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Advances in Statistical Climatology, Meteorology and Oceanography An international open-access journal on applied statistics
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Volume 4, issue 1/2
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 65–86, 2018
https://doi.org/10.5194/ascmo-4-65-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Adv. Stat. Clim. Meteorol. Oceanogr., 4, 65–86, 2018
https://doi.org/10.5194/ascmo-4-65-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  14 Dec 2018

14 Dec 2018

Hourly probabilistic snow forecasts over complex terrain: a hybrid ensemble postprocessing approach

Reto Stauffer1, Georg J. Mayr2, Jakob W. Messner3, and Achim Zeileis1 Reto Stauffer et al.
  • 1Department of Statistics, Faculty of Economics and Statistics, Universität Innsbruck, Universitätsstraße 15, 6020 Innsbruck, Austria
  • 2Institute of Atmospheric and Cryospheric Sciences, Faculty of Geo- and Atmospheric Sciences, Universität Innsbruck, Innrain 52, 6020 Innsbruck, Austria
  • 3Department of Electrical Engineering, Technical University of Denmark, Elektrovej, Building 325, 2800 Kgs. Lyngby, Denmark

Abstract. Accurate and high-resolution snowfall and fresh snow forecasts are important for a range of economic sectors as well as for the safety of people and infrastructure, especially in mountainous regions. In this article a new hybrid statistical postprocessing method is proposed, which combines standardized anomaly model output statistics (SAMOS) with ensemble copula coupling (ECC) and a novel re-weighting scheme to produce spatially and temporally high-resolution probabilistic snow forecasts. Ensemble forecasts and hindcasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) serve as input for the statistical postprocessing method, while measurements from two different networks provide the required observations.

This new approach is applied to a region with very complex topography in the eastern European Alps. The results demonstrate that the new hybrid method allows one not only to provide reliable high-resolution forecasts, but also to combine different data sources with different temporal resolutions to create hourly probabilistic and physically consistent predictions.

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Snowfall forecasts are important for a range of economic sectors as well as for the safety of people and infrastructure, especially in mountainous regions. This work presents a novel statistical approach to provide accurate forecasts for fresh snow amounts and the probability of snowfall combining data from various sources. The results demonstrate that the new approach is able to provide reliable high-resolution hourly snowfall forecasts for the eastern European Alps up to 3 days ahead.
Snowfall forecasts are important for a range of economic sectors as well as for the safety of...
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