielded valuable insights on important processes impacting glaciers and ice fields, quantitative assessment of mass gains or losses (the sum of which in the upper subsurface and surface is referred to as the glacier’s climatic mass balance, or CMB) has been limited by the simplistic representation of the cryosphere in WRF. In the available land surface models, glaciers are treated as permanently snow-covered, fully saturated, and fully frozen soils. This treatment leads to unrealistic estimation of surface conditions and, therefore, of near-surface meteorological fields and precludes the representation of englacial processes (such as melting, refreezing, percolation, densification, and penetrating shortwave radiation) that are key for accurately quantifying subsurface mass fluxes.
This issue has been addressed by running offline simulations with glacier CMB models and by the development of a coupled WRF and glacier CMB modelling system. The coupled, or interactive, modelling approach is the most physically consistent, as the impact of changing glacier surface conditions can provide feedback to the atmospheric forcing fields. However, the coupled model has not been made available to the wider scientific community for two reasons. First, the glacier model is not available for public distribution and its treatment of the snowpack is too simplified for global applications. Second, the WRF source code is written in Fortran 90 and the glacier model was integrated by translating the entire code from MATLAB. As improved versions of both models are issued regularly, this coupling approach is not sustainable for keeping the modelling system up to date for public use.
I propose to implement a simpler coupling mechanism between WRF and the recently released open-source glacier CMB model, Python COSIPY. COSIPY provides a sophisticated treatment of snow and ice energy and mass balance. The model is optimized for parallel computing and is computationally efficient, with an annual simulation for a domain of 1000 x 1000 x 200 at hourly timesteps finishing in approximately three minutes.