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干旱区地理 >

2022 , Vol. 45 >Issue 5: 1370 - 1380

DOI: https://doi.org/10.12118/j.issn.1000-6060.2021.599

气候变化

2001—2020年三江源地区积雪日数变化及地形分异

  • 曹晓云 ,
  • 肖建设 ,
  • 郝晓华 ,
  • 史飞飞 ,
  • 刘致远 ,
  • 李素雲
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  • 1.青海省防灾减灾重点实验室,青海 西宁 810001
    2.青海省气象科学研究所,青海 西宁 810001
    3.中国科学院西北生态环境资源研究院,甘肃 兰州 730099
    4.青海师范大学地理科学学院,青海 西宁 810001
曹晓云（1993-）,女,硕士,工程师,主要从事青藏高原气候与环境研究. E-mail: xiaoyun_cao@126.com

收稿日期: 2021-12-14

  修回日期: 2022-02-07

  网络出版日期: 2022-10-20

基金资助

青海省防灾减灾重点实验室开放基金项目(QFZ-2021-Z01);国家自然科学基金项目(41761078);国家自然科学基金项目(41861049);风云卫星应用先行计划项目(FY-APP-2021.0409);青海省科技计划项目(2020-ZJ-731);科技部国家科技基础资源调查专项(2017FY100501)

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Variation of snow cover days and topographic differentiation in Sanjiangyuan area from 2001 to 2020

  • Xiaoyun CAO ,
  • Jianshe XIAO ,
  • Xiaohua HAO ,
  • Feifei SHI ,
  • Zhiyuan LIU ,
  • Suyun LI
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  • 1. Key Laboratory of Disaster Prevention and Mitigation of Qinghai Province, Xining 810001, Qinghai, China
    2. Institute of Qinghai Meteorological Science Research, Xining 810001, Qinghai, China
    3. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730099, Gansu, China
    4. School of Geographical Sciences, Qinghai Normal University, Xining 810001, Qinghai, China

Received date: 2021-12-14

  Revised date: 2022-02-07

  Online published: 2022-10-20

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摘要

基于积雪面积逐日无云遥感产品和气象观测资料,分析了2001—2020年三江源地区积雪日数的水平、垂直分布特征及变化规律,并对积雪日数与气温和降水量进行了相关分析。结果表明：（1） 2001—2020年三江源地区积雪日数呈西高东低,高海拔山脉大于盆地平原的分布格局,高海拔山脉地区积雪日数均值普遍大于200 d,85.48%的区域积雪日数呈波动增加趋势,显著增加区域占比为16.59%,平均增加速率为0.98 d·a-1。（2） 积雪日数及其变化趋势存在明显的海拔和坡向分异,积雪日数随海拔上升呈指数型增加,较低海拔（<3.0 km）区域积雪日数少、呈减少趋势且减少速率随海拔高度上升而加快;高海拔区域积雪日数较多且呈增多趋势,但海拔大于4.4 km后积雪日数增多速率随海拔上升而减缓,且5.5~6.0 km地区积雪日数呈减少趋势,高海拔地区积雪日数存在一定程度的“海拔依赖性”。积雪日数北坡大于南坡、西坡大于东坡,西北坡积雪日数最多,为78.30 d,不同坡向的积雪日数均呈增多趋势,其中西坡的增多速率最快,达1.04 d·a-1。（3） 近20 a三江源地区明显的“暖湿化”气候特征是影响积雪日数变化的主要原因,其中降水量是主要驱动因素,积雪日数增多与降水量增加密切相关,且高海拔地区积雪日数对降水量的依赖性更强。

关键词： 三江源地区; 积雪日数; 气候变化; 地形分异

本文引用格式

曹晓云 , 肖建设 , 郝晓华 , 史飞飞 , 刘致远 , 李素雲 . 2001—2020年三江源地区积雪日数变化及地形分异[J]. 干旱区地理, 2022 , 45(5) : 1370 -1380 . DOI: 10.12118/j.issn.1000-6060.2021.599

Abstract

In this work, based on daily cloudless remote sensing of snow cover and meteorological observation data, the horizontal and vertical distribution characteristics of and variations in snow cover days in the Sanjiangyuan (Three Rivers Headwaters) area of Qinghai, China from 2001 to 2020 are analyzed; the correlation between snow cover days and temperature and precipitation are also analyzed using the same data source. The results showed that: (1) From 2001 to 2020, the number of snow cover days in Sanjiangyuan area was higher in the west and lower in the east; the number of snow cover days is higher in the high-altitude mountain regions than in the basin plain. The average snow cover days in high-altitude mountains was generally greater than 200 d. The number of snow cover days in 85.48% of the areas showed an increasing tendency (with fluctuations), increasing by 16.59%, and the average rate of increase was 0.98 d·a-1. (2) There were clear differences in the number of snow cover days and their variation over the study period based on the altitude and aspectality of the study region. The number of snow cover days increases exponentially with increasing altitude: at low altitude (<3.0 km) the snow covered area was found to be small and shows a decreasing trend. At low altitudes the number of snow cover days rate of reduction accelerates with increasing altitude. At high-altitude areas the number of snow cover days is larger and shows an increasing tendency, but the increase rate in the number of snow cover days at heights of more than 4.4 km decreases as the altitude increases. In the elevation range 5.5-6.0 km, the number of snow covered days showed a tendency to decrease. The number of snow cover days onnorth-facing slopes is greater than that on south-facing slopes; west-facing slopes show a larger number of snow cover days than east-facing slopes. Northwest-facing slopes have the largest number of snow cover days with 78.30 d. The rate at which the number of snow covered days increases was found to be greatest for west-facing slopes (1.04 d·a-1). (3) The warm and humid climatic characteristics of the Sanjiangyuan area over the past 20 years were the main causes of the change in the number of snow cover days; precipitation was also a primary driving factor, and the increase of snow cover days was closely related to the increase in precipitation; snow cover days at high altitudes are more dependent on precipitation.

Key words： Sanjiangyuan area; snow cover days; climate change; topographic differentiation

参考文献

[1] 张欢, 邱玉宝, 郑照军, 等. 基于MODIS的青藏高原季节性积雪去云方法可行性比较研究[J]. 冰川冻土, 2016, 38(3): 714-724.
[1] [Zhang Huan, Qiu Yubao, Zheng Zhaojun, et al. Comparative study of the feasibility of cloud removal methods based on MODIS seasonal snow cover data over the Tibetan Plateau[J]. Journal of Glaciology and Geocryology, 2016, 38(3): 714-724. ]
[2] 易颖, 刘时银, 朱钰, 等. 2002—2018年叶尔羌河流域积雪时空变化研究[J]. 干旱区地理, 2021, 44(1): 15-26.
[2] [Yi Ying, Liu Shiyin, Zhu Yu, et al. Spatiotemporal variation of snow cover in the Yarkant River Basin during 2002—2018[J]. Arid Land Geography, 2021, 44(1): 15-26. ]
[3] 拉巴卓玛, 邱玉宝, 次旦巴桑, 等. 西藏高原MODIS每日积雪产品去云算法过程对比验证研究[J]. 冰川冻土, 2016, 38(1): 159-169.
[3] [Laba Zhuoma, Qiu Yubao, Cidan Basang, et al. The validation of MODIS daily snow-cover products after cloud removal in Tibet Autonomous Region[J]. Journal of Glaciology and Geocryology, 2016, 38(1): 159-169. ]
[4] 王建, 车涛, 李震, 等. 中国积雪特性及分布调查[J]. 地球科学进展, 2018, 33(1): 12-26.
[4] [Wang Jian, Che Tao, Li Zhen, et al. Investigation on snow characteristics and their distribution in China[J]. Advances in Earth Science, 2018, 33(1): 12-26. ]
[5] 李茜, 魏凤英, 雷向杰. 1961—2016年秦岭山区冷季积雪日数变化特征及其影响因子[J]. 冰川冻土, 2020, 42(3): 780-790.
[5] [Li Qian, Wei Fengying, Lei Xiangjie. The variation characteristics of snow days and its influencing factors in cold season in the Qinling Mountains from 1961 to 2016[J]. Journal of Glaciology and Geocryology, 2020, 42(3): 780-790. ]
[6] 陈鹏, 王勇, 张青, 等. 基于FY-3D/MERSI-II归一化积雪指数和MOD10A1的精度对比分析[J]. 干旱区地理, 2020, 43(2): 434-439.
[6] [Chen Peng, Wang Yong, Zhang Qing, et al. Comparison of normalized snow cover indices between FY-3D/MERSI-II and MODIS[J]. Arid Land Geography, 2020, 43(2): 434-439. ]
[7] 曹晓云. 基于MODIS的青藏高原地表反照率时空变化研究[D]. 南京: 南京信息工程大学, 2018: 12-30.
[7] [Cao Xiaoyun. Temporal and spatial variation of surface albedo over Qinghai Xizang Plateau based on MODIS[D]. Nanjing: Nanjing University of Information Engineering, 2018: 12-30. ]
[8] 靳铮, 游庆龙, 吴芳营, 等. 青藏高原三江源地区近60 a气候与极端气候变化特征分析[J]. 大气科学学报, 2020, 43(6): 1042-1055.
[8] [Jin Zheng, You Qinglong, Wu Fangying, et al. Changes of climate and climate extremes in the Three-Rivers Headwaters Region over the Tibetan Plateau during the past 60 years[J]. Journal of Atmospheric Science, 2020, 43(6): 1042-1055. ]
[9] Yao T D, Thompson L, Yang W. Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings[J]. Nature Climate Change, 2012, 2: 663-667.
[10] 傅敏宁. 青藏高原气候变化响应对我国防灾减灾的挑战[J]. 中国减灾, 2021, 4(7): 46-49.
[10] [Fu Minning. The response of climate change in the Qinghai Tibet Plateau to the challenge of disaster prevention and reduction in China[J]. Disaster Reduction in China, 2021, 4(7): 46-49. ]
[11] 刘晓琼, 吴泽洲, 刘彦随, 等. 1960—2015年青海三江源地区降水时空特征[J]. 地理学报, 2019, 74(9): 1803-1820.
[11] [Liu Xiaoqiong, Wu Zezhou, Liu Yansui, et al. Spatial-temporal characteristics of precipitation from 1960 to 2015 in the Three Rivers’ Headstream Region, Qinghai, China[J]. Acta Geographica Sinica, 2019, 74(9): 1803-1820. ]
[12] Deng M S, Meng X H, Li Z G, et al. Responses of soil moisture to regional climate change over the Three Rivers Source Region on the Tibetan Plateau[J]. International Journal of Climatology, 2020, 40(4): 2403-2417.
[13] Li S S, Yao Z J, Wang R, et al. Dryness/wetness pattern over the Three-River Headwater Region: Variation characteristic, causes, and drought risks[J]. International Journal of Climatology, 2020, 40(7): 3550-3566.
[14] 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.
[14] [Che Tao, Hao Xiaohua, Dai Liyun, et al. Snow cover variation and its impacts over the Qinghai-Tibet Plateau[J]. Bulletin of Chinese Academy of Sciences, 2019, 34(11): 1247-1253. ]
[15] Zhong X Y, Zhang T J, Zheng L, et al. Spatiotemporal variability of snow depth across the Eurasian continent from 1966 to 2012[J]. The Cryosphere, 2018, 12(1): 227-245.
[16] 白淑英, 吴奇, 史建桥, 等. 青藏高原积雪深度时空分布与地形的关系[J]. 国土资源遥感, 2015, 27(4): 171-178.
[16] [Bai Shuying, Wu Qi, Shi Jianqiao, et al. Relationship between the spatial and temporal distribution of snow depth and the terrain over the Tibetan Plateau[J]. Remote Sensing for Land & Resources, 2015, 27(4): 171-178. ]
[17] 郭建平, 刘欢, 安林昌, 等. 2001—2012年青藏高原积雪覆盖率变化及地形影响[J]. 高原气象, 2016, 35(1): 24-33.
[17] [Guo Jianping, Liu Huan, An Linchang, et al. Study on variation of snow cover and its orographic impact over Qinghai-Xizang Plateau during 2001—2012[J]. Plateau Meteorology, 2016, 35(1): 24-33. ]
[18] 除多, 达娃, 拉巴卓玛, 等. 基于MODIS数据的青藏高原积雪时空分布特征分析[J]. 国土资源遥感, 2017, 29(2): 117-124.
[18] [Chu Duo, Da Wa, Laba Zhuoma, et al. An analysis of spatial-temporal distribution features of snow cover over the Tibetan Plateau based on MODIS data[J]. Remote Sensing for Land & Resources, 2017, 29(2): 117-124. ]
[19] 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.
[19] [Shen Liucheng, Wu Tao, You Qinglong, et al. Analysis of the characteristics of spatial and temporal variations of snow depth and their causes over the central and eastern Tibetan Plateau[J]. Journal of Glaciology and Geocryology, 2019, 41(5): 1150-1161. ]
[20] You Q L, Chen D L, Wu F Y, et al. Elevation dependent warming over the Tibetan Plateau: Patterns, mechanisms and perspectives[J]. Earth-Science Reviews, 2020, 210: 103349, doi: 10.1016/j.earscirev.2020.103349.
[21] Guo D L, Sun J Q, Yang K, et al. Revisiting recent elevation-dependent warming on the Tibetan Plateau using satellite-based data sets[J]. Journal of Geophysical Research: Atmospheres, 2019, 124(15): 8511-8521.
[22] Guo D L, Pepin N, Yang K, et al. Local changes in snow depth dominate the evolving pattern of elevation-dependent warming on the Tibetan Plateau[J]. Science Bulletin, 2021, 66(11): 1146-1150.
[23] Hall D K, Riggs G A, Salomonson V V. Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data[J]. Remote Sensing of Environment, 1995, 54(2): 127-140.
[24] 王宏伟, 黄春林, 郝晓华, 等. 北疆地区积雪时空变化的影响因素分析[J]. 冰川冻土, 2014, 36(3): 508-516.
[24] [Wang Hongwei, Huang Chunlin, Hao Xiaohua, et al. Analyses of the spatiotemporal variations of snow cover in north Xinjiang[J]. Journal of Glaciology and Geocryology, 2014, 36(3): 508-516. ]
[25] 赵文宇, 刘海隆, 王辉, 等. 基于MODIS积雪产品的天山年积雪日数空间分布特征研究[J]. 冰川冻土, 2016, 38(6): 1510-1517.
[25] [Zhao Wenyu, Liu Hailong, Wang Hui, et al. A study of spatial distribution of snow days in the Tianshan Mountains based on MODIS snow products[J]. Journal of Glaciology and Geocryology, 2016, 38(6): 1510-1517. ]
[26] Zhang H B, Zhang F, Zhang G Q, et al. Ground-based evaluation of MODIS snow cover product V6 across China: Implications for the selection of NDSI threshold[J]. Science of the Total Environment, 2019, 651(Pt2): 2712-2726.
[27] 高扬, 郝晓华, 和栋材, 等. 基于不同土地覆盖类型NDSI阈值优化下的青藏高原积雪判别[J]. 冰川冻土, 2019, 41(5): 1162-1172.
[27] [Gao Yang, Hao Xiaohua, He Dongcai, et al. Snow cover mapping algorithm in the Tibetan Plateau based on NDSI threshold optimization of different land cover types[J]. Journal of Glaciology and Geocryology, 2019, 41(5): 1162-1172. ]
[28] Zhao H Y, Hao X H, Wang J, et al. The spatial-spectral-environmental extraction endmember algorithm and application in the MODIS fractional snow cover retrieval[J]. Remote Sensing, 2020, 12(22): 3693, doi: 10.3390/rs12223693.
[29] Hao X H, Huang G H, Zheng Z J, et al. Development and validation of a new MODIS snow-cover-extent product over China[J]. Hydrology and Earth System Sciences. 2021-11-22. https://doi.org/10.5194/hess-2021-556.
[30] 刘志红, Li Lingtao, McVicar Tim R, 等. 专用气候数据空间插值软件ANUSPLIN及其应用[J]. 气象, 2008, 34(2): 92-100.
[30] [Liu Zhihong, Li Lingtao, McVicar Tim R, et al. Introduction of the professional interpolation software for meteorology data: ANUSPLINN[J]. Meteorological Monthly, 2008, 34(2): 92-100. ]
[31] 黄嘉佑, 李庆祥. 气象数据统计分析方法[M]. 北京: 气象出版社, 2015: 35-38.
[31] [Huang Jiayou, Li Qingxiang. Statistical analysis method of meteorological data[M]. Beijing: Meteorological Publishing House, 2015: 35-38. ]
[32] 黄葵, 卢毅敏, 魏征, 等. 土地利用和气候变化对海河流域蒸散发时空变化的影响[J]. 地球信息科学学报, 2019, 21(12): 1888-1902.
[32] [Huang Kui, Lu Yimin, Wei Zheng, et al. Effects of land use and climate change on temporal and spatial changes of evapotranspiration in Haihe River Basin[J]. Journal of Geo-information Science, 2019, 21(12): 1888-1902. ]
[33] 姜琪, 罗斯琼, 文小航, 等. 1961—2014年青藏高原积雪时空特征及其影响因子[J]. 高原气象, 2020, 39(1): 24-36.
[33] [Jiang Qi, Luo Siqiong, Wen Xiaohang, et al. Temporal and spatial characteristics and influencing factors of snow cover on the Qinghai Tibet Plateau from 1961 to 2014[J]. Plateau Meteorology, 2020, 39(1): 24-36. ]
[34] Sun B, Wang H J. Interannual variation of the spring and summer precipitation over the Three River Source Region in China and the associated regimes[J]. Journal of Climate, 2018, 31(18): 7441-7457.
[35] Sun B, Wang H J. Enhanced connections between summer precipitation over the Three-River-Source region of China and the global climate system[J]. Climate Dynamics, 2018, 52(5-6): 3471-3488.
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