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.

Snowfall variability, trends and their altitudinal dependence in the European Alps from ERA5, HISTALP and in-situ observations / Terzago, Silvia; Gatti, Ludovica Martina; Arnone, Enrico; Matiu, Michael Christian. - (2024). (Intervento presentato al convegno EGU24 tenutosi a Vienna, Austria nel 14 - 19 April 2024) [10.5194/egusphere-egu24-17624].

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

Matiu, Michael Christian
2024-01-01

Abstract

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.
2024
EGU General Assembly 2024
Vienna, Austria
Copernicus Meetings
Snowfall variability, trends and their altitudinal dependence in the European Alps from ERA5, HISTALP and in-situ observations / Terzago, Silvia; Gatti, Ludovica Martina; Arnone, Enrico; Matiu, Michael Christian. - (2024). (Intervento presentato al convegno EGU24 tenutosi a Vienna, Austria nel 14 - 19 April 2024) [10.5194/egusphere-egu24-17624].
Terzago, Silvia; Gatti, Ludovica Martina; Arnone, Enrico; Matiu, Michael Christian
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/408895
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex ND
social impact