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中国月平均温度的气候噪声和潜在可预报性
引用本文:乐群,曹俊武,林振山,马开玉.中国月平均温度的气候噪声和潜在可预报性[J].气象学报,1999,57(5):604-612.
作者姓名:乐群  曹俊武  林振山  马开玉
作者单位:南京大学大气科学系!南京,210093
基金项目:国家教委跨世纪优秀人才基金
摘    要:利用中国74个测站1960~1991年日平均温度研究了中国月平均温度的气候噪声和潜在可预报性。气候噪声是在Yamamoto等人的思想基础上设计的方法估计的,而潜在可预报性则是用月平均温度的年际变化与自然变化(气候噪声)之比表示的。一般情况下中国月平均温度的气候噪声随纬度和高度增加而增加,并随季节变化而变化。来自西伯利亚和蒙古的变性大陆干冷气团对气候噪声有很大的影响,一般而言,海洋对气候噪声起着调节和减弱作用(除了热带海洋在春秋过渡季节外)。月平均温度的潜在可预报性有较大的季节和区域差异。但总的来说中国月平均温度在α=0.10的统计显著性水平上是潜在可预报的。这些结果表明由于气候噪声和潜在可预报性有季节和区域的差异,所以不能要求用一个气候模式在任何时候对每一地区都得到满意的结果。要对各月的气候进行预报,需根据不同月份至少不同季节建立区域气候模式可能更有发展前景。

关 键 词:气候噪声  潜在可预报性  月平均温度
收稿时间:1997/7/15 0:00:00
修稿时间:1998/1/16 0:00:00

CLIMATIC NOISE AND POTENTIAL PREDICTABILITY OF MONTHLY MEAN TEMPERATURE OVER CHINA
Yue Qun,Cao Junwu,Lin Zhenshan and Ma Kaiyu.CLIMATIC NOISE AND POTENTIAL PREDICTABILITY OF MONTHLY MEAN TEMPERATURE OVER CHINA[J].Acta Meteorologica Sinica,1999,57(5):604-612.
Authors:Yue Qun  Cao Junwu  Lin Zhenshan and Ma Kaiyu
Institution:Department of Atmospheric Sciences. Nanjing University. Nanjing 210093
Abstract:Climatic noise and potential predictability of monthly mean temperature have been studied based on the data at 74 stations selected over China from 1960 t0 1991. The method ofestimating climatic noise is based on the idea of Yamamoto et al and the potential predictability is expressed by the ratio of the estimated interannual variation to the estimated naturalvariation (or climatic noise). Generally the climatic noise of monthly mean temperature increases with latitude and altitude, varies with seasons. The continental air from the Siberiaand Mongolia plays a significant role and the ocean acts as adjustment and reduction in theclimatic noise except for the tropical ocean in transitional season. The potential predictabilityis diversified from month to month and one station to another, but generally the monthlymean temperature over China is potentially predictable at statistical significance level 0. 10.The results suggest that we could not ask a climate model to predict the climate with satisfactory results worldwide in all season and that the regional model could be a hopeful way topredict the climate.
Keywords:Climatic noise  Potential predictability  Monthly mean temperature
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