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Titel |
Simulation of snow accumulation and melt in needleleaf forest environments |
VerfasserIn |
C. R. Ellis, J. W. Pomeroy, T. Brown, J. MacDonald |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1027-5606
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Digitales Dokument |
URL |
Erschienen |
In: Hydrology and Earth System Sciences ; 14, no. 6 ; Nr. 14, no. 6 (2010-06-14), S.925-940 |
Datensatznummer |
250012333
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Publikation (Nr.) |
copernicus.org/hess-14-925-2010.pdf |
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Zusammenfassung |
Drawing upon numerous field studies and modelling exercises of snow
processes, the Cold Regions Hydrological Model (CRHM) was developed to
simulate the four season hydrological cycle in cold regions. CRHM includes
modules describing radiative, turbulent and conductive energy exchanges to
snow in open and forest environments, as well as account for losses from
canopy snow sublimation and rain evaporation. Due to the physical-basis and
rigorous testing of each module, there is a minimal need for model
calibration. To evaluate CRHM, simulations of snow accumulation and melt
were compared to observations collected at paired forest and clearing sites
of varying latitude, elevation, forest cover density, and climate. Overall,
results show that CRHM is capable of characterising the variation in snow
accumulation between forest and clearing sites, achieving a model efficiency
of 0.51 for simulations at individual sites. Simulations of canopy
sublimation losses slightly overestimated observed losses from a weighed cut
tree, having a model efficiency of 0.41 for daily losses. Good model
performance was demonstrated in simulating energy fluxes to snow at the
clearings, but results were degraded from this under forest cover due to
errors in simulating sub-canopy net longwave radiation. However, expressed
as cumulative energy to snow over the winter, simulated values were 96%
and 98% of that observed at the forest and clearing sites, respectively.
Overall, the good representation of the substantial variations in mass and
energy between forest and clearing sites suggests that CRHM may be useful as
an analytical or predictive tool for snow processes in needleleaf forest
environments. |
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