• Barkstrom, B. R., 1984: The Earth Radiation Budget Experiment (ERBE). Bull. Amer. Meteor. Soc.,65, 1170–1185.

  • Bates, J. J., X. Wu, and D. L. Jackson, 1996: Interannual variability of upper troposphere water vapor band brightness temperature. J. Climate,9, 427–438.

  • Chou, M. D., 1994: Coolness in the tropical Pacific during an El Niño episode. J. Climate,7, 1684–1692.

  • Elliott, W. P., and D. J. Gaffen, 1991: On the utility of radiosonde humidity archives for climate studies. Bull. Amer. Meteor. Soc.,72, 1507–1520.

  • Gates, W. L., 1992: AMIP: The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc.,73, 791–794.

  • Hartmann, D. L., and M. L. Michelsen, 1993: Large-scale effects on the regulation of tropical sea surface temperature. J. Climate,6, 2049–2062.

  • Inamdar, A. K., and V. Ramanathan, 1994: Physics of the greenhouse effect and convection in warm oceans. J. Climate,7, 715–731.

  • IPCC, 1990: Climate Change: The IPCC Scientific Assessment. Cambridge University Press, 365 pp.

  • ——, 1992: The IPCC Supplementary Report. Cambridge University Press, 200 pp.

  • Lindzen, R. S., 1990: Some coolness concerning global warming. Bull. Amer. Meteor. Soc.,71, 288–299.

  • ——, and S. Nigam, 1987: On the role of sea surface temperature gradients in forcing low-level winds and convergence in the tropics. J. Atmos. Sci.,44, 2418–2436.

  • Oort, A. H., and J. J. Yienger, 1996: Observed variability in the Hadley circulation and its connection to ENSO. J. Climate,9, 2751–2767.

  • Raval, A., and V. Ramanathan, 1989: Observational determination of the greenhouse effect. Nature,342, 758–762.

  • Reynolds, R. W., 1988: A real-time global sea surface temperature analysis. J. Climate,1, 75–86.

  • Rind, D., E. W. Chiou, W. Chu, J. Larsen, S. Oltmans, J. Lerner, M. P. McCormick, and L. McMaster, 1991: Positive water vapour feedback in climate models confirmed by satellite data. Nature,349, 500–503.

  • Soden, B. J., and R. Fu, 1995: A satellite analysis of deep convection, upper tropospheric humidity, and the greenhouse effect. J. Climate,8, 2333–2351.

  • ——, and F. P. Bretherton, 1996: Interpretation of TOVS water vapor radiances in terms of layer-average relative humidities: Method and climatology for the upper, middle, and lower troposphere. J. Geophys. Res.,101, 9333–9343.

  • ——, and J. R. Lanzante, 1996: An assessment of satellite and radiosonde climatologies of upper tropospheric water vapor. J. Climate,9, 1235–1250.

  • Stephens, G. L., 1990: On the relationship between water vapor over oceans and sea surface temperature. J. Climate,3, 634–645.

  • ——, D. A. Randall, I. L. Wittmeyer, D. A. Dazlich, and S. Tjemkes, 1993: The earth’s radiation budget and its relation to atmospheric hydrology 3: Comparison of observations over oceans with a GCM. J. Geophys. Res.,99, 4391–4950.

  • Sun, D. Z., and R. S. Lindzen, 1993: Distribution of tropical tropospheric water vapor. J. Atmos. Sci.,50, 1644–1660.

  • ——, and I. M. Held, 1996: A comparison of modeled and observed relationships between interannual variations of water vapor and temperature. J. Climate,9, 665–675.

  • Thomas, D., J. P. Duvel, and R. Kandel, 1995: Diurnal bias in calibration of broad-band radiance measurements from space. IEEE Trans. Geosci. Remote Sens.,3, 670–682.

  • Thompson, S. L., and S. G. Warren, 1982: Parameterization of outgoing infrared radiation derived from detailed radiative calculations. J. Atmos. Sci.,39, 2667–2880.

  • Wetherald, R. T., V. Ramaswamy, and S. Manabe, 1991: A comparative study of the observations of high clouds and simulations by an atmospheric general circulation model. Climate Dyn.,5, 135–143.

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Variations in the Tropical Greenhouse Effect during El Niño

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  • 1 Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton, New Jersey
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Abstract

Observations of the clear-sky outgoing longwave radiation and sea surface temperature are combined to examine the evolution of the tropical greenhouse effect from colder La Niña conditions in early 1985 to warmer El Niño conditions in late 1987. Although comparison of individual months can suggest a decrease in greenhouse trapping from cold to warm conditions, when the entire 4-yr record is considered a distinct increase in tropical-mean greenhouse trapping of ∼2 W m−2 is observed in conjunction with a ∼0.4 K increase in tropical-mean sea surface temperature. This observed increase compares favorably with GCM simulations of the change in the clear-sky greenhouse effect during El Niño–Southern Oscillation (ENSO). Superimposed on top of the SST-driven change in greenhouse trapping are dynamically induced changes in tropical moisture apparently associated with a redistribution of SST during ENSO. The GCM simulations also successfully reproduce this feature, providing reassurance in the ability of GCMs to predict both dynamically and thermodynamically driven changes in greenhouse trapping.

Corresponding author address: Dr. Brian J. Soden, GFDL/NOAA, Princeton University, P.O. Box 308, Princeton, NJ 08542.

Email: bjs@gfdl.gov

Abstract

Observations of the clear-sky outgoing longwave radiation and sea surface temperature are combined to examine the evolution of the tropical greenhouse effect from colder La Niña conditions in early 1985 to warmer El Niño conditions in late 1987. Although comparison of individual months can suggest a decrease in greenhouse trapping from cold to warm conditions, when the entire 4-yr record is considered a distinct increase in tropical-mean greenhouse trapping of ∼2 W m−2 is observed in conjunction with a ∼0.4 K increase in tropical-mean sea surface temperature. This observed increase compares favorably with GCM simulations of the change in the clear-sky greenhouse effect during El Niño–Southern Oscillation (ENSO). Superimposed on top of the SST-driven change in greenhouse trapping are dynamically induced changes in tropical moisture apparently associated with a redistribution of SST during ENSO. The GCM simulations also successfully reproduce this feature, providing reassurance in the ability of GCMs to predict both dynamically and thermodynamically driven changes in greenhouse trapping.

Corresponding author address: Dr. Brian J. Soden, GFDL/NOAA, Princeton University, P.O. Box 308, Princeton, NJ 08542.

Email: bjs@gfdl.gov

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