• Barnett, T. P., 1995: Monte Carlo climate forecasting. J. Climate, 8 , 10051022.

  • Bladé, I., 1997: The influence of midlatitude ocean–atmosphere coupling on the low-frequency variability of a GCM. Part I: No tropical SST forcing. J. Climate, 10 , 20872106.

    • Search Google Scholar
    • Export Citation
  • Bladé, I., 1999: The influence of midlatitude ocean–atmosphere coupling on the low-frequency variability of a GCM. Part II: Interannual variability induced by tropical SST forcing. J. Climate, 12 , 2145.

    • Search Google Scholar
    • Export Citation
  • Chen, W. Y., 2004: Significant change of extratropical natural variability associated with tropical ENSO anomaly. J. Climate, 17 , 20192030.

    • Search Google Scholar
    • Export Citation
  • Chen, W. Y., and H. Van den Dool, 1995: Low-frequency variabilities for widely different basic flows. Tellus, 47A , 526540.

  • DeWeaver, E., and S. Nigam, 2002: Linearity in ENSO’s atmospheric response. J. Climate, 15 , 24462461.

  • Gadgil, S., P. V. Joseph, and N. V. Joshi, 1984: Ocean–atmosphere coupling over monsoon regions. Nature, 312 , 141143.

  • Graham, N. E., and T. P. Barnett, 1987: Sea surface temperature, surface wind divergence and convection over tropical ocean. Science, 238 , 657659.

    • Search Google Scholar
    • Export Citation
  • Hannachi, A., 2001: Toward a nonlinear identification of the atmospheric response to ENSO. J. Climate, 14 , 21382149.

  • Hazrallah, A., and R. Sadourny, 1995: Internal versus SST-forced variability as simulated by an atmospheric general circulation model. J. Climate, 8 , 474495.

    • Search Google Scholar
    • Export Citation
  • Hoerling, M. P., A. Kumar, and M. Zhong, 1997: El Niño, La Niña, and the nonlinearity of their teleconnections. J. Climate, 10 , 17691786.

    • Search Google Scholar
    • Export Citation
  • Hoerling, M. P., A. Kumar, and T-Y. Xu, 2001: Robustness of the nonlinear climate response to ENSO’s extreme cases. J. Climate, 14 , 12771293.

    • Search Google Scholar
    • Export Citation
  • Horel, J. D., and J. M. Wallace, 1981: Planetary-scale atmospheric phenomena associated with the Southern Oscillation. Mon. Wea. Rev., 109 , 813829.

    • Search Google Scholar
    • Export Citation
  • Hoskins, B. J., and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38 , 11791196.

    • Search Google Scholar
    • Export Citation
  • Kanamitsu, M., and Coauthors, 2002a: NCEP dynamical seasonal forecast system 2000. Bull. Amer. Meteor. Soc, 83 , 10191037.

  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter, 2002b: NCEP–DOE AMIP-II Reanalysis (R-2). Bull. Amer. Meteor. Soc., 83 , 16311643.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 1995: Prospects and limitations of atmospheric GCM climate predictions. Bull. Amer. Meteor. Soc., 76 , 335345.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 1997: Interpretation and implications of the observed inter–El Niño variability. J. Climate, 10 , 8391.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 1998: Annual cycle of Pacific–North American seasonal predictability associated with different phases of ENSO. J. Climate, 11 , 32953308.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 2000: Analysis of a conceptual model of seasonal climate variability and implications for seasonal predictions. Bull. Amer. Meteor. Soc., 81 , 255264.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and F. Yang, 2003: Comparative influence of snow and SST variability on extratropical climate in northern winter. J. Climate, 16 , 22482261.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., A. G. Barnston, P. Peng, M. P. Hoerling, and L. Goddard, 2000: Changes in the spread of the variability of the seasonal mean atmospheric states associated with ENSO. J. Climate, 13 , 31393151.

    • Search Google Scholar
    • Export Citation
  • Lau, N-C., 1997: Interactions between global SST anomalies and the midlatitude atmospheric circulation. Bull. Amer. Meteor. Soc., 78 , 2133.

    • Search Google Scholar
    • Export Citation
  • Livezey, R. E., and K. C. Mo, 1987: Tropical–extratropical teleconnections during the Northern Hemisphere winter. Part II: Relationships between monthly mean Northern Hemisphere circulation patterns and proxies for tropical convection. Mon. Wea. Rev., 115 , 31153132.

    • Search Google Scholar
    • Export Citation
  • Palmer, T. N., 1988: Medium and extended range predictability and stability of the Pacific/ North American mode. Quart. J. Roy. Meteor. Soc., 114 , 619713.

    • Search Google Scholar
    • Export Citation
  • Palmer, T. N., 1993: Extended-range atmospheric prediction and the Lorenz model. Bull. Amer. Meteor. Soc., 74 , 4966.

  • Renshaw, A. C., D. P. Rowell, and C. K. Folland, 1998: Wintertime low-frequency weather variability in the North Pacific–American sector 1949–1993. J. Climate, 11 , 10731093.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface temperature analyses using optimum interpolation. J. Climate, 7 , 929948.

    • Search Google Scholar
    • Export Citation
  • Robertson, A. W., and M. Ghil, 1999: Large-scale weather regimes and local climate over the western United States. J. Climate, 12 , 17961813.

    • Search Google Scholar
    • Export Citation
  • Rowell, D. P., 1998: Assessing potential seasonal predictability with an ensemble of multidecadal GCM simulations. J. Climate, 11 , 109120.

    • Search Google Scholar
    • Export Citation
  • Sardeshmukh, P. D., G. P. Compo, and C. Penland, 2000: Changes of probability associated with El Niño. J. Climate, 13 , 42684286.

  • Schubert, S. D., M. J. Suarez, Y. Chang, and G. Branstator, 2001: The impact of ENSO on extratropical low-frequency noise in seasonal forecasts. J. Climate, 14 , 23512365.

    • Search Google Scholar
    • Export Citation
  • Sheng, J., 2002: GCM experiments on changes in atmospheric predictability associated with the PNA pattern and tropical SST anomalies. Tellus, 54 , 317329.

    • Search Google Scholar
    • Export Citation
  • Shukla, J., and Coauthors, 2000: Dynamical seasonal prediction. Bull. Amer. Meteor. Soc., 81 , 25932606.

  • Straus, D. M., and J. Shukla, 2002: Does ENSO force the PNA? J. Climate, 15 , 23402358.

  • Trenberth, K. E., G. Branstator, G. W. Karoly, A. Kumar, N-C. Lau, and C. Ropelewski, 1998: Progress during TOGA in understanding and modeling global teleconnections with tropical sea surface temperatures. J. Geophys. Res., 103 , 1429114324.

    • Search Google Scholar
    • Export Citation
  • Wang, W., and A. Kumar, 1998: A GCM assessment of atmospheric seasonal predictability associated with soil moisture anomalies over North America. J. Geophys. Res., 103 , 2863728646.

    • Search Google Scholar
    • Export Citation
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A Large Ensemble Analysis of the Influence of Tropical SSTs on Seasonal Atmospheric Variability

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  • 1 Climate Prediction Center, Camp Springs, Maryland
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Abstract

Based on a 40-member ensemble for the January–March (JFM) seasonal mean for the 1980–2000 period using an atmospheric general circulation model (AGCM), interannual variability in the first and second moments of probability density function (PDF) of atmospheric seasonal means with sea surface temperatures (SSTs) is analyzed. Based on the strength of the SST anomaly in the Niño-3.4 index region, the years between 1980 and 2000 were additionally categorized into five separate bins extending from strong cold to strong warm El Niño events. This procedure further enhances the size of the ensemble for each SST category. All the AGCM simulations were forced with the observed SSTs, and different ensemble members for specified SST boundary forcing were initiated from different atmospheric initial conditions.

The main focus of this analysis is on the changes in the seasonal mean and the internal variability of tropical rainfall and extratropical 200-mb heights with SSTs. For the tropical rainfall, results indicate that in the equatorial tropical Pacific, internal variability of the tropical rainfall anomaly decreases (increases) for the La Niña (El Niño) events. On the other hand, seasonal mean variability of extratropical 200-mb height decreases for the El Niño events. Although there is increase in the seasonal mean variability of 200-mb heights for the La Niña events, results are rather inclusive. Analysis also indicates that for the variables studied, the influence of the interannual variability in SSTs is much stronger on the first moment of seasonal means compared to their influence on the internal variability. As a consequence, seasonal predictability due to changes in SSTs can be attributed primarily to the shift in the PDFs of the seasonal atmospheric means and less to changes in their spread.

Modes of internal variability for 200-mb extratropical seasonal mean heights for different SST categories are also analyzed. The dominant mode of internal variability has little dependence on the tropical SST forcing, while larger influence on the second mode of internal variability is found. For SST forcing changing from a La Niña to El Niño state, the spatial pattern of the second mode shifts eastward. For the cold events, the spatial patterns bear more resemblance to the Pacific–North American (PNA) pattern, while for the warm events, it more resembles the tropical–North Hemispheric (TNH) pattern. Change in the spatial pattern of this mode from strong cold to a strong warm event resembles the change in the spatial pattern of response in the mean state.

Corresponding author address: Dr. Peitao Peng, Climate Prediction Center, W/NP51, 5200 Auth Road, Room 800, Camp Springs, MD 20746. Email: peitao.peng@noaa.gov

Abstract

Based on a 40-member ensemble for the January–March (JFM) seasonal mean for the 1980–2000 period using an atmospheric general circulation model (AGCM), interannual variability in the first and second moments of probability density function (PDF) of atmospheric seasonal means with sea surface temperatures (SSTs) is analyzed. Based on the strength of the SST anomaly in the Niño-3.4 index region, the years between 1980 and 2000 were additionally categorized into five separate bins extending from strong cold to strong warm El Niño events. This procedure further enhances the size of the ensemble for each SST category. All the AGCM simulations were forced with the observed SSTs, and different ensemble members for specified SST boundary forcing were initiated from different atmospheric initial conditions.

The main focus of this analysis is on the changes in the seasonal mean and the internal variability of tropical rainfall and extratropical 200-mb heights with SSTs. For the tropical rainfall, results indicate that in the equatorial tropical Pacific, internal variability of the tropical rainfall anomaly decreases (increases) for the La Niña (El Niño) events. On the other hand, seasonal mean variability of extratropical 200-mb height decreases for the El Niño events. Although there is increase in the seasonal mean variability of 200-mb heights for the La Niña events, results are rather inclusive. Analysis also indicates that for the variables studied, the influence of the interannual variability in SSTs is much stronger on the first moment of seasonal means compared to their influence on the internal variability. As a consequence, seasonal predictability due to changes in SSTs can be attributed primarily to the shift in the PDFs of the seasonal atmospheric means and less to changes in their spread.

Modes of internal variability for 200-mb extratropical seasonal mean heights for different SST categories are also analyzed. The dominant mode of internal variability has little dependence on the tropical SST forcing, while larger influence on the second mode of internal variability is found. For SST forcing changing from a La Niña to El Niño state, the spatial pattern of the second mode shifts eastward. For the cold events, the spatial patterns bear more resemblance to the Pacific–North American (PNA) pattern, while for the warm events, it more resembles the tropical–North Hemispheric (TNH) pattern. Change in the spatial pattern of this mode from strong cold to a strong warm event resembles the change in the spatial pattern of response in the mean state.

Corresponding author address: Dr. Peitao Peng, Climate Prediction Center, W/NP51, 5200 Auth Road, Room 800, Camp Springs, MD 20746. Email: peitao.peng@noaa.gov

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