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近30年全球干旱半干旱区的蒸散变化特征

张霞 李明星 马柱国

张霞, 李明星, 马柱国. 近30年全球干旱半干旱区的蒸散变化特征[J]. 大气科学, 2018, 42(2): 251-267. doi: 10.3878/j.issn.1006-9895.1709.16288
引用本文: 张霞, 李明星, 马柱国. 近30年全球干旱半干旱区的蒸散变化特征[J]. 大气科学, 2018, 42(2): 251-267. doi: 10.3878/j.issn.1006-9895.1709.16288
Xia ZHANG, Mingxing LI, Zhuguo MA. Evapotranspiration Variability over Global Arid and Semi-arid Regions from 1982 to 2011[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(2): 251-267. doi: 10.3878/j.issn.1006-9895.1709.16288
Citation: Xia ZHANG, Mingxing LI, Zhuguo MA. Evapotranspiration Variability over Global Arid and Semi-arid Regions from 1982 to 2011[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(2): 251-267. doi: 10.3878/j.issn.1006-9895.1709.16288

近30年全球干旱半干旱区的蒸散变化特征

doi: 10.3878/j.issn.1006-9895.1709.16288
基金项目: 

公益性行业(气象)科研专项(重大专项) GYHY201506001-1

国家自然科学基金项目 41575087

国家自然科学基金项目 41530532

详细信息
    作者简介:

    张霞, 女, 1993年出生, 硕士研究生, 主要从事全球及区域气候变化的研究。E-mail:zhangxia@tea.ac.cn

    通讯作者:

    李明星, E-mail:limx@tea.ac.cn

  • 中图分类号: P426.2

Evapotranspiration Variability over Global Arid and Semi-arid Regions from 1982 to 2011

Funds: 

China Special Fund for Meteorological Research in the Public Interest GYHY201506001-1

National Natural Science Foundation of China 41575087

National Natural Science Foundation of China 41530532

  • 摘要: 全球变暖加剧了气候系统能量和水分循环相互作用的变化,水分平衡变化导致极端旱涝事件频发。地表蒸散是能量水分循环的重要过程,是理解气候变化的关键环节。本文基于1982~2011年FLUXNET-MTE观测资料和ERA-Interim再分析资料,分析了全球干旱半干旱区蒸散的时空变化特征及典型区域的变幅、趋势和季节变化。结果表明:(1)干旱半干旱区多年平均蒸散量小于300 mm。冬季蒸散量最小,夏季最大且变率也最强。1990年代前后,干旱半干旱区蒸散发生了明显的年代际转变,暖季的年代际差异尤为明显。(2)近30年来,东半球干旱半干旱区蒸散量呈增加趋势,西半球呈减小趋势。典型区域来看,南非呈显著增加趋势[25.14 mm(10 a)-1],美国西南部呈显著减小趋势[-19.86 mm(10 a)-1];萨赫勒、中国北部和澳大利亚呈增加趋势,阿根廷及智利南部呈减小趋势。(3)蒸散变化与温度、降水的变化联系密切,三者具有相似的年循环变化,但三者间相关性在干旱半干旱区具有显著的差异性。
  • 图  1  FLUXNET全球陆地观测站点的分布图(https://fluxnet.ornl.gov/introduction [2017-3-31])

    Figure  1.  Sites distribution of the FLUXNET global network (https://fluxnet.ornl.gov/introduction [2017-3-31])

    图  2  1982~2011年(a、c)蒸散量均值和(b、d)线性变化趋势(斜线区为通过95%信度水平检验)的空间分布:(a、b)FLUXNET-MTE观测数据;(c、d)ERA-Interim再分析数据。空白区为数据缺测区域

    Figure  2.  Spatial distributions of (a, c) the mean values of ET (Evapotranspiration) and (b, d) linear trends of ET from 1982 to 2011, hatched areas in (b) and (d) denote the 95% confidence level. (a, b) FLUXNET-MTE observations; (c, d) ERA-Interim reanalysis. Blank areas have no observations

    图  3  1982~2011年FLUXNET-MTE与ERA-Interim数据年蒸散量(a)对应格点的相关系数的空间分布[打点区域表示通过95%信度水平检验,方框表示所选六个典型区域的范围(详见表 1)]以及(b)空间相关系数的时间变化

    Figure  3.  (a) Spatial pattern of temporal correlation coefficient and (b) temporal evolution of spatial correlation coefficient between FLUXNET-MTE and ERA-Interim data for annual evapotranspiration from 1982 to 2011. In (a), dotted areas denote 95% confidence level, the rectangles denote six typical areas selected (see Table 1 for details)

    图  4  (a–f)六个典型区域标准化蒸散量的年际变化。AVG表示两套数据的算术平均,图中括号内数字表示两套数据的相关系数,所有区域均通过95%信度水平检验

    Figure  4.  Temporal evolutions of standardized annual ET for (a–f) six typical regions. AVG denotes the average of the two datasets. Values in parentheses indicate correlation coefficient between the two datasets passing the 95% confidence level

    图  5  全球干旱半干旱区蒸散均值(左列)及其变化趋势(右列;斜线区表示通过95%信度水平检验)空间分布的季节变化。黑色曲线表示干旱半干旱区边界线(地表湿润指数0.5等值线)

    Figure  5.  Spatial distributions of averaged seasonal values (left column) and their linear trends (right column; hatched areas: 95% confidence level) of ET across global arid and semi-arid regions. Black curves: arid and semi-arid boundary (contours that surface wetness index is 0.5)

    图  6  1982~2011年全球陆地(60°S~60°N)的(a)蒸散距平及其(b)离散功率谱分析。红色虚线表示标准差

    Figure  6.  (a) Evapotranspiration anomalies and (b) spectrum analysis over global land (60°S–60°N) from 1982 to 2011. Red dotted lines denote standard deviation

    图  7  (a)1982~1986年和(b)1997~2001年全球陆地蒸散量的距平百分率值的空间分布。黑色曲线表示干旱半干旱区边界线(地表湿润指数0.5等值线)

    Figure  7.  Spatial distributions of percentage ET anomaly (a) from 1982 to 1986 and (b) from 1997 to 2001 over global land. Black curves: arid and semi-arid boundary (contours that surface wetness index is 0.5)

    图  8  六个典型干旱半干旱区蒸散量的年际变化。“ *”表示变化趋势通过95%信度水平检验

    Figure  8.  Annually averaged time series of ET values in six typical arid and semi-arid areas. "*" denotes the 95% confidence level

    图  9  1982~2011年六个典型区蒸散量的统计分析(频率分布直方图以及概率拟合曲线)

    Figure  9.  Statistical analysis of ET values in six typical areas from 1982 to 2011 (frequency histograms and probability fitting curves)

    图  10  六个典型干旱半干旱区逐月标准化蒸散量、降水量和温度的趋势变化

    Figure  10.  Time series of trend coefficients of monthly standardized ET, precipitation, and temperature for six typical arid and semi-arid areas

    图  11  干旱半干旱区六个典型区域1990年代前后的蒸散量年内分配的变化

    Figure  11.  Intra-annual distributions of ET for six typical arid and semi-arid areas around the 1990s

    图  12  全球陆地(a)气温和(b)降水量的线性趋势(单位分别为℃ a−1和mm a−1)的空间分布。斜线区表示通过95%信度水平检验

    Figure  12.  Spatial distributions of linear trends of global terrestrial (a) temperature (units: ℃ a−1) and (b) precipitation (units: mm a−1). Hatched areas denote 95% confidence level

    图  13  全球陆地蒸散量与温度(左列)、降水量(右列)的相关性。(a、b)斜线区通过95%信度水平检验,(c、d)回归线的相关检验均通过95%信度水平检验

    Figure  13.  Correlation analysis between global terrestrial ET and temperature (left column), and precipitation (right column). Hatched areas in (a), (b) and correlation coefficients in (c), (d) denote 95% confidence level

    图  14  全球陆地标准化的蒸散量、降水量和气温的年内变化

    Figure  14.  Intra-annual variations of global terrestrial ET, precipitation, and temperature

    表  1  六个典型分区概况

    Table  1.   Basic geographic information of six typical regions

    区号 区域 经度 纬度
    美国西南部 113.5°W~104°W 31°N~42°N
    萨赫勒 15°W~40°E 15°N~20°N
    中国北部 85°E~118°E 35°N~42°N
    阿根廷及智利的南部 9°E~22.5°E 40°S~55°S
    南非 14°E~35°E 22°S~33°S
    澳大利亚 115°E~147°E 18°S~36°S
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  • [1] Aphalo P J, Jarvis P G. 1993. The boundary layer and the apparent responses of stomatal conductance to wind speed and to the mole fractions of CO2 and water vapour in the air[J]. Plant, Cell & Environment, 16 (7):771-783, doi: 10.1111/j.1365-3040.1993.tb00499.x.
    [2] Baldocchi D, Falge E, Gu L H, et al. 2001. FLUXNET:A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities[J]. Bull. Amer. Meteor. Soc., 82 (11):2415-2434, doi:10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2.
    [3] Betts A K, Köhler M, Zhang Y C. 2009. Comparison of river basin hydrometeorology in ERA-Interim and ERA-40 reanalyses with observations[J]. J. Geophys. Res., 114 (D2):D02101, doi: 10.1029/2008JD010761.
    [4] Bonan G B. 2002. Ecological Climatology:Concepts and Applications[M]. New York:Cambridge University Press, 678pp.
    [5] Bonan G B, Lawrence P J, Oleson K W, et al. 2011. Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data[J]. J. Geophys. Res., 116 (G2):G02014, doi: 10.1029/2010JG001593.
    [6] Bradley R S, Diaz H F, Eischeid J K, et al. 1987. Precipitation fluctuations over Northern Hemisphere land areas since the mid-19th century[J]. Science, 237 (4811):171-175, doi: 10.1126/science.237.4811.171.
    [7] Cai X T, Yang Z L, Xia Y L, et al. 2014. Assessment of simulated water balance from Noah, Noah-MP, CLM, and VIC over CONUS using the NLDAS test bed[J]. J. Geophys. Res., 119 (24):13751-13770, doi: 10.1002/2014JD022113.
    [8] Chattopadhyay N, Hulme M. 1997. Evaporation and potential evapotranspiration in India under conditions of recent and future climate change[J]. Agricultural and Forest Meteorology, 87 (1):55-73, doi: 10.1016/S0168-1923(97)00006-3.
    [9] Chiodo G, Haimberger L. 2010. Interannual changes in mass consistent energy budgets from ERA-Interim and satellite data[J]. J. Geophys. Res., 115 (D2):D02112, doi: 10.1029/2009JD012049.
    [10] Chou C, Lan C W. 2012. Changes in the annual range of precipitation under global warming[J]. J. Climate, 25 (1):222-235, doi: 10.1175/JCLI-D-11-00097.1.
    [11] Cohen S, Ianetz A, Stanhill G. 2002. Evaporative climate changes at Bet Dagan, Israel, 1964-1998[J]. Agricultural and Forest Meteorology, 111 (2):83-91, doi: 10.1016/S0168-1923(02)00016-3.
    [12] Collatz G J, Ball J T, Grivet C, et al. 1991. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration:A model that includes a laminar boundary layer[J]. Agricultural and Forest Meteorology, 54 (2-4):107-136, doi: 10.1016/0168-1923(91)90002-8.
    [13] Cook E R, Woodhouse C A, Eakin C M, et al. 2004. Long-term aridity changes in the western United States[J]. Science, 306 (5698):1015-1018, doi: 10.1126/science.1102586.
    [14] 董晴晴, 占车生, 王会肖, 等. 2016. 2000年以来的渭河流域实际蒸散发时空格局分析[J].干旱区地理, 39 (2):327-335. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=ghqdl201602012

    Dong Qingqing, Zhan Chesheng, Wang Huixiao, et al. 2016. Spatio-temporal patterns of actual evapotranspiration in the Weihe River basin since 2000[J]. Arid Land Geography (in Chinese), 39 (2):327-335. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=ghqdl201602012
    [15] Dee D P, Uppala S. 2009. Variational bias correction of satellite radiance data in the ERA-Interim reanalysis[J]. Quart. J. Roy. Meteor. Soc., 135 (644):1830-1841, doi: 10.1002/qj.493.
    [16] Dee D P, Uppala S M, Simmons A J, et al. 2011. The ERA-Interim reanalysis:Configuration and performance of the data assimilation system[J]. Quart. J. Roy. Meteor. Soc., 137 (656):553-597, doi: 10.1002/qj.828.
    [17] Dewar R. 2003. Information theory explanation of the fluctuation theorem, maximum entropy production and self-organized criticality in non-equilibrium stationary states[J]. Journal of Physics A:Mathematical and General, 36 (3):631-641, doi: 10.1088/0305-4470/36/3/303.
    [18] Dewar R C. 2005. Maximum entropy production and the fluctuation theorem[J]. Journal of Physics A:Mathematical and General, 38 (21):L371-L381, doi: 10.1088/0305-4470/38/21/L01.
    [19] 符淙斌, 温刚. 2002.中国北方干旱化的几个问题[J].气候与环境研究, 7 (1):22-29. doi: 10.3969/j.issn.1006-9585.2002.01.003

    Fu Congbin, Wen Gang. 2002. Several issues on aridification in the northern China[J]. Climatic and Environmental Research (in Chinese), 7 (1):22-29, doi:10.3969/j.issn.1006-9585.2002. 01.003.
    [20] 符淙斌, 马柱国. 2008.全球变化与区域干旱化[J].大气科学, 32 (4):752-760. doi: 10.3878/j.issn.1006-9895.2008.04.05

    Fu Congbin, Ma Zhuguo. 2008. Global change and regional aridification[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 32 (4):752-760, doi: 10.3878/j.issn.1006-9895.2008.04.05.
    [21] Goyal R K. 2004. Sensitivity of evapotranspiration to global warming:A case study of arid zone of Rajasthan (India)[J]. Agricultural Water Management, 69 (1):1-11, doi: 10.1016/j.agwat.2004.03.014.
    [22] 韩婷婷. 2014. 再分析和协同观测数据的差异性分析研究[D]. 兰州大学硕士学位论文. http://cdmd.cnki.com.cn/Article/CDMD-10730-1014301863.htm

    Han Tingting. 2014. The analysis of the differences between reanalysis data and cooperative observation data[D]. M. S. thesis (in Chinese), Lanzhou University. http://cdmd.cnki.com.cn/Article/CDMD-10730-1014301863.htm
    [23] 黄嘉佑. 2004.气象统计分析与预报方法[M]. 3版.北京:气象出版社, 215-225.

    Huang Jiayou. 2004. Statistical Analysis and Forecasting Method in Meteorology (in Chinese)[M]. 3rd ed. Beijing:China Meteorological Press, 215-225.
    [24] 黄建平, 季明霞, 刘玉芝, 等. 2013.干旱半干旱区气候变化研究综述[J].气候变化研究进展, 9 (1):9-14. doi: 10.3969/j.issn.1673-1719.2013.01.002

    Huang Jianping, Ji Mingxia, Liu Yuzhi, et al. 2013. An overview of arid and semi-arid climate change[J]. Progressus Inquisitiones de Mutatione Climatis (in Chinese), 9 (1):9-14, doi: 10.3969/j.issn.1673-1719.2013.01.002.
    [25] 黄锡荃. 1993.水文学[M].北京:高等教育出版社, 41-59.

    Huang Xiquan. 1993. Hydrology (in Chinese)[M]. Beijing:Higher Education Press, 41-59.
    [26] Hulme M. 1996. Recent climatic change in the world's drylands[J]. Geophys. Res. Lett., 23 (1):61-64, doi: 10.1029/95GL03586.
    [27] Harris I, Jones P D, Osborn T J, et al. 2014. Updated high-resolution grids of monthly climatic observations-The CRU TS3.10 dataset[J]. International Journal of Climatology, 34 (3):623-642, doi:10.1002/joc. 3711.
    [28] Huang J, Guan X, Ji F. 2012. Enhanced cold-season warming in semi-arid regions[J]. Atmospheric Chemistry and Physics, 12 (12):5391-5398, doi: 10.5194/acp-12-5391-2012.
    [29] Huntington T G. 2006. Evidence for intensification of the global water cycle:Review and synthesis[J]. J. Hydrol., 319 (1-4):83-95, doi: 10.1016/j.jhydrol.2005.07.003.
    [30] IPCC. 2013. Summary for policymakers[M]//Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Stocker T F, Qin D, Plattner G K, et al, Eds. Cambridge, UK and New York, USA: Cambridge University Press, 35pp.
    [31] Jacobson M Z. 2005. Fundamentals of Atmospheric Modeling[M]. 2nd ed. Cambridge:Cambridge University Press, 53-62.
    [32] Jung M, Reichstein M, Bondeau A. 2009. Towards global empirical upscaling of FLUXNET eddy covariance observations:Validation of a model tree ensemble approach using a biosphere model[J]. Biogeosciences, 6 (10):2001-2013, doi: 10.5194/bg-6-2001-2009.
    [33] Jung M, Reichstein M, Ciais P, et al. 2010. Recent decline in the global land evapotranspiration trend due to limited moisture supply[J]. Nature, 467 (7318):951-954, doi: 10.1038/nature09396.
    [34] Jung M, Reichstein M, Margolis H A, et al. 2011. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations[J]. J. Geophys. Res., 116 (G3):G00J07, doi: 10.1029/2010JG001566.
    [35] 李鹏飞, 孙小明, 赵昕奕. 2012.近50年中国干旱半干旱地区降水量与潜在蒸散量分析[J].干旱区资源与环境, 26 (7):57-63. http://industry.wanfangdata.com.cn/dl/Detail/Periodical?id=Periodical_ghqzyyhj201207011

    Li Pengfei, Sun Xiaoming, Zhao Xinyi. 2012. Analysis of precipitation and potential evapotranspiration in arid and semi arid area of China in recent 50 years[J]. Journal of Arid Land Resources and Environment (in Chinese), 26 (7):57-63. http://industry.wanfangdata.com.cn/dl/Detail/Periodical?id=Periodical_ghqzyyhj201207011
    [36] Long S P. 1991. Modification of the response of photosynthetic productivity to rising temperature by atmospheric CO2 concentrations:Has its importance been underestimated?[J]. Plant, Cell & Environment, 14 (8):729-739, doi: 10.1111/j.1365-3040.1991.tb01439.x.
    [37] Lorenz C, Kunstmann H. 2012. The hydrological cycle in three state-of-the-art reanalyses:Intercomparison and performance analysis[J]. Journal of Hydrometeorology, 13 (5):1397-1420, doi: 10.1175/JHM-D-11-088.1.
    [38] 马柱国. 2005.我国北方干湿演变规律及其与区域增暖的可能联系[J].地球物理学报, 48 (5):1011-1018. doi: 10.3321/j.issn:0001-5733.2005.05.006

    Ma Zhuguo. 2005. Dry/wet variation and its relationship with regional warming in arid-regions of northern China[J]. Chinese Journal of Geophysics (in Chinese), 48 (5):1011-1018, doi: 10.3321/j.issn:0001-5733.2005.05.006.
    [39] 马柱国, 符淙斌. 2007. 20世纪下半叶全球干旱化的事实及其与大尺度背景的联系[J].中国科学D辑:地球科学, 37 (2):222-233. doi: 10.3321/j.issn:1006-9267.2007.02.010

    Ma Zhuguo, Fu Congbin. 2007. Evidences of drying trend in the global during the later half of 20th century and their relationship with large-scale climate background[J]. Science in China Series D:Earth Sciences, 50 (5):776-788, doi: 10.3321/j.issn:1006-9267.2007.02.010.
    [40] Mueller B, Hirschi M, Seneviratne S I. 2011. New diagnostic estimates of variations in terrestrial water storage based on ERA-Interim data[J]. Hydrological Processes, 25 (7):996-1008, doi: 10.1002/hyp.7652.
    [41] New M, Lister D, Hulme M, et al. 2002. A high-resolution data set of surface climate over global land areas[J]. Climate Research, 21 (1):1-25, doi: 10.3354/cr021001.
    [42] 潘淑芬. 2014. 全球陆地初级生产力, 蒸散发及水分利用效率对全球变化的响应[D]. 中国科学院生态环境研究中心博士学位论文. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2675481

    Pan Shufen. 2014. Global terrestrial net primary production, evapotranspiration and water use efficiency in responses to climate change and increasing atmospheric CO2 in the 21st century[D]. Ph. D. dissertation (in Chinese), Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=Y2675481
    [43] Peterson T C, Golubev V S, Groisman P Y. 2002. Evaporation losing its strength[J]. Nature, 377 (6551):687-688, doi: 10.1038/377687b0.
    [44] Pielke R A, Avissar R, Raupach M, et al. 1998. Interactions between the atmosphere and terrestrial ecosystems:Influence on weather and climate[J]. Global Change Biology, 4 (5):461-475, doi:10.1046/j.1365-2486. 1998.t01-1-00176.x.
    [45] Roderick M L, Farquhar G D. 2002. The cause of decreased pan evaporation over the past 50 years[J]. Science, 298 (5597):1410-1411, doi: 10.1126/science.1075390-a.
    [46] 芮孝芳. 2004.水文学原理[M].北京:中国水利水电出版社, 105-106.

    Rui Xiaofang. 2004. Hydrological Principles (in Chinese)[M]. Beijing:China Water & Power Press, 105-106.
    [47] Seneviratne S I, Lüthi D, Litschi M, et al. 2006. Land-atmosphere coupling and climate change in Europe[J]. Nature, 443 (7108):205-209, doi: 10.1038/nature05095.
    [48] 施能, 陈绿文, 封国林, 等. 2004. 1920~2000年全球陆地降水气候特征与变化[J].高原气象, 23 (4):435-443. doi: 10.3321/j.issn:1000-0534.2004.04.003

    Shi Neng, Chen Luwen, Feng Guolin, et al. 2004. Climate characters and changes in global land precipitation field from 1920 to 2000[J]. Plateau Meteorology (in Chinese), 23 (4):435-443, doi: 10.3321/j.issn:1000-0534.2004.04.003.
    [49] Stanhill G, Cohen S. 2001. Global dimming:A review of the evidence for a widespread and significant reduction in global radiation with discussion of its probable causes and possible agricultural consequences[J]. Agricultural and Forest Meteorology, 107 (4):255-278, doi: 10.1016/S0168-1923(00)00241-0.
    [50] 苏京志, 温敏, 丁一汇, 等. 2016.全球变暖趋缓研究进展[J].大气科学, 40 (6):1143-1153. doi: 10.3878/j.issn.1006-9895.1512.15242

    Su Jingzhi, Wen Min, Ding Yihui, et al. 2016. Hiatus of global warming:A review[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 40 (6):1143-1153, doi:10.3878/j.issn.1006-9895. 1512.15242.
    [51] 苏涛. 2016. 基于多套再分析资料的全球蒸发量时空变化特征及其成因研究[D]. 兰州大学博士学位论文. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=D01032933

    Su Tao. 2016. Research on spatial-temporal variation characteristics and its causes of global evaporation based on multi-reanalysis datasets[D]. Ph. D. dissertation (in Chinese), Lanzhou University. http://www.wanfangdata.com.cn/details/detail.do?_type=degree&id=D01032933
    [52] Trenberth K E. 2011. Changes in precipitation with climate change[J]. Climate Res., 47 (1-2):123-138, doi: 10.3354/cr00953.
    [53] 王媛媛, 谢正辉, 贾炳浩, 等. 2015.基于陆面过程模式CLM4的中国区域植被总初级生产力模拟与评估[J].气候与环境研究, 20 (1):97-110. doi: 10.3878/j.issn.1006-9585.2014.13208

    Wang Yuanyuan, Xie Zhenghui, Jia Binghao, et al. 2015. Simulation and evaluation of gross primary productivity in China by using land surface model CLM4[J]. Climatic and Environmental Research (in Chinese), 20 (1):97-110, doi:10.3878/j.issn.1006-9585. 2014.13208.
    [54] 闻新宇, 王绍武, 朱锦红, 等. 2006.英国CRU高分辨率格点资料揭示的20世纪中国气候变化[J].大气科学, 30 (5):894-904. doi: 10.3878/j.issn.1006-9895.2006.05.18

    Wen Xinyu, Wang Shaowu, Zhu Jinhong, et al. 2006. An overview of China climate change over the 20th century using UK UEA/CRU high resolution grid data[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 30 (5):894-904, doi: 10.3878/j.issn.1006-9895.2006.05.18.
    [55] Wang K C, Dickinson R E. 2012. A review of global terrestrial evapotranspiration:Observation, modeling, climatology, and climatic variability[J]. Rev. Geophys., 50 (2):RG2005, doi: 10.1029/2011RG000373.
    [56] Wilks D S. 2005. Statistical Methods in the Atmospheric Sciences[M]. San Diego:Academic Press, 30-33, 381-398.
    [57] 张文君, 周天军, 宇如聪. 2007.中国东部水分收支的初步分析[J].大气科学, 31 (2):329-345. doi: 10.3878/j.issn.1006-9895.2007.02.14

    Zhang Wenjun, Zhou Tianjun, Yu Rucong. 2007. A preliminary analysis on the moisture budget of East China[J]. Chinese Journal of Atmospheric Sciences (in Chinese), 31 (2):329-345, doi: 10.3878/j.issn.1006-9895.2007.02.14.
    [58] 周蕾, 王绍强, 陈镜明, 等. 2009. 1991年至2000年中国陆地生态系统蒸散时空分布特征[J].资源科学, 31 (6):962-972. doi: 10.3321/j.issn:1007-7588.2009.06.010

    Zhou Lei, Wang Shaoqiang, Chen Jingming, et al. 2009. The spatial-temporal characteristics of evapotranspiration of China's terrestrial ecosystems during 1991-2000[J]. Resources Science (in Chinese), 31 (6):962-972, doi: 10.3321/j.issn:1007-7588.2009.06.010.
    [59] Zhang K, Kimball J S, Running S W. 2016. A review of remote sensing based actual evapotranspiration estimation[J]. Wiley Interdisciplinary Reviews:Water, 3 (6):834-853, doi: 10.1002/wat2.1168.
    [60] Zhu G F, Zhang K, Li X, et al. 2016. Evaluating the complementary relationship for estimating evapotranspiration using the multi-site data across North China[J]. Agricultural and Forest Meteorology, 230-231:33-44, doi: 10.1016/j.agrformet.2016.06.006.
    [61] Zveryaev I I, Allan R P. 2010. Summertime precipitation variability over Europe and its links to atmospheric dynamics and evaporation[J]. J. Geophys. Res., 115 (D12):D12102, doi: 10.1029/2008JD011213.
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  • 收稿日期:  2016-12-19
  • 网络出版日期:  2017-09-12
  • 刊出日期:  2018-03-15

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