Evolution and Driving Factors of Snow Phenology in the Chinese Tianshan Mountainous Region

doi:10.11873/j.issn.1004-0323.2022.6.1350

Remote Sensing Technology and Application

2022, Vol. 37

Issue (6): 1350-1360 DOI: 10.11873/j.issn.1004-0323.2022.6.1350

Evolution and Driving Factors of Snow Phenology in the Chinese Tianshan Mountainous Region

Bo Zhang^1,^2,³(

),Xuemei Li^1,^2,³(

),Qiyong Qin^1,^2,³

^1.Faculty of Geomatics，Lanzhou Jiaotong University，Lanzhou 730070，China
^2.Gansu Provincial Engineering Laboratory for National Geographic State Monitoring，Lanzhou 730070，China
^3.National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring，Lanzhou 730070，China

Download:

HTML

PDF (6663KB)
Export: BibTeX | EndNote (RIS)

Abstract

Due to the lack of studies on phenological evolution and driving factors of snow cover in the Chinese Tianshan Mountainous Region （CTMR）， this study calculated the number of Snow Cover Days （SCD）， Snow Onset Date （SOD） and Snow End Date （SED） in the CTMR in each hydrological year on a pixel-by-pixel basis based on the daily cloud-free snow area products of MODIS from 2002 to 2017. Then combined the temperature and precipitation data to analyze the temporal and spatial characteristics of snow phenology and its response to topography and climate change. The results were followed： The spatial distribution of snow phenology in the CTMR was different. SCD presented a distribution pattern of high in the west and low in the east， high in the north and low in the south. In high-altitude areas， SOD was earlier and SED was later. SOD in the central and western regions showed an advance trend， in which the advance trend in Bayinbulak prairie was obvious. The delayed SOD happened in southwest slope， north slope and eastern region. And the delayed SED occurred in the middle and ridgeline areas. Below 5 000 m asl， the average gradients of SCD， SOD and SED with altitude were 4.93 d/100 m， -1.64 d/100 m and 2.94 d-1.64 d/100 m， respectively. The growth trend of SCD reached the maximum at 2 500-3 000 m， and that of SED gradually decreased with the increase of altitude. The response of SED to topographic change was similar to that of SCD， but the impact of altitude on SED was weaker than that of SCD. The warming and wetting in autumn were the main reason for the postponement of SOD in the CTMR. And the warming in spring can promote the advance of SED， while wetting in spring can contribute to the postponement of SED. This study can effectively monitor the SOD and SED， reveal the climate change， and provide significant information support for the prediction of river runoff and the early warning of natural disasters such as flood and debris flow.

Key words: Snow Phenology Topography Climate Change Chinese Tianshan Mountainous Region

Received: 27 October 2021 Published: 15 February 2023

ZTFLH:

P407

Corresponding Authors: Xuemei Li E-mail: 18235118550@163.com;lixuemei@lzjtu.edu.cn

	Service
	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Bo Zhang
	Xuemei Li
	Qiyong Qin

Cite this article:

Bo Zhang,Xuemei Li,Qiyong Qin. Evolution and Driving Factors of Snow Phenology in the Chinese Tianshan Mountainous Region. Remote Sensing Technology and Application, 2022, 37(6): 1350-1360.

URL:

http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2022.6.1350 OR http://www.rsta.ac.cn/EN/Y2022/V37/I6/1350

Fig.1 Topographic map of the study area

Fig.2 The change of snow cover rate in the CTMR

Fig.3 Temporal and spatial distribution， change trend and significance distribution of snow cover phenology parameters in the CTMR

Tab. 1 The property，coverage ratio and average altitude of regions with different SCD in the CTMR

Fig. 4 Changes and trends of snow cover phenology parameters at different altitudes in the CTMR

Fig.5 Changes and trends of snow cover phenology at different aspect in the CTMR

Fig.6 Spatial distribution and trend of average temperature and precipitation in the CTMR from 1970 to 2017

Fig.7 Correlation and significant area distribution of snow cover phenology parameters and meteorological factors

1	Allchin M I， Déry Stephen J. A spatio-temporal analysis of trends in Northern Hemisphere snow-dominated area and duration，1971-2014［J］. Annals of Glaciology，2017，58（75pt1）： 21-35.DOI: . doi: 10.1017/aog.2017.47
2	Barnett T P， Adam J C， Lettenmaier D P. Potential impact of a warming climate on water availability in snow-dominated regions［J］. Nature， 2005， 438（7066）： 303-309.
3	Huss M， Bookhagen B， Huggel C， et al. Toward mountains without permanent snow and ice［J］. Earth’s Future， 2017， 5（5）： 418-435.
4	Bormann K J， Brown R D， Derksen C， et al. Estimating snow-cover trends from space［J］. Nature Climate Change， 2018，8：924-928.DOI: . doi: 10.1038/s41558-018-0318-3
5	Bulygina O N, Groisman P Y,Razuvaev,et al.Changes in snow cover characteristics over Northern Eurasia since 1966[J].Environmental Research Letters,2011,6:045204. DOI: . doi: 10. 1088/1748-9326/6/4/045204
6	Choi G， Robinson D A， Kang S. Changing Northern Hemisphere Snow Seasons［J］. Journal of Climate， 2010， 23（19）： 5305-5310.
7	Peng S， Piao S， Ciais P， et al. Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades［J］. Environmental Research Letters， 2013， 8（1）：1880-1885.
8	Chen X， Liang S， Cao Y， et al. Observed contrast changes in snow cover phenology in northern middle and high latitudes from 2001-2014［J］. Scientific report，2015，5（1）：16820.DOI: . doi: 10.1038/s41558-018-0318-3
9	Chen X， Liang S， Cao Y. Satellite observed changes in the Northern Hemisphere snow cover phenology and the associated radiative forcing and feedback between 1982 and 2013［J］. Environmental Research Letters， 2016， 11（8）： 084002.DOI: . doi: 10.1088/1748-9326/11/8/084002
10	Wang Xiaoyue， Wang Siyuan， Yi Hang， et al. Snow phenology variability in the Qinghai-Tibetan Plateau and its response to climate change during 2002-2012［J］. Journal of Geo-information Science，2016，18（11）：1573-1579.
10	汪箫悦，王思远，尹航，等. 2002-2012年青藏高原积雪物候变化及其对气候的响应［J］. 地球信息科学学报，2016，18（11）：1573-1579.
11	Wang X， Wu C， Wang H， et al. No evidence of widespread decline of snow cover on the Tibetan Plateau over 2000–2015［J］. Scientific Reports， 2017， 7（1）： 14645.DOI: . doi: 10.1038/s41598-017-15208-9
12	Qiao Dejing， Wang Nianqin， Li Zhen， et al. Spatial-temporal changes of snow phenology in the Qinhai-Tibetan Plateau during the hydrological year of 1980-2009［J］. Climate Change Research， 2018，14（2）：137-143.
12	乔德京，王念秦，李震，等. 1980-2009水文年青藏高原积雪物候时空变化遥感分析［J］. 气候变化研究进展， 2018， 14（2）： 137-143.
13	Tang Z， Wang X， Wang J，et al.Spatiotemporal variation of snow cover in Tianshan Mountains， Central Asia， based on cloud-free MODIS fractional snow cover product，2001-2015［J］. Remote Sensing，2017，9（10）：1045. DOI： . doi: 10.3390/re 9101045
14	Yang T， Li Q， Ahmad S， et al. Changes in snow phenology from 1979 to 2016 over the Tianshan Mountains， Central Asia［J］. Remote Sensing，2019，11（5）：499. DOI: . doi: 10.3390/rs 11050499
15	Li Xuemei， Gao Pei， Li Qian， et al. Muti-paths impact from climate change on snow cover in Tianshan Mountainous Area of China［J］. Climate Change Research，2016，12（4）：303-312.
15	李雪梅，高培，李倩，等. 中国天山积雪对气候变化响应的多通径分析［J］.气候变化研究进展，2016，12（4）：303-312.
16	Qin Yan， Ding Jianli， Zhao Qiudong， et al. Spatial-temporal variation of snow cover in the Tianshan Mountains from 2001 to 2015， and its relation to temperature and precipitation ［J］. Journal of Glaciology and Geocryology， 2018， 40（2）： 249-260.
16	秦艳，丁建丽，赵求东，等. 2001-2015年天山山区积雪时空变化及其与气温和降水的关系［J］. 冰川冻土， 2018， 40（2）： 249-260.
17	Ren Rui， Li Xuemei， Li lanhai， et al. Discrimination of driving factors of precipitation forms in Tianshan Mountains area of China［J］ Journal of Arid Land Resources and Environment， 2020， 34（3）： 112-117.
17	任瑞，李雪梅，李兰海，等. 中国天山山区降水形态转变的驱动因子辨析［J］. 干旱区资源与环境， 2020， 34（3）： 112-117.
18	Chen Y， Li W， Deng H， et al. Changes in Central Asia's water tower： Past， present and future［J］. Scientific Reports， 2016，6（1）：35458.DOI: . doi: 10.1038srep35458
19	Zhao Wenyu， Liu Hailong， Wang Hui， et al. A study of spatial distribution of snow cover days in the Tianshan Mountains based on MODIS snow products［J］. Journal of Glaciology and Geocryology，2016，38（6）：1510-1517．
19	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.
20	Qiu Yubao， Guo Huadong， Chu Duo， et al. MODIS daily cloud-free snow cover product over the Tibetan Plateau［EB/OL］. V2. 2016. 2016-03-03. DOI： ∥www.doi.org/10.11922/sciencedb.55.邱玉宝， doi: 10.11922/sciencedb.55； http：
20	郭华东，除多，等. 青藏高原MODIS逐日无云积雪面积数据集［EB/OL］. V2. 2016. 2016-03-03. DOI： doi: 10.11922/sciencedb.55； http：
21	Qiu Yubao， Guo Huadong， Chu Duo， et al. MODIS daily cloud-free snow cover product over the Tibetan Plateau［EB/OL］. China Scientific Data， 2016（1）： 7-17.
21	邱玉宝，郭华东，除多，等. 青藏高原MODIS逐日无云积雪面积数据集（2002-2015年）［EB/OL］. 中国科学数据（中英文网络版）， 2016（1）： 7-17.
22	Peng Shouzhang. （2019）. 1-km monthly mean temperature dataset for china（1901-2017）［EB/OL］. National Tibetan Plateau Data Center， DOI： 10.11888/Meteoro.tpdc.270961. CSTR： 18406.11.Meteoro.tpdc.27096.彭守璋（2019）. 中国1km分辨率逐月平均气温数据集（1901-2017）［EB/OL］. 国家青藏高原科学数据中心， DOI： . doi: 10.11888/Meteoro.tpdc.270961. CSTR： 18406.11.Meteoro.tpdc.270961
23	Peng S Z， Gang C， Cao Y， et al. Assessment of climate change trends over the Loess Plateau in China from 1901 to 2100［J］. International Journal of Climatology A Journal of the Royal Meteorological Society， 2018. 38（5）： 2250-2264.
24	Peng S Z， Ding Y X， Liu W， et al. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017［J］. Earth System Science Data， 2019， 11（4）： 1931-1946.
25	Peng S Z， Ding Y X， Wen Z， et al. Spatiotemporal change and trend analysis of potential evapotranspiration over the Loess Plateau of China during 2011–2100［J］. Agricultural and Forest Meteorology， 2017， 233（Complete）： 183-194.
26	Ding Y X， Peng S Z. Spatiotemporal trends and attribution of drought across China from 1901-2100［J］. Sustainability， 2020， 12（2）： 477. DOI: . doi: 10.3390/su12020477
27	Peng Shouzhang. （2020）. 1-km monthly precipitation dataset for China （1901-2017）［EB/OL］. National Tibetan Plateau Data Center， DOI： . doi: 10.5281/zenodo.3185722
27	彭守璋. （2020）. 中国1km分辨率逐月降水量数据集（1901-2017）［EB/OL］. 国家青藏高原科学数据中心， DOI： . doi: 10.5281/zenodo.3185722
28	Wang X， Xie H. New methods for studying the spatiotemporal variation of snow cover based on combination products of MODIS Terra and Aqua［J］. Journal of Hydrology， 2009， 371（1-4）： 192-200.
29	Li Peiji， Mi Desheng. Distribution of snow cover in China［J］. Journal of Glaciology and Geocryology，1983，5（4）：9-18.
29	李培基，米德生.中国积雪的分布［J］.冰川冻土，1983，5（4）：9-18.
30	Hüsler F， Jonas T， Riffler， et al. A satellite-based snow cover climatology （1985-2011） for the European Alps derived from AVHRR data［J］. The Cryosphere，2014，8：73-90.DOI: . doi: 10.5194/tc-8-73-2014
31	Peng S S， Piao S L， Ciais P， et al. Change in snow phenology and its potential feedback to temperature in the Northern Hemisphere over the last three decades［J］. Environmental Research Letters， 2013， 8（014008）： 1-8.DOI: . doi: 10.1088/1748-9326/8/1/014008
32	Deng Haijun， Chen Yaning. The glacier and snow variations and their impact on water resources in mountain regions：A case study in Tianshan Mountains of Central Asia［J］ Acta Geographica Sinica， 2018， 73（7）： 1309-1323.
32	邓海军，陈亚宁. 中亚天山山区冰雪变化及其对区域水资源的影响［J］. 地理学报， 2018， 73（7）： 1309-1323.
33	Chen Yaning， Li Zhi， Fang Gonghuan， et al. Impact climate change on water resources in the Tianshan Mountains， Central Asia［J］. Acta Geographica Sinica， 2017， 72（1）： 18-26.
33	陈亚宁，李稚，方功焕，等. 气候变化对中亚天山山区水资源影响研究［J］. 地理学报， 2017， 72（1）： 18-26.
34	Chen Y N， Li W D， Deng H J， et al. Changes in Central Asia's water tower： Past， present and future［J］. Scientific Reports， 2016， 6： 35458.DOI: . doi: 10.1038srep35458
35	Li Y P， Chen Y N， Li Z. Climate and topographic controls on snow phenology dynamics in the Tienshan Mountains， Central Asia［J］. Atmospheric Research， 2019， 236：104813.DOI: . doi: 10.1016/j.atmosres.2019.104813
36	Chen X N， Long D， Hong Y， et al. Climatology of snow phenology over the Tibetan Plateau for the period 2001-2014 using multisource data［J］. International Journal of Climatology， 2018， 38（6）： 2718-2729.
37	Chen X， Liang S， Cao Y， et al. Distribution， attribution， and radiative forcing of snow cover changes over China from 1982 to 2013［J］. Climatic Change， 2016， 137（3-4）： 363-377.

[1]	WANG Xu-feng,MA Ming-guo,YAO Hui. Advance in Dynamic Global Vegetation Models[J]. Remote Sensing Technology and Application, 2009, 24(2): 246 -251 .
[2]	He Wei,Yang Hua. EFAST Method for Global Sensitivity Analysisof Remote Sensing Model’s Parameters[J]. Remote Sensing Technology and Application, 2013, 28(5): 836 -843 .
[3]	Li Yan,Huang Chunlin,Lu Ling. Global Sensitivity Analysis of SEBS Model Parameters based on EFAST Method[J]. Remote Sensing Technology and Application, 2014, 29(5): 719 -726 .
[4]	Feng Min,Li Zaiming,Qiu Bingwen,Wang Chongyang,Luo Yuhan. Spatio-temporal Difference of Crops and Natural Vegetation Phenology in China at the Beginning of the 21st Century[J]. Remote Sensing Technology and Application, 2016, 31(5): 1003 -1012 .
[5]	Hao Binfei，Han Xujun，Ma Mingguo，Liu Yitao，Li Shiwei. Research Progress on the Application of Google Earth Engine in Geoscience and Environmental Sciences[J]. Remote Sensing Technology and Application, 2018, 33(4): 600 -611 .
[6]	Jiang Qiaoling, Xu Hanqiu. Cross-Comparison between GF-1 PMS2 and GF-2 PMS2 Sensor Data[J]. Remote Sensing Technology and Application, 2018, 33(6): 1084 -1094 .
[7]	Ming Shen,Yunsheng Ding,Hongtao Duan. Construction of “Beautiful Lakes” Comprehensive Assessment System based on Big Earth Data and SDG 6.3.2[J]. Remote Sensing Technology and Application, 2020, 35(2): 295 -301 .
[8]	Shimei Wei, Jinghu Pan, Wenliang Tuo. Estimation and Spatial-temporal Distribution Characteristics of PM2.5 Concentration by Remote Sensing in China in 2015[J]. Remote Sensing Technology and Application, 2020, 35(4): 845 -854 .
[9]	Yongkang Li,Xinjun Wang,Yanfei Ma,Bei Chen,Linan Yan,Guanhong Zhang. Downscaling Land Surface Temperature through AMSR-2 Observations by Using Machine Learning Algorithms[J]. Remote Sensing Technology and Application, 2022, 37(2): 474 -487 .
[10]	Junfei Cai,Wei Zhao,Mengjiao Yang,Qiqi Zhan,Hao Fu,Kunlong He. Spatiotemporal Changes of Evapotranspiration on the Qinghai-Tibet Plateau from 2001 to 2018 based on GLASS Data[J]. Remote Sensing Technology and Application, 2022, 37(4): 888 -896 .

Viewed

Full text

Abstract

Cited

Shared

Discussed