Skip to main content
Log in

Seasonal differences of model predictability and the impact of SST in the Pacific

  • Published:
Advances in Atmospheric Sciences Aims and scope Submit manuscript

Abstract

Both seasonal potential predictability and the impact of SST in the Pacific on the forecast skill over China are investigated by using a 9-level global atmospheric general circulation model developed at the Institute of Atmospheric Physics under the Chinese Academy of Sciences (IAP9L-AGCM). For each year during 1970 to 1999, the ensemble consists of seven integrations started from consecutive observational daily atmospheric fields and forced by observational monthly SST. For boreal winter, spring and summer, the variance ratios of the SST-forced variability to the total variability and the differences in the spatial correlation coefficients of seasonal mean fields in special years versus normal years are computed respectively. It follows that there are slightly inter-seasonal differences in the model potential predictability in the Tropics. At northern middle and high latitudes, prediction skill is generally low in spring and relatively high either in summer for surface air temperature and middle and upper tropospheric geopotential height or in winter for wind and precipitation. In general, prediction skill rises notably in western China, especially in northwestern China, when SST anomalies (SSTA) in the Niño-3 region are significant. Moreover, particular attention should be paid to the SSTA in the North Pacific (NP) if one aims to predict summer climate over the eastern part of China, i.e., northeastern China, North China and southeastern China.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ajaya Mohan, R. S. and B. N. Goswami, 2003: Potential predictability of the Asian summer monsoon on monthly and seasonal time scales.Meteor. Atmos. Phys., doi: 10.1007/s00703-002-0576-4.

  • Atlas, R., N. Wolfson, and J. Terry, 1993: The effect of SST and soil moisture anomalies on GLA model simulations of the 1988 U.S. summer drought.J. Climate,6, 2034–2048.

    Article  Google Scholar 

  • Bi Xunqiang, 1993: IAP 9-level atmospheric general circulation model and climate simulation. Ph. D. dissertation, Institute of Atmospheric Physics, Chinese Academy of Sciences, 210pp. (in Chinese)

  • Branković, Č., and T. N. Palmer, 1997: Atmospheric seasonal predictability and estimates of ensemble size.Mon. Wea. Rev.,125, 859–874.

    Article  Google Scholar 

  • Branković, Č., T. N. Palmer, and L. Ferranti, 1994: Predictability of seasonal atmospheric variations.J. Climate,7, 217–237.

    Article  Google Scholar 

  • Charney, J. G., and J. Shukla, 1981: Predictability of monsoons.Monsoon Dynamics. J. Lighthill and R. Pearce, Eds., Cambridge University Press, 735pp.

  • Chen Lieting, and Wu Renguang, 1998: The joint effects of SST anomalies over different Pacific regions on summer rainbelt patterns in eastern China.Chinese J. Atmos. Sci.,22, 718–726. (in Chinese)

    Google Scholar 

  • Chen, W. Y., and H. M. van den Dool, 1997: Atmospheric predictability of seasonal, annual, and decadal climate means and the role of the ENSO cycle: A model study.J. Climate,10, 1236–1254.

    Article  Google Scholar 

  • Gao Xuejie, and Zhao Zongci, 2000: The experiment of seasonal prediction in China by OSU/NCC GCM for flood season.Quarterly Journal of Applied Meteorology,11, 180–188. (in Chinese)

    Google Scholar 

  • Kang, I. S., and Coauthors, 2002: Intercomparison of the climatological variations of Asian summer monsoon precipitation simulated by 10 GCMs.Climate Dyn.,19, 383–395.

    Article  Google Scholar 

  • Kumar, A., 2003: Variability, and predictability of 200-mb seasonal mean heights during summer and winter.J. Geophys. Res.,108, 4169, doi: 10.1029/2002JD002728.

    Article  Google Scholar 

  • Kusunoki, S., M. Sugi, A. Kitoh, C. Kobayashi, and K. Takano, 2001: Atmospheric seasonal predictability experiments by the JMA AGCM.J. Meteor. Soc. Japan,79, 1183–1206.

    Article  Google Scholar 

  • Lang Xianmei, Wang Huijun, and Jiang Dabang, 2003a: Study on the impact of atmospheric initial anomalies on extraseasonal seasonal prediction.Chinese J. Atmos. Sci.,28, 231–240. (in Chinese)

    Google Scholar 

  • Lang Xianmei, Wang Huijun, and Jiang Dabang, 2003b: Extraseasonal ensemble numerical predictions of winter climate over China.Chinese Sciences Bulletin,48, 2121–2125.

    Article  Google Scholar 

  • Lang Xianmei, Wang Huijun, and Jiang Dabang, 2004a: Extraseasonal short-term predictions of summer climate with IAP9L-AGCM.Chinese Journal of Geophysics,47, 22–28.

    Google Scholar 

  • Lang Xianmei, Wang Huijun, Zhou Guangqing, and Jiang Dabang, 2004b: Prediction of summer climate over China for 2002 with IAP9L-AGCM and its performance verification.Journal of Nanjing Institute of Meteorology,27, 101–107. (in Chinese)

    Google Scholar 

  • Lau, K. -M., J. H. Kim, and Y. Sud, 1996: Intercomparison of hydrologie processes in AMIP GCMs.Bull. Amer. Meteor. Soc.,77, 2209–2227.

    Article  Google Scholar 

  • Li Yuefeng, and Ding Yihui, 2002: Sea surface temperature, land surface temperature and the summer rainfall anomalies over eastern China.Climatic and Environmental Research,7, 87–101. (in Chinese)

    Google Scholar 

  • Liang Xinzhong, 1996: Description of a nine-level grid point atmospheric general circulation model.Adv. Atmos. Sci.,13, 269–298.

    Article  Google Scholar 

  • Liang, Xinzhong, W. C. Wang, and A. N. Samel, 2001: Biases in AMIP model simulations of the East China monsoon system.Climate Dyn.,17, 291–304.

    Article  Google Scholar 

  • Liu Yongqiang, and Ding Yihui, 1995: Reappraisal of the influence of ENSO events on seasonal precipitation and temperature in China.Chinese J. Atmos. Sci.,19, 200–208. (in Chinese)

    Google Scholar 

  • Oglesby, R. J., 1991: Springtime soil moisture, natural climatic variability, and North American drought as simulated by the NCAR Community Climate Model.J. Climate,4, 890–897.

    Article  Google Scholar 

  • Rowell, D. P., 1998: Assessing potential seasonal predictability with an ensemble of multidecadal GCM simulations.J. Climate,11, 109–120.

    Article  Google Scholar 

  • Rowell, D. P., C. K. Folland, K. Maskell, and M. N. Ward, 1995: Variability of summer rainfall over tropical North Africa (1906–92): Observations and modeling.Quart J. Roy. Meteor. Soc.,121, 669–704.

    Google Scholar 

  • Shukla, J., 1981: Dynamical predictability of monthly means.J. Atmos. Sci.,38, 2547–2572.

    Article  Google Scholar 

  • Shukla, J., and Coauthors, 2000: Dynamical seasonal prediction.Bull. Amer. Meteor. Soc.,81, 2593–2606.

    Article  Google Scholar 

  • Sugi, M., R. Kawamura and N. Sato, 1997: A study of SST-forced variability and potential predictability of seasonal mean fields using the JMA global model.J. Meteor. Soc. Japan,75, 717–736.

    Google Scholar 

  • US National Research Council, 1994:GOALS (Global Ocean-Atmosphere-Land System) for Predicting Seasonal-to-International Climate. National Academy Press, Washington DC, 103pp.

    Google Scholar 

  • Wang Huijun, 1997: A preliminary study on the uncertainty of seasonal prediction.Climatic and Environmental Research,2, 333–338. (in Chinese)

    Google Scholar 

  • Wang Huijun, Lang Xianmei, Zhou Guangqing, and Kang Dujuan, 2003: A preliminary report of the model prediction on the forthcoming winter and spring dust climate over China.Chinese J. Atmos. Sci.,27, 136–140. (in Chinese)

    Google Scholar 

  • Yan Huasheng, Wang Huijun, Yan Xiaodong, Cao Jie, and Han Jinping, 2003: Analysis of the impact of Pacific SST variations on precipitation predictability in China.Plateau Meteorology,22, 155–161. (in Chinese)

    Google Scholar 

  • Yang Xiuqiong, J. L. Anderson, and W. F. Stren, 1998: Reproducible forced modes in AGCM ensemble integrations and potential predictability of atmospheric seasonal variations in the extratropics.J. Climate,11, 2942–2959.

    Article  Google Scholar 

  • Zeng Qingcun, Yuan Chongguang, Zhang Xuehong, Liang Xinzhong, and Bao Ning, 1987: A global grid-point general circulation model. In a collection of papers presented at the WMO/IUGG NWP Symposium (Special volume of J. Meteorol. Soc. Japan), Tokyo, 4–8 August 1986, 421–430.

  • Zeng Qingcun, Zhang Xuehong, Liang Xinzhong, Yuan Chongguang, and S. F. Chen, 1989: Documentation of IAP two-level atmospheric general circulation model. DOE/ER/60314-HI, TRO44, 383pp.

  • Zhang Xuehong, 1990: Dynamical framework of IAP ninelevel atmospheric general circulation model.Adv. Atmos. Sci.,7, 66–77.

    Article  Google Scholar 

  • Zhao Yan, Guo Yufu, Yuan Chongguang, and Li Xu, 2000: Study on the predictability of numerical seasonal prediction.Quarterly Journal of Applied Meteorology,11, 64–71. (in Chinese)

    Google Scholar 

  • Zhou Guangqing, Li Xu, and Zeng Qingcun, 1998: A coupled ocean-atmosphere general circulation model for ENSO prediction and 1997/1998 ENSO forecast.Climatic and Environmental Research,3, 349–357. (in Chinese)

    Google Scholar 

  • Zhu Bingyuan, and Li Dongliang, 1991: Relationship between tropic Pacific SST and summer precipitation over northwest China.Acta Meteorologica Sinica,49, 21–28. (in Chinese)

    Google Scholar 

  • Zhu Qiangen, Teng Ying, and Xu Guoqiang, 2000: The possible mechanism of the effects of SSTA in North Pacific on East China summer rainfall.Journal of Nanjing Institute of Meteorology,23, 1–8. (in Chinese)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lang Xianmei.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xianmei, L., Huijun, W. Seasonal differences of model predictability and the impact of SST in the Pacific. Adv. Atmos. Sci. 22, 103–113 (2005). https://doi.org/10.1007/BF02930873

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02930873

Key words

Navigation