基于MODIS白天地温产品的青藏高原海拔依赖型变暖特征分析

吴芳营; 游庆龙; 蔡子怡; 张玲; 康世昌; 翟盘茂

doi:10.3878/j.issn.1006-9895.2111.21157

基于MODIS白天地温产品的青藏高原海拔依赖型变暖特征分析

doi: 10.3878/j.issn.1006-9895.2111.21157

吴芳营^1,,
游庆龙^{1, 2, ,},
蔡子怡¹,
张玲³,
康世昌⁴,
翟盘茂⁵

1.
复旦大学大气与海洋科学系/大气科学研究院，上海200438
2.
中国气象局—复旦大学海洋气象灾害联合实验室，上海200438
3.
南京信息工程大学气象灾害教育部重点实验室，南京210044
4.
中国科学院西北生态环境资源研究院冰冻圈科学国家重点实验室，兰州730000
5.
中国气象科学研究院，北京100081

基金项目: “第二次青藏高原综合科学考察研究”专项2019QZKK0105

详细信息

作者简介:
吴芳营，女，1995年出生，博士研究生，主要从事青藏高原气候变化研究。E-mail: wufangy1@163.com

通讯作者:
游庆龙，E-mail: qlyou@fudan.edu.cn；张玲，E-mail: lingzhang@nuist.edu.cn

中图分类号: P467
计量
- 文章访问数: 262
- HTML全文浏览量: 103
- PDF下载量: 45
- 被引次数: 0
出版历程
- 收稿日期: 2021-08-19
- 录用日期: 2021-12-21
- 网络出版日期: 2021-12-22
- 刊出日期: 2022-03-16

Characteristics of Elevation Dependent Warming over the Tibetan Plateau Based on the MODIS Daytime Land Surface Temperature Data

1.
Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai 200438
2.
China Meteorological Administration–Fudan University (CMA-FDU) Joint Laboratory of Marine Meteorology，Shanghai 200438
3.
Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Nanjing University of Information Science and Technology (NUIST), Nanjing 210044
4.
State Key Laboratory of Cryospheric Science, Chinese Academy of Sciences (CAS), Lanzhou 730000
5.
Chinese Academy of Meteorological Sciences, Beijing 100081

Funds: Second Tibetan Plateau Scientific Expedition and Research (STEP) Project (Grant 2019QZKK0105)

摘要

摘要: 基于2001～2018年中分辨率成像光谱仪（MODIS）探测的白天地面温度（简称MODIS 白天地温）资料，与青藏高原（简称高原）122个气象站点观测的最高气温资料，在年尺度上评估了MODIS 白天地温在高原的适用性，研究了高原五个干湿分区下MODIS 白天地温的海拔依赖型变暖特征，得到以下主要结论：（1）MODIS白天地温能够基本再现观测的最高气温的时空以及海拔依赖型变暖特征；（2）高原整体上，MODIS白天地温存在显著的海拔依赖型变暖特征，平均海拔每增加100 m，其趋势增加0.02°C (10a)⁻¹，且受积雪—反照率反馈主导；（3）干湿分区下，海拔依赖型变暖特征在高原表现为偏湿润地区强于偏干旱地区；季风区强于西风区。海拔依赖型特征强弱：半湿润地区＞湿润半湿润地区＞半干旱地区＞湿润地区＞干旱地区。平均海拔每增加100 m，以上区域的地温趋势分别增加0.06，0.03，0.03，0.01，0.01°C (10a)⁻¹。半湿润和湿润半湿润地区年均温在0°C左右，在气候变暖背景下积雪—反照率反馈作用最为强烈，是其海拔依赖型变暖的主导因素；干旱与半干旱地区年均温相对更低，气候变暖程度对积雪影响相对较小，积雪—反照率反馈作用被限制，但仍对上述地区的海拔依赖型变暖起主导作用；而湿润地区的积雪覆盖率的上升可能是由于降雪（固态降水）增加抵消了积雪融化损耗，云辐射、水汽等其他因素主导了其海拔依赖型变暖。
- 青藏高原 /
- MODIS白天地温 /
- 海拔依赖型变暖
Abstract: Based on the moderate-resolution imaging spectroradiometer daytime land surface temperature (MODIS daytime LST) and maximum surface air temperature data of 122 meteorological stations from 2001 to 2018, the applicability of the MODIS daytime LST over the Tibetan Plateau (TP) was evaluated on an annual scale, and the elevation-dependent warming (EDW) characteristics of the MODIS daytime LST over five dry and wet subregions over the TP are studied. The main conclusions are as follows: (1) The MODIS daytime LST can capture the spatiotemporal and EDW characteristics of the observed maximum temperature over the TP. (2) On the whole, there is a significant EDW over the TP derived from the MODIS daytime LST. The temperature trend increases by 0.02°C (10a)⁻¹ per 100 m, which is dominated by the snow albedo feedback. (3) In terms of subregions, EDW characteristics are stronger in the humid region than in the arid region, which also stronger in monsoon regions than in westerly regions. The characteristics of EDW are: semihumid region > humid /semihumid region > semiarid region > humid region > arid region. The MODIS daytime LST trend in the above regions increases by 0.06, 0.03, 0.03, 0.01, and 0.01°C(10a)⁻¹ per 100 m, respectively. Annual mean temperatures in semihumid and humid/semihumid regions are about 0°C, and the snow albedo feedback is the strongest in a warming climate, dominating the EDW of the above regions. Annual mean temperatures in the arid and semiarid regions are relatively lower, and the influence of climate warming on the snow cover is relatively weaker with a weak snow albedo feedback. The increase in the snow cover in the humid region may be due to the increase in snowfall (solid precipitation) offsetting the loss of snow melting. Other factors such as cloud radiation and water vapor dominate its EDW over these regions.
- Tibetan Plateau /
- Elevation dependent warming /
- MODIS daytime land surface temperature

HTML全文

图 1 青藏高原（简称高原）分区以及气象站点（红点）分布，图中字符ID1、IC2等意义见表1

Figure 1. Ecosystem zones and distribution of meteorological stations over the Tibetan Plateau (TP), and the meanings of characters ID1, IC2, etc. in the figure are shown in Table 1

下载: 全尺寸图片幻灯片

图 2 （a–f）2001~2018年观测的最高气温与中分辨率成像光谱仪（MODIS）白天地温在青藏高原不同海拔区间的时间序列，右下角数字表示两序列的相关系数，括号内蓝色数字代表该海拔区间内气象站点数；（g）观测的最高气温趋势随海拔区间的变化，EDW后的数字表示趋势与海拔的相关系数；（h，i）观测的最高气温与MODIS白天地温在不同海拔区间（彩色圆点）趋势的散点图：（h）站点所在像元的MODIS，（i）海拔区间的MODIS，右下角数字表示相关系数（相关系数后***表示通过0.01显著性水平的t检验）

Figure 2. (a–f) Time series of the observed maximum temperature and Moderate-resolution Imaging Spectroradiometer (MODIS) daytime Land Surface Temperature (LST) at different elevation ranges over the TP during 2001–2018. The number in the bottom right corner represents the correlation coefficient of the two sequences. The blue numbers in brackets of the figure title represent the number of meteorological stations in the elevation range. (g) Trend of observed maximum temperature changes with the elevation. The number after EDW indicates the correlation coefficient between the trend and elevation. (h–i) Scatter plots of the trend of the the observed maximum temperature and MODIS daytime LST at different elevation ranges (colored dot): (h) the MODIS of the pixel where the station is located; (i) the MODIS of the elevation range (the number in the bottom right corner represents the correlation coefficient, *** indicates that passed the t-test of 0.01 significance level)

下载: 全尺寸图片幻灯片

图 3 2001~2018年 MODIS白天地温在高原以及五个干湿分区的时间序列。Trend表示趋势（均未通过显著性检验），单位：°C (10a)⁻¹ ；rstd表示一元回归系数的标准误差，相当于趋势的标准误差，单位：°C a⁻¹

Figure 3. Time series of the MODIS daytime LST over the TP and its five subregions during 2001–2018. “Trend” represents the trend (none of them passed the significance test), units: °C (10a)⁻¹, and “rstd” represents standard error of the estimated regression coefficient, units: °C a⁻¹

下载: 全尺寸图片幻灯片

图 4 高原以及五个干湿分区下2001~2018 年MODIS白天地温的年际趋势随海拔区间的变化。柱状图上数字代表相应海拔区间的平均白天地面温度

Figure 4. Trend of the MODIS daytime LST changes with elevation ranges over the TP and its five subregions during 2001–2018. The numbers on the histogram represents the mean MODIS daytime LST in the corresponding elevation range

下载: 全尺寸图片幻灯片

图 5 2001~2018年MODIS积雪覆盖率在高原的（a）气候态、（b）变化趋势分布、（c）趋势随海拔区间的变化以及（d）不同海拔区间的MODIS白天地温趋势与MODIS积雪覆盖率趋势比较。图中数字为相关系数（**表示通过0.05显著性水平的t检验）

Figure 5. Spatial distributions of (a) climatology, (b) trend, and (c) trend change with elevation ranges from the MODIS snow cover percent (SCP) and (d) trend from the MODIS daytime LST versus trend from the snow cover in different elevation range over the TP during 2001–2018. The number in figure d represents the correlation coefficient (** indicates that it passed the t-test of 0.05 significance level)

下载: 全尺寸图片幻灯片

图 6 2001~2018年高原以及五个干湿分区下不同海拔区间的MODIS白天地温与MODIS积雪覆盖率趋势比较。左下角数字表示两者相关系数（***、**分别表示相关系数通过0.01、0.05显著性水平的t检验）

Figure 6. Trend from the MODIS daytime LST versus the trend from the snow cover percent (SCP) in different elevation ranges over the TP and its five subregions during 2001–2018. The number in the bottom left corner represents the correlation coefficient (*** and ** indicate that the correlation coefficients passed the t-test of 0.01 and 0.05 significant level, respectively)

下载: 全尺寸图片幻灯片

表 1 高原分区

Table 1. Information of ecosystem zones over the TP

温度带	干湿地区	自然地带
I 高原亚寒带	B 半湿润地区	IB1 果洛那曲，高寒灌丛草甸地带
	C 半干旱地区	IC1 青南，高寒草甸草原地带
		IC2 羌塘，高寒草原地带
	D 干旱地区	ID1 昆仑，高寒荒漠地带
II 高原温带	A/B 湿润/半湿润地区	IIAB1 川西藏东，山地针叶林地带
	C 半干旱地区	IIC1 藏南，山地灌丛草原地带
		IIC2 青东祁连，山地草原地带
	D 干旱地区	IID1 阿里，山地半荒漠、荒漠地带
		IID2 柴达木，山地荒漠地带
		IID3 昆仑北翼，山地荒漠地带
O 山地亚热带	A 湿润地区	OA1 东喜马拉雅南翼山地常绿阔叶林地带

下载: 导出CSV

表 2 基于MODIS和数字高程模型（DEM）资料的高原以及五个干湿分区的基本特征（趋势均未通过显著性检验）

Table 2. Basic characteristics of the TP and its five subregions based on MODIS and Digital Elevation Model data (none of them passed the significance test)

	基本特征
分区	平均海拔/m	像元数（比例）	平均温度/°C （趋势/°C (10a)⁻¹）	平均积雪覆盖率（趋势/°C (10a)⁻¹）
高原整体	4436.8	97246（100.00%）	11.86（0.22）	17.76%（−0.46）
干旱地区	4290.6	28897（29.71%）	12.63（0.17）	19.25%（−1.03）
半干旱地区	4698.3	40495（41.64%）	12.39（0.24）	12.03%（0.04）
半湿润地区	4463.2	9882（10.16%）	11.42（0.14）	18.41%（0.19）
湿润半湿润地区	4167.0	16140（16.60%）	9.83（0.32）	25.46%（−1.17）
湿润地区	3258.4	1720（1.77%）	8.71（-0.01）	46.42%（1.10）

下载: 导出CSV

表 3 高原以及五个干湿分区2001～2018 年MODIS白天地温的年际趋势与海拔的相关系数（***，**，*分别表示通过0.01，0.05，0.1显著性水平的$t$检验）

Table 3. Correlation coefficients between the trend of the MODIS daytime LST and elevation over the TP and its five subregions during 2001–2018 (***, **, and * indicates that passed the $ t $-test of 0.01, 0.05, and 0.1 significant level, respectively)

	相关系数
分区	海拔 >2 km	2~5 km	>5 km	趋势随海拔变化速率/°C (10a)⁻¹ (100 m)⁻¹
高原整体	0.23***	0.17***	−0.01	0.02
干旱地区	0.11***	0.06***	−0.02*	0.01
半干旱地区	0.34***	0.26***	0.03***	0.03
半湿润地区	0.46***	0.41***	0.10***	0.06
湿润半湿润地区	0.40***	0.39***	−0.07***	0.03
湿润地区	0.29***	0.28***	0.18	0.01

下载: 导出CSV

参考文献(50)

[1]	Barnett T P, Adam J C, Lettenmaier D P. 2005. Potential impacts of a warming climate on water availability in snow-dominated regions [J]. Nature, 438(7066): 303−309. doi: 10.1038/nature04141
[2]	Bolch T, Kulkarni A V, Kääb A, et al. 2012. The state and fate of Himalayan glaciers [J]. Science, 336(6079): 310−314. doi: 10.1126/science.1215828
[3]	Chen B, Chao W C, Liu X. 2003. Enhanced climatic warming in the Tibetan Plateau due to doubling CO₂: A model study [J]. Climate Dyn., 20(4): 433. doi: 10.1007/s00382-003-0308-6
[4]	陈德亮, 徐柏青, 姚檀栋, 等. 2015. 青藏高原环境变化科学评估: 过去、现在与未来 [J]. 科学通报, 60(32): 3025−3035. doi: 10.1360/N972014-01370 Chen Deliang, Xu Baiqing, Yao Tandong, et al. 2015. Assessment of past, present and future environmental changes on the Tibetan Plateau [J]. Chinese Science Bulletin (in Chinese), 60(32): 3025−3035. doi: 10.1360/N972014-01370
[5]	杜军. 2001. 西藏高原近40年的气温变化 [J]. 地理学报, 56(6): 682−690. doi: 10.3321/j.issn:0375-5444.2001.06.007 Du Jun. 2001. Change of temperature in Tibetan Plateau from 1961 to 2000 [J]. Acta Geographica Sinica (in Chinese), 56(6): 682−690. doi: 10.3321/j.issn:0375-5444.2001.06.007
[6]	Duan A M, Wu G X. 2004. Main heating modes over the Tibetan Plateau in July and the correlation patterns of circulation and precipitation over East Asia [J]. J. Meteor. Res., 18(2): 167−178.
[7]	Duan A M, Wu G X. 2005. Role of the Tibetan Plateau thermal forcing in the summer climate patterns over subtropical Asia [J]. Climate Dyn., 24(7-8): 793−807. doi: 10.1007/s00382-004-0488-8
[8]	Duan A M, Wu G X. 2006. Change of cloud amount and the climate warming on the Tibetan Plateau [J]. Geophys. Res. Lett., 33(22): L22704. doi: 10.1029/2006GL027946
[9]	段安民, 肖志祥, 吴国雄. 2016. 1979–2014年全球变暖背景下青藏高原气候变化特征 [J]. 气候变化研究进展, 12(5): 374−381. doi: 10.12006/j.issn.1673-1719.2016.039 Duan Anmin, Xiao Zhixiang, Wu Guoxiong. 2016. Characteristics of climate change over the Tibetan Plateau under the global warming during 1979–2014 [J]. Climate Change Research (in Chinese), 12(5): 374−381. doi: 10.12006/j.issn.1673-1719.2016.039
[10]	Gao Y H, Chen F, Lettenmaier D P, et al. 2018. Does elevation-dependent warming hold true above 5000 m elevation? Lessons from the Tibetan Plateau [J]. npj Climate and Atmospheric Science, 1(1): 19. doi: 10.1038/s41612-018-0030-z
[11]	Guo D L, Sun J Q, Yang K, et al. 2019. Revisiting recent elevation-dependent warming on the Tibetan Plateau using satellite-based data sets [J]. J. Geophys. Res.: Atmos., 124(15): 8511−8521. doi: 10.1029/2019JD030666
[12]	Guo D L, Sun J Q, Yang K, et al. 2020. Satellite data reveal southwestern Tibetan Plateau cooling since 2001 due to snow–albedo feedback [J]. Int. J. Climatol., 40(3): 1644−1655. doi: 10.1002/joc.6292
[13]	Immerzeel W W, van Beek L P H, Bierkens M F P. 2010. Climate change will affect the Asian water towers [J]. Science, 328(5984): 1382−1385. doi: 10.1126/science.1183188
[14]	Kang S C, Xu Y W, You Q L, et al. 2010. Review of climate and cryospheric change in the Tibetan Plateau [J]. Environ. Res. Lett., 5(1): 015101. doi: 10.1088/1748-9326/5/1/015101
[15]	Kuang X X, Jiao J J. 2016. Review on climate change on the Tibetan Plateau during the last half century [J]. J. Geophys. Res. :Atmos., 121(8): 3979−4007. doi: 10.1002/2015JD024728
[16]	Li B F, Chen Y N, Shi X. 2020. Does elevation dependent warming exist in high mountain Asia? [J]. Environ. Res. Lett., 15(2): 024012. doi: 10.1088/1748-9326/ab6d7f
[17]	林振耀, 赵昕奕. 1996. 青藏高原气温降水变化的空间特征[J]. 中国科学(D 辑), 26(4): 354–358. Lin Zhenyao, Zhao Xinyi. 1996. Spatial characteristics of temperature and precipitation over the Tibetan Plateau [J]. Science in China (Series D) (in Chinese), 26(4): 354–358.
[18]	刘晓东, 侯萍. 1998. 青藏高原及其邻近地区近30年气候变暖与海拔高度的关系 [J]. 高原气象, 17(3): 245−249. doi: 10.3321/j.issn:1006-9267.1998.03.009 Liu Xiaodong, Hou Ping. 1998. Relationship between the climatic warming over the Qinghai–Xizang Plateau and its surrounding areas in recent 30 years and the elevation [J]. Plateau Meteorology (in Chinese) (in Chinese), 17(3): 245−249. doi: 10.3321/j.issn:1006-9267.1998.03.009
[19]	刘宣飞, 汪靖. 2006. 东亚副热带夏季风环流指数及其与中国气候的关系 [J]. 热带气象学报, 22(6): 533−538. doi: 10.3969/j.issn.1004-4965.2006.06.003 Liu Xuanfei, Wang Jing. 2006. The East Asian subtropical summer monsoon index and its relation with climate anomalies in China [J]. Journal of Tropical Meteorology (in Chinese), 22(6): 533−538. doi: 10.3969/j.issn.1004-4965.2006.06.003
[20]	Liu X D, Cheng Z G, Yan L B, et al. 2009. Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan Plateau and its surroundings [J]. Glob. Planet. Change, 68(3): 164−174. doi: 10.1016/j.gloplacha.2009.03.017
[21]	吕京国, 张小咏, 蒋玲梅, 等. 2009. MODIS地表产品数据的相关算法及处理过程 [J]. 遥感信息, 24(4): 25−29. doi: 10.3969/j.issn.1000-3177.2009.04.005 Lü Jingguo, Zhang Xiaoyong, Jiang Lingmei, et al. 2009. The algorithms and process of the MODIS land surface product [J]. Remote Sensing Information (in Chinese), 24(4): 25−29. doi: 10.3969/j.issn.1000-3177.2009.04.005
[22]	Mountain Research Initiative EDW Working Group. 2015. Elevation-dependent warming in mountain regions of the world [J]. Nat. Climate Change, 5(5): 424−430. doi: 10.1038/nclimate2563
[23]	Niu X R, Tang J P, Chen D L, et al. 2021a. Elevation-dependent warming over the Tibetan Plateau from an ensemble of CORDEX-EA regional climate simulations [J]. J. Geophys. Res. :Atmos., 126(9): e2020JD033997. doi: 10.1029/2020JD033997
[24]	Niu X R, Tang J P, Chen D L, et al. 2021b. The performance of CORDEX-EA-II simulations in simulating seasonal temperature and elevation-dependent warming over the Tibetan Plateau [J]. Climate Dyn., 57(3-4): 1135−1153. doi: 10.1007/s00382-021-05760-6
[25]	Palazzi E, Mortarini L, Terzago S, et al. 2019. Elevation-dependent warming in global climate model simulations at high spatial resolution [J]. Climate Dyn., 52(5-6): 2685−2702. doi: 10.1007/s00382-018-4287-z
[26]	Pepin N C, Maeda E E, Williams R. 2016. Use of remotely sensed land surface temperature as a proxy for air temperatures at high elevations: Findings from a 5000 m elevational transect across Kilimanjaro [J]. J. Geophys. Res. :Atmos., 121(17): 9998−10015. doi: 10.1002/2016JD025497
[27]	秦大河, 丁一汇, 王绍武, 等. 2002. 中国西部环境演变及其影响研究 [J]. 地学前缘, 9(2): 321−328. doi: 10.3321/j.issn:1005-2321.2002.02.009 Qin D H, Ding Y H, Wang S W, et al. 2002. A study of environment change and its impacts in western China [J]. Earth Science Frontiers, 9(2): 321−328. doi: 10.3321/j.issn:1005-2321.2002.02.009
[28]	Qin J, Yang K, Liang S L, et al. 2009. The altitudinal dependence of recent rapid warming over the Tibetan Plateau [J]. Climatic Change, 97(1-2): 321−327. doi: 10.1007/s10584-009-9733-9
[29]	Rangwala I, Miller J R. 2012. Climate change in mountains: A review of elevation-dependent warming and its possible causes [J]. Climatic Change, 114(3-4): 527−547. doi: 10.1007/s10584-012-0419-3
[30]	Rangwala I, Miller J R, Xu M. 2009. Warming in the Tibetan Plateau: Possible influences of the changes in surface water vapor [J]. Geophys. Res. Lett., 36(6): L06703. doi: 10.1029/2009GL037245
[31]	宋辞, 裴韬, 周成虎. 2012. 1960年以来青藏高原气温变化研究进展 [J]. 地理科学进展, 31(11): 1503−1509. doi: 10.11820/dlkxjz.2012.11.011 Song Ci, Pei Tao, Zhou Chenghu. 2012. Research progresses of surface temperature characteristic change over Tibetan Plateau since 1960 [J]. Progress in Geography (in Chinese), 31(11): 1503−1509. doi: 10.11820/dlkxjz.2012.11.011
[32]	Thakuri S, Salerno F, Bolch T, et al. 2016. Factors controlling the accelerated expansion of Imja Lake, Mount Everest region, Nepal [J]. Ann. Glaciol., 57(71): 245−257. doi: 10.3189/2016AoG71A063
[33]	王朋岭, 唐国利, 曹丽娟, 等. 2012. 1981~2010年青藏高原地区气温变化与高程及纬度的关系 [J]. 气候变化研究进展, 8(5): 313−319. doi: 10.3969/j.issn.1673-1719.2012.05.001 Wang Pengling, Tang Guoli, Cao Lijuan, et al. 2012. Surface air temperature variability and its relationship with altitude & latitude over the Tibetan Plateau in 1981–2010 [J]. Progressus Inquisitiones de Mutatione Climatis (in Chinese), 8(5): 313−319. doi: 10.3969/j.issn.1673-1719.2012.05.001
[34]	Wang Q X, Fan X H, Wang M B. 2014. Recent warming amplification over high elevation regions across the globe [J]. Climate Dyn., 43(1-2): 87−101. doi: 10.1007/s00382-013-1889-3
[35]	魏凤英. 1999. 现代气候统计诊断与预测技术[M]. 北京: 气象出版社, 269pp Wei Fengying. 1999. Modern Climate Statistical Diagnosis and Prediction Technology (in Chinese) [M]. Beijing: China Meteorological Press, 269pp.
[36]	韦志刚, 黄荣辉, 董文杰. 2003. 青藏高原气温和降水的年际和年代际变化 [J]. 大气科学, 27(2): 157−170. doi: 10.3878/j.issn.1006-9895.2003.02.03 Wei Zhigang, Huang Ronghui, Dong Wenjie. 2003. Interannual and interdecadal variations of air temperature and precipitation over the Tibetan Plateau [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 27(2): 157−170. doi: 10.3878/j.issn.1006-9895.2003.02.03
[37]	吴国雄, 刘屹岷, 刘新, 等. 2005. 青藏高原加热如何影响亚洲夏季的气候格局 [J]. 大气科学, 29(1): 47−56. doi: 10.3878/j.issn.1006-9895.2005.01.06 Wu Guoxiong, Liu Yimin, Liu Xin, et al. 2005. How the heating over the Tibetan Plateau affects the Asian climate in summer [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 29(1): 47−56. doi: 10.3878/j.issn.1006-9895.2005.01.06
[38]	Wu G X, Liu Y M, Zhang Q, et al. 2007. The influence of mechanical and thermal forcing by the Tibetan Plateau on Asian climate [J]. J. Hydrometeorol., 8(4): 770−789. doi: 10.1175/JHM609.1
[39]	杨凯, 胡田田, 王澄海. 2017. 青藏高原南、北积雪异常与中国东部夏季降水关系的数值试验研究 [J]. 大气科学, 41(2): 345−356. doi: 10.3878/j.issn.1006-9895.1604.16119 Yang Kai, Hu Tiantian, Wang Chenghai. 2017. A numerical study on the relationship between the spring–winter snow cover anomalies over the northern and southern Tibetan Plateau and summer precipitation in east China [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 41(2): 345−356. doi: 10.3878/j.issn.1006-9895.1604.16119
[40]	Yao T D, Xue Y K, Chen D L, et al. 2019. Recent third pole’s rapid warming accompanies cryospheric melt and water cycle intensification and interactions between monsoon and environment: Multidisciplinary approach with observations, modeling, and analysis [J]. Bull. Amer. Meteor. Soc., 100(3): 423−444. doi: 10.1175/BAMS-D-17-0057.1
[41]	Yan Y P, You Q L, Wu F Y, et al. 2020. Surface mean temperature from the observational stations and multiple reanalyses over the Tibetan Plateau [J]. Climate Dyn., 55(9-10): 2405−2419. doi: 10.1007/s00382-020-05386-0
[42]	You Q L, Kang S C, Pepin N, et al. 2010. Relationship between temperature trend magnitude, elevation and mean temperature in the Tibetan Plateau from homogenized surface stations and reanalysis data [J]. Glob. Planet. Change, 71(1-2): 124−133. doi: 10.1016/j.gloplacha.2010.01.020
[43]	You Q L, Min J Z, Kang S C. 2016. Rapid warming in the Tibetan Plateau from observations and CMIP5 models in recent decades [J]. Int. J. Climatol., 36(6): 2660−2670. doi: 10.1002/joc.4520
[44]	You Q L, Zhang Y Q, Xie X Y, et al. 2019. Robust elevation dependency warming over the Tibetan Plateau under global warming of 1.5°C and 2°C [J]. Climate Dyn., 53(3-4): 2047−2060. doi: 10.1007/s00382-019-04775-4
[45]	You Q L, Wu F Y, Shen L C, et al. 2020a. Tibetan Plateau amplification of climate extremes under global warming of 1.5℃, 2℃ and 3℃ [J]. Glob. Planet. Change, 192: 103261. doi: 10.1016/j.gloplacha.2020.103261
[46]	You Q L, Chen D L, Wu F Y, et al. 2020b. Elevation dependent warming over the Tibetan Plateau: Patterns, mechanisms and perspectives [J]. Earth-Sci. Rev., 210: 103349. doi: 10.1016/j.earscirev.2020.103349
[47]	You Q L, Wu F Y, Wang H G, et al. 2020c. Projected changes in snow water equivalent over the Tibetan Plateau under global warming of 1.5° and 2°C [J]. J. Climate, 33(12): 5141−5154. doi: 10.1175/JCLI-D-19-0719.1
[48]	Zhang H B, Zhang F, Zhang G Q, et al. 2016. Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau [J]. Atmos. Chem. Phys., 16(21): 13681−13696. doi: 10.5194/acp-16-13681-2016
[49]	Zhang H B, Zhang F, Zhang G Q, et al. 2018. How accurately can the air temperature lapse rate over the Tibetan Plateau be estimated from MODIS LSTs? [J]. J. Geophys. Res.: Atmos., 123(8): 3943−3960. doi: 10.1002/2017JD028243
[50]	郑度. 1996. 青藏高原自然地域系统研究 [J]. 中国科学(D辑), 26(4): 336−341. doi: 10.3321/j.issn:1006-9267.1996.04.007 Zheng Du. 1996. Study on the ecosystem zones over the Tibetan Plateau [J]. Science in China(Series D) (in Chinese), 26(4): 336−341. doi: 10.3321/j.issn:1006-9267.1996.04.007