气候变化领域集成服务门户(CCPortal): Simulation of Daily Snow Depth Data in China Based on the NEX-GDDP

CCPortal

DOI	10.3390/w13243599
	Simulation of Daily Snow Depth Data in China Based on the NEX-GDDP
	Chen, Hongju; Yang, Jianping; Ding, Yongjian; He, Qingshan; Ji, Qin
通讯作者	Yang, JP (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, Lanzhou 730030, Peoples R China.
发表日期	2021
EISSN	2073-4441
卷号	13 期号:24
英文摘要	In this study, a backpropagation artificial neural network snow simulation model (BPANNSIM) is built using data collected from the National Climate Reference Station to obtain simulation data of China's future daily snow depth in terms of representative concentration pathways (RCP4.5 and RCP8.5). The input layer of the BPANNSIM comprises the current day's maximum temperature, minimum temperature, snow depth, and precipitation data, and the target layer comprises snow depth data of the following day. The model is trained and validated based on data from the National Climate Reference Station over a baseline period of 1986-2005. Validation results show that the temporal correlations of the observed and the model iterative simulated values are 0.94 for monthly cumulative snow cover duration and 0.88 for monthly cumulative snow depth. Subsequently, future daily snow depth data (2016-2065) are retrieved from the NEX-GDPP dataset (Washington, DC/USA: the National Aeronautics and Space Administration(NASA)Earth Exchange/Global Daily Downscaled Projections data), revealing that the simulation data error is highly correlated with that of the input data; thus, a validation method for gridded meteorological data is proposed to verify the accuracy of gridded meteorological data within snowfall periods and the reasonability of hydrothermal coupling for gridded meteorological data.
关键词	COVER CLIMATE VARIABILITY LOADS
英文关键词	future daily snow depth; simulation; artificial neural network; snow cover
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
WOS类目	Environmental Sciences ; Water Resources
WOS记录号	WOS:000737878800001
来源期刊	WATER
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/253919
作者单位	[Chen, Hongju; Yang, Jianping; Ding, Yongjian; He, Qingshan; Ji, Qin] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, Lanzhou 730030, Peoples R China; [Chen, Hongju; Ding, Yongjian] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Ecohydrol Inland River Basin, Lanzhou 730030, Peoples R China; [Chen, Hongju; He, Qingshan; Ji, Qin] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Ding, Yongjian] Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China; [Ding, Yongjian] CAS, HEC, China Pakistan Joint Res Ctr Earth Sci, Islamabad 45320, Pakistan
推荐引用方式 GB/T 7714	Chen, Hongju,Yang, Jianping,Ding, Yongjian,et al. Simulation of Daily Snow Depth Data in China Based on the NEX-GDDP[J]. 中国科学院西北生态环境资源研究院,2021,13(24).
APA	Chen, Hongju,Yang, Jianping,Ding, Yongjian,He, Qingshan,&Ji, Qin.(2021).Simulation of Daily Snow Depth Data in China Based on the NEX-GDDP.WATER,13(24).
MLA	Chen, Hongju,et al."Simulation of Daily Snow Depth Data in China Based on the NEX-GDDP".WATER 13.24(2021).