C12 Coupling Processes between the Atmospheric Boundary-Layer and Snow/Ice Surfaces: Observations and Modelling

IACS (Cryosphere)



27-Jun-2015, 15:00 - 16:30


 
Abstract content:

A high density observation station network in the Berchtesgaden Alps for snow hydrological model evaluation.

Modeling the spatio-temporal distribution of snow cover properties (SWE and SD) in alpine environments is still very challenging. Frequently used model algorithms were often developed in regions and climatic conditions (e.g. flat, low-elevated and open terrain), different to them they are finally applied to (e.g. steep, high-elevated, wind-exposed, or forested). Snow model verification and validation in complex terrain are crucial in order to improve snow hydrological modeling in diverse mountainous landscapes. However, this requires high quality datasets with a high spatial distribution and temporal resolution.
We present an observation network providing data from 34 climate stations in the region of the Berchtesgaden Alps in southeastern Germany. Additionally a network of 25 snow monitoring stations (SnoMoS) and 10 time-lapse cameras was established in the investigated catchment (433 km2) including paired stations at open and forested sites.
Measured SD and SWE data in different elevations and expositions, as well as at forested and open sites were analyzed to characterize the seasonal snow cover distribution. The data was then used to evaluate the snow cover distribution simulated by the physically based distributed hydrological models AMUNDSEN and WaSiM. Preliminary results show that the observed timing of seasonal snowfall and melt out dates as well as SD and SWE values are well reproduced by the models throughout a large range of elevations and expositions. The models are able to simulate the meteorological conditions and snow amounts inside forests but have shown to require very accurate input data characterizing the forest canopy.

 
Author(s):
M. Warscher1, J. Garvelmann1, U. Strasser2, H. Franz3, H. Kunstmann1.
1Karlsruhe Institute of Technology KIT, Campus Alpin - Institute of Meteorology and Climate Research IMK-IFU, Garmisch-Partenkirchen, Germany.
2University of Innsbruck, Institute of Geography, Innsbruck, Austria.
3Berchtesgaden National Park Authority, Research and Information Systems, Berchtesgaden, Germany.

 

Keywords:
snow hydrology     observation network     snow modeling     SnoMoS     hydrological modeling