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Volume 27 Issue 6

Nov.  2010

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2010 >  27(6): 1438-1452

Influences of Climate Change and Its Interannual Variability on Surface Energy Fluxes from 1948 to 2000

  • 1.

    Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871, Department of Physics, Atmospheric Sciences, and Geoscience, Jackson State University, Jackson, MS, U.S.A.,Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871,Department of Physics, Atmospheric Sciences, and Geoscience, Jackson State University, Jackson, MS, U.S.A.


doi: 10.1007/s00376-010-9215-z

  • Understanding changes in land surface processes over the past several decades requires knowledge of trends and interannual variability in surface energy fluxes in response to climate change. In our study, the Community Land Model version 3.5 (CLM3.5), driven by the latest updated hybrid reanalysis-observational surface climate data from Princeton University, is used to obtain global distributions of surface energy fluxes during 1948 to 2000. Based on the climate data and simulation results, long-term trends and interannual variability (IAV) of both climatic variables and surface energy fluxes for this span of 50+ years are derived and analyzed. Regions with strong long-term trends and large IAV for both climatic variables and surface energy fluxes are identified. These analyses reveal seasonal variations in the spatial patterns of climate and surface fluxes; however, spatial patterns in trends and IAV for surface energy fluxes over the past ～50 years do not fully correspond to those for climatic variables, indicating complex responses of land surfaces to changes in the climatic forcings.
  • [1] FU Yuanhai, LU Riyu, 2010: Simulated Change in the Interannual Variability of South Asian Summer Monsoon in the 21st Century, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 992-1002.  doi: 10.1007/s00376-009-9124-1
    [2] Siqiong LUO, Zihang CHEN, Jingyuan WANG, Tonghua WU, Yao XIAO, Yongping QIAO, 2024: Impact of Initial Soil Conditions on Soil Hydrothermal and Surface Energy Fluxes in the Permafrost Region of the Tibetan Plateau, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 717-736.  doi: 10.1007/s00376-023-3100-z
    [3] LIU Xiangwen, WU Tongwen, YANG Song, LI Qiaoping, CHENG Yanjie, LIANG Xiaoyun, FANG Yongjie, JIE Weihua, NIE Suping, 2014: Relationships between Interannual and Intraseasonal Variations of the Asian-Western Pacific Summer Monsoon Hindcasted by BCC_CSM1.1(m), ADVANCES IN ATMOSPHERIC SCIENCES, 31, 1051-1064.  doi: 10.1007/s00376-014-3192-6
    [4] WangHuijun, Xue Feng, Bi Xunqiang, 1997: The Interannual Variability and Predictability in a Global Climate Model, ADVANCES IN ATMOSPHERIC SCIENCES, 14, 554-562.  doi: 10.1007/s00376-997-0073-2
    [5] Kaiqing YANG, Dabang JIANG, 2017: Interannual Climate Variability Change during the Medieval Climate Anomaly and Little Ice Age in PMIP3 Last Millennium Simulations, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 497-508.  doi: 10.1007/s00376-016-6075-1
    [6] ZHI Hai, WANG Panxing, DAN Li, YU Yongqiang, XU Yongfu, ZHENG Weipeng, 2009: Climate-Vegetation Interannual Variability in a Coupled Atmosphere-Ocean-Land Model, ADVANCES IN ATMOSPHERIC SCIENCES, 26, 599-612.  doi: 10.1007/s00376-009-0599-6
    [7] Hai ZHI, Rong-Hua ZHANG, Fei ZHENG, Pengfei LIN, Lanning WANG, Peng YU, 2016: Assessment of Interannual Sea Surface Salinity Variability and Its Effects on the Barrier Layer in the Equatorial Pacific Using BNU-ESM, ADVANCES IN ATMOSPHERIC SCIENCES, 33, 339-351.  doi: 10.1007/s00376-015-5163-y
    [8] Ya GAO, Huijun WANG, Dong CHEN, 2017: Interdecadal Variations of the South Asian Summer Monsoon Circulation Variability and the Associated Sea Surface Temperatures on Interannual Scales, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 816-832.  doi: 10.1007/ s00376-017-6246-8
    [9] Li Wei, Yu Rucong, Zhang Xuehong, 2001: Impacts of Sea Surface Temperature in the Tropical Pacific on Interannual Variability of Madden-Julian Oscillation in Precipitation, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 429-444.  doi: 10.1007/BF02919322
    [10] FU Jiaolan, QIAN Weihong, LIN Xiang, Deliang CHEN, 2008: Trends in Graded Precipitation in China from 1961 to 2000, ADVANCES IN ATMOSPHERIC SCIENCES, 25, 267-278.  doi: 10.1007/s00376-008-0267-2
    [11] REN Guoyu, DING Yihui, ZHAO Zongci, ZHENG Jingyun, WU Tongwen, TANG Guoli, XU Ying, 2012: Recent Progress in Studies of Climate Change in China, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 958-977.  doi: 10.1007/s00376-012-1200-2
    [12] Jeong-Hyeong LEE, Byungsoo KIM, Keon-Tae SOHN, Won-Tae KOWN, Seung-Ki MIN, 2005: Climate Change Signal Analysis for Northeast Asian Surface Temperature, ADVANCES IN ATMOSPHERIC SCIENCES, 22, 159-171.  doi: 10.1007/BF02918506
    [13] Wang Huijun, 2000: The Interannual Variability of East Asian Monsoon and Its Relationship with SST in a Coupled Atmosphere-Ocean-Land Climate Model, ADVANCES IN ATMOSPHERIC SCIENCES, 17, 31-47.  doi: 10.1007/s00376-000-0041-6
    [14] CHEN Xiao, YAN Youfang, CHENG Xuhua, QI Yiquan, 2013: Performances of Seven Datasets in Presenting the Upper Ocean Heat Content in the South China Sea, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1331-1342.  doi: 10.1007/s00376-013-2132-1
    [15] XUE Feng, ZENG Qingcun, HUANG Ronghui, LI Chongyin, LU Riyu, ZHOU Tianjun, 2015: Recent Advances in Monsoon Studies in China, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 206-229.  doi: 10.1007/s00376-014-0015-8
    [16] HAN Zuoqiang, YAN Zhongwei*, LI Zhen, LIU Weidong, and WANG Yingchun, 2014: Impact of Urbanization on Low-Temperature Precipitation in Beijing during 19602008, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 48-56.  doi: 10.1007/s00376-013-2211-3
    [17] ZHANG Lixia* and ZHOU Tianjun, , 2014: An Assessment of Improvements in Global Monsoon Precipitation Simulation in FGOALS-s2, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 165-178.  doi: 10.1007/s00376-013-2164-6
    [18] Julian X.L. Wang, Dian J. Gaffen, 2001: Trends in Extremes of Surface Humidity, Temperature, and Summertime Heat Stress in China, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 742-751.
    [19] Vladimir A. Lobanov, 2001: Empirical-Statistical Methodology and Methods for Modeling and Forecasting of Climate Variability of Different Temporal Scales, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 844-863.
    [20] Bo HAN, Shihua LÜ, Ruiqing LI, Xin WANG, Lin ZHAO, Cailing ZHAO, Danyun WANG, Xianhong MENG, 2017: Global Land Surface Climate Analysis Based on the Calculation of a Modified Bowen Ratio, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 663-678.  doi: 10.1007/s00376-016-6175-y
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    • Manuscript History

    Manuscript received: 10 November 2010
    Manuscript revised: 10 November 2010
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

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    Influences of Climate Change and Its Interannual Variability on Surface Energy Fluxes from 1948 to 2000

    • 1. Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871, Department of Physics, Atmospheric Sciences, and Geoscience, Jackson State University, Jackson, MS, U.S.A.,Department of Atmospheric Sciences, School of Physics, Peking University, Beijing 100871,Department of Physics, Atmospheric Sciences, and Geoscience, Jackson State University, Jackson, MS, U.S.A.
    • Manuscript received: 2010-11-10
    • Manuscript revised: 2010-11-10

    Abstract: Understanding changes in land surface processes over the past several decades requires knowledge of trends and interannual variability in surface energy fluxes in response to climate change. In our study, the Community Land Model version 3.5 (CLM3.5), driven by the latest updated hybrid reanalysis-observational surface climate data from Princeton University, is used to obtain global distributions of surface energy fluxes during 1948 to 2000. Based on the climate data and simulation results, long-term trends and interannual variability (IAV) of both climatic variables and surface energy fluxes for this span of 50+ years are derived and analyzed. Regions with strong long-term trends and large IAV for both climatic variables and surface energy fluxes are identified. These analyses reveal seasonal variations in the spatial patterns of climate and surface fluxes; however, spatial patterns in trends and IAV for surface energy fluxes over the past ～50 years do not fully correspond to those for climatic variables, indicating complex responses of land surfaces to changes in the climatic forcings.

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