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The Representation of slope- and ridge-Scale wind and snowfall patterns in models of different complexity

Authors

Mott,  Rebecca
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Kruyt,  Bert
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Fiddes,  Joel
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Gerber,  Franziska
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Reynolds,  Dylan
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Sharma,  Varun
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Mott, R., Kruyt, B., Fiddes, J., Gerber, F., Reynolds, D., Sharma, V. (2023): The Representation of slope- and ridge-Scale wind and snowfall patterns in models of different complexity, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4195


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021634
Abstract
We compare three models of different complexity in their ability to downscale and represent wind and snow fall patterns at the ridge- and slope scale. We present a comparison of three downscaling methods of varying complexity, that are used to downscale data from the Numerical Weather Prediction model COSMO-1 at 1.1 km horizontal resolution to 250 and 50 m in highly complex terrain. We compare WRF, a dynamical atmospheric model; ICAR, a model of intermediate complexity; and TopoSCALE, an efficient topography-based downscaling scheme. While point-scale validation at meteorological stations shows similar results for all three models, the spatial patterns vary significantly. Spatial snow deposition patterns are validated against LIDAR data and indicate that WRF is able to capture preferential deposition of snow, while ICAR shows a weak signal. Qualitative comparison of 3D ridge-flow interactions shows reasonable agreement between ICAR and WRF at 250 m resolution, yet at 50 m resolution WRF simulates complex flow patterns that ICAR cannot reproduce. Based on these findings and the significant reduction in computational costs, ICAR is a cost-efficient alternative to WRF at the 250 m resolution but is not able to capture complex ridge-scale flow patterns. TopoScale performs very well in point-scale comparisons, but it is unclear if this can be attributed to the model itself or to the forcing data and the observations assimilated therein. These finding motivated the recent development of a new model variant of the ICAR model (HICAR) which further improved the model performance at high resolutions and complex terrain.