Analysis of snow precipitation in 2000-09 and evaluation of a MSG/SEVIRI snow cover algorithm in SW Italian Alps

Authors

  • Silvia Terzago Dipartimento di Scienze della Terra, Università degli Studi di Torino, Torino, Italy Author
  • Roberto Cremonini ARPA Piemonte - Sistemi Previsionali, Torino, Italy Author
  • Claudio Cassardo Dipartimento di Fisica Generale «Amedeo Avogadro», Università degli Studi di Torino, Torino, Italy Author
  • Simona Fratianni Dipartimento di Scienze della Terra, Università degli Studi di Torino, Torino, Italy Author

DOI:

https://doi.org/10.4461/GFDQ.2012.35.9

Keywords:

Snow cover, Alps, Satellite, MSG SEVIRI, Climate change

Abstract

The automatic meteorological station network of Piedmont (North- West Italy), whose realization started in 1988, together with the pre-existing manned stations are now providing snow depth and fresh snow depth measurements in more than 100 sites spread out over Western Alps, also outside the geographical borders of the Region. The high spatial resolution network in combination with satellite devices can be used for an integrated monitoring of snow cover that combines information on snow depth, amount of snow precipitation and snow cover extension. In particular satellites can provide complementary knowledge on snow cover over large scale with spatial continuity, supplying the lack of data where surface measurements are not available. This study focus the attention on the decade 2000-2009, for which both surface and satellite data are accessible. The high density of meteorological stations in Western Italian Alps makes this area appropriate for testing a novel snow cover algorithm using Meteosat Second Generation (MSG) satellite data. In the first part the analysis of the mean condition of snow precipitation over South Western Italian Alps is presented. Ground-based automatic daily total and fresh snow depth measurements provided by the Regional Agency for the Environmental Protection (ARPA Piemonte) have been used to determinate snow indices and the snow precipitation variability over the 10 years period. In the second part a novel method to estimate the snow cover extension using satellite data from the SMG Spinning Enhanced Visible and Infrared Imager (SEVIRI) is described and discussed. The snow cover algorithm minimizes the number of unclassified pixel due to cloud obscuration taking advantage of the MSG high frequency of acquisition, which provides daylight images over the investigated area every 15 minutes. The algorithm has been tested for 19 case-studies referring to the period 2007- 2009 using surface stations data and then it has been applied to assess and compare the snow cover extension during the 2006-07 and 2007-08 snow seasons.

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Published

2024-06-12

Issue

Section

Research and review papers

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