Ocean Surface Impacts on the Seasonal-Mean Precipitation over the Tropical Indian Ocean

Mingyue Chen Climate Prediction Center, NOAA/NWS/NCEP, Camp Springs, Maryland

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Wanqiu Wang Climate Prediction Center, NOAA/NWS/NCEP, Camp Springs, Maryland

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Arun Kumar Climate Prediction Center, NOAA/NWS/NCEP, Camp Springs, Maryland

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Hui Wang Climate Prediction Center, NOAA/NWS/NCEP, Camp Springs, Maryland, and WYLE Information Systems, McLean, Virginia

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Bhaskar Jha Climate Prediction Center, NOAA/NWS/NCEP, Camp Springs, Maryland, and WYLE Information Systems, McLean, Virginia

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Abstract

This study analyzes factors affecting the predictability of seasonal-mean precipitation over the tropical Indian Ocean. The analysis focuses on the contributions from the local sea surface temperature (SST) forcing in the Indian Ocean, the remote SST forcing related to ENSO in the tropical eastern Pacific, and the role of local air–sea coupling. To understand the impacts of the individual factors, the prediction skill over the tropical Indian Ocean for four model simulations, but with different treatments for the ocean, are compared. The seasonality in precipitation skill, the local precipitation–SST relationship, and prediction skill related to Indian Ocean dipole mode (IODM) are examined. It is found that the importance of the accuracy of local SST and the presence of local air–sea coupling in the Indian Ocean has a strong seasonal dependence. Accurate local SSTs are important during the boreal fall season, whereas the local air–sea coupling is important during the boreal spring. The precipitation skill over the Indian Ocean during boreal winter is primarily from ENSO. However, ENSO impacts are better realized with the inclusion of an interactive ocean. For all four seasons, the simulation without the interannual variations of local SST in the Indian Ocean shows the least precipitation skill and a much weaker seasonality. It is also found that, for the simulation where the global SSTs are relaxed to the observations and hence maintain some level of active air–sea coupling, the observed seasonal cycle of precipitation–SST relationship is reproduced reasonably well. In addition, the analysis also shows that simulations with accurate SST forcing display high precipitation skill during strong IODM events, indicating that IODM SST acts as a forcing for the atmospheric variability.

Corresponding author address: Mingyue Chen, CPC, NOAA/NWS/NCEP, 5200 Auth Road, Room 605, Camp Springs, MD 20746. E-mail: mingyue.chen@noaa.gov

Abstract

This study analyzes factors affecting the predictability of seasonal-mean precipitation over the tropical Indian Ocean. The analysis focuses on the contributions from the local sea surface temperature (SST) forcing in the Indian Ocean, the remote SST forcing related to ENSO in the tropical eastern Pacific, and the role of local air–sea coupling. To understand the impacts of the individual factors, the prediction skill over the tropical Indian Ocean for four model simulations, but with different treatments for the ocean, are compared. The seasonality in precipitation skill, the local precipitation–SST relationship, and prediction skill related to Indian Ocean dipole mode (IODM) are examined. It is found that the importance of the accuracy of local SST and the presence of local air–sea coupling in the Indian Ocean has a strong seasonal dependence. Accurate local SSTs are important during the boreal fall season, whereas the local air–sea coupling is important during the boreal spring. The precipitation skill over the Indian Ocean during boreal winter is primarily from ENSO. However, ENSO impacts are better realized with the inclusion of an interactive ocean. For all four seasons, the simulation without the interannual variations of local SST in the Indian Ocean shows the least precipitation skill and a much weaker seasonality. It is also found that, for the simulation where the global SSTs are relaxed to the observations and hence maintain some level of active air–sea coupling, the observed seasonal cycle of precipitation–SST relationship is reproduced reasonably well. In addition, the analysis also shows that simulations with accurate SST forcing display high precipitation skill during strong IODM events, indicating that IODM SST acts as a forcing for the atmospheric variability.

Corresponding author address: Mingyue Chen, CPC, NOAA/NWS/NCEP, 5200 Auth Road, Room 605, Camp Springs, MD 20746. E-mail: mingyue.chen@noaa.gov
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  • Alexander, M. A., I. Bladé, M. Newman, J. R. Lanzante, N.-C. Lau, and J. D. Scott, 2002: The atmospheric bridge: The influence of ENSO teleconnections on air–sea interaction over the global oceans. J. Climate, 15, 22052231.

    • Search Google Scholar
    • Export Citation
  • Annamalai, H., S.-P. Xie, J.-P. McCreary, and R. Murtugudde, 2005: Impact of Indian Ocean sea surface temperature on developing El Niño. J. Climate, 18, 302319.

    • Search Google Scholar
    • Export Citation
  • Arakawa, O., and A. Kitoh, 2004: Comparison of local precipitation–SST relationship between the observation and a reanalysis dataset. Geophys. Res. Lett., 31, L12206, doi:10.1029/2004GL020283.

    • Search Google Scholar
    • Export Citation
  • Barnett, T. P., K. Arpe, L. Bengtsson, M. Ji, and A. Kumar, 1997: Potential predictability and AMIP implications of midlatitude climate variability in two general circulation models. J. Climate, 10, 23212329.

    • Search Google Scholar
    • Export Citation
  • Brankovic, C., T. N. Palmer, and L. Ferranti, 1994: Predictability of seasonal atmospheric variations. J. Climate, 7, 217237.

  • Chen, M., W. Wang, and A. Kumar, 2010: Prediction of monthly-mean temperature: The role of atmospheric and land initial conditions and sea surface temperature. J. Climate, 23, 717725.

    • Search Google Scholar
    • Export Citation
  • Janowiak, J. E., and P. Xie, 1999: CAMS–OPI: A global satellite-rain gauge merged product for real-time precipitation monitoring applications. J. Climate, 12, 33353342.

    • Search Google Scholar
    • Export Citation
  • Jin, E. K., and J. L. Kinter III, 2009: Characteristics of tropical Pacific SST predictability in coupled GCM forecasts using the NCEP CFS. Climate Dyn., 32, 675691, doi:10.1007/s00382-008-0418-2.

    • Search Google Scholar
    • Export Citation
  • Kang, I.-S., and Coauthors, 2002: Intercomparison of atmospheric GCM simulated anomalies associated with the 1997/98 El Niño. J. Climate, 15, 27912805.

    • Search Google Scholar
    • Export Citation
  • Klein, S. A., B. J. Sode, and N.-C. Lau, 1999: Remote sea surface temperature variations during ENSO: Evidence for a tropical atmospheric bridge. J. Climate, 12, 917932.

    • Search Google Scholar
    • Export Citation
  • Krishna Kumar, K., M. Hoerling, and B. Rajagopalan, 2005: Advancing dynamical prediction of Indian monsoon rainfall. Geophys. Res. Lett., 32, L08704, doi:10.1029/2004GL021979.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 1998: Specification of regional sea surface temperatures in atmospheric general circulation model simulations. J. Geophys. Res., 103, 89018907.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and M. P. Hoerling, 2003: The nature and causes for delayed atmospheric response to El Niño. J. Climate, 16, 13911403.

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

    • Search Google Scholar
    • Export Citation
  • Kumar, A., B. Jha, Q. Zhang, and L. Bounoua, 2007: A new methodology for estimating the unpredictable component of seasonal atmospheric variability. J. Climate, 20, 38883901.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., M. Chen, and W. Wang, 2011: An analysis of prediction skill of monthly mean climate variability. Climate Dyn., 37, 11191131, doi:10.1007/s00382-010-0901-4.

    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., and M. J. Nath, 2000: Impact of ENSO on the variability of the Asian–Australian monsoons as simulated in GCM experiments. J. Climate, 13, 42874309.

    • Search Google Scholar
    • Export Citation
  • Lau, N.-C., and M. J. Nath, 2003: Atmosphere–ocean variations in the Indo-Pacific sector during ENSO episodes. J. Climate, 16, 320.

    • Search Google Scholar
    • Export Citation
  • Livezey, R. E., M. Masutani, and M. Ji, 1996: SST-forced seasonal simulation and prediction skill for versions of the NCEP/MRF model. Bull. Amer. Meteor. Soc., 77, 507517.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., S. Masson, A. Behera, and T. Yamagata, 2007: Experimental forecast of the Indian Ocean dipole using a coupled OAGCM. J. Climate, 20, 21782190.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., S. Behera, Y. Masumoto, H. Sakuma, and T. Yamagata, 2008: Successful prediction of the consecutive IOD in 2006 and 2007. Geophys. Res, Lett., 35, L14S02, doi:10.1029/2007GL032793.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., R. Zhang, S. K. Behera, Y. Masumoto, F.-F. Jin, R. Lukas, and T. Yamagata, 2010: Interaction between El Niño and extreme Indian Ocean dipole. J. Climate, 23, 726742.

    • Search Google Scholar
    • Export Citation
  • Nigam, S., and H.-S. Shen, 1993: Structure of oceanic and atmospheric low-frequency variability over the tropical Pacific and Indian Ocean. Part I: COADS observations. J. Climate, 6, 657676.

    • Search Google Scholar
    • Export Citation
  • Pacanowski, R. C., and S. M. Griffies, 1998: MOM 3.0 manual. NOAA/Geophysical Fluid Dynamics Laboratory Rep., 668 pp.

  • Peng, P., and A. Kumar, 2005: A large ensemble analysis of the influence of tropical SSTs on seasonal atmospheric variability. J. Climate, 18, 10681085.

    • Search Google Scholar
    • Export Citation
  • Peng, P., A. Kumar, and W. Wang, 2009: An analysis of seasonal predictability in coupled model forecasts. Climate Dyn., 36, 637648, doi:10.1007/s00382-009-0711-8.

    • Search Google Scholar
    • Export Citation
  • Reynolds, W. R., N. A. Rayner, T. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625.

    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2006: The NCEP Climate Forecast System. J. Climate, 19, 34833517.

  • Saji, N. H., B. N. Goswami, P. N. Vinayachandran, and T. Yamagata, 1999: A dipole mode in the tropical Indian Ocean. Nature, 401, 360363.

    • Search Google Scholar
    • Export Citation
  • Saji, N. H., T. Ambrizzi, and S. E. T. Ferraz, 2005: Indian Ocean dipole mode events and austral surface air temperature anomalies. Dyn. Atmos. Oceans, 39, 87101, doi:10.1016/j.dynatmoce.2004.10.015.

    • Search Google Scholar
    • Export Citation
  • Saji, N. H., S.-P. Xie, T. Yamagata, 2006: Tropical Indian Ocean variability in the IPCC twentieth-century climate simulations. J. Climate, 19, 43974417.

    • Search Google Scholar
    • Export Citation
  • Schubert, S. D., M. J. Suare, P. J. Pegion, R. D. Koster, and J. T. Bacmeister, 2008: Potential predictability of long-term drought and pluvial conditions in the U.S. Great Plains. J. Climate, 21, 802816.

    • Search Google Scholar
    • Export Citation
  • Shukla, J., and J. M. Wallace, 1983: Numerical simulation of the atmospheric response to equatorial sea surface temperature anomalies. J. Atmos. Sci., 40, 16131630.

    • Search Google Scholar
    • Export Citation
  • Trenberth, K. E., and D. J. Shea, 2005: Relationships between precipitation and surface temperature. Geophys. Res. Lett., 32, L14703, doi:10.1029/2005GL022760.

    • Search Google Scholar
    • Export Citation
  • van den Dool, H. M., P. Peng, A. Johansson, M. Chelliah, A. Shabbar, and S. Saha, 2006: Seasonal-to-decadal predictability and prediction of North American climate—The Atlantic influence. J. Climate, 19, 60056024.

    • Search Google Scholar
    • Export Citation
  • Wang, B., R. Wu, and K. M. Lau, 2001: Interannual variability of the Asian summer monsoon: Contrasts between the Indian and the western North Pacific–East Asian monsoons. J. Climate, 14, 40734090.

    • Search Google Scholar
    • Export Citation
  • Wang, B., I.-S. Kang, and J.-Y. Li, 2004: Ensemble simulation of Asian–Australian monsoon variability by 11 AGCMs. J. Climate, 17, 803818.

    • Search Google Scholar
    • Export Citation
  • Wang, B., Q. Ding, X. Fu, I.-S. Kang, K. Jin, J. Shukla, and F. Doblas-Reyes, 2005: Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys. Res. Lett., 32, L15711, doi:10.1029/2005GL022734.

    • Search Google Scholar
    • Export Citation
  • Wang, W., S. Saha, H.-L. Pan, S. Nadiga, and G. White, 2005: Simulation of ENSO in the new NCEP coupled forecast system model (CFS03). Mon. Wea. Rev., 133, 15741593.

    • Search Google Scholar
    • Export Citation
  • Wang, W., M. Chen, and A. Kumar, 2010: An assessment of the CFS real-time seasonal forecasts. Wea. Forecasting, 25, 950969.

  • Webster, P. J., V. O. Magana, T. N. Palmer, J. Shukla, R. A. Tomas, M. Yanai, and T. Yasunari, 1998: Monsoons: Processes, predictability, and the prospects for prediction. J. Geophys. Res., 103, 14 45114 510.

    • Search Google Scholar
    • Export Citation
  • Webster, P. J., A. M. Moor, J. P. Loschnigg, and R. R. Leben, 1999: Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997-98. Nature, 401, 356360.

    • Search Google Scholar
    • Export Citation
  • Wu, R., and B. P. Kirtman, 2004: Impacts of the Indian Ocean on the Indian summer monsoon–ENSO relationship. J. Climate, 17, 30373054.

    • Search Google Scholar
    • Export Citation
  • Wu, R., and B. P. Kirtman, 2005: Roles of Indian and Pacific Ocean air–sea coupling in tropical atmospheric variability. Climate Dyn., 25, 155170.

    • Search Google Scholar
    • Export Citation
  • Wu, R., and S.-W. Yeh, 2010: A further study of the tropical Indian Ocean asymmetric mode in boreal spring. J. Geophys. Res., 115, D08101, doi:10.1029/2009JD012999.

    • Search Google Scholar
    • Export Citation
  • Wu, R., B. P. Kirtman, and K. Pegion, 2006: Local air–sea relationship in observations and model simulations. J. Climate, 19, 49144932.

    • Search Google Scholar
    • Export Citation
  • Wu, R., B. P. Kirtman, and V. Krishnamurthy, 2008: An asymmetric mode of tropical Indian Ocean rainfall variability in boreal spring. J. Geophys. Res., 113, D05104, doi:10.1029/2007JD009316.

    • Search Google Scholar
    • Export Citation
  • Yu, J.-Y., C. R. Mechoso, J. C. McWilliams, and A. Arakawa, 2002: Impacts of Indian Ocean on ENSO cycles. Geophys. Res. Lett., 29, 1204, doi:10.1029/2001GL014098.

    • Search Google Scholar
    • Export Citation
  • Zhang, C., 1993: Large-scale variability of atmospheric deep convection in relation to sea surface temperature in the tropics. J. Climate, 6, 18981913.

    • Search Google Scholar
    • Export Citation
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