Forward and Backward Linkages between Land Surface Temperature and Leaf Area Index for the Summer in Belarus

被引:0
|
作者
Lysenko, S. A. [1 ]
机构
[1] Natl Acad Sci Belarus, Inst Nat Management, Minsk, BELARUS
关键词
climate change; land degradation; leaf area index; land surface temperature; feedbacks; CLIMATE; ATMOSPHERE;
D O I
10.1134/S000143382309013X
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
On the basis of Earth remote sensing data for 2000-2020, quantitative estimates of the influence of vegetation cover degradation on the summer warming in Belarus have been obtained. The average leaf area index of Belarus for this period increased by 3.3%, mainly due to forest areas, the leaf index of which increased by about 8%. The growth of the leaf area index slowed down the summer warming of forest lands in the north (above 54 degrees N) by about half and by more than a quarter in the south of Belarus. At the same time, the leaf area index of croplands decreased by about 5%, which caused their additional warming and amplified their land surface temperature daily cycle for the summer period. Statistically significant signs of bioclimatic land degradation have been found on the territory of Belarus with a total area of about 400 000 ha, which are enhanced by high values of positive feedback between temperature, vegetation cover, and soil moisture. About of 58% of the degrading lands are agricultural lands located mainly in the southern part of the country. On these lands, the summer temperature grows twice as fast as the average for Belarus, and the leaf index decreases at a rate of about 2% per year, which indicates the insufficiency of agriculture climate mitigation in certain regions of Belarus.
引用
收藏
页码:1137 / 1149
页数:13
相关论文
共 50 条
  • [1] Forward and Backward Linkages between Land Surface Temperature and Leaf Area Index for the Summer in Belarus
    S. A. Lysenko
    Izvestiya, Atmospheric and Oceanic Physics, 2023, 59 : 1137 - 1149
  • [2] Modeling land surface phenology in a mixed temperate forest using MODIS measurements of leaf area index and land surface temperature
    Jonathan M. Hanes
    Mark D. Schwartz
    Theoretical and Applied Climatology, 2011, 105 : 37 - 50
  • [3] Modeling land surface phenology in a mixed temperate forest using MODIS measurements of leaf area index and land surface temperature
    Hanes, Jonathan M.
    Schwartz, Mark D.
    THEORETICAL AND APPLIED CLIMATOLOGY, 2011, 105 (1-2) : 37 - 50
  • [4] A Trend Analysis of Leaf Area Index and Land Surface Temperature and Their Relationship from Global to Local Scale
    Rasul, Azad
    Ibrahim, Sa'ad
    Onojeghuo, Ajoke R.
    Balzter, Heiko
    LAND, 2020, 9 (10) : 1 - 17
  • [5] The relationship between land surface temperature and water index in the urban area of a tropical city
    Achmad, A.
    Zainuddin
    Muftiadi, M.
    INTERNATIONAL CONFERENCE ON AGRICULTURAL TECHNOLOGY, ENGINEERING AND ENVIRONMENTAL SCIENCES 2019, 2019, 365
  • [6] Ecosystem sensitivity to land-surface models and leaf area index
    Parton, WJ
    Haxeltine, A
    Thornton, P
    Anne, R
    Hartman, M
    GLOBAL AND PLANETARY CHANGE, 1996, 13 (1-4) : 89 - 98
  • [7] Estimation of Turbulent Heat Fluxes and Gross Primary Productivity by Assimilating Land Surface Temperature and Leaf Area Index
    He, Xinlei
    Xu, Tongren
    Bateni, Sayed M.
    Ki, Seo Jin
    Xiao, Jingfeng
    Liu, Shaomin
    Song, Lisheng
    He, Xiangping
    WATER RESOURCES RESEARCH, 2021, 57 (11)
  • [8] Reprocessing the MODIS Leaf Area Index products for land surface and climate modelling
    Yuan, Hua
    Dai, Yongjiu
    Xiao, Zhiqiang
    Ji, Duoying
    Shangguan, Wei
    REMOTE SENSING OF ENVIRONMENT, 2011, 115 (05) : 1171 - 1187
  • [9] Numerical experiments on the spatial scaling of land surface albedo and leaf area index
    Liang, Shunlin
    Remote Sensing Reviews, 2000, 19 (1-4): : 225 - 242
  • [10] The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model
    Rahman, Azbina
    Maggioni, Viviana
    Zhang, Xinxuan
    Houser, Paul
    Sauer, Timothy
    Mocko, David M.
    REMOTE SENSING, 2022, 14 (03)