Water Vapor, Surface Temperature, and the Greenhouse Effect—A Statistical Analysis of Tropical-Mean Data

Hu Yang Department of Applied Mathematics, University of Washington, Seattle, Washington

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Ka Kit Tung Department of Applied Mathematics, University of Washington, Seattle, Washington

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Abstract

Water vapor feedback is one of the important factors that determine the response of the atmosphere to surface warming. To take into account the compensating drying effects in downdraft regions, averaging over the whole Tropics is necessary. However, this operation drastically reduces the number of degrees of freedom and raises questions concerning the statistical significance of any correlative results obtained using observational data. A more involved statistical analysis is performed here, using multiple datasets, including the global water vapor datasets of Special Sensor for Microwave/Imaging (column water), upper-tropospheric relative humidity, the Television Infrared Observational Satellite Operational Vertical Sounder retrieved upper-tropospheric specific humidity, and the surface temperature data from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis dataset. The tropical-mean correlations between relative humidity and surface temperature cannot be established, but those between specific humidity and the surface temperature are found to be positive and shown to be statistically significant. This conclusion holds even when the averaging is done on the natural logarithm of the upper-tropospheric water vapor content. The effect on the tropical-mean outgoing longwave radiation is also discussed.

Corresponding author address: Dr. Ka Kit Tung, Department of Applied Mathematics, University of Washington, Box 352420, Seattle, WA 98195.

Abstract

Water vapor feedback is one of the important factors that determine the response of the atmosphere to surface warming. To take into account the compensating drying effects in downdraft regions, averaging over the whole Tropics is necessary. However, this operation drastically reduces the number of degrees of freedom and raises questions concerning the statistical significance of any correlative results obtained using observational data. A more involved statistical analysis is performed here, using multiple datasets, including the global water vapor datasets of Special Sensor for Microwave/Imaging (column water), upper-tropospheric relative humidity, the Television Infrared Observational Satellite Operational Vertical Sounder retrieved upper-tropospheric specific humidity, and the surface temperature data from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis dataset. The tropical-mean correlations between relative humidity and surface temperature cannot be established, but those between specific humidity and the surface temperature are found to be positive and shown to be statistically significant. This conclusion holds even when the averaging is done on the natural logarithm of the upper-tropospheric water vapor content. The effect on the tropical-mean outgoing longwave radiation is also discussed.

Corresponding author address: Dr. Ka Kit Tung, Department of Applied Mathematics, University of Washington, Box 352420, Seattle, WA 98195.

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