The spatiotemporal variation of land surface heat fluxes in Tibetan Plateau during 2001-2022

被引:2
|
作者
Li, Na [1 ]
Zhao, Ping [2 ,4 ]
Zhou, Changyan [3 ]
机构
[1] Chengdu Univ Informat Technol, Coll Atmospher Sci, Plateau Atmosphere & Environm Key Lab Sichuan Prov, Chengdu, Peoples R China
[2] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing, Peoples R China
[3] China Meteorol Adm, Inst Plateau Meteorol, Heavy Rain & Drought Flood Disasters Plateau & Bas, Chengdu, Peoples R China
[4] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, 46 Zhong Guan Cun South Ave, Beijing 100081, Peoples R China
关键词
Tibetan Plateau; Maximum entropy production model; Multi-Source datasets; Sensible heat flux; Latent heat flux; ENTROPY-PRODUCTION-MODEL; ENERGY BUDGETS; EVAPOTRANSPIRATION; REANALYSIS; UNCERTAINTIES; BALANCE; WATER;
D O I
10.1016/j.atmosres.2023.107081
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The surface energy budget is important for understanding of energy and water cycle processes in the Tibetan Plateau (TP). In this study, the daily sensible (SH) and latent (LE) heat fluxes at the horizontal resolution of 1 degrees are first estimated using the maximum entropy production (MEP) model (hereinafter SHMEP and LEMEP) in the entire TP during 2001-2022. The MEP model is built on physical and statistical principles to simulate surface heat fluxes. The surface net radiation, soil moisture (SM), and land surface temperature (LST) are the main driving variables for MEP model. To select the relatively accurate MEP input data, the merged surface net radiation (Rn-merged) under all-sky conditions are generated from CERES, ISCCP-FH, and ERA5 using the Bayesian Model Averaging scheme. Besides, the TP SM and LST from various data sources are evaluated using the in-situ observations at site scale. Based on the daily Rn-merged, ERA5 SM, CERES LST, and the MEP model, the daily SH and LE are estimated in the entire TP. The results show the daily SHMEP and LEMEP perform well at the validation sites, with the regional mean correlation coefficient (R) above 0.7, root-mean-square error (RMSE) of <19 W m(-2), absolute value of bias and mean absolute error (MAE) below 11 W m(-2). The monthly SHMEP has the regional mean R of 0.96 and RMSE of 6.30 W m(-2) at all the measurement stations. For LEMEP, the regional mean R and RMSE values are 0.93 and 10.01 W m(-2), respectively. The MEP simulation results are superior to the SH and LE in ERA5, ERA-Interim, MERRA-2, and JRA-55 reanalysis datasets and previous studies, especially for LE. Based on this new dataset, the spatial and temporal varying characteristics of SH and LE in the TP are analyzed. The annual mean SHMEP value are large in the western TP, the Qaidam Basin in the northern TP, and the Himalaya ranges, and small in the southeastern TP. The annual mean LEMEP has the maximum value in southeastern TP, and minimum value in western TP and the Qaidam Basin. The annual mean SHMEP and LEMEP over the entire TP are 34.79 W m(-2) and 20.16 W m(-2), with the significant declining trends of -0.17 W m(-2) year(-1) and - 0.052 W m(-2) year(-1) during the study period, respectively. The spatial distributions of the MEP surface heat fluxes and their trends are mainly influenced by the model inputs of Rn and SM in the TP.
引用
收藏
页数:15
相关论文
共 50 条
  • [21] Spatiotemporal distribution and variation of wind erosion over the Tibetan Plateau based on a coupled land-surface wind-erosion model
    Jiang, Yingsha
    Gao, Yanhong
    He, Cenlin
    Liu, Benli
    Pan, Yongjie
    Li, Xia
    AEOLIAN RESEARCH, 2021, 50
  • [22] Review on simulation of land-surface processes on the Tibetan Plateau
    Chen, Rui
    Yang, MeiXue
    Wang, XueJia
    Wan, GuoNing
    SCIENCES IN COLD AND ARID REGIONS, 2019, 11 (02): : 93 - 115
  • [23] Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau
    Ge, Nan
    Zhong, Lei
    Ma, Yaoming
    Cheng, Meilin
    Wang, Xian
    Zou, Mijun
    Huang, Ziyu
    REMOTE SENSING, 2019, 11 (24)
  • [24] Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data
    Nan GE
    Lei ZHONG
    Yaoming MA
    Yunfei FU
    Mijun ZOU
    Meilin CHENG
    Xian WANG
    Ziyu HUANG
    AdvancesinAtmosphericSciences, 2021, 38 (08) : 1299 - 1314
  • [25] Variations of Surface Heat Fluxes over the Tibetan Plateau before and after the Onset of the South Asian Summer Monsoon during 1979-2016
    Han, Yizhe
    Ma, Weiqiang
    Ma, Yaoming
    Sun, Cuiyan
    JOURNAL OF METEOROLOGICAL RESEARCH, 2019, 33 (03) : 491 - 500
  • [26] Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data
    Nan Ge
    Lei Zhong
    Yaoming Ma
    Yunfei Fu
    Mijun Zou
    Meilin Cheng
    Xian Wang
    Ziyu Huang
    Advances in Atmospheric Sciences, 2021, 38 : 1299 - 1314
  • [27] Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data
    Ge, Nan
    Zhong, Lei
    Ma, Yaoming
    Fu, Yunfei
    Zou, Mijun
    Cheng, Meilin
    Wang, Xian
    Huang, Ziyu
    ADVANCES IN ATMOSPHERIC SCIENCES, 2021, 38 (08) : 1299 - 1314
  • [28] Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau
    Ma, Xiaogang
    Jin, Jiming
    Zhu, Lingjing
    Liu, Jian
    PEERJ, 2021, 9
  • [29] IMPROVING LAND SURFACE ENERGY AND WATER FLUXES SIMULATION OVER THE TIBETAN PLATEAU WITH USING A LAND DATA ASSIMILATION SYSTEM
    Lu, Hui
    Koike, Toshio
    Yang, Kun
    Li, Xin
    Tsutsui, Hiroyuki
    Tamagawa, Katsunori
    Xu, Xiangde
    2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 1207 - 1210
  • [30] Relationship between Tibetan Plateau Surface Heat Fluxes and Daily Heavy Precipitation in the Middle and Lower Yangtze River Basins (1980-2022)
    Li, Lu
    Dong, Xiaohua
    Ma, Yaoming
    Jin, Hanyu
    Wei, Chong
    Su, Bob
    REMOTE SENSING, 2024, 16 (20)