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.
Wegmann, M., Orsolini, Y., Dutra, E., Bulygina, O., Sterin, A., & Brönnimann, S. (2017). Eurasian snow depth in long-term climate reanalyses. Cryosphere, 11(2), 923–935. https://doi.org/10.5194/tc-11-923-2017