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遥感技术与应用  2020, Vol. 35 Issue (6): 1263-1272    DOI: 10.11873/j.issn.1004-0323.2020.6.1263
冰雪遥感专栏     
北半球及典型区雪深时空分布与变化特征
岳珊娜1,2(),车涛1(),戴礼云1,肖林3,邓婕1,2
1.中国科学院西北生态资源环境研究院,甘肃省遥感重点实验室,中国科学院黑河遥感试验 研究站,甘肃 兰州 730000
2.中国科学院大学,北京 100049
3.四川农业大学林学院,长江上游森林资源保育与生态安全国家林业和草原局重点实验室,长江上游林业生态工程四川省重点实验室,四川 成都 611130
Temporal and Spatial Distribution and Variation Characteristics of Snow Depth in the Northern Hemisphere and Typical Areas
Shanna Yue1,2(),Tao Che1(),Liyun Dai1,Lin Xiao3,Jie Deng1,2
1.Northwest Institute of Eco-environment and Resources,Key Laboratory of Remote Sensing of Gansu Province,Heihe Remote Sensing Experimental Research Station,Chinese Academy of Sciences,Lanzhou 730000,China
2.University of Chinese Academy of Sciences,Beijing 100049,China
3.National Forestry and Grassland Administration Key Laboratory of Forest Resources Conservation and Ecological Safety on the Upper Reaches of the Yangtze River,Sichuan Province Key Laboratory of Ecological Forestry Engineering on the Upper Reaches of the Yangtze River,College of Forestry,Sichuan Agricultural University,Chengdu 611130,China
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摘要:

基于欧空局的GlobSnow雪水当量数据集和国家青藏高原科学数据中心的北半球长时间序列雪深数据集NHSD研究了北半球及9个典型区的雪深时空分布与变化特征。结果表明:北半球1988~2018年平均雪深总体呈显著下降趋势(p<0.01),年际变化幅度为-0.55 cm·(10 a)-1。在高纬度地区,加拿大北部和阿拉斯加年平均雪深下降明显(p<0.01),下降速率分别为3.48 cm·(10 a)-1和3 cm·(10 a)-1,两地区月平均雪深在冬季显著下降。西西伯利亚平原和东欧平原年平均雪深呈下降趋势,其中东欧平原雪深下降较为明显(p<0.01),变化速率为-2.3 cm·(10 a)-1,两地区的月平均雪深在春季显著下降,其中5月份最为明显。东西伯利亚山地的雪深年际变化呈增加趋势,除堪察加半岛外,其月平均雪深在冬季呈显著增加趋势。对于高山区,阿尔卑斯山脉和落基山脉的年平均雪深呈缓慢增长趋势,而青藏高原地区雪深呈缓慢下降趋势。阿尔卑斯山脉的月平均雪深在冬季呈显著增加趋势,5月份显著减小。落基山脉和青藏高原雪深变化呈现出空间异质性:在整个研究时段,落基山脉北部月平均雪深呈下降趋势,中部和南部呈上升趋势;青藏高原的北部边缘山脉雪深呈显著上升趋势,中部大多数地区呈下降趋势。喜马拉雅山脉的北坡雪深增加,南坡雪深减小,但其变化率绝对值小于0.5 cm·a-1。东南部雪深较大的念青唐古拉山脉冬季雪深呈显著下降趋势。对9个典型区雪深的年内分析(2001~2010年平均值)结果显示:高山区雪深峰值远低于高纬度地区雪深峰值。除青藏高原外,高山区的积雪融化起始日期明显早于高纬度地区。

关键词: 雪深北半球高山区高纬度地区遥感    
Abstract:

The temporal and spatial variation characteristics of snow depth over the Northern Hemisphere and nine typical areas were analyzed based on the GlobSnow snow water equivalent datasets of European Space Agency and the NHSD sow depth datasets of the National Qinghai-Tibet Plateau Scientific Data Center. The results showed that: the Average Annual Snow Depth (AASD) over the Northern Hemisphere generally decreased significantly (p<0.01) during 1988 to 2018, with a change slope of -0.55 cm·(10 a)-1. For high latitudes, the AASD in the northern Canada and Alaska decreased significantly (p<0.01), with a rate of 3.48 cm·(10 a)-1 and 3 cm·(10 a)-1, respectively; and the Average Monthly Snow Depth(AMSD) decreased significantly in winner. The AASD decreased in the West Siberian Plain and Eastern European Plain with a significant change rate of -2.3 cm·(10 a)-1 in the latter (p<0.01), and the AMSD decreased significantly in spring, especially in May. The AASD in the Eastern Siberia showed an increased trend, except in Kamchatka Peninsula, and the AMSD increased significantly in winner. For high mountainous areas, the AASD showed a slow increase rate in the Alps and Rockies, and slight decrease change in the Qinghai-Tibet Plateau (QTP). The AMSD in Alps increased significantly in winner and decreased significantly in May. The variation of snow depth in the Rockies and the QTP presented spatial heterogeneity. During the whole study period, the AMSD decreased in the north of the Rockies and most areas of central region of QTP, while increased in the central and south of Rockies and the mountains on the northern edge of the QTP. The snow depth increased on the north slope of The Himalayas, while decreased on the south slope, with the absolute change rates of less than 0.5 cm·a-1. The AMSD of Nianqing Dangla Mountains which has deep snow showed a significant downward trend in winner. The seasonal variation analysis of snow depth (average snow depth from 2001 to 2010) in 9 typical areas showed that the peak values of snow depth in high mountainous areas are much smaller than those in high latitudes. The snow melting dates in high mountainous areas are obviously earlier than those in high latitudes except for the QTP.

Key words: Snow depth    Northern Hemisphere    High mountainous area    High latitude    Remote sensing
收稿日期: 2020-07-05 出版日期: 2021-01-26
ZTFLH:  TP75  
基金资助: 科技部国家科技基础资源调查专项 “中国积雪特性及分布调查”(2017FY100500);国家自然科学基金项目(41771389);中国科学院“西部之光” 人才培养引进计划
通讯作者: 车涛     E-mail: ysn@lzb.ac.cn;chetao@lzb.ac.cn
作者简介: 岳珊娜 (1996-),女,河南郑州人,硕士研究生,主要从事积雪遥感研究。E?mail: ysn@lzb.ac.cn
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引用本文:

岳珊娜,车涛,戴礼云,肖林,邓婕. 北半球及典型区雪深时空分布与变化特征[J]. 遥感技术与应用, 2020, 35(6): 1263-1272.

Shanna Yue,Tao Che,Liyun Dai,Lin Xiao,Jie Deng. Temporal and Spatial Distribution and Variation Characteristics of Snow Depth in the Northern Hemisphere and Typical Areas. Remote Sensing Technology and Application, 2020, 35(6): 1263-1272.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.6.1263        http://www.rsta.ac.cn/CN/Y2020/V35/I6/1263

图1  北半球及典型区空间示意图 审图号:GS(2016)1593号
图2  GlobSnow和NHSD数据处理流程图
图3  北半球1988/1989~2017/2018年平均雪深的年际变化
图4  北半球多年平均雪深变化率 审图号:GS(2016)1593号
图5  北半球多年平均雪深变化率显著性 审图号:GS(2016)1593号
图6  北半球月平均雪深年际变化率 审图号:GS(2016)1593号
图7  北半球月平均雪深年际变化率显著性 审图号:GS(2016)1593号
图8  典型区平均雪深年际变化
图9  典型区雪深的年内变化
1 Brown R D, Goodison B E. Interannual Variability in Reconstructed Canadian Snow Cover, 1915–1992[J]. Journal of Climate, 1996, 9(6): 1299-1318.
2 Barnett T P, Adam J C, Lettenmaier D P. Potential Impacts of a Warming Climate on Water Availability in Snow-dominated Regions[J]. Nature, 2005, 438(7066):303-309.
3 Armstrong R L, Brodzik M J. Recent Northern Hemisphere Snow Extent: A Comparison of Data Derived from Visible and Microwave Satellite Sensors[J]. Geophysical Research Letters, 2001, 28(19):3673-3676.
4 Zhang Ningli, Fan Xiangtao, Zhu Junjie. Analysis of Temporal and Spatial Distribution of Snow Cover in Northern Hemisphere based on MODIS Snow Products[J]. Remote Sensing Information, 2012, 27(6):28-34.
4 张宁丽, 范湘涛, 朱俊杰. 基于MODIS雪产品的北半球积雪时空分布变化特征分析[J],遥感信息, 2012, 27(6): 28-34.
5 Li Z , Liu J, Tian B. Spatial and Temporal Series Analysis of Snow Cover Extent and Snow Water Equivalent for Satellite Passive Microwave Data in the Northern Hemisphere(1978-2010)[C]∥ Geoscience & Remote Sensing Symposium, IEEE, 2012. doi:10.1109/igarss.2012.6352521.
doi: 10.1109/igarss.2012.6352521
6 Xiao X, Zhang T, Zhong X, et al. Spatiotemporal Variation of Snow Depth in the Northern Hemisphere from 1992 to 2016[J]. Remote Sensing, 2020, 12(17): 2728. doi:10.3390/rs12172728.
doi: 10.3390/rs12172728
7 Wang Y, Huang X, Liang H, et al. Tracking Snow Variations in the Northern Hemisphere Using Multi-source Remote Sensing Data (2000-2015)[J]. Remote Sensing, 2018, 10(30). doi:10.3390/rs10010136.
doi: 10.3390/rs10010136
8 Bormann K J, Brown R D, Derksen C, et al. Estimating Snow-cover Trends from Space[J].Nature Climate Change, 2018. doi:10.1038/s41558-018-0318-3.
doi: 10.1038/s41558-018-0318-3
9 Brown R D, Robinson D A. Northern Hemisphere Spring Snow Cover Variability and Change over 1922-2010 Including an Assessment of Uncertainty[J]. The Cryosphere, 2011, 5(1): 219-229.
10 Derksen C, Brown R, Mudryk L, et al. Terrestrial Snow Cover[R]. In Arctic Report Card2016. http://www.arctic.noaa.gov/ Report-Card.
11 Estilow T W, Young A H, Robinson D A. A Long-term Northern Hemisphere Snow Cover Extent Data Record for Climate Studies and Monitoring[J]. Earth System Science Data, 2015, 7:137-142.
12 Pulliainen J, Luojus K, Derksen C, et al. Patterns and Trends of Northern Hemisphere Snow Mass from 1980 to 2018[J]. Nature, 2020, 581(7808): 294-298. doi:10.1038/s41586-020-2258-0.
doi: 10.1038/s41586-020-2258-0
13 Xu B , Chen H , Gao C , et al. Regional Response of Winter Snow Cover over the Northern Eurasia to Late Autumn Arctic Sea Ice and Associated Mechanism[J].Atmospheric research, 2019,222(JUL.):100-113. doi:10.1016/j.atmosres.2019. 02.010.
doi: 10.1016/j.atmosres.2019. 02.010
14 Chen Yueliang, Huang Fei, Wang Hong, et al. Seasonal and Interannual Scales of Snow Water Equivalent in the Northern Hemisphere[J], Periodical of Ocean University of China, 2015, 45(7):11-17.
14 陈月亮, 黄菲, 王宏, 等. 北半球雪水当量季节和年际尺度时空主模态变化特征[J], 中国海洋大学学报(自然科学版), 2015, 45(7):11-17.
15 Jeong D I, Sushama L, Naveed Khaliq M. Attribution of Spring Snow Water Equivalent(SWE) Changes over the Northern Hemisphere to Anthropogenic Effects[J]. Climate Dynamics, 2016, 48(11-12):3645-3658. doi:10.1007/s00382-016-3291-4.
doi: 10.1007/s00382-016-3291-4
16 Notarnicola C. Hotspots of Snow Cover Changes in Global Mountain Regions over 2000-2018[J]. Remote Sensing of Environment,2020,243:111781.doi:10.1016/j.rse.2020.111781.
doi: 10.1016/j.rse.2020.111781
17 Bocchiola D, Diolaiuti G. Evidence of Climate Change Within the Adamello Glacier of Italy[J]. Theoretical & Applied Climatology, 2010, 100(3-4):351-369. doi:10.1007/s00704-009-0186-x.
doi: 10.1007/s00704-009-0186-x
18 Marty C, Tilg A M, Jonas T. Recent Evidence of Large-Scale Receding Snow Water Equivalents in the European Alps[J]. Journal of Hydrometeorology, 2017, 18(4):1021-1031. doi:10.1175/jhm-d-16-0188.1.
doi: 10.1175/jhm-d-16-0188.1
19 Dyrrdal A V, Saloranta T, Skaugen T, et al. Changes in Snow Depth in Norway during the Period 1961-2010[J]. Hydrology Research, 2013, 44(1):169-179. doi:10.2166/nh.2012.064.
doi: 10.2166/nh.2012.064
20 Beniston M, Farinotti D, Stoffel M, et al. The European Mountain Cryosphere: A Review of Its Current State, Trends, and Future Challenges[J]. The Cryosphere, 2018, 12(2):759-794. doi:10.5194/tc-12-759-2018.
doi: 10.5194/tc-12-759-2018
21 Mote P W, Li S, Lettenmaier D P, et al. Dramatic Declines in Snowpack in the Western US[J]. Npj Climate and Atmospheric Science,2018,1(1).doi:10.1038/s41612-018-0012-1.
doi: 10.1038/s41612-018-0012-1
22 Seidel F C, Rittger K, Skiles S M, et al. Case Study of Spatial and Temporal Variability of Snow Cover, Grain size, Albedo and Radiative Forcing in the Sierra Nevada and Rocky Mountain Snowpack Derived from Imaging Spectroscopy[J]. The Cryosphere, 2016, 10(3): 1229-1244.
23 Shen Liucheng, Wu Tao, You Qinglong, et al. Spatial and Temporal Variation of Snow Cover Depth in the Middle and Eastern Part of the Qinghai-tibet Plateau and Its Genetic Analysis[J], Journal of Glaciology and Geocryology,2019,41(5):1150-1161.
23 沈鎏澄, 吴涛, 游庆龙, 等.青藏高原中东部积雪深度时空变化特征及其成因分析[J], 冰川冻土, 2019, 41(5):1150-1161.
24 Che Tao, Hao Xiaohua, Dai Liyun, et al. The Change of Snow Cover in Qinghai-Tibet Plateau and Its Influence[J],Bulletin of Chinese Academy of Sciences,2019,34(11):1247-1253.
24 车涛, 郝晓华,戴礼云, 等.青藏高原积雪变化及其影响[J],中国科学院院刊,2019,34(11):1247-1253.
25 Wang X X, Wu C Y, Wang H J, et al. No Evidence of Widespread Decline of Snow Cover on the Tibetan Plateau over 2000-2015[J]. Scientific Reports,2017,7(1):3065-3077. doi:10.1038/s41598-017-15208-9.
doi: 10.1038/s41598-017-15208-9
26 Takala M, Luojus K, Pulliainen J, et al. Estimating Northern Hemisphere Snow Water Equivalent for Climate Research Through Assimilation of Space-borne Radiometer Data and Ground-based Measurements[J]. Remote Sensing of Environment, 2011, 115(12): 3517-3529. doi:10.1016/j.rse. 2011.08.014.
doi: 10.1016/j.rse. 2011.08.014
27 Che Tao, Li Xin, Dai Liyun. Long-term Series of Daily Global Snow Depth (1979-2017)[DB/OL]. National Tibetan Plateau Data Center,2019.
27 车涛,李新,戴礼云. 全球长时间序列逐日雪深数据集(1979-2017)[DB/OL]. 国家青藏高原科学数据中心, 2019.
28 Lemke P, Ren J. Observations: Changes in Snow, Ice and Frozen Ground[C]∥ Fourth Assessment Report the Intergovernmental Panel on Climate Change(Chapter 4). Paris: The Intergovernmental Panel on Climate Change, 2007: 48.
29 Pulliainen J. Mapping of Snow Water Equivalent and Snow Depth in Boreal and Sub-arctic Zones by Assimilating Space-borne Microwave Radiometer Data and Ground-based Observations[J]. Remote Sensing of Environment, 2006, 101(2): 257-269.
30 Dai L Y Che T, Ding Y J. Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China[J].Remote Sensing,2015,7(6):7212-7230.
31 Chang A T C, Foster J L, Hall D K. Nimbus-7 SMMR Derived Globsnow Snow Cover Parameters[J]. Annals of Glaciology, 1987, 9(1): 39-44.
32 Wei F Y. Modern Climatic Statistical Diagnosis and Prediction Technology[M]. Beijing: Meteorological Press,2007.
32 魏凤英. 现代气候统计诊断与预测技术[M]. 北京:气象出版社,2007.
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