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Estimate Of Potential Predictability Of Monthly And Seasonal Mean Temperature And Precipitation In China

Posted on:2009-10-21Degree:MasterType:Thesis
Country:ChinaCandidate:X C ZhaoFull Text:PDF
GTID:2120360242996002Subject:Science of meteorology
Abstract/Summary:PDF Full Text Request
Base on the observational data of daily precipitation and temperature in the period of 1955~2004,the potential predictability of seasonal mean temperature(SMT),monthly mean temperature(MMT),seasonal precipitation(SP) and monthly precipitation(MP)have been analyzed systemically.Then,the upper limits of forecast accuracy have been estimated.The researches about SMT and MMT indicate that with latitude and altitude increasing,the increase of the interannual mean square deviation of SMT or MMT is larger in winter than in summer,in north than in south or in the inland areas than in the coastal areas.The interannual mean square deviation of SMT or MMT varies markedly with seasons or months.It is greater in winter and smaller in summer.The interannual mean square deviation of MMT is larger than that of SMT in the same season.Since the mean square deviation of climatic noise of SMT or MMT has reference to latitude,ocean,relief,the continental air, subtropical high,synoptic system and so on,it varies markedly with zones, seasons or months.Generally the mean square deviation of climatic noise of SMT or MMT,which is greater in winter and is smaller in summer,increases with latitude.The mean square deviation of climatic noise of MMT is larger than that of SMT in the same season.The difference between them is larger in north than in south.The signal-to-noise of SMT or MMT is over 1 in a majority of China,so there are predictable climate signals over china.Since the signal-to-noise of SMT or MMT has reference to latitude,ocean,relief,synoptic system and so on,it varies markedly with zones,seasons or months.The signal-to-noise is the greatest in winter in a majority of China.Generally the signal-to-noise of MMT is lower than that of SMT.Potential predictability of SMT or MMT varies markedly with stations,seasons or months,but it is good in a majority of China.Except for February,the potential predictability of MMT is lower than that of SMT.Although the upper limit of forecast accuracy of SMT or MMT varies markedly with stations,seasons or months,as a whole,it is higher in winter and in summer and varies markedly in other seasons or months.Except for some stations in February, the upper limit of forecast accuracy of MMT is lower than that of SMT.The researches about SP and MP indicate that potential predictability of precipitation implied by low frequency white noise extension and by the analysis of variance under the assumption dependence is well,but potential predictability of precipitation implied by the analysis of variance under the assumption independence is larger.The spatial and temporal distributions of the interannual mean square deviation and the mean square deviation of climatic noise of SP or MP accord with the spatial and temporal distributions of SP or MP,which decrease gradually from south to north and from the coastal areas to the inland areas and vary markedly with seasons or months.Although the signal-to-noise of SP or MP varies markedly with stations,seasons or months,it is over 1 in a majority of China.There are predictable climate signals over china,but the variance due to climatic signal is smaller than the variance due to climatic noise in a majority of China.Although potential predictability of SP or MP varies markedly with stations,seasons or months,as a whole,it is higher in winter and lower in summer.The upper limits of forecast accuracy of SP or MP vary markedly with stations,seasons or months.With the absolute error smaller than 0.68 times of standard deviation as the criterion of correct prediction,the upper limits of forecast accuracy of SP or MP would be from 50%to 60%in a majority of China.It is obvious that the upper limits of forecast accuracy of SP or MP are low in a majority of China.
Keywords/Search Tags:seasonal/monthly mean temperature, seasonal/monthly precipitation, potential predictability
PDF Full Text Request
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