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| Titel |
Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements |
| VerfasserIn |
A. Hedrick, H.-P. Marshall, A. Winstral, K. Elder, S. Yueh, D. Cline |
| 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 ; 9, no. 1 ; Nr. 9, no. 1 (2015-01-06), S.13-23 |
| Datensatznummer |
250116732
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| Publikation (Nr.) |
 copernicus.org/tc-9-13-2015.pdf |
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| Zusammenfassung |
Repeated light detection and ranging (lidar) surveys are quickly becoming the
de facto method for measuring spatial variability of montane snowpacks at
high resolution. This study examines the potential of a 750 km2
lidar-derived data set of snow depths, collected during the 2007 northern
Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for
an operational hydrologic snow model. The SNOw Data Assimilation System
(SNODAS) model framework, operated by the US National Weather Service,
combines a physically based energy-and-mass-balance snow model with
satellite, airborne and automated ground-based observations to provide daily
estimates of snowpack properties at nominally 1 km resolution over the
conterminous United States. Independent validation data are scarce due to the
assimilating nature of SNODAS, compelling the need for an independent
validation data set with substantial geographic coverage.
Within 12 distinctive 500 × 500 m study areas located throughout the
survey swath, ground crews performed approximately 600 manual snow depth
measurements during each of the CLPX-2 lidar acquisitions. This supplied a
data set for constraining the uncertainty of upscaled lidar estimates of snow
depth at the 1 km SNODAS resolution, resulting in a root-mean-square
difference of 13 cm. Upscaled lidar snow depths were then compared
to the SNODAS estimates over the entire study area for the dates of the lidar
flights. The remotely sensed snow depths provided a more spatially continuous
comparison data set and agreed more closely to the model estimates than that
of the in situ measurements alone. Finally, the results revealed
three distinct areas where the differences between lidar observations and
SNODAS estimates were most drastic, providing insight into the causal
influences of natural processes on model uncertainty. |
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