气候变化领域集成服务门户(CCPortal): Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate

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DOI	10.1002/2016JD025506
	Improving snow process modeling with satellite-based estimation of near-surface-air-temperature lapse rate
	Wang, Lei; Sun, Litao; Shrestha, Maheswor; Li, Xiuping; Liu, Wenbin; Zhou, Jing; Yang, Kun; Lu, Hui; Chen, Deliang
通讯作者	Wang, L (通讯作者)
发表日期	2016
ISSN	2169-897X
EISSN	2169-8996
起始页码	12005
结束页码	12030
卷号	121 期号:20
英文摘要	In 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.
关键词	DISTRIBUTED HYDROLOGICAL MODEL UPPER TONE RIVER PARAMETERIZATION SIB2 ATMOSPHERIC GCMS UNITED-STATES RUNOFF CHINA PRODUCTS BASIN VALIDATION
英文关键词	lapse rate; distributed hydrological model; water and energy cycle; snow process; MODIS land surface temperature
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Meteorology & Atmospheric Sciences
WOS记录号	WOS:000388293100014
来源期刊	JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/258837
推荐引用方式 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]. 中国科学院青藏高原研究所,2016,121(20).
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).
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).