IGSNRR OpenIR
Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate
Wang, Lei1,2,3; Sun, Litao1,3; Shrestha, Maheswor4; Li, Xiuping1; Liu, Wenbin5; Zhou, Jing1; Yang, Kun1,2; Lu, Hui6,7; Chen, Deliang8
2016-10-27
Source PublicationJOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
ISSN2169-897X
Volume121Issue:20Pages:12005-12030
Corresponding AuthorWang, Lei(wanglei@itpcas.ac.cn)
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.
Keywordlapse rate distributed hydrological model water and energy cycle snow process MODIS land surface temperature
DOI10.1002/2016JD025506
WOS KeywordDISTRIBUTED HYDROLOGICAL MODEL ; UPPER TONE RIVER ; PARAMETERIZATION SIB2 ; ATMOSPHERIC GCMS ; UNITED-STATES ; RUNOFF ; CHINA ; PRODUCTS ; BASIN ; VALIDATION
Indexed BySCI
Language英语
Funding ProjectNational Key Basic Research Program of China[2013CBA01800] ; National Natural Science Foundation of China[41322001] ; National Natural Science Foundation of China[41190083] ; National Natural Science Foundation of China[41571033] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB03030302] ; Key Technologies R&D Program of China[2013BAB05B03] ; Hundred Talents Program of Chinese Academy of Sciences ; Top-Notch Young Talents Program of China ; Swedish VR ; BECC ; MERGE
Funding OrganizationNational Key Basic Research Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Key Technologies R&D Program of China ; Hundred Talents Program of Chinese Academy of Sciences ; Top-Notch Young Talents Program of China ; Swedish VR ; BECC ; MERGE
WOS Research AreaMeteorology & Atmospheric Sciences
WOS SubjectMeteorology & Atmospheric Sciences
WOS IDWOS:000388293100014
PublisherAMER GEOPHYSICAL UNION
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/65541
Collection中国科学院地理科学与资源研究所
Corresponding AuthorWang, Lei
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
GB/T 7714
Wang, Lei,Sun, Litao,Shrestha, Maheswor,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, Lei.,Sun, Litao.,Shrestha, Maheswor.,Li, Xiuping.,Liu, Wenbin.,...&Chen, Deliang.(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, Lei,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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang, Lei]'s Articles
[Sun, Litao]'s Articles
[Shrestha, Maheswor]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang, Lei]'s Articles
[Sun, Litao]'s Articles
[Shrestha, Maheswor]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang, Lei]'s Articles
[Sun, Litao]'s Articles
[Shrestha, Maheswor]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.