Item: Modeling snow water equivalent exclusively from daily snow depths
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Title: Modeling snow water equivalent exclusively from daily snow depths
Proceedings: International Snow Science Workshop Proceedings 2018, Innsbruck, Austria
Authors:
- Michael Winkler [ ZAMG - Zentralanstalt f ür Meteorologie und Geodynamik, Innsbruck, Austria ]
- Harald Schellander [ ZAMG - Zentralanstalt f ür Meteorologie und Geodynamik, Innsbruck, Austria ]
Date: 2018-10-07
Abstract: Many applications and studies, like climate and extreme value analyses, are seeking for longterm records of snow water equivalent (SWE). Measurements of SWE are principally scarce; SWE data older than 50 years hardly exist at all. However, there are many observation sites with long-term snow depth records. In order to assign SWEs to snow depths, different models have been developed. On the one side there are process-based snowpack models. They depend on meteorological input which often is not available for old snow records. On the other side there are parametrizations of snow density based on its statistical relations to snow depth, date, altitude and climate region. These often fail to model seasonal maxima of SWE and are unsuited to provide SWE of a certain day. A new semi-empirical snow model is presented, bridging the gap between above mentioned models. It is a layer model addressing basic settlement mechanisms as well as rain-on-snow events and ablation. Preliminary results show a clear improvement in SWE modeling compared to statistical models, whereas computational efforts stay small and necessary input is limited to snow depth only.
Object ID: ISSW2018_P05.9.pdf
Language of Article: English
Presenter(s):
Keywords: snow depth, snow water equivalent, snow density, semi-empirical model, long-term snow data.
Page Number(s): 462-465
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