| The error of numeric weather predicting is always existing, and increasing with the predicting lengths, although the numeric model and the calculating accuracy become better with the time. This gives a big problem for weather forecasting. Now medium range numeric predicting model provide forecast products within 10 day. It is very difficult either in theory or in method that to forecast the weather from 11 to 30 day’s.In order to decrease the error of numeric weather forecast, the developmental mainstream is increasing the resolving power of the model, so as to describe various physical processes more realistically, that is to say, decreasing the error along the frontal path by improving every part of the model. The more to improve weather forecast accuracy, the more the difficulty is. Resent year there are many study aimed at correction and application of numeric predicting products (NPP), and making some improvement, but they all have the same deficiency, that is, they all don’t use the historical meteorological data sufficiently. If meteorological forecast department improve forecast accuracy all according to the mainstream, they would wasted a lot of resource both on manpower and economy. In fact, a great deal of useful information for weather prediction contained in the historical meteorological data, but that information don’t used in numeric predicting. In this study, the purpose is trying to correct the NPP, and to extend the corrected NPP from 11 to 30 days, based on present NPP and historical meteorological data.First, the height field, temperature field, wind field, vertical velocity field, and Specific humidity field of the T213 L31 NPP in range of east Asia on standard pressure level have been evaluated, by using correlation coefficient, climate anomaly correlation coefficient, 24h variation correlation coefficient and root-mean-square error (RMSE). The results are as follows:1) For the height field forecast, the higher credible (that is 24h variation correlation coefficient exceed 0.4, and climate anomaly correlation coefficient exceed 0.6) predicting lengths can reach 6-7 day at middle and upper layer of troposphere, and can reach 5 day at middle and lower layer of troposphere. The predicting lengths that 24h variation correlation coefficient can pass the significance test at the level of=0.001 is 10 days;2) For the temperature field forecast, the higher credible predicting lengths can reach 4 day at middle and upper layer of troposphere, and can reach 5 day at middle and lower layer of troposphere. The predicting lengths that 24h variation correlation coefficient can pass the significance test at the level of=0.001 is 9 days;3) For the wind field forecast, the higher credible predicting lengths can reach 5 day at upper layer of troposphere, can reach 4 day at middle layer of troposphere, and can reach 3 day at middle and lower layer of troposphere. The predicting lengths that can 24h variation correlation coefficient pass the significance test at the level of=0.001 is 8 days;4) For the vertical velocity field forecast, the higher credible predicting lengths can only reach 1-2 day at troposphere. The predicting lengths that 24h variation correlation coefficient can pass the significance test at the level of=0.001 is 5 days;5) For the Specific humidity field forecast, the higher credible predicting lengths can reach 2 day at middle layer of troposphere, and can reach 3-4 day at lower layer of troposphere. The predicting lengths that 24h variation correlation coefficient can pass the significance test at the level of=0.001 is 6 days;To sum up, T213 L31 NPP forecast effect, height field forecast is the best, temperature field forecast is second, wind field and Specific humidity forecast is the third, vertical velocity field forecast is the worst, the higher credible predicting lengths is 5-7day,4-5day, 3-5day,2-4day, and 1-2day respectively.Second, by theoretic analyzing, the actual change of atmosphere can be dividing into three parts:model change, similarity case change and random change. The contribution ratio can be decided through statistics method of regression. According to the viewpoint mentioned above, a scheme to correct T213 L31 NPP has been put forward by using the historical meteorological data. The correcting scheme can be divided into two part:the initial correction and second correction, again, each part can also be divided into three step:to chose basic similarity case, to chose the best similarity case for each meteorological element field and to establish the correction equation. The calculating results show that to correct T213 L31 NPP by using the historical meteorological data of NCEP, the best number of similarity case are 50. The correcting scheme divided into two steps can better absorb information from similarity case.24 hour variation correction equation for the height field, temperature field, wind field, vertical velocity field, and Specific humidity field of T213 L31 NPP in range of east Asia at standard pressure level 100-1000hPa have been established by using T213 L31 NPP from 2003 to 2006 and NCEP data from 1948 to 2005. The return correction for 2003-2006 and try correction for 2007-2008 about height field, temperature field, wind field, vertical velocity field, and Specific humidity field of the T213 L31 NPP in range of east Asia on standard pressure level have been evaluated, by using correlation coefficient, climate anomaly correlation coefficient,24 hours variation correlation coefficient and root-mean-square error(RMSE). The result as follows:1) Evaluated by correlation coefficient, the correction effect of height field, temperature field, wind field and Specific humidity field are effective, and the correction effect become more obviously with forecast lengths. The lower the layer, the more effective the correction effect of height fields and wind field. Vertical velocity correction effect is decrease within 72 hour. Over 96 hours and above 700hPa, the correlation coefficient increase, and the correction effect become more obviously with the rise of pressure layer or the increase of forecast lengths.2) Evaluated by climate anomaly correlation coefficient, the correction effect of height field and temperature field are mainly positive during 24-96 hours and mainly negative during 120-240 hours. The correction effects of wind field are mainly positive during 24-48 and 216-240 hour and mainly negative during 72-192 hours. The climate anomaly correlation coefficient of vertical velocity field is deceased after correction. For Specific humidity field, the correction effect are the most obviously, the climate anomaly correlation coefficient are all increase below 500hPa layer during all forecast lengths, also increase above 500 hPa during 72-192 hours.3) Evaluated by 24 hours variation correlation coefficient, the correct effect of height field, temperature field, wind field and Specific humidity field are positive during all forecast lengths, especially during 96-192 hours. For vertical velocity field, it increases during 24-72 hours.4) Evaluated by RMSE, the correction effect of height field, temperature field, wind field, vertical velocity field and Specific humidity field are all positive and obviously, and become more obviously with forecast lengths.5) Correction effect is different in different region. For height field, Correction effect is obviously at high latitude, and not so obviously at low latitude. For temperature field Correction effect obviously at low latitude. For wind field, Correction effect is obviously around Qinghai-Tibetan plateau during 24-96 hours, and is obviously at high latitude during 120-240. For vertical velocity field, Correction effect is obviously at south China during 24-96 hour. For Specific humidity field, Correction effect is obviously at east China and west Pacific Ocean. 6) Tried correction effect and return correction effect is the same result, show that the correction scheme is stable and dependable.The end, a method to forecast the extended-rang (11-30 days) weather was putting forward by combining period extending with similarity. And a tried forecast for extended rang have been made by using T213 L31 NPP during 2003-2008 and NCEP data since 1948. Extended rang forecast of the height field, temperature field, wind field, vertical velocity field, and Specific humidity field have been evaluated, by using correlation coefficient, climate anomaly correlation coefficient, 24 hours variation correlation coefficient and root-mean-square error(RMSE). The results are as follows:1) Evaluated by correlation coefficient, extended rang forecast of the height field, temperature field, U-wind field, vertical velocity field, and Specific humidity field are credible (all passed the significance test at the level of=0.001), that of V-wind field and vertical velocity field are not so credible as height field (merely several layer of vertical velocity field can pass the significance test at the level of=0.001). The correlation coefficient of height field and U-wind field are obviously at high layer and are inapparent at low layer; The correlation coefficient of temperature field and Specific humidity field are obviously at lower layer and are in apparent at high layer; The correlation coefficient of U-wind field and vertical velocity field are obviously at high and low layer, and are inapparent at middle layer.2) Climate anomaly correlation coefficient of height fieldit for the extended range forecast can pass the significance test at the level of=0.001 on most layer and forecast lengths.3) All of 24 hours variation correlation coefficient can not pass the significance test at the level of=0.05, but they are all positive.4) Evaluated by root mean square error, the extended rang forecast error of height field, temperature field, wind field, vertical velocity field and Specific humidity field, are slowly increased with the forecast lengths.5) The extended range forecast of height field, temperature field, wind field, vertical velocity field and Specific humidity field was explained by using step by step similar filter. The results are as follows:TS score of the forecast for 11-30 days 24 hours temperature variation is above 73% in the region around Bohai Sea, and individual station can reach to 80%. |
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