Comparison of glacier surface classes in the Ötztal Alps from the openAMUNDSEN model and from remote sensing data

Assigned Session: #AGM28: Generic Meeting Session

Abstract ID: 28.7477 | Accepted as Poster | Poster | 2025-02-28 12:45 - 14:15 | Ágnes‐Heller‐Haus/Small Lecture Room

Anne Hartig (0)
Rottler, Erwin (1), Schwaizer, Gabriele (2), Strasser, Ulrich (1)
Anne Hartig ((0) University of Innsbruck, Innrain 52f, 6020, Innsbruck, Tyrol, AT)
Rottler, Erwin (1), Schwaizer, Gabriele (2), Strasser, Ulrich (1)

(0) University of Innsbruck, Innrain 52f, 6020, Innsbruck, Tyrol, AT
(1) Institute of Geography, University of Innsbruck, Innsbruck, Austria
(2) ENVEO-Environmental Earth Observation Information Technology GmbH, Innsbruck, Austria

(1) Institute of Geography, University of Innsbruck, Innsbruck, Austria
(2) ENVEO-Environmental Earth Observation Information Technology GmbH, Innsbruck, Austria

Categories: Glacial Hydrology
Keywords: Glacier Surface Classes, Ötztal Alps

Categories: Glacial Hydrology
Keywords: Glacier Surface Classes, Ötztal Alps

This study focuses on the multi-temporal (2015–2021) analysis of a remote sensing derived glacier surface classification (GSC) product and the retrieval of snow line altitudes (SLA) through openAMUNDSEN model results as well as an intercomparison of both data sets. The spatial focus is on the Ötztal Alps and selected glaciers within this high alpine region. The temporal focus is on the ablation period, from May to September each year between 2015 and 2021.

GSC mapping differs from conventional snow cover mapping in glacierized regions by the differentiation of the glacier surface into classes such as new snow, old snow and/or firn, and glacier ice. A GSC dataset was obtained using the cryolayer approach of the openAMUNDSEN model. It provides several additional state variables for the individual classes, including their thickness. The GSC data from remote sensing data was generated by ENVEO-Environmental Earth Observation Information Technology GmbH within the ESA EXRPO+ AlpGlacier project and kindly provided for the use in this work. It reveals the spatial extent of these glacier surface classes. Both datasets are analyzed for their temporal changes in the spatial distribution of the GSC. Additionally, the snowline is calculated from both.

We thereby aim to answer the following research questions:

– To which degree is it possible to model a GSC dataset similar to the remote sensing product?

– Which multi-annual changes can be identified from the analysis of the GSC distribution and SLA retreat per season as well as over the whole timeframe?

– Which differences can be identified in the two datasets and how can this be used in future studies? Preliminary results indicate that it is possible to model a GSC dataset using the cryolayer approach of the openAmundsen model. Modeling with the thickness of the layers as a state variable allows for tracing melting processes affecting the layers at different time steps.

Both datasets exhibit discontinuous, patchy melting patterns and a complete melt-out of the snow cover on the glaciers per ablation season. In the case of the model, the results not only show melting of the snowpack but also the glacier ice beneath it. The SLA in both datasets exhibits a similar tendency, following a seasonal pattern of upward propagation on the glaciers, except for interruptions caused by snowfall events.

The comparability of the datasets is limited by differences in the temporal resolution. The modeled dataset offers daily, continuous data, while the remote sensing dataset provides discontinuous data, depending on the acquisition date and cloud free observation conditions. The model tends to show a delayed snow retreat compared to what is observed in the remote sensing data. However, towards the end of each water year, the model appears to “catch up” with the observed data.

The findings can contribute to a better understanding of glacier surface processes during the ablation season, the influence of lateral transport mechanisms on later melt patterns, and long-term change of ablation season patterns due to climate change.


NAME:
Small Lecture Room
BUILDING:
Ágnes‐Heller‐Haus
FLOOR:
0
TYPE:
Lecture Hall
CAPACITY:
200
ACCESS:
Only Participants
ADDITIONAL:
TBA
FIND ME:
>> Google Maps