This dataset contains UAV-based atmospheric profile observations and high-resolution atmospheric model simulations collected and produced during the first intensive observation period (IOP1) of the HEFEX III field campaign at Hintereisferner glacier.
\nThe HEFEX III campaign investigated glacier–atmosphere interactions and boundary-layer processes over alpine glaciers using a combination of in-situ observations, remote sensing techniques, and high-resolution numerical modelling.
\nThe observational component consists of vertical atmospheric profiles obtained using uncrewed aerial vehicles (UAVs) equipped withan iMet XQ-2 meteorological sensors.
\nTemperature and humidity measurements were obtained with an iMet XQ-2 sensor package, providing measurements at a sampling rate of 1 Hz.
\nObserved variables include:
\nWind information is derived from the UAV flight log and provided as 5-second averaged values, including:
\nDuring the campaign, UAV flights performed vertical ascents up to approximately 400 m above ground level.
\nProfiles were conducted every three hours, with an approximate ascent rate of 1 m/s, allowing high-resolution vertical sampling of the lower atmospheric boundary layer above the glacier.
\nThe dataset also contains large-eddy simulations performed with ICON in LES mode (ICON-LES) at a horizontal resolution of 51 m for the same time period as the lidar observations.
\nTo enable direct comparison with the UAV measurements, the dataset provides model output extracted from the grid cells corresponding to the UAV profile locations.
\nThe model data include the same atmospheric variables as the UAV observations where available, including:
\nModel values are provided for the lowest 50 model levels, corresponding to approximately 1300 m above ground level.
\nICON-LES outputs are provided as instantaneous model values at full-hour timestamps, corresponding to the times of UAV profiling.
\nThe dataset contains:
\nThe provided aggregation simplifies comparison between datasets but does not account for elevation offsets between the UAV launch location and the model topography.
\nDetailed descriptions of variables, units, file formats, and processing steps are provided in the accompanying README file.
\nThis dataset enables:
\nThe Glacier Space Zenodo Community hosts datasets generated within the research project “Glacier Space: Assessing the resilience and vulnerability of mountain ice masses.” The project investigates how glacier–atmosphere interactions shape the microclimate over mountain glaciers and how these processes influence glacier stability under ongoing climate change.
\nMountain glaciers interact with the atmosphere through a thin, stably stratified boundary layer near the ice surface. This layer often generates a characteristic downslope glacier wind that can partially isolate the glacier from the surrounding atmosphere. We refer to this protective microclimatic regime as a glacier “safe-space.” As glaciers shrink and their geometry changes—typically becoming smaller and steeper—the structure and strength of this boundary layer may weaken. This can increase the influence of external atmospheric disturbances and may accelerate glacier melt through positive feedback mechanisms.
\nThe Glacier Space project combines high-resolution field observations, micrometeorological measurements, remote sensing, and state-of-the-art atmospheric modelling to quantify how glacier microclimates evolve and how the protective “safe-space” may change in a warming climate. Field observations focus on the Alpine glacier Hintereisferner, which provides one of the world’s longest glacier monitoring records and an exceptional infrastructure for cryosphere–atmosphere research.
\nThis community provides open access to datasets produced within the project to support transparent, reproducible, and collaborative research on mountain glaciers and atmospheric processes.
\nThe Glacier Space Zenodo Community includes datasets generated through observational campaigns, modelling activities, and data processing workflows within the project. Data types may include:
\nThe community aims to provide datasets that support research on glacier–atmosphere coupling, mountain meteorology, turbulent processes, and glacier response to climate change.
\nDatasets published in this community follow principles of open science and reproducible research.
\nWhere possible, datasets adhere to FAIR principles (Findable, Accessible, Interoperable, Reusable).
\nWhen using datasets from this community, please cite the specific dataset DOI provided by Zenodo. Each dataset record contains a recommended citation format.
\nIn addition:
\nProper citation ensures that data producers receive credit and supports the continued sharing of high-quality research data.
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