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全球温度场信息熵的时空特征分析

冯爱霞 龚志强 黄琰 王启光

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全球温度场信息熵的时空特征分析

冯爱霞, 龚志强, 黄琰, 王启光

Spatiotemporal analysis of information entropy of the global temperature

Wang Qi-Guang, Feng Ai-Xia, Gong Zhi-Qiang, Huang Yan
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  • 本文基于信息熵理论定义气象要素信息熵,并运用其分析全球温度场在不同时空尺度上偏离气候态(1971—2000)的不确定性. 研究结果表明:1)温度场气候态信息熵(CE)具有明显的纬向分布特征,总体表现为温度场CE由低纬度地区向中高纬度地区递增,且海陆差异显著,可以较好地区分各个气候带;其垂直变化,在低纬度地区表现为随高度的升高而增加,但在中高纬度地区则以300hPa为界呈准对称分布,在此高度之上其值随高度升高而增加,之下则相反,这一特征在高纬度地区更为明显.2)温度场月信息熵(ME)的季节性差异显著,总体表
    Based on the concept of entropy in information theory, the entropy of meteorological elements is determined and used to analyze the uncertainty of the global temperature field anomaly from the climate state (1971—2000) on different time and spatial scales. It is found that the temperature climate entropy (CE) possesses a zonal distribution, increases from tropics to mid-high latitudes and has an obvious difference between the ocean region and the continent, thereby being able to distinguish the climatic zones properly. The temperature CE in low-mid troposphere increases with altitude increasing, while in extratropical the situation retains above 300 hPa but below 300 hPa the situation is reversed, and this feature is more obvious in high latituderegions. On the whole, the temperature monthly entropy (ME) is obviously dependent on season change: it is smallest in summer and largest in winter. Besides, there exists a distinguishable interdecadal period. Different monthly ME values from low atmosphere to high atmosphere each have an obvious five -to-ten year quasi-period oscillation. All the spatiotemporal characteristics and their relationships with annual temperature range verify the usefulness of the entropy in meteorology, and it is an effective method to measure the uncertainty of the meteorological elements.
    • 基金项目: 国家自然科学基金(批准号:40930952,40875040和40905034),公益性行业专项 (批准号:GYHY201006021)和国家科技支撑计划(批准号:2007BAC29B01)资助的课题.
    [1]

    Chou J F, 1997 Bull. Chin. Acad. Sci. 5 325 (in Chinese)[丑纪范 1997 中国科学院院刊 5 325]

    [2]

    Feng G L, Dong W J 2004 Chin. Phys. 13 413

    [3]

    Feng G L, Gong Z Q, Dong W J, Li J P 2005 Acta Phys. Sin. 54 5494 (in Chinese)[封国林、龚志强、董文杰、李建平 2005 54 5494]

    [4]

    Feng G L, Dong W J, Gong Z Q, Hou W, Wan S Q, Zhi R 2006 Nonlinear theories and methods on spatial-temporal distribution of the observational data (Beijing: Metrological Press) (in Chinese)[封国林、董文杰、龚志强、侯威、万仕全、支 蓉 2006 观测数据非线性时空分布理论和方法(北京:气象出版社)]

    [5]

    Feng G L, Gao X Q, Dong W J, Li J P 2008 Chaos Soli. Fract. 37 487

    [6]

    Feng G L, Gong Z Q, Zhi R, Zhang D Q 2008 Chin. Phys. B 17 2745

    [7]

    Li J P, Gao L 2006 Chin. J. Atmos. Sci. 30 834 (in Chinese) [李建平、高 丽 2006 大气科学 30 834]

    [8]

    Li J P, Wang X L 2003 Adv. Atmos. Sci. 20 661

    [9]

    Li J P, Chou J F 1997 Acta Meteor. Sin. 11 57

    [10]

    Li J P, Zeng Q C, Chou J F 2000 Sci. China. (E) 30 550 (in Chinese)[李建平、曾庆存、丑纪范 2000中国科学 (E辑) 30 550]

    [11]

    Dai X G, Wang P, Chou J F 2004 Pro. Nat. Sci. 14 73

    [12]

    Gong Z Q, Zhou L, Zhi R, Feng G L 2008 Acta Pyhs. Sin. 57 5351 (in Chinese)[龚志强、周 磊、支 蓉、封国林 2008 57 5351]

    [13]

    Ding Y H, Li Q Q, Li W J, Luo Y, Zhang P Q, Zhang Z Q, Shi X L, Liu Y M, Wang L N 2004 Acta Meteor. Sin. 62 598 (in Chinese) [丁一汇、李清泉、李维京、罗 勇、张培群、张祖强、史学丽、刘一鸣、王兰宁 2004 气象学报 62 598 ]

    [14]

    Liu H B, Zhang D L, Wang B 2006 Climatic Environ. Res. 11 649 (in Chinese)[刘鸿波、张大林、王 斌 2006气候与环境研究 11 649 ]

    [15]

    Shannon C E 1948 Bell Sys. Tech. J. 27 379

    [16]

    Zhang X W 1981 Weather forecasting using information analysis (Beijing: Science Press) (in Chinese) (in Chinese) [张学文 1981 气象预告问题的信息分析 (北京:科学出版社)]

    [17]

    Zhang X W, Ma L 1992 Entropy Meteorology (Beijing: Meteorology Press)(in Chinese)[张学文、马 力 1992 熵气象学(北京:气象出版社)]

    [18]

    Leung L Y, North G R 1990 J. Climate 3 5

    [19]

    Zhang J G, Liu X R 2000 Advan. Water Sci. 11 133 (in Chinese)[张继国、刘新仁 2000 水科学进展 11 133]

    [20]

    Delsole T 2004 J. Atmos. Sci. 61 2425

    [21]

    Zhao W T, Chen X, Zhao P Z 1988 Entropy and cross Science: Information Entropy in Meteorology (Beijing: Meteorology Press) p127—130 (in Chinese)[赵文桐、陈 霞、赵佩章 1988 信息熵于气象熵,熵与交叉科学(北京:气象出版社)第127—130页]

    [22]

    Wang J Y, Fu Z T, Zhang L, Liu S D 2005 Plate. Meteor. 24 38 (in Chinese)[汪景烨、付遵涛、张 霖、刘式达 2005 高原气象 24 38]

    [23]

    Wang Q G, Zhang Z P 2008 Acta Phys. Sin. 57 1976 (in Chinese)[王启光、张增平 2008 57 1976]

    [24]

    Feng G L,Wang Q G, Hou W, Gong Z Q, Zhi R 2009 Acta. Phys. Sin. 58 4 (in Chinese)[封国林、王启光、侯 威、龚志强、支 蓉 2009 58 4]

    [25]

    Hao C Y, WU S H, Li S C 2007 Geo. Graphi. Res. 26 46 (in Chinese)[郝成元、吴绍洪、李双成 2007 地理研究 26 46]

    [26]

    Zhang Z S, Gong Z Q, Zhi R, Feng G L, Hu J G 2011 Chin. Phys. B 20

    [27]

    Li J P, Ding R Q 2008 Chin. J. Atmos Sci. 32 975 (in Chinese)[李建平、丁瑞强 2008 大气科学 32 975]

    [28]

    Ding R Q, Li J P 2009 Acta Meteor. Sin. 67 343 (in Chinese)[丁瑞强、李建平 2009 气象学报 67 343]

    [29]

    Zhi R, Gong Z Q, Feng G L, Zhou L 2010 Acta Meteor. Sin. 24 150

    [30]

    Feng G L, Gong Z Q, Zhi R, Zhang D Q 2008 Chin. Phys. B 17 2745

    [31]

    Gong Z Q, Wang X J, Zhi R, Feng G L 2009 Acta. Phys. Sin. 58 4342(in Chinese)[龚志强、王晓娟、支 蓉、封国林2009 58 4342]

    [32]

    Wang Y, Shi N, Gu J Q, Feng G L, Zhang L B 2006 Chin. J. Atmos Sci. 30 162(in Chinese)[王 颖、施 能、顾俊强、封国林、张立波 2006 大气科学 30 162]

    [33]

    Shi N 2005 Chin. Phys. 14 844

  • [1]

    Chou J F, 1997 Bull. Chin. Acad. Sci. 5 325 (in Chinese)[丑纪范 1997 中国科学院院刊 5 325]

    [2]

    Feng G L, Dong W J 2004 Chin. Phys. 13 413

    [3]

    Feng G L, Gong Z Q, Dong W J, Li J P 2005 Acta Phys. Sin. 54 5494 (in Chinese)[封国林、龚志强、董文杰、李建平 2005 54 5494]

    [4]

    Feng G L, Dong W J, Gong Z Q, Hou W, Wan S Q, Zhi R 2006 Nonlinear theories and methods on spatial-temporal distribution of the observational data (Beijing: Metrological Press) (in Chinese)[封国林、董文杰、龚志强、侯威、万仕全、支 蓉 2006 观测数据非线性时空分布理论和方法(北京:气象出版社)]

    [5]

    Feng G L, Gao X Q, Dong W J, Li J P 2008 Chaos Soli. Fract. 37 487

    [6]

    Feng G L, Gong Z Q, Zhi R, Zhang D Q 2008 Chin. Phys. B 17 2745

    [7]

    Li J P, Gao L 2006 Chin. J. Atmos. Sci. 30 834 (in Chinese) [李建平、高 丽 2006 大气科学 30 834]

    [8]

    Li J P, Wang X L 2003 Adv. Atmos. Sci. 20 661

    [9]

    Li J P, Chou J F 1997 Acta Meteor. Sin. 11 57

    [10]

    Li J P, Zeng Q C, Chou J F 2000 Sci. China. (E) 30 550 (in Chinese)[李建平、曾庆存、丑纪范 2000中国科学 (E辑) 30 550]

    [11]

    Dai X G, Wang P, Chou J F 2004 Pro. Nat. Sci. 14 73

    [12]

    Gong Z Q, Zhou L, Zhi R, Feng G L 2008 Acta Pyhs. Sin. 57 5351 (in Chinese)[龚志强、周 磊、支 蓉、封国林 2008 57 5351]

    [13]

    Ding Y H, Li Q Q, Li W J, Luo Y, Zhang P Q, Zhang Z Q, Shi X L, Liu Y M, Wang L N 2004 Acta Meteor. Sin. 62 598 (in Chinese) [丁一汇、李清泉、李维京、罗 勇、张培群、张祖强、史学丽、刘一鸣、王兰宁 2004 气象学报 62 598 ]

    [14]

    Liu H B, Zhang D L, Wang B 2006 Climatic Environ. Res. 11 649 (in Chinese)[刘鸿波、张大林、王 斌 2006气候与环境研究 11 649 ]

    [15]

    Shannon C E 1948 Bell Sys. Tech. J. 27 379

    [16]

    Zhang X W 1981 Weather forecasting using information analysis (Beijing: Science Press) (in Chinese) (in Chinese) [张学文 1981 气象预告问题的信息分析 (北京:科学出版社)]

    [17]

    Zhang X W, Ma L 1992 Entropy Meteorology (Beijing: Meteorology Press)(in Chinese)[张学文、马 力 1992 熵气象学(北京:气象出版社)]

    [18]

    Leung L Y, North G R 1990 J. Climate 3 5

    [19]

    Zhang J G, Liu X R 2000 Advan. Water Sci. 11 133 (in Chinese)[张继国、刘新仁 2000 水科学进展 11 133]

    [20]

    Delsole T 2004 J. Atmos. Sci. 61 2425

    [21]

    Zhao W T, Chen X, Zhao P Z 1988 Entropy and cross Science: Information Entropy in Meteorology (Beijing: Meteorology Press) p127—130 (in Chinese)[赵文桐、陈 霞、赵佩章 1988 信息熵于气象熵,熵与交叉科学(北京:气象出版社)第127—130页]

    [22]

    Wang J Y, Fu Z T, Zhang L, Liu S D 2005 Plate. Meteor. 24 38 (in Chinese)[汪景烨、付遵涛、张 霖、刘式达 2005 高原气象 24 38]

    [23]

    Wang Q G, Zhang Z P 2008 Acta Phys. Sin. 57 1976 (in Chinese)[王启光、张增平 2008 57 1976]

    [24]

    Feng G L,Wang Q G, Hou W, Gong Z Q, Zhi R 2009 Acta. Phys. Sin. 58 4 (in Chinese)[封国林、王启光、侯 威、龚志强、支 蓉 2009 58 4]

    [25]

    Hao C Y, WU S H, Li S C 2007 Geo. Graphi. Res. 26 46 (in Chinese)[郝成元、吴绍洪、李双成 2007 地理研究 26 46]

    [26]

    Zhang Z S, Gong Z Q, Zhi R, Feng G L, Hu J G 2011 Chin. Phys. B 20

    [27]

    Li J P, Ding R Q 2008 Chin. J. Atmos Sci. 32 975 (in Chinese)[李建平、丁瑞强 2008 大气科学 32 975]

    [28]

    Ding R Q, Li J P 2009 Acta Meteor. Sin. 67 343 (in Chinese)[丁瑞强、李建平 2009 气象学报 67 343]

    [29]

    Zhi R, Gong Z Q, Feng G L, Zhou L 2010 Acta Meteor. Sin. 24 150

    [30]

    Feng G L, Gong Z Q, Zhi R, Zhang D Q 2008 Chin. Phys. B 17 2745

    [31]

    Gong Z Q, Wang X J, Zhi R, Feng G L 2009 Acta. Phys. Sin. 58 4342(in Chinese)[龚志强、王晓娟、支 蓉、封国林2009 58 4342]

    [32]

    Wang Y, Shi N, Gu J Q, Feng G L, Zhang L B 2006 Chin. J. Atmos Sci. 30 162(in Chinese)[王 颖、施 能、顾俊强、封国林、张立波 2006 大气科学 30 162]

    [33]

    Shi N 2005 Chin. Phys. 14 844

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出版历程
  • 收稿日期:  2010-11-24
  • 修回日期:  2010-12-19
  • 刊出日期:  2011-09-15

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