Acta Meteorologica Sinica

, Volume 27, Issue 5, pp 725–741 | Cite as

Synoptic verification of medium-extended-range forecasts of the northwest pacific subtropical high and South Asian high based on multi-center TIGGE data

  • Ruoyun Niu (牛若芸)Email author
  • Panmao Zhai (翟盘茂)


Synoptic verification of medium-extended-range forecasts of the Northwest Pacific subtropical high (NWPSH) and South Asian high (SAH) is performed for the summers of 2010–2012 using TIGGE data from four operational centers at the CMA, ECMWF, JMA, and NCEP. The overall activities of the NWPSH and SAH are examined along with their local characteristics such as the spatial coverage of each high in the East Asian key area (10°–40°N, 105°–130°E), the mean position of the ridge of each high over 110°–122.5°E, the westward extent of the NWPSH ridge, and the eastward extent of the SAH ridge. Focus on the NWPSH and SAH is justified because these two systems have pronounced influences on the summertime persistent heavy rainfall in China. Although the overall activities of both highs are reproduced reasonably well in the TIGGE data, their spatial coverages are reduced in the East Asian key area and both of them are weaker compared with observations. On average, their ridges shift more northward relative to observations. The NWPSH ridge is less westward while the SAH ridge is generally more eastward early in the forecast but too westward later in the forecast. The JMA ensemble prediction system (EPS) produces the best mediumrange (1–10 days) forecasts of the NWPSH based on these metrics, while the ECMWF EPS produces the best medium-range forecasts of the SAH and the most reliable extended-range (11–15 days) forecasts of both highs. Forecasts of the spatial coverage of both highs in the East Asian key area and the mean positions of the ridges are generally valid out to lead times of 7–12 days. By contrast, forecasts of the longitudinal extent of the ridges are typically only valid to lead times of 5–7 days. All the four operational centers’ models produce excellent forecasts of the mean zonal position of the SAH ridge. The ensemble mean forecast is more reliable than the control forecast over the areas where the NWPSH (20°–30°N, 135°–165°E) and SAH (23°–30°N, 70°–100°E) are most active. Forecasts of both highs have advantages and disadvantages in the peripheral areas away from their respective center of high activity.

Key words

TIGGE data Northwest Pacific subtropical high South Asian high medium-extended-range forecast synoptic verification 


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  1. Candille, G., C. Côté, P. L. Houtekamer, et al., 2007: VVerification of an ensemble prediction system against observations. Mon. Wea. Rev., 135, 2688–2699.CrossRefGoogle Scholar
  2. Froude, L. S. R., 2010: TIGGE: Comparison of the prediction of Northern Hemisphere extratropical cyclones by different ensemble prediction systems. Wea. Forecasting, 25, 819–836.CrossRefGoogle Scholar
  3. —, 2011: TIGGE: Comparison of the prediction of Southern Hemisphere extratropical cyclones by different ensemble prediction systems. Wea. Forecasting, 26, 388–398.CrossRefGoogle Scholar
  4. Huang Jiayou, 1990: Application of Statistic to Weather Forecast. China Meteorological Press, 298 pp. (in Chinese)Google Scholar
  5. Ji Yongming, Chen Jing, Jiao Meiyan, et al., 2011: The preliminary experiment of GRAPES-MESO ensemble prediction based on TIGGE data. Meteor. Mon., 37(4), 392–402. (in Chinese)Google Scholar
  6. Li Yong, Zhou Bing, and Jin Ronghua, 2010: The characteristics of low frequency circulation during the heavy rainfall season over the Huaihe River basin in 2007. Acta Meteor. Sinica, 68(5), 740–747. (in Chinese)Google Scholar
  7. Lin Chunze, Zhi Xiefei, Han Yan, et al., 2009: Multimodel superensemble forecasts of the surface temperature using the TIGGE data. J. Appl. Meteor. Sci., 20(6), 706–712. (in Chinese)Google Scholar
  8. Luo Jiali, Tian Wentao, Zhang Peiqun, et al., 2012: Analysis of the anomalous signals around the tropopause and in the stratosphere before the Meiyu onset. Acta Meteor. Sinica, 70(4), 655–669. (in Chinese)Google Scholar
  9. Ma Yin, Chen Wen, and Wang Lin, 2011: A comparative study of the interannual variation of summer rainfall anomolies between the Huaihe Meiyu season and the Jiangnan Meiyu season and their climate background. Acta Meteor. Sinica, 69(2), 334–343. (in Chinese)Google Scholar
  10. Mccollor, D., and R. Stull, 2009: Evaluation of probabilistic medium-range temperature forecasts from the North American ensemble forecast system. Wea. Forecasting, 24, 3–17.CrossRefGoogle Scholar
  11. Niu Ruoyun, Su Aifang, Ma Jie, et al., 2011: The difference of the atmospheric circulation features and dynamical diagnosis about the typical Meiyu patterns of southern flood (drought) and northern drought (flood). Chinese J. Atmos. Sci., 35(1), 95–104. (in Chinese)Google Scholar
  12. —, Zhang Zhigang, and Jin Ronghua, 2012: The atmospheric circulation features of two persistent heavy rainfalls over southern China in the summer of 2010. J. Appl. Meteor. Sci., 23(4), 385–394. (in Chinese)Google Scholar
  13. Sun, B., and H. J. Wang, 2012: Larger variability, better predictability? Int. J. Climatol., doi: 10.1002/joc.3582.Google Scholar
  14. Wang Donghai, Xia Rudi, and Liu Ying, 2011: A preliminary study of the flood causing rainstorm during the first rainy season in South China in 2008. Acta Meteor. Sinica, 69(1), 137–148. (in Chinese)Google Scholar
  15. Wedam, G. B., L. A. Mcmurdie, and C. F. Mass, 2009: Comparison of model forecast skill of sea level pressure along the east and west coasts of the United States. Wea. Forecasting, 24, 843–854.CrossRefGoogle Scholar
  16. Zheng Fei, Zhu Jiang, and Wang Hui, 2007: The verifications for ENSO ensemble prediction system. Climatic and Environ. Res., 12(5), 587–594. (in Chinese)Google Scholar
  17. Zhi Xiefei, Qi Haixia, Bai Yongqing, et al., 2012: A comparison of three kinds of multimodel ensemble forecast techniques based on the TIGGE data. Acta Meteor. Sinica, 26(1), 41–51.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ruoyun Niu (牛若芸)
    • 1
    Email author
  • Panmao Zhai (翟盘茂)
    • 2
  1. 1.National Meteorological Center, China Meteorological AdministrationBeijingChina
  2. 2.Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijingChina

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