The Correlation Characteristics Of Global Meteorological Element Fields And Its Application Research On Precipitation Forecasting Of Raining Season

Based on temperature and height field correlation matrixes constructed by NCEP/NCAR and ERA40 reanalysis data, we study the correlation characteristics of global meteorological elements. Main conclusions are as follows:(1) By comparison of temperature and random correlation matrixes, we find that noise and true correlations both exist in global temperature field, and the 99% confidence test is used in order to filter correlation'noise'. We construct correlation matrixes based on moving average of temperature series and find that 365-730d maybe a turning of time scale of temperature field. Global average correlation coefficient CTglobal increase along with time scale, but the rate is slower and slower. The positive correlation center (162.5°E-102.5°W,7.5°N-12.5°S) (AreaⅠ) and the negative correlation center (157.5°E-147.5°W,27.5°-47.5°N) (AreaⅡ) are the two areas we concern on, there is strong negative correlation between them. With the help of a 10a slipping window, we find that CTglobal had an abrupt change between 1981-1987a, so did AreaⅠandⅡ. And the position of AreaⅡchange with time. We defined a new index named Moving North Pacific Index (MNPI) based on the value of the strongest negative correlation of Area II.(2) We construct matrixes in case of considering time delay, the results show that: with the delay time increasing, CTglobal weakened. However, different delay time corresponding to different rule, take 1-30d for instance, generally based on decreasing speed can be divided into three sections:1-7d,8-20d and 21-30d. The spatial distribution pattern of temperature coefficient did not significantly changed with the increasing delay time, but the overall distribution of change in value was the strip along the latitudinal, and most of the Asian continent and the eastern equatorial Pacific are reverse to the trend of other areas in the same latitude.(Area I and II show more complex evolution rules than the average state.(3) We discussion the effection of warming/cooling trends of temperature and extreme temperature events on the temperature field correlation matrixes, the results show that:based on the NCEP/NCAR reanalysis data, by removing the warming/ cooling trends, regions that originally show cooling trends have enhanced regional correlation, and regions that originally show warming trends have weakened regional correlation, but by the ERA40 reanalysis data, there is no such correspondence. Overall, the conclusions of the two sets of data are shown that warming/cooling trend of temperature can not significantly affected the spatial distribution of the correlation of global temperature field. Different alternative methods of the extreme temperature make quite different reasons after 1990s, and it may be associated with the great change of correlation distribution of the southern and northern hemisphere before and after 1990s.(4) Aim at model prediction error of summer precipitation of Yangtze River region, we use the MNPI we defined and the NPI defined Trenberth et al. to find the 4 similar years of precipitation forecast error, and make the arithmetic average of them as the model prediction error. The results showed that MNPI perform better than NPI. On this basis, combined with the Euclidean distance weighted average method can further improve the forecast skill. The results of 2003-2009 summer precipitation independent sample return prediction show that MNPI perform good on prediction of summer precipitation of Yangtze River region. MNPI shows interdecadal variations, consistent with the evolution characteristics of North Pacific sea surface temperature. Finally, we give the forecast of summer precipitation in China in 2009 with MNPI, and reached a very high forecast skill.(5) Correlation matrixes are constructed with NCEP/NCAR global height field data and surface pressure data, furthermore, the characteristics of these two matrixes are analyzed. Research results shows that correlations at all levels of height field are better in middle-low latitudes and descend to the high latitudes, presenting characteristics of quasi-zonal distribution. In the vertical direction, correlations of low levels are weaker and become more and more stronger with the increase of height. There is always a negative correlation center in the north pacific at all levels of height, reflecting a certain degree of particularity. Results of delayed correlation shows that decreased with the increasing of delay time, the tendency became gently when the delay tine reach 15d and there is an obvious turning point when the delay tine reach 60d. From the angle of space, the decay rate of correlation increase with latitude and the decrease of height. Changes over time of CT global in three height fields and surface pressure are almost the same, two abrupt changes occurred during 1978-1982 and 1996-1998.(6) Further research on the spatial distribution of the North Pacific negative correlation center showes that:the strong correlation centers associated with the North Pacific negative correlation center consistent from low-to-high levels, mainly in three regions:the central equatorial Pacific (center A) and the Bering Strait (center B), and southeastern North American continent (center C). The cumulative effect of correlation among North Pacific and the other three centers are as follows:we can get clear negative centers in the North Pacific region on all levels. The negative center moves from low to high by the following rules:first eastward, then westward; first moved south, moving north after; and changes have occurred both on the 500hpa height field. On surface pressure field, the correlation between the center C and the North Pacific region is the weakest, on the other levers, the most significant center correlated to the North Pacific region is the center A.