• Alexander, M. A., 1992: Midlatitude air–sea interaction during El Niño. Part I: The North Pacific Ocean. J. Climate,5, 944–958.

  • Barsugli, J. J., 1995: Idealized models of intrinsic midlatitude atmosphere–ocean interaction. Ph.D. dissertation, University of Washington, 189 pp.

  • Bhatt, U. S., M. A. Alexander, D. S. Battisti, D. D. Houghton, and L. A. Keller, 1998. Atmosphere–ocean interaction in the North Atlantic: Near surface climate variability. J. Climate, in press.

  • 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, 2087–2106.

  • Frankignoul, C., 1985: Sea surface temperature anomalies, planetary waves, and air–sea feedback in the middle latitudes. Rev. Geophys.,23, 357–390.

  • ——, and K. Hasselmann, 1977: Stochastic climate models. Part II:Application to sea-surface temperature anomalies and thermocline variability. Tellus,29, 284–305.

  • ——, and R. W. Reynolds, 1983: Testing a dynamical model for midlatitude sea surface temperature anomalies. J. Phys. Oceanogr.,13, 1131–1145.

  • Gates, W. L., 1992: AMIP: The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc.,73, 1962–1970.

  • Hasselmann, K., 1976: Stochastic climate models. I, Theory. Tellus,28, 473–485.

  • Held, I. M., and M. J. Suarez, 1978: A two-level primitive equation atmospheric model designed for climatic sensitivity experiments. J. Atmos. Sci.,35, 206–229.

  • Kim, K.-Y., and G. R. North, 1992: Seasonal cycle and second-moment statistics of a simple coupled climate system. J. Geophys. Res.,97, 10069–10081.

  • Latif, M., and T. P. Barnett, 1996: Decadal climate variability over the North Pacific and North America: Dynamics and predictability. J. Climate,9, 2407–2423.

  • Lau, N.-C., and M. J. Nath, 1994: A modeling study of the relative roles of tropical and extratropical SST anomalies in the variability of the global atmosphere–ocean system. J. Climate,7, 1184–1207.

  • ——, and ——, 1996: The role of the “atmospheric bridge” in linking tropical Pacific ENSO events to extratropical SST anomalies. J. Climate,9, 2036–2057.

  • Liu, Z., 1993: Interannual positive feedbacks in a simple extratropical air–sea coupling system. J. Atmos. Sci.,50, 3022–3028.

  • Manabe, S., and R. J. Stouffer, 1996: Low-frequency variability of surface air temperature in a 1000-yr integration of a coupled ocean–atmosphere model. J. Climate,9, 376–393.

  • Marotzke, J., and D. W. Reynolds, 1997: On spatial scales and lifetimes of SST anomalies beneath a diffusive atmosphere. J. Phys. Oceanogr.,27, 133–139.

  • Miller, A. J., 1992: Large-scale ocean–atmosphere interactions in a simplified coupled model of the midlatitude wintertime circulation. J. Atmos. Sci.,49, 273–286.

  • ——, and J. O. Roads, 1990: A simplified coupled model of extended-range predictability. J. Climate,3, 523–542.

  • Nitsche, G., 1996: Some aspects of planetary-scale atmospheric variability in a low-resolution general circulation model. Ph.D. dissertation, University of Washington, 207 pp.

  • North, G. F., and R. F. Cahalan, 1981: Predictability in a solvable stochastic climate model. J. Atmos. Sci.,38, 504–513.

  • —–, J. Mengel, and D. Short, 1983: Simple energy balance model resolving the seasons and the continents: Application to the astronomical theory of the ice ages. J. Geophys. Res.,88, 6576–6586.

  • Palmer, T. N., and Z. Sun, 1985: A modeling and observational study of the relationship between sea surface temperatures in the northwest Atlantic and the atmospheric general circulation. Quart. J. Roy. Meteor. Soc.,111, 947–975.

  • Peng, S., L. A. Mysak, H. Ritchie, J. Derome, and B. Dugas, 1995:The differences between early and midwinter atmospheric responses to sea surface temperature anomalies in the northwest Atlantic. J. Climate,8, 137–157.

  • Ronca, R. E., and D. S. Battisti, 1997: Anomalous sea surface temperatures and local air–sea energy exchange on intraannual timescales in the northeastern subtropical Pacific. J. Climate,10, 102–117.

  • Schneider, E. K., and J. L. Kinter III, 1994: An examination of internally generated variability in long climate simulations. Climate Dyn.,10, 181–204.

  • Schopf, P. S., 1985: Modeling tropical sea-surface temperature: Implications of various atmospheric responses. Coupled Ocean-Atmosphere Models, J. C. J. Nihoul, Ed., Elsevier, 727–734.

  • Zubarev, A. P., and P. F. Demchenko, 1992: Predictability of the averaged global air temperature in a simple stochastic atmosphere–ocean interaction model. Izv. Atmos. Oceanic Phys.,28, 19–23.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 270 270 19
PDF Downloads 170 170 20

The Basic Effects of Atmosphere–Ocean Thermal Coupling on Midlatitude Variability

View More View Less
  • 1 CIRES, University of Colorado, Boulder, Colorado
  • | 2 Department of Atmospheric Sciences, University of Washington, Seattle, Washington
© Get Permissions
Restricted access

Abstract

Starting from the assumption that the atmosphere is the primary source of variability internal to the midlatitude atmosphere–ocean system on intraseasonal to interannual timescales, the authors construct a simple stochastically forced, one-dimensional, linear, coupled energy balance model. The coupled system is then dissected into partially coupled and uncoupled systems in order to quantify the effects of coupling. The simplicity of the model allows for analytic evaluation of many quantities of interest, including power spectra, total variance, lag covariance between atmosphere and ocean, and surface flux spectra. The model predicts that coupling between the atmosphere and ocean in the midlatitudes will enhance the variance in both media and will decrease the energy flux between the atmosphere and the ocean. The model also demonstrates that specification of historical midlatitude sea surface temperature anomalies as a boundary condition for an atmospheric model will not generally lead to a correct simulation of low-frequency atmospheric thermal variance.

This model provides a simple conceptual framework for understanding the basic aspects of midlatitude coupled variability. Given the simplicity of the model, it agrees well with numerical simulations using a two-level atmospheric general circulation model coupled to a slab mixed layer ocean. The simple model results are also qualitatively consistent with the results obtained in several other studies in which investigators coupled realistic atmospheric general circulation models to ocean models of varying complexity. This suggests that the experimental design of an atmospheric model coupled to a mixed layer ocean model would provide a reasonable null hypothesis against which to test for the presence of distinctive decadal variability.

Corresponding author address: Dr. Joseph Barsugli, CIRES, University of Colorado, Campus Box 449, Boulder, CO 80309-0449.

Email: jjb@cdc.noaa.gov

Email: david@atmos.washington.edu

Abstract

Starting from the assumption that the atmosphere is the primary source of variability internal to the midlatitude atmosphere–ocean system on intraseasonal to interannual timescales, the authors construct a simple stochastically forced, one-dimensional, linear, coupled energy balance model. The coupled system is then dissected into partially coupled and uncoupled systems in order to quantify the effects of coupling. The simplicity of the model allows for analytic evaluation of many quantities of interest, including power spectra, total variance, lag covariance between atmosphere and ocean, and surface flux spectra. The model predicts that coupling between the atmosphere and ocean in the midlatitudes will enhance the variance in both media and will decrease the energy flux between the atmosphere and the ocean. The model also demonstrates that specification of historical midlatitude sea surface temperature anomalies as a boundary condition for an atmospheric model will not generally lead to a correct simulation of low-frequency atmospheric thermal variance.

This model provides a simple conceptual framework for understanding the basic aspects of midlatitude coupled variability. Given the simplicity of the model, it agrees well with numerical simulations using a two-level atmospheric general circulation model coupled to a slab mixed layer ocean. The simple model results are also qualitatively consistent with the results obtained in several other studies in which investigators coupled realistic atmospheric general circulation models to ocean models of varying complexity. This suggests that the experimental design of an atmospheric model coupled to a mixed layer ocean model would provide a reasonable null hypothesis against which to test for the presence of distinctive decadal variability.

Corresponding author address: Dr. Joseph Barsugli, CIRES, University of Colorado, Campus Box 449, Boulder, CO 80309-0449.

Email: jjb@cdc.noaa.gov

Email: david@atmos.washington.edu

Save