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Article Type:
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The Equatorial Pacific Cold Tongue Bias in a Coupled Climate Model

Vasubandhu Misra Institute of Global Environment and Society, Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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L. Marx Institute of Global Environment and Society, Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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M. Brunke Department of Atmospheric Science, The University of Arizona, Tucson, Arizona

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X. Zeng Department of Atmospheric Science, The University of Arizona, Tucson, Arizona

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Print Publication:
15 Nov 2008
DOI:
https://doi.org/10.1175/2008JCLI2205.1
Page(s):
5852–5869
Restricted access

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Abstract

A set of multidecadal coupled ocean–atmosphere model integrations are conducted with different time steps for coupling between the atmosphere and the ocean. It is shown that the mean state of the equatorial Pacific does not change in a statistically significant manner when the coupling interval between the atmospheric general circulation model (AGCM) and the ocean general circulation model (OGCM) is changed from 1 day to 2 or even 3 days. It is argued that because the coarse resolution of the AGCM precludes resolving realistic “weather” events, changing the coupling interval from 1 day to 2 or 3 days has very little impact on the mean coupled climate.

On the other hand, reducing the coupling interval to 3 h had a much stronger impact on the mean state of the equatorial Pacific and the concomitant general circulation. A novel experiment that incorporates a (pseudo) interaction of the atmosphere with SST at every time step of the AGCM was also conducted. In this unique coupled model experiment, the AGCM at every time step mutually interacts with the skin SST. This skin SST is anchored to the bulk SST, which is updated from the OGCM once a day. Both of these experiments reduced the cold tongue bias moderately over the equatorial Pacific Ocean with a corresponding reduction in the easterly wind stress bias relative to the control integration. It is stressed from the results of these model experiments that the impact of high-frequency air–sea coupling is significant on the cold tongue bias.

The interannual variation of the equatorial Pacific was less sensitive to the coupling time step between the AGCM and the OGCM. Increasing (reducing) the coupling interval of the air–sea interaction had the effect of weakening (marginally strengthening) the interannual variations of the equatorial Pacific Ocean.

It is argued that the low-frequency response of the upper ocean, including the cold tongue bias, is modulated by the atmospheric stochastic forcing on the coupled ocean–atmosphere system. This effect of the atmospheric stochastic forcing is affected by the frequency of the air–sea coupling and is found to be stronger than the rectification effect of the diurnal variations of the air–sea interaction on the low frequency. This may be a result of a limitation in the coupled model used in this study in which the OGCM has an inadequate vertical resolution in the mixed layer to sustain diurnal variations in the upper ocean.

* Current affiliation: Department of Meteorology, and Center for Ocean–Atmosphere Prediction Studies, The Florida State University, Tallahassee, Florida.

Corresponding author address: Vasubandhu Misra, Department of Meteorology, The Florida State University, 404 Love Building, Tallahassee, FL 32312. Email: vmisra@fsu.edu

Abstract

A set of multidecadal coupled ocean–atmosphere model integrations are conducted with different time steps for coupling between the atmosphere and the ocean. It is shown that the mean state of the equatorial Pacific does not change in a statistically significant manner when the coupling interval between the atmospheric general circulation model (AGCM) and the ocean general circulation model (OGCM) is changed from 1 day to 2 or even 3 days. It is argued that because the coarse resolution of the AGCM precludes resolving realistic “weather” events, changing the coupling interval from 1 day to 2 or 3 days has very little impact on the mean coupled climate.

On the other hand, reducing the coupling interval to 3 h had a much stronger impact on the mean state of the equatorial Pacific and the concomitant general circulation. A novel experiment that incorporates a (pseudo) interaction of the atmosphere with SST at every time step of the AGCM was also conducted. In this unique coupled model experiment, the AGCM at every time step mutually interacts with the skin SST. This skin SST is anchored to the bulk SST, which is updated from the OGCM once a day. Both of these experiments reduced the cold tongue bias moderately over the equatorial Pacific Ocean with a corresponding reduction in the easterly wind stress bias relative to the control integration. It is stressed from the results of these model experiments that the impact of high-frequency air–sea coupling is significant on the cold tongue bias.

The interannual variation of the equatorial Pacific was less sensitive to the coupling time step between the AGCM and the OGCM. Increasing (reducing) the coupling interval of the air–sea interaction had the effect of weakening (marginally strengthening) the interannual variations of the equatorial Pacific Ocean.

It is argued that the low-frequency response of the upper ocean, including the cold tongue bias, is modulated by the atmospheric stochastic forcing on the coupled ocean–atmosphere system. This effect of the atmospheric stochastic forcing is affected by the frequency of the air–sea coupling and is found to be stronger than the rectification effect of the diurnal variations of the air–sea interaction on the low frequency. This may be a result of a limitation in the coupled model used in this study in which the OGCM has an inadequate vertical resolution in the mixed layer to sustain diurnal variations in the upper ocean.

* Current affiliation: Department of Meteorology, and Center for Ocean–Atmosphere Prediction Studies, The Florida State University, Tallahassee, Florida.

Corresponding author address: Vasubandhu Misra, Department of Meteorology, The Florida State University, 404 Love Building, Tallahassee, FL 32312. Email: vmisra@fsu.edu

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  • Bacmeister, J., P. J. Pegion, S. D. Schubert, and M. J. Suarez, 2000: An atlas of seasonal means simulated by the NSIPP-1 atmospheric GCM. Goddard Space Flight Center, NASA Tech. Memo. 104606, Vol. 17, 194 pp.

  • Berger, A., 1978: Long-term variations of daily insolation and quaternary climate changes. J. Atmos. Sci., 35 , 2362–2367.

  • Bernie, D. J., S. J. Woolnough, J. M. Slingo, and E. Guilyardi, 2005: Modeling diurnal and intraseasonal variability of the ocean mixed layer. J. Climate, 18 , 1190–1202.

    • Search Google Scholar
    • Export Citation

  • Bernie, D. J., E. Guilyardi, G. Madec, J. M. Slingo, and S. J. Woolnough, 2007: Impact of resolving the diurnal cycle in an ocean-atmosphere GCM. Part 1: A diurnally forced OGCM. Climate Dyn., 29 , 575–590. doi:10.1007/s00382-007-0249-6.

    • Search Google Scholar
    • Export Citation

  • Brunke, M. A., C. W. Fairall, X. Zeng, L. Eymard, and J. A. Curry, 2003: Which bulk aerodynamic algorithms are least problematic in computing ocean surface turbulent fluxes? J. Climate, 16 , 619–635.

    • Search Google Scholar
    • Export Citation

  • Brunke, M. A., X. Zeng, V. Misra, and A. Beljaars, 2008: Integration of a prognostic sea surface skin temperature scheme into weather and climate models. J. Geophys Res., in press.

    • Search Google Scholar
    • Export Citation

  • Cash, B., X. Rodo, and J. L. Kinter III, 2007: Links between tropical Pacific SST and the regional climate of Bangladesh: Role of the eastern and central tropical Pacific. COLA Tech. Rep. 236, 33 pp. [Available online at ftp://grads.iges.org/pub/ctr/ctr_236.pdf.].

  • Chao, W. C., and B. Chen, 2004: Single and double ITCZ in an aqua-planet model with constant sea surface temperature and solar angle. Climate Dyn., 22 , 447–459. doi:10.1007/s00382-003-0387-4.

    • Search Google Scholar
    • Export Citation

  • Clayson, C. A., and D. Weitlich, 2007: Variability of tropical diurnal sea surface temperature. J. Climate, 20 , 334–352.

  • Collins, W. D., and Coauthors, 2006: The Community Climate System Model version 3 (CCSM3). J. Climate, 19 , 2122–2143.

  • Danabasoglu, G., W. G. Large, J. J. Tribbia, P. R. Gent, and B. P. Briegleb, 2006: Diurnal coupling in the tropical oceans of CCSM3. J. Climate, 19 , 2347–2365.

    • Search Google Scholar
    • Export Citation

  • Delsole, T., M. Zhao, P. A. Dirmeyer, and B. P. Kirtman, 2008: Empirical correction of a coupled land–atmosphere model. Mon. Wea. Rev., 136 , 4063–4076.

    • Search Google Scholar
    • Export Citation

  • Dirmeyer, P. A., and F. J. Zeng, 1999: Precipitation infiltration in the simplified SiB land surface scheme. J. Meteor. Soc. Japan, 77 , 291–303.

    • Search Google Scholar
    • Export Citation

  • Fairall, C. W., E. F. Bradley, J. S. Godfrey, G. A. Wick, and J. B. Edson, 1996a: Cool-skin and warm-layer effects on sea surface temperature. J. Geophys. Res., 101 , 1295–1308.

    • Search Google Scholar
    • Export Citation

  • Fairall, C. W., E. F. Bradley, D. P. Rogers, J. B. Edson, and G. S. Young, 1996b: Bulk parameterization of air-sea fluxes for Tropical Ocean-Global Atmosphere Coupled-Ocean Atmosphere Response Experiment. J. Geophys. Res., 101 , 3747–3764.

    • Search Google Scholar
    • Export Citation

  • Gent, P. R., and J. C. McWilliams, 1990: Isopycnal mixing in ocean circulation models. J. Phys. Oceanogr., 25 , 150–155.

  • Ghil, M., and Coauthors, 2002: Advanced spectral methods for climatic time series. Rev. Geophys., 40 .1003, doi:10.1029/2000RG000092.

  • Hong, S. Y., and H. L. Pan, 1996: Nonlocal boundary layer vertical diffusion in a medium range forecast model. Mon. Wea. Rev., 124 , 2322–2339.

    • Search Google Scholar
    • Export Citation

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437–471.

  • Kiehl, J. T., J. J. Hack, G. Bonan, B. A. Boville, D. L. Williamson, and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11 , 1131–1149.

    • Search Google Scholar
    • Export Citation

  • Kirtman, B. P., and E. Schneider, 2000: A spontaneously generated tropical atmospheric general circulation. J. Atmos. Sci., 57 , 2080–2093.

    • Search Google Scholar
    • Export Citation

  • Kirtman, B. P., and J. Shukla, 2002: Interactive coupled ensemble: A new coupling strategy for GCMs. Geophys. Res. Lett., 29 .1367, doi:10.1029/2002GL014834.

    • Search Google Scholar
    • Export Citation

  • Kirtman, B. P., K. Pegion, and S. M. Kinter, 2005: Internal atmospheric dynamics and tropical Indo-Pacific climate variability. J. Atmos. Sci., 62 , 2220–2233.

    • Search Google Scholar
    • Export Citation

  • Large, W. G., J. C. McWilliams, and S. C. Doney, 1994: Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization. Rev. Geophys., 32 , 363–403.

    • Search Google Scholar
    • Export Citation

  • Latif, M., and Coauthors, 2001: ENSIP: The El Niño simulation intercomparison project. Climate Dyn., 18 , 255–272.

  • Lin, J. L., and Coauthors, 2006: Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: Convective signals. J. Climate, 19 , 2665–2690.

    • Search Google Scholar
    • Export Citation

  • Luo, J-J., S. Masson, E. Roeckner, G. M. Adec, and T. Yamagata, 2005: Reducing climatology bias in an ocean–atmosphere CGCM with improved coupling physics. J. Climate, 18 , 2344–2360.

    • Search Google Scholar
    • Export Citation

  • Mechoso, C. R., and Coauthors, 1995: The seasonal cycle over the tropical Pacific in coupled ocean–atmosphere general circulation models. Mon. Wea. Rev., 123 , 2825–2838.

    • Search Google Scholar
    • Export Citation

  • Misra, V., and L. Marx, 2007: Manifestation of remote response over the equatorial Pacific in a climate model. J. Geophys. Res., 112 .D20105, doi:10.1029/2007JD008597.

    • Search Google Scholar
    • Export Citation

  • Misra, V., and Coauthors, 2007: Validating and understanding ENSO simulation in two coupled climate models. Tellus, 59A , 292–308.

  • Misra, V., L. Marx, M. Fennessey, B. Kirtman, and J. L. Kinter III, 2008: A comparison of climate prediction and simulation over tropical Pacific. J. Climate, 21 , 3601–3611.

    • Search Google Scholar
    • Export Citation

  • Moorthi, S., and M. J. Suarez, 1992: Relaxed Arakawa–Schubert: A parameterization of moist convection for general circulation models. Mon. Wea. Rev., 120 , 978–1002.

    • Search Google Scholar
    • Export Citation

  • Pacanowski, R. C., and S. M. Griffies, 1998: MOM3.0 manual. NOAA/Geophysical Fluid Dynamics Laboratory, 638 pp.

  • Randall, D. A., and Coauthors, 2007: Climate models and their evaluation. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 591–648.

    • Search Google Scholar
    • Export Citation

  • Rao, A. K., and K. R. Sperber, 2006: ENSO simulation in coupled ocean-atmosphere models: Are the current models better? Climate Dyn., 27 , 1–15.

    • Search Google Scholar
    • Export Citation

  • Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108 .4407, doi:10.1029/2002JD002670.

    • Search Google Scholar
    • Export Citation

  • Redi, M. H., 1982: Oceanic isopycnal mixing by coordinate rotate. J. Phys. Oceanogr., 12 , 1154–1158.

  • Saha, S., and Coauthors, 2006: The NCEP Climate Forecast System. J. Climate, 19 , 3483–3517.

  • Smagorinsky, J., 1963: General circulation experiments with the primitive equations: I. The basic experiment. Mon. Wea. Rev., 91 , 99–164.

    • Search Google Scholar
    • Export Citation

  • Sperber, K. R., S. Gualdi, S. Legutke, and V. Gayler, 2005: The Madden–Julian oscillation in ECHAM4 coupled and uncoupled general circulation models. Climate Dyn., 25 , 117–140. doi:10.1007/s00382-005-0026-3.

    • Search Google Scholar
    • Export Citation

  • Sumi, A., 1992: Pattern formation of convective activity over the aqua-planet with globally uniform sea surface temperature. J. Meteor. Soc. Japan, 70 , 855–876.

    • Search Google Scholar
    • Export Citation

  • Sura, P., and C. Penland, 2002: Sensitivity of a double-gyre ocean model to details of stochastic forcing. Ocean Modell., 4 , 327–345.

  • Tiedtke, M., 1984: The effect of penetrative cumulus convection on the large-scale flow in a general circulation model. Beitr. Phys. Atmos., 57 , 216–239.

    • Search Google Scholar
    • Export Citation

  • Webster, P. J., C. A. Clayson, and J. A. Curry, 1996: Clouds, radiation, and the diurnal cycle of sea surface temperature in the tropical western Pacific. J. Climate, 9 , 1712–1730.

    • Search Google Scholar
    • Export Citation

  • Wu, Z., E. K. Schneider, and B. P. Kirtman, 2004: Causes of low frequency North Atlantic SST variability in a coupled GCM. Geophys. Res. Lett., 31 .L09210, doi:10.1029/2004GL019548.

    • Search Google Scholar
    • Export Citation

  • Xue, Y-K., P. J. Sellers, J. L. Kinter III, and J. Shukla, 1991: A simplified Biosphere Model for global climate studies. J. Climate, 4 , 345–364.

    • Search Google Scholar
    • Export Citation

  • Xue, Y-K., F. J. Zeng, and C. A. Schlosser, 1996: SSiB and its sensitivity to soil properties: A case study using HAPEX-Mobilhy data. Global Planet. Change, 13 , 183–194.

    • Search Google Scholar
    • Export Citation

  • Yu, J-Y., and C. R. Mechoso, 1999: Links between annual variations of Peruvian stratocumulus clouds and of SST in the eastern equatorial Pacific. J. Climate, 12 , 3305–3318.

    • Search Google Scholar
    • Export Citation

  • Zeng, X., and A. Beljaars, 2005: A prognostic scheme of sea surface skin temperature for modeling and data assimilation. Geophys. Res. Lett., 32 .L14605, doi:10.1029/2005GL023030.

    • Search Google Scholar
    • Export Citation

  • Zeng, X., M. Zhao, R. E. Dickinson, and Y. He, 1999: A multiyear hourly sea surface skin temperature data set derived from the TOGA TAO bulk temperature and wind speed over the tropical Pacific. J. Geophys. Res., 104 , 1525–1536.

    • Search Google Scholar
    • Export Citation

  • Zhang, C., 2005: Madden-Julian Oscillation. Rev. Geophys., 43 .RG2003, doi:10.1029/2004RG000158.

  • Zhang, G. J., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmos.–Ocean, 33 , 407–446.

    • Search Google Scholar
    • Export Citation

  • Zhang, G. J., and M. Mu, 2005: Effects of modification to the Zhang-McFarlane convection parameterization on the simulation of the tropical precipitation in the National Center for Atmospheric Research Community Climate Model, version 3. J. Geophys. Res., 110 .D09109, doi:10.1029/2004JD005617.

    • Search Google Scholar
    • Export Citation

  • Zhang, G. J., and H. Wang, 2006: Toward mitigating the double ITCZ problem in NCAR CCSM3. Geophys. Res. Lett., 33 .L06709, doi:10.1029/2005GL025229.

    • Search Google Scholar
    • Export Citation
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