Theoretical and Applied Climatology

, Volume 131, Issue 1–2, pp 1–17 | Cite as

Daily and climatological fields of precipitation over the western Alps with a high density network for the period of 1990–2012

  • Pierre LasseguesEmail author
Original Paper


There is still considerable uncertainty about precipitation at high elevation in mountain terrain due to the relatively few in situ measurements available and to the particular variability of the parameter. In this study, several spatialization techniques were tested, some for climatological time scale and others for daily fields, for precipitation over the western Alps for the period of 1990–2012. The study domain and period were chosen for the quality of available in situ observations and density of the network. First, a weather-type classification was established with a technique based on canonical correlation analysis combining large- and regional-scale data. The spatialization techniques applied for the climatological time scale were adapted from the Aurelhy method which uses elevation and principal components of the topography as predictors. The spatialization techniques applied to daily fields were based on kriging of daily rain gauges and used the climatological fields as predictors. This study aims to validate the advantage of using the climatology of the weather type of the day as predictor for daily fields over a monthly climatology. The climatology of the weather type of the day seems to demonstrate some small improvement.

Finally, annual means over the period of 1990–2012 were produced using several methods, including some from accumulation of daily fields and others from the spatialization of in situ station means. Precipitation at high elevations and vertical climatological gradients were particularly scrutinized. Annual means based on sums of daily fields seem to have better performances.

This paper only presents results for precipitation but temperature was also analysed.



This study was realized with the help of the software R (

The author of this study expresses his acknowledgements to the providers of the data: ARPA Piemonte, ARPA Val d’Aosta, Météo-France and Meteo-Swiss.

Supplementary material

704_2016_1954_MOESM1_ESM.pdf (2 mb)
ESM 1 (PDF 2009 kb)


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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  1. 1.Météo-France Direction de la Climatologie (DCSC)ToulouseFrance

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