EGU24-17624, updated on 11 Mar 2024
https://doi.org/10.5194/egusphere-egu24-17624
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Snowfall variability, trends and their altitudinal dependence in the European Alps from ERA5, HISTALP and in-situ observations

Silvia Terzago1, Ludovica Martina Gatti2, Enrico Arnone3, and Michael Christian Matiu4
Silvia Terzago et al.
  • 1National Research Council of Italy, Institute of Atmospheric Sciences and Climate, Torino, Italy (s.terzago@isac.cnr.it)
  • 2University of Potsdam, Institute of Physics and Astronomy, Potsdam, Germany
  • 3University of Torino, Department of Physics, Torino, Italy
  • 4University of Trento, Department of Civil, Environmental and Mechanical Engineering, Trento, Italy

Mountain precipitation is a key feature of the hydrological cycle since it feeds snowpack, glaciers, river runoff and supports ecosystems and human life both locally and downstream. However, available precipitation datasets are affected by large uncertainties in mountain regions, especially during the cold season when most of the precipitation falls as snow: on one hand, commonly used precipitation gauges can have systematic losses up to 80-100% in case of snow precipitation, mainly owing to wind undercatch; on the other hand, reanalysis datasets generally provide much larger precipitation amounts when compared to observations and observation-based datasets. So, an accurate quantification of the snowfall component is crucially needed to reduce the uncertainty on mountain total precipitation in the cold season.    

In this work we present an extensive analysis of snowfall precipitation over the Greater Alpine Region (GAR) considering snowfall data from different data sources, including long-term in-situ observations, reanalysis and gridded datasets. We analyze: i) the most comprehensive observational dataset of monthly fresh snow depth (commonly employed as a measure of snowfall precipitation), consisting of more than 2000 in-situ station time series, covering 6 alpine countries (Switzerland, Austria, Germany, Slovenia, Italy and France); ii) the snowfall dataset provided by the ECMWF ERA5 global reanalysis at 0.25° spatial resolution, and iii) the HISTALP gridded snowfall dataset at 0.08° spatial resolution, which is based on temperature and precipitation observations. We compare the three datasets over the last decades to investigate i) climatological features of seasonal and monthly snowfall over the GAR; ii) snowfall variability and trends in relation to elevation; iii) snowfall trends in relation to temperature and total precipitation, based on the best available observational datasets; iv) uncertainties in the snowfall climatology and trends, by comparing the different data sources. This study provides a first comprehensive evaluation of the quality of ERA5 and HISTALP snowfall datasets against ground observations. Moreover, by quantifying the snowfall component, it contributes to better characterize mountain precipitation in the cold season.  

How to cite: Terzago, S., Gatti, L. M., Arnone, E., and Matiu, M. C.: Snowfall variability, trends and their altitudinal dependence in the European Alps from ERA5, HISTALP and in-situ observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17624, https://doi.org/10.5194/egusphere-egu24-17624, 2024.