From: Subject: A comparison of physically based and degree-day representations of snowpack / atmosphere turbulent fluxes in an alpine watershed Date: Sun, 22 May 2005 20:57:54 -0700 MIME-Version: 1.0 Content-Type: multipart/related; type="text/html"; boundary="----=_NextPart_000_002F_01C55F10.EC96ABE0" X-MimeOLE: Produced By Microsoft MimeOLE V6.00.2900.2180 This is a multi-part message in MIME format. ------=_NextPart_000_002F_01C55F10.EC96ABE0 Content-Type: text/html; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable Content-Location: http://www.agu.org/cgi-bin/SFgate/SFgate?language=English&verbose=0&listenv=table&application=fm04&convert=&converthl=&refinequery=&formintern=&formextern=&transquery=an%3d%22C31A-0304%22&_lines=&multiple=0&descriptor=%2fdata%2fepubs%2fwais%2findexes%2ffm04%2ffm04%7c1000%7c4285%7cA%20comparison%20of%20physically%20based%20and%20degree-day%20representations%20of%20snowpack%20%2f%20atmosphere%20turbulent%20fluxes%20in%20an%20alpine%20watershed%7cHTML%7clocalhost:0%7c%2fdata%2fepubs%2fwais%2findexes%2ffm04%2ffm04%7c7618653%207622938%20%2fdata2%2fepubs%2fwais%2fdata%2ffm04%2ffm04.txt A comparison of physically based and degree-day = representations of snowpack / atmosphere turbulent fluxes in an alpine = watershed
2004 Fall=20 = Meeting          
Search=20 Results		 Cite = abstracts as=20 Author(s) (2004), Title, Eos Trans. AGU,
85(47), = Fall=20 Meet. Suppl., Abstract = xxxxx-xx
Your query was:
an=3D"C31A-0304"

HR: 0800h
AN: C31A-0304
TI: A comparison = of physically=20 based and degree-day representations of snowpack / atmosphere = turbulent=20 fluxes in an alpine watershed
AU: Jacobson, P=20
EM: pjacobson@colorado.edu
AF: Department of Geological Sciences, University of = Colorado,=20 Boulder, 399 UCB, Boulder, CO 80309-0001 United States =
AU:=20 * Molotch, N P
EM: molotch@cires.colorado.edu
AF: Cooperative Institute for Research in Environmental = Sciences,=20 University of Colorado, Boulder, 216 UCB, Boulder, CO 80309-0216 = United=20 States
AU: Bales, R C
EM: = rbales@ucmerced.edu
AF: Division of=20 Engineering, University of California, Merced, P.O. Box 2039, = Merced, CA=20 95344 United States
AU: Colee, M = T
EM:=20 mtc@icess.ucsb.edu
AF: Donald Bren=20 School of Environmental Science and Management, University of = California,=20 Santa Barbara, Bren Hall, Santa Barbara, CA 93106 United States=20
AU: Dozier, J
EM: dozier@bren.ucsb.edu
AF: Donald Bren=20 School of Environmental Science and Management, University of = California,=20 Santa Barbara, Bren Hall, Santa Barbara, CA 93106 United States=20
AB: The degree-day turbulent flux = algorithm of=20 the Snowmelt Runoff Model (SRM) was compared with a physically = based=20 turbulent flux algorithm to evaluate the trade-offs between model=20 complexity, data input intensity and model accuracy. The two = different=20 turbulent flux representations were used in a snowpack mass and = energy=20 balance model that explicitly represents net radiation. Snowmelt=20 simulations were coupled with a time-series of remotely sensed = snow=20 covered area (SCA) data to simulate daily snowmelt volume in the=20 19.1-km$^{2}$ Tokopah Basin of the southern Sierra Nevada, = California.=20 Modeled daily snowmelt rates for each 30-m pixel were scaled by = the SCA=20 and integrated over the snowmelt season to obtain estimates of = maximum SWE=20 accumulation. Evaluation of model performance using remotely = sensed snow=20 covered area indicated that snow cover depletion rates were = reasonably=20 simulated using the physically based model but were overestimated = using=20 the degree-day model, with total snow disappearance occurring at = least 16=20 days prior to observed disappearance. Un-calibrated correlations = between=20 modeled basin-wide snowmelt volume and observed runoff indicated = that the=20 timing of snowmelt was simulated adequately with the degree-day = model=20 (R$^{2}$ =3D 0.59) relative to the physically based model (R$^{2}$ = =3D 0.62).=20 Modeled peak snowmelt occurred 18 days prior to peak observed = runoff in=20 both cases. Results from a regression tree and co-kriging = interpolation of=20 397 snow depth observations obtained at maximum SWE were compared = with the=20 maximum SWE reconstructions from the snowmelt models. Model SWE=20 reconstruction error was 36 percent for the degree-day model = versus 12=20 percent for the physically based model. Relative to the physically = based=20 model, the degree-day model was able to adequately represent the = timing of=20 snowmelt with a significantly lower computational and input data=20 requirement.
DE: 1800 = HYDROLOGY
DE:=20 1836 Hydrologic budget (1655)
DE: 1863 Snow and ice (1827)
DE: 1878=20 Water/energy interactions
DE: 1884 = Water=20 supply
SC: Cryosphere [C]
MN: = 2004 AGU Fall Meeting

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