Terrestrial and Atmospheric Controls on Surface Energy Partitioning and Evaporative Fraction Regimes Over the Tibetan Plateau in the Growing Season

被引:13
作者
Yang, Chenyi [1 ,5 ]
Ma, Yaoming [1 ,2 ,3 ,4 ,5 ]
Yuan, Yuan [1 ,5 ]
机构
[1] Lanzhou Univ, Frontier Ctr Ecoenvironm & Climate Change Panthir, Lanzhou, Peoples R China
[2] Chinese Acad Sci, Inst Tibetan Plateau Res, State Key Lab Tibetan Plateau Earth Syst & Resour, Land Atmosphere Interact & Its Climat Effects Grp, Beijing, Peoples R China
[3] Univ Chinese Acad Sci, Beijing, Peoples R China
[4] Chinese Acad Sci, CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China
[5] Lanzhou Univ, Coll Atmospher Sci, Lanzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
land-atmosphere interactions; land heterogeneous components; water-energy interactions; evaporative fraction; Tibetan Plateau; SOIL-MOISTURE; BOUNDARY-LAYER; LAND-SURFACE; CLIMATE-CHANGE; PRECIPITATION; VEGETATION; FEEDBACKS; EVAPOTRANSPIRATION; ASSIMILATION; DIAGNOSTICS;
D O I
10.1029/2021JD035011
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Land-atmosphere interactions are an essential component of the climate system. However, no detailed description of the underlying effects of the surface forcing of the atmosphere has been established. In this study, GLEAM, MODIS, and ERA5 were the input set of multiple analysis algorithms, "segmentation" was the core idea of the analysis method. The study area is segmented into six surface response functional groups, and the multidimensional evaporation regime function was segmented into piecewise functions controlled by segment authoritative variables. Inspired by the surface heat balance equation and moisture-limited, energy-limited evaporation regimes, we chose soil moisture content and the net radiation flux to represent the moisture and energy status, respectively, and chose the leaf area index (LAI) to characterize the vegetation cover to investigate the primary effects of surface parameters on the energy partitioning of the land surface and evaporative regime. The results show that though a coupling strength 1.8 times greater was obtained when the LAI was used as the response variable instead of soil moisture, soil moisture was still the highest response variable in the regression tree analysis. This is consistent with the essence of the evaporative fraction and indicates that water should be the most fundamental response variable. The evaporative regime was subdivided from two phases into five phases according to the effects such as water extraction by vegetation, photosynthesis, soil shading, and roughness changes, each with an authoritative response variable.
引用
收藏
页数:20
相关论文
共 60 条
  • [1] The influence of land cover on surface energy partitioning and evaporative fraction regimes in the US Southern Great Plains
    Bagley, Justin E.
    Kueppers, Lara M.
    Billesbach, Dave P.
    Williams, Ian N.
    Biraud, Sebastien C.
    Torn, Margaret S.
    [J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2017, 122 (11) : 5793 - 5807
  • [2] Drought and Deforestation: Has Land Cover Change Influenced Recent Precipitation Extremes in the Amazon?
    Bagley, Justin E.
    Desai, Ankur R.
    Harding, Keith J.
    Snyder, Peter K.
    Foley, Jonathan A.
    [J]. JOURNAL OF CLIMATE, 2014, 27 (01) : 345 - 361
  • [3] Precipitation Sensitivity to Surface Heat Fluxes over North America in Reanalysis and Model Data
    Berg, Alexis
    Findell, Kirsten
    Lintner, Benjamin R.
    Gentine, Pierre
    Kerr, Christopher
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2013, 14 (03) : 722 - 743
  • [4] Land-Surface-Atmosphere Coupling in Observations and Models
    Betts, Alan K.
    [J]. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2009, 1
  • [5] Forests and climate change: Forcings, feedbacks, and the climate benefits of forests
    Bonan, Gordon B.
    [J]. SCIENCE, 2008, 320 (5882) : 1444 - 1449
  • [6] Budyko M. I., 1974, Climate and life
  • [7] Caliski T., 1974, COMMUN STAT, V3, P1, DOI [10.1080/03610927408827101, DOI 10.1080/03610927408827101]
  • [8] Spatial performance of multiple reanalysis precipitation datasets on the southern slope of central Himalaya
    Chen, Yingying
    Sharma, Shankar
    Zhou, Xu
    Yang, Kun
    Li, Xin
    Niu, Xiaolei
    Hu, Xin
    Khadka, Nitesh
    [J]. ATMOSPHERIC RESEARCH, 2021, 250
  • [9] Predicting and explaining patronage behavior toward web and traditional stores using neural networks: a comparative analysis with logistic regression
    Chiang, WYK
    Zhang, DS
    Zhou, L
    [J]. DECISION SUPPORT SYSTEMS, 2006, 41 (02) : 514 - 531
  • [10] L band microwave remote sensing and land data assimilation improve the representation of prestorm soil moisture conditions for hydrologic forecasting
    Crow, W. T.
    Chen, F.
    Reichle, R. H.
    Liu, Q.
    [J]. GEOPHYSICAL RESEARCH LETTERS, 2017, 44 (11) : 5495 - 5503