全球温度场信息熵的时空特征分析  

Spatiotemporal analysis of information entropy of the global temperature

作　　者：冯爱霞[1] 龚志强[2] 黄琰[3] 王启光[1,2] 

机构地区：[1]兰州大学大气科学学院,兰州730000 [2]国家气候中心,中国气象局气候研究开放实验室,北京100081 [3]中国气象科学研究院,气候系统研究所,北京100081

出　　处：《物理学报》2011年第9期833-841,共9页Acta Physica Sinica

基　　金：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);国家科技支撑计划(批准号:2007BAC29B01)资助的课题~~

摘　　要：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,总体表现为ME在夏季最小,冬季最大,春秋季居中的特点.3)ME的年代际变化特征显著,不同月份、不同层次的ME值均具有5—10年的准周期振荡特征.温度场信息熵的时空变化特征及其与气温较差的联系表明,信息熵在气象领域具有较好的应用前景,是分析气象要素不确定性的一种有效方法和工具.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.

关 键 词：信息熵 温度场 可预测性 

分 类 号：P423[天文地球—大气科学及气象学]