000183661 001__ 183661
000183661 005__ 20180507064531.0
000183661 0247_ $$2doi$$a10.1029/2012WR012285
000183661 022__ $$a00431397
000183661 02470 $$2ISI$$a000309609000006
000183661 037__ $$aARTICLE
000183661 245__ $$aImproved snowmelt simulations with a canopy model forced with photo-derived direct beam canopy transmissivity
000183661 260__ $$aWashington$$bAmer Geophysical Union$$c2012
000183661 269__ $$a2012
000183661 300__ $$a21
000183661 336__ $$aJournal Articles
000183661 520__ $$aThe predictive capacity of a physically based snow model to simulate point-scale, subcanopy snowmelt dynamics is evaluated in a mixed conifer forest, southern Sierra Nevada, California. Three model scenarios each providing varying levels of canopy structure detail were tested. Simulations of three water years initialized at locations of 24 ultrasonic snow depth sensors were evaluated against observations of snow water equivalent (SWE), snow disappearance date, and volumetric soil water content. When canopy model parameters canopy openness and effective leaf area index were obtained from satellite and literature-based sources, respectively, the model was unable to resolve the variable subcanopy snowmelt dynamics. When canopy parameters were obtained from hemispherical photos, the improvements were not statistically significant. However, when the model was modified to accept photo-derived time-varying direct beam canopy transmissivity, the error in the snow disappearance date was reduced by as much as one week and positive and negative biases in melt-season SWE and snow cover duration were significantly reduced. Errors in the timing of soil meltwater fluxes were reduced by 11 days on average. The optimum aggregated temporal model resolution of direct beam canopy transmissivity was determined to be 30 min; hourly averages performed no better than the bulk canopy scenarios and finer time steps did not increase overall model accuracy. The improvements illustrate the important contribution of direct shortwave radiation to subcanopy snowmelt and confirm the known nonlinear melt behavior of snow cover. © 2012. American Geophysical Union. All Rights Reserved.
000183661 700__ $$aMusselman, K. N.
000183661 700__ $$aMolotch, N. P.
000183661 700__ $$aMargulis, S. A.
000183661 700__ $$0245914$$aLehning, M.$$g167659
000183661 700__ $$aGustafsson, D.
000183661 773__ $$j48$$k10$$tWater Resources Research
000183661 909CO $$ooai:infoscience.tind.io:183661$$pENAC$$particle
000183661 909C0 $$0252326$$pCRYOS$$xU12533
000183661 917Z8 $$x219016
000183661 937__ $$aEPFL-ARTICLE-183661
000183661 973__ $$aOTHER$$rNON-REVIEWED$$sPUBLISHED
000183661 980__ $$aARTICLE