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Multispectral analysis of a tropical radiance set from the TIROS operational vertical sounder

L. L. Anderson

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Abstract

This research examines the information content of the TIROS-N Operational Vertical Sounder (TOVS) during 20-29 Jan 1979 over the tropical Pacific Ocean. Vertical, horizontal, and temporal statistical characteristics are examined. The TOVS channels are highly correlated except for the infrared water vapor channels and the microwave window and 300 mb channels. The horizontal structure varies according to spectral channel (absorbing constituent and effective evaluation), geography, and synoptic condition. Horizontal correlation is particularly sensitive to water vapor and cloud amount. In equatorial sectors, moisture channels have higher correlations and larger length scales than thermal sensing channels; in the subtropics, the opposite is true. Temporal variation is largest in the water vapor and microwave window channels, and in synoptically active regions with brightness temperature variances typically ten times larger than in synoptically quiescent regions. Attempts to augment TOVS data in cloudy regions and for missing passed using a full quadratic response surface regression model were only marginally successful. TVOS channels with peak energy contribution from below 90 mb were synthesized using principal components analysis. Over 94% of the areal variance at any particular time is represented by the first 5 eigenfunctions.

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What this paper is about

This research examines the information content of the TIROS-N Operational Vertical Sounder (TOVS) during 20-29 Jan 1979 over the tropical Pacific Ocean. Vertical, horizontal, and temporal statistical characteristics are examined. The TOVS channels are highly correlated except for the infrared water vapor channels and the microwave window and 300 mb channels. The horizontal structure varies according to spectral channel (absorbing constituent and effective evaluation), geography, and synoptic condition. Horizontal correlation is particularly sensitive to water vapor and cloud amount. In equatorial sectors, moisture channels have higher correlations and larger length scales than thermal sensing channels; in the subtropics, the opposite is true. Temporal variation is largest in the water vapor and microwave window channels, and in synoptically active regions with brightness temperature variances typically ten times larger than in synoptically quiescent regions. Attempts to augment TOVS data in cloudy regions and for missing passed using a full quadratic response surface regression model were only marginally successful. TVOS channels with peak energy contribution from below 90 mb were synthesized using principal components analysis. Over 94% of the areal variance at any particular time is represented by the first 5 eigenfunctions.

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Available abstract

This research examines the information content of the TIROS-N Operational Vertical Sounder (TOVS) during 20-29 Jan 1979 over the tropical Pacific Ocean. Vertical, horizontal, and temporal statistical characteristics are examined. The TOVS channels are highly correlated except for the infrared water vapor channels and the microwave window and 300 mb channels. The horizontal structure varies according to spectral channel (absorbing constituent and effective evaluation), geography, and synoptic condition. Horizontal correlation is particularly sensitive to water vapor and cloud amount. In equatorial sectors, moisture channels have higher correlations and larger length scales than thermal sensing channels; in the subtropics, the opposite is true. Temporal variation is largest in the water vapor and microwave window channels, and in synoptically active regions with brightness temperature variances typically ten times larger than in synoptically quiescent regions. Attempts to augment TOVS data in cloudy regions and for missing passed using a full quadratic response surface regression model were only marginally successful. TVOS channels with peak energy contribution from below 90 mb were synthesized using principal components analysis. Over 94% of the areal variance at any particular time is represented by the first 5 eigenfunctions.

Key concepts: Radiance, Multispectral image, Remote sensing, Environmental science, Meteorology, Geology, Geography

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