基于偏相关分析的2003—2020年青藏高原地表温度变化驱动因子量化研究

doi:10.11947/j.AGCS.2024.20230206

测绘学报 ›› 2024, Vol. 53 ›› Issue (5): 848-859.doi: 10.11947/j.AGCS.2024.20230206

• 青藏高原冰冻圈重大变化专栏 • 上一篇下一篇

基于偏相关分析的2003—2020年青藏高原地表温度变化驱动因子量化研究

杨梦娇¹^,²^,³(), 赵伟²(), 詹琪琪²^,⁴, 张亚¹^,³, 孟晓荣¹^,³, 蔡俊飞²^,⁵, 杨羽佳²^,⁶

^1.中国地质调查局昆明自然资源综合调查中心，云南　昆明　650100
^2.中国科学院、水利部成都山地灾害与环境研究所，四川　成都　610299
^3.自然资源部自然生态系统碳汇工程技术创新中心，云南　昆明　650100
^4.中国地质调查局军民融合地质调查中心，四川　成都　610036
^5.重庆市地理信息和遥感应用中心，重庆　401147
^6.中国科学院大学，北京　100049

收稿日期:2023-05-22 修回日期:2024-04-26 发布日期:2024-06-19
通讯作者: 赵伟 E-mail:1525830216@qq.com;zhaow@imde.ac.cn
作者简介:杨梦娇（1996—），女，硕士，助理工程师，研究方向为地表温度遥感监测与应用。E-mail：1525830216@qq.com
基金资助:
国家自然科学基金(42222109);第二次青藏高原综合科学考察研究(2019QZKK0404);中国地质调查局地质调查项目(DD20230482);自然资源综合调查指挥中心科技创新基金(KC20230021)

Quantitative study on driving factors of land surface temperature trends on the Qinghai-Tibet Plateau from 2003 to 2020 based on partial correlation analysis

Mengjiao YANG¹^,²^,³(), Wei ZHAO²(), Qiqi ZHAN²^,⁴, Ya ZHANG¹^,³, Xiaorong MENG¹^,³, Junfei CAI²^,⁵, Yujia YANG²^,⁶

^1.Kunming General Survey of Natural Resources Center, China Geological Survey, Kunming 650100, China
^2.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
^3.Technology Innovation Center for Natural Ecosystem Carbon Sink, Ministry of Natural Resources, Kunming 650100, China
^4.Civil-Military Integration Center of China Geological Survey, Chengdu 610036, China
^5.Chongqing Geomatics and Remote Sensing Center, Chongqing 401147, China
^6.University of Chinese Academy of Sciences, Beijing 100049, China

Received:2023-05-22 Revised:2024-04-26 Published:2024-06-19
Contact: Wei ZHAO E-mail:1525830216@qq.com;zhaow@imde.ac.cn
About author:YANG Mengjiao (1996—), female, master, assistant engineer, majors in remote sensing monitoring of land surface temperature and application. E-mail: 1525830216@qq.com
Supported by:
The National Natural Science Foundation of China(42222109);The Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0404);The Project of China Geological Survey(DD20230482);Science and Technology Innovation Foundation of Command Center of Integrated Natural Resources Survey Center(KC20230021)

摘要/Abstract

摘要：

地表温度（LST）作为地气相互作用的关键参数，在地表水热循环中发挥重要作用，能准确表征地表热环境的变化。青藏高原拥有除极地以外储量最大的冰冻圈范围，对区域和全球气候系统及生态经济具有深远影响。作为受气候变化影响最显著的区域之一，深入了解青藏高原冰冻圈LST变化驱动因子，能为精准认知青藏高原冰冻圈热环境变化规律及驱动机制提供关键科学支撑。本研究基于地表温度年周期模型提取的年均地表温度（MAST），采用偏相关分析，分析了2003—2020年MAST与云量、植被覆盖度、积雪覆盖率、降水和气温5个与MAST变化密切相关的驱动因子之间的关系，揭示青藏高原不同区域MAST变化的主要驱动因子及其空间分布特征。结果表明，白天云量、植被覆盖度、积雪覆盖率和降水这4个驱动因子主要以负偏相关为主，晚上则以正偏相关为主，对于气温来说昼夜都以正偏相关为主。就青藏高原MAST动态的主导因子来说，昼夜MAST在青藏高原不同区域的主导因素存在明显差异，白天青藏高原的MAST的变化主要受云量的影响（主导变化面积占比达38.17%），影响区域集中分布于青藏高原的西北部和西部，且以负偏相关性为主。夜晚青藏高原MAST变化主要以气温为主导（主导变化面积超过48%），且以正偏相关为主，反映出夜晚MAST受气候变暖的影响强于白天。本研究能为气候变化背景下青藏高原冰冻圈保护和可持续发展提供科学的参考。

关键词: 地表温度, 青藏高原, 驱动因子, 偏相关分析, 冰冻圈变化

Abstract:

As a key parameter of land-atmosphere interaction, land surface temperature (LST) plays an important role in the surface water-heat cycle and can accurately characterize changes in the surface thermal environment. The Qinghai-Tibet Plateau has the largest cryosphere except for the polar regions, which has a profound impact on the regional and global climate system and ecological economy. As the region with the most significant climate change, an in-depth understanding of the driving factors of LST dynamic changes in the cryosphere of the Qinghai-Tibet Plateau can provide important scientific support for an accurate understanding of the changing laws and driving mechanisms of the cryosphere thermal environment of the Qinghai-Tibet Plateau. Based on the mean annual surface temperature (MAST) extracted from the annual temperature cycle model, this study used partial correlation analysis to analyze the relationship between the MASTs and cloud amount, vegetation coverage, snow cover, precipitation, and air temperature from 2003 to 2020 and revealed the main driving factors of the change of MAST in different regions of the Qinghai-Tibet Plateau. The results show that the four driving factors of cloud amount, vegetation coverage, snow cover, and precipitation mainly have negative partial correlations during the daytime while positive partial correlations during the nighttime, and there are positive partial correlations for air temperature during both the daytime and nighttime. For the dominant factors of MAST dynamic changes on the Qinghai-Tibet Plateau, there are significant differences in the dominant factors of MAST in different regions of the Qinghai-Tibet Plateau. The MAST dynamic changes on the Qinghai-Tibet Plateau during the daytime are mainly affected by cloud amount with a main negative partial correlation (the dominant change area accounts for 38.17%), and the affected area is concentrated on the northwest and the west of the Qinghai-Tibet Plateau. The overall MAST changes on the Qinghai-Tibet Plateau at nighttime are mainly dominated by air temperature with a positive partial correlation (the dominant change area exceeds 48%), reflecting that the influence of climate warming on MAST at nighttime is stronger than that during the daytime. This study can provide a scientific reference for the protection and sustainable development of the cryosphere on the Qinghai-Tibet Plateau under the background of climate change.

Key words: land surface temperature, Qinghai-Tibet Plateau, driving factors, partial correlation analysis, cryosphere changes

中图分类号:

P237

杨梦娇, 赵伟, 詹琪琪, 张亚, 孟晓荣, 蔡俊飞, 杨羽佳. 基于偏相关分析的2003—2020年青藏高原地表温度变化驱动因子量化研究[J]. 测绘学报, 2024, 53(5): 848-859.

Mengjiao YANG, Wei ZHAO, Qiqi ZHAN, Ya ZHANG, Xiaorong MENG, Junfei CAI, Yujia YANG. Quantitative study on driving factors of land surface temperature trends on the Qinghai-Tibet Plateau from 2003 to 2020 based on partial correlation analysis[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(5): 848-859.

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基于偏相关分析的2003—2020年青藏高原地表温度变化驱动因子量化研究

Quantitative study on driving factors of land surface temperature trends on the Qinghai-Tibet Plateau from 2003 to 2020 based on partial correlation analysis

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