Verification of analysed and forecasted winter precipitation in complex terrain
Numerical Weather Prediction (NWP) models are rarely verified for mountainous regions during the winter season, although avalanche forecasters and other decision makers frequently rely on NWP models. Winter precipitation from two NWP models (GEM-LAM and GEM15) and from a precipitation analysis syste...
Published in: | The Cryosphere |
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Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Copernicus Publications
2015
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Subjects: | |
Online Access: | https://doi.org/10.5194/tc-9-587-2015 https://noa.gwlb.de/receive/cop_mods_00017070 https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00017025/tc-9-587-2015.pdf https://tc.copernicus.org/articles/9/587/2015/tc-9-587-2015.pdf |
Summary: | Numerical Weather Prediction (NWP) models are rarely verified for mountainous regions during the winter season, although avalanche forecasters and other decision makers frequently rely on NWP models. Winter precipitation from two NWP models (GEM-LAM and GEM15) and from a precipitation analysis system (CaPA) was verified at approximately 100 stations in the mountains of western Canada and the north-western US. Ultrasonic snow depth sensors and snow pillows were used to observe daily precipitation amounts. For the first time, a detailed objective validation scheme was performed highlighting many aspects of forecast quality. Overall, the models underestimated precipitation amounts, although low precipitation categories were overestimated. The finer resolution model GEM-LAM performed best in all analysed aspects of model performance, while the precipitation analysis system performed worst. An analysis of the economic value of large precipitation categories showed that only mitigation measures with low cost–loss ratios (i.e. measures that can be performed often) will benefit from these NWP models. This means that measures with large associated costs relative to anticipated losses when the measure is not performed should not or not primarily depend on forecasted precipitation. |
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