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| Titel |
Evaluation of the snow regime in dynamic vegetation land surface models using field measurements |
| VerfasserIn |
E. Kantzas, S. Quegan, M. Lomas, E. Zakharova |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1994-0416
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| Digitales Dokument |
URL |
| Erschienen |
In: The Cryosphere ; 8, no. 2 ; Nr. 8, no. 2 (2014-03-24), S.487-502 |
| Datensatznummer |
250116081
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| Publikation (Nr.) |
 copernicus.org/tc-8-487-2014.pdf |
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| Zusammenfassung |
| An increasing number of studies have demonstrated significant climatic and
ecological changes occurring in the northern latitudes over the past decades.
As coupled Earth-system models attempt to describe and simulate the dynamics
and complex feedbacks of the Arctic environment, it is important to reduce
their uncertainties in short-term predictions by improving the description of
both system processes and its initial state. This study focuses on
snow-related variables and makes extensive use of a historical data set
(1966–1996) of field snow measurements acquired across the extent of the
former Soviet Union to evaluate a range of simulated snow metrics produced by
several land surface models, most of them embedded in IPCC-standard climate
models. We reveal model-specific failings in simulating snowpack properties
such as magnitude, inter-annual variability, timings of snow water equivalent
and evolution of snow density. We develop novel and model-independent
methodologies that use the field snow measurements to extract the values of
fresh snow density and snowpack sublimation, and exploit them to assess model
outputs. By directly forcing the surface heat exchange formulation of a land
surface model with field data on snow depth and snow density, we evaluate how
inaccuracies in simulating snow metrics affect soil temperature, thaw depth
and soil carbon decomposition. We also show how field data can be assimilated
into models using optimization techniques in order to identify model defects
and improve model performance. |
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