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Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate
Wang, L (Wang, Lei)1,2,3; Sun, LT (Sun, Litao)1,3; Shrestha, M (Shrestha, Maheswor)4; Li, XP (Li, Xiuping)1; Liu, WB (Liu, Wenbin)5; Zhou, J (Zhou, Jing)1; Yang, K (Yang, Kun)1,2; Lu, H (Lu, Hui)6,7; Chen, DL (Chen, Deliang)8; Wang, L
Source PublicationJOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
2016
Volume121Issue:20Pages:12005-12030
DOI10.1002/2016JD025506
AbstractIn distributed hydrological modeling, surface air temperature (T-air) is of great importance in simulating cold region processes, while the near-surface-air-temperature lapse rate (NLR) is crucial to prepare T-air (when interpolating T-air from site observations to model grids). In this study, a distributed biosphere hydrological model with improved snow physics (WEB-DHM-S) was rigorously evaluated in a typical cold, large river basin (e.g., the upper Yellow River basin), given a mean monthly NLRs. Based on the validated model, we have examined the influence of the NLR on the simulated snow processes and streamflows. We found that the NLR has a large effect on the simulated streamflows, with a maximum difference of greater than 24% among the various scenarios for NLRs considered. To supplement the insufficient number of monitoring sites for near-surface-air-temperature at developing/undeveloped mountain regions, the nighttime Moderate Resolution Imaging Spectroradiometer land surface temperature is used as an alternative to derive the approximate NLR at a finer spatial scale (e.g., at different elevation bands, different land covers, different aspects, and different snow conditions). Using satellite-based estimation of NLR, the modeling of snow processes has been greatly refined. Results show that both the determination of rainfall/snowfall and the snowpack process were significantly improved, contributing to a reduced summer evapotranspiration and thus an improved streamflow simulation.
Subject Area自然地理学
WOS IDWOS:000388293100014
Language英语
Indexed BySCI
KeywordDistributed Hydrological Model Upper Tone River Parameterization Sib2 Atmospheric Gcms United-states Runoff China Products Basin Validation
Cooperation Status国际
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itpcas.ac.cn/handle/131C11/7535
Collection图书馆
Corresponding AuthorWang, L
Affiliation1.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing, Peoples R China
2.CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Coll Earth Sci, Beijing, Peoples R China
4.Water & Energy Commiss Secretariat, Kathmandu, Nepal
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing, Peoples R China
6.Tsinghua Univ, Ctr Earth Syst Sci, Beijing, Peoples R China
7.Minist Educ, Key Lab Numer Simulat Earth Syst, Beijing, Peoples R China
8.Univ Gothenburg, Dept Earth Sci, Reg Climate Grp, Gothenburg, Sweden
Recommended Citation
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Wang, L ,Sun, LT ,Shrestha, M ,et al. Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2016,121(20):12005-12030.
APA Wang, L .,Sun, LT .,Shrestha, M .,Li, XP .,Liu, WB .,...&Wang, L.(2016).Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,121(20),12005-12030.
MLA Wang, L ,et al."Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 121.20(2016):12005-12030.
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