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contributor authorShrestha, Maheswor
contributor authorWang, Lei
contributor authorKoike, Toshio
contributor authorXue, Yongkang
contributor authorHirabayashi, Yukiko
date accessioned2017-06-09T17:14:23Z
date available2017-06-09T17:14:23Z
date copyright2012/02/01
date issued2011
identifier issn1525-755X
identifier otherams-81654.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4224681
description abstractn this study, a distributed biosphere hydrological model with three-layer energy-balance snow physics [an improved version of the Water and Energy Budget?based Distributed Hydrological Model (WEB-DHM-S)] is applied to the Dudhkoshi region of the eastern Nepal Himalayas to estimate the spatial distribution of snow cover. Simulations are performed at hourly time steps and 1-km spatial resolution for the 2002/03 snow season during the Coordinated Enhanced Observing Period (CEOP) third Enhanced Observing Period (EOP-3). Point evaluations (snow depth and upward short- and longwave radiation) at Pyramid (a station of the CEOP Himalayan reference site) confirm the vertical-process representations of WEB-DHM-S in this region. The simulated spatial distribution of snow cover is evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow-cover extent (MOD10A2), demonstrating the model?s capability to accurately capture the spatiotemporal variations in snow cover across the study area. The qualitative pixel-to-pixel comparisons for the snow-free and snow-covered grids reveal that the simulations agree well with the MODIS data to an accuracy of 90%. Simulated nighttime land surface temperatures (LST) are comparable to the MODIS LST (MOD11A2) with mean absolute error of 2.42°C and mean relative error of 0.77°C during the study period. The effects of uncertainty in air temperature lapse rate, initial snow depth, and snow albedo on the snow-cover area (SCA) and LST simulations are determined through sensitivity runs. In addition, it is found that ignoring the spatial variability of remotely sensed cloud coverage greatly increases bias in the LST and SCA simulations. To the authors? knowledge, this work is the first to adopt a distributed hydrological model with a physically based multilayer snow module to estimate the spatial distribution of snow cover in the Himalayan region.
publisherAmerican Meteorological Society
titleModeling the Spatial Distribution of Snow Cover in the Dudhkoshi Region of the Nepal Himalayas
typeJournal Paper
journal volume13
journal issue1
journal titleJournal of Hydrometeorology
identifier doi10.1175/JHM-D-10-05027.1
journal fristpage204
journal lastpage222
treeJournal of Hydrometeorology:;2011:;Volume( 013 ):;issue: 001
contenttypeFulltext


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