By considering distance error and direction error, Tropical Cyclone(TC) track forecasts with abnormal forecast error(AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related t...By considering distance error and direction error, Tropical Cyclone(TC) track forecasts with abnormal forecast error(AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related to AFE cases are investigated. There are 7 factors which are closely related to AFE cases. The most common one is Landfall or Passing through big island(LP) which appears 21 times among all 55 AFE cases. But LP often coexists with other factors to cause AFE cases. The second in the list is Coexistence with other TC or cloud cluster(CO) which affects more than one third of all AFE cases. Besides those 7 factors, fault of TCtracker also results in some AFE cases. There are no simple indicators for forecasters to anticipate a possible AFE case in advance. It seems that forecasters still have to anticipate AFE cases by their experiences and with synthetic analysis on all available data. Some possible ways to improve AFE cases are discussed and proposed to forecasters. That includes relying on products from ensemble prediction system or guidance from other models, simple translation process and manual analysis of TC track by forecasters under some circumstances.展开更多
This paper investigates the possible sources of errors associated with tropical cyclone （TC） tracks forecasted using the Global/Regional Assimilation and Prediction System （GRAPES）. The GRAPES forecasts were made ...This paper investigates the possible sources of errors associated with tropical cyclone （TC） tracks forecasted using the Global/Regional Assimilation and Prediction System （GRAPES）. The GRAPES forecasts were made for 16 landfaIling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions （＂initials＂, hereafter）, which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.展开更多
Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determin...Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determined that the short-time forecast effect was better than the original objective mode. By selecting four types of integration schemes after multiple mode path integration for those four objective modes, the forecast effect of the multi-mode path integration is better, on average, than any single model. Moreover, multi-mode ensemble forecasting has obvious advantages during the initial 36 h.展开更多
This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model ca...This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.展开更多
文摘By considering distance error and direction error, Tropical Cyclone(TC) track forecasts with abnormal forecast error(AFE) at lead time of 48 h by ECMWF-IFS are selected out from 2010 to 2013. Factors closely related to AFE cases are investigated. There are 7 factors which are closely related to AFE cases. The most common one is Landfall or Passing through big island(LP) which appears 21 times among all 55 AFE cases. But LP often coexists with other factors to cause AFE cases. The second in the list is Coexistence with other TC or cloud cluster(CO) which affects more than one third of all AFE cases. Besides those 7 factors, fault of TCtracker also results in some AFE cases. There are no simple indicators for forecasters to anticipate a possible AFE case in advance. It seems that forecasters still have to anticipate AFE cases by their experiences and with synthetic analysis on all available data. Some possible ways to improve AFE cases are discussed and proposed to forecasters. That includes relying on products from ensemble prediction system or guidance from other models, simple translation process and manual analysis of TC track by forecasters under some circumstances.
基金supported by the National Science and Technology Support Program(Grant.No.2012BAC22B03)the National Natural Science Foundation of China(Grant No.41475100)+1 种基金the Youth Innovation Promotion Association of Chinese Academy of Sciencesthe Japan Society for the Promotion of Science KAKENHI(Grant.No.26282111)
文摘This paper investigates the possible sources of errors associated with tropical cyclone （TC） tracks forecasted using the Global/Regional Assimilation and Prediction System （GRAPES）. The GRAPES forecasts were made for 16 landfaIling TCs in the western North Pacific basin during the 2008 and 2009 seasons, with a forecast length of 72 hours, and using the default initial conditions （＂initials＂, hereafter）, which are from the NCEP-FNL dataset, as well as ECMWF initials. The forecasts are compared with ECMWF forecasts. The results show that in most TCs, the GRAPES forecasts are improved when using the ECMWF initials compared with the default initials. Compared with the ECMWF initials, the default initials produce lower intensity TCs and a lower intensity subtropical high, but a higher intensity South Asia high and monsoon trough, as well as a higher temperature but lower specific humidity at the TC center. Replacement of the geopotential height and wind fields with the ECMWF initials in and around the TC center at the initial time was found to be the most efficient way to improve the forecasts. In addition, TCs that showed the greatest improvement in forecast accuracy usually had the largest initial uncertainties in TC intensity and were usually in the intensifying phase. The results demonstrate the importance of the initial intensity for TC track forecasts made using GRAPES, and indicate the model is better in describing the intensifying phase than the decaying phase of TCs. Finally, the limit of the improvement indicates that the model error associated with GRAPES forecasts may be the main cause of poor forecasts of landfalling TCs. Thus, further examinations of the model errors are required.
基金National Natural Science Foundation of China(41475060,41275067,41405060)
文摘Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determined that the short-time forecast effect was better than the original objective mode. By selecting four types of integration schemes after multiple mode path integration for those four objective modes, the forecast effect of the multi-mode path integration is better, on average, than any single model. Moreover, multi-mode ensemble forecasting has obvious advantages during the initial 36 h.
基金the project"A study on improving forecast skill using a su-percomputer"of Meteorological Research Institute,KMA,2001.
文摘This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.
