Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
21 Nov 2016
Review status
A revision of this discussion paper was accepted for the journal The Cryosphere (TC) and is expected to appear here in due course.
Eurasian snow depth in long-term climate reanalyses
Martin Wegmann1,2,3, Yvan Orsolini4, Emanuel Dutra5, Olga Bulygina6, Alexander Sterin6, and Stefan Brönnimann2,3 1Institut des Géosciences de l'Environnement, University of Grenoble, France
2Oeschger Centre for Climate Change Research, University of Bern, Switzerland
3Institute of Geography, University of Bern, Switzerland
4NILU – Norwegian Institute for Air Research, Kjeller, Norway
5ECMWF European Centre for Medium-Range Weather Forecasts, Reading, UK
6All-Russian Research Institute of Hydrometeorological Information – World Data Centre, Obninsk, Russian Federation
Abstract. Snow cover variability has significant effects on local and global climate evolution. By changing surface energy fluxes and hydrological conditions, changes in snow cover can alter atmospheric circulation and lead to remote climate effects. To analyze such multi-scale climate effects, atmospheric reanalysis and derived products offer the opportunity to analyze snow variability in great detail far back in time. So far only little is know about their quality. Comparing four long-term reanalysis datasets with Russian in situ snow depth data, a good representation of daily to sub-decadal snow variability was found. However, the representation of pre-1950 inter-decadal snow variability is questionable, since datasets divert towards different base states. Limited availability of independent long-term snow data hinders investigating this bifurcation of snow states in great detail, but initial investigations reveal a non-stationary performance of snow evolution representation. This study demonstrates the ability of long-term reanalysis to reproduce snow variability accordingly.

Citation: Wegmann, M., Orsolini, Y., Dutra, E., Bulygina, O., Sterin, A., and Brönnimann, S.: Eurasian snow depth in long-term climate reanalyses, The Cryosphere Discuss., doi:10.5194/tc-2016-253, in review, 2016.
Martin Wegmann et al.
Martin Wegmann et al.


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Short summary
We investigate long-term climate reanalyses datasets to infer their quality in reproducing snow depth values compared to in-situ measured data from meteorological stations that go back until 1900. We found out that the long-term reanalyses do a good job in reproducing snow depths, but have some questionable snow states early in the 20th century. Thus, with care, climate reanalyses can be a valuable tool to investigate spatial snow evolution in global warming and climate change studies.
We investigate long-term climate reanalyses datasets to infer their quality in reproducing snow...