 |
| Titel |
Methodological approaches to inferring end-of-winter snow distribution on alpine glaciers |
| VerfasserIn |
L. Sold, M. Huss, M. Hoelzle, P. Joerg, N. Salzmann, M. Zemp |
| Konferenz |
EGU General Assembly 2012
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250069777
|
|
|
|
|
|
| Zusammenfassung |
| End-of-winter snow distribution is a key variable in terms of glacier mass balance. However,
such measurements are typically rare and not adequately represented in today’s mass balance
models. A better understanding of processes governing preferential snow deposition and
redistribution on glacierized surfaces is a prerequisite for a more reliable impact assessment
of climate change on glaciers.
We present measurements of snow accumulation distribution from the 2009/2010 season
on Findelengletscher, Valais, Switzerland, a large alpine valley glacier (13.4 km2). Field data
were obtained simultaneously in April 2010 from (a) manual snow probing, (b) airborne
Ground Penetrating Radar (GPR) and (c) surface elevation changes given by two LIDAR
(Light Detection and Ranging) Digital Elevation Models (DEM). In this study, we aim at
combining and comparing these data sources of point, line and area type. In-situ snow
probings serve as ground reference. This data set consists of 463 point values covering the
entire glacier elevation range. Additionally, snow density was measured in 13 snow pits
across the glacier. The 500 MHz GPR survey was carried out from helicopter along 12.7
km of linear tracks providing about 10,000 evaluated traces. The surface elevation
change based on LIDAR DEMs of Oct. 2009 and Apr. 2010 is corrected for the
glacier dynamics using ice emergence velocity estimated with the 5-year average
surface mass balance and observed geometry changes. This data source provides fully
distributed spatial information on snow depth on a 1x1 m resolution grid over the entire
glacier.
The LIDAR-derived snow depth distribution differs from in-situ snow probings and the
GPR-based data particularly in crevassed areas and due to difficulties in the spatial correction
of glacier dynamics. These deviations are assessed by localizing error magnitudes and by
their dependency on elevation. The GPR-based measurements reveal general problems of
scale when comparing them with point-based snow probings on a rough surface such as on a
glacier. This is addressed by a variogram analysis to detect possible systematic biases.
Further, we compute the winter mass balance from the raw LIDAR surface elevation change
and snow density measurements as 0.620 m water equivalent (w.e.). Extrapolating the
snow distribution from the in-situ snow probings yields a higher winter balance of
0.780 m w.e. and allows a cross-validation with the GPR- and LIDAR-based data
sets.
Our results show that surface elevation change from LIDAR DEMs provides valuable
information on end-of-winter snow distribution but has to be carefully corrected
for glacier dynamics. Although not being truly distributed, the GPR-based data is
reliable and unaffected by glacier dynamics. Thus, helicopter-borne GPR offers a
straightforward and efficient tool for mapping the snow distribution on alpine glaciers.
Cross-comparison of the three data sets indicates that the conventional method of
extrapolating snow distribution from point probings might be subject to a systematic bias. |
|
|
|
|
|
|