Operational and experimental snow observation systems in the upper Rofental: data from 2017 to 2023

• Published in: Earth system science data 2024-08, Vol.16 (8), p.3579-3599
• Main Authors: Warscher, Michael, Marke, Thomas, Rottler, Erwin, Strasser, Ulrich
• Format: Article
• Language: English
• Subjects: Altitude; Automatic weather stations; Blowing rate; Blowing snow; Blowing time; Catchment area; Climate change; Data collection; Datasets; Drift; Drift rate; Equivalence; Field study; Forecasting services; Geography; Glaciers; High altitude; High-altitude environments; Hydrology; Hydrometeorological data; Hydrometeorology; Precipitation; Precipitation (Meteorology); Radiation measurement; Research centers; Snow; Snow accumulation; Snow cover; Snow density; Snow depth; Snow transport; Snow-water equivalent; Snowdrifts; Surface temperature; Temperature profile; Temperature profiles; Time series; Water; Water depth; Weather; Weather forecasting; Wind measurement; Wind speed
• ISSN: 1866-3516; 1866-3508; 1866-3516
• DOI: 10.5194/essd-16-3579-2024

This publication presents a comprehensive hydrometeorological data set for three research sites in the upper Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria) and is a companion publication to a data collection published in 2018. The time series presented here comprise data from 2017 to 2023 and originate from three meteorological and snow hydrological stations at 2737, 2805, and 2919 m a.s.l. The fully equipped automatic weather stations include a specific set of sensors to continuously record snow cover properties. These are automatic measurements of snow depth, snow water equivalent, volumetric solid and liquid water contents, snow density, layered snow temperature profiles, and snow surface temperature. One station is extended by a particular arrangement of two snow depth and water equivalent recording devices to observe and quantify wind-driven snow transport. These devices are installed at nearby wind-exposed and sheltered locations and are complemented by an acoustic-based snow drift sensor. We present data for temperature, precipitation, humidity, wind speed, and radiation fluxes and explore the continuous snow measurements by combined analyses of meteorological and snow data to show typical seasonal snow cover characteristics. The potential of the snow drift observations is demonstrated with examples of measured wind speeds, snow drift rates, and redistributed snow amounts during several blowing snow events. The data complement the scientific monitoring infrastructure in the research catchment and represent a unique time series of high-altitude mountain weather and snow observations. They enable comprehensive insights into the dynamics of high-altitude meteorological and snow processes and are collected to support the scientific community, local stakeholders, and the interested public, as well as operational warning and forecasting services. The data are publicly available from the GFZ Data Services repository: https://doi.org/10.5880/fidgeo.2023.037 (Department of Geography, University of Innsbruck, 2024).