On the information content of the thermal infrared cooling rate profile from satellite instrument measurements

Abstract

This work investigates how remote sensing of the quantities required to calculate clear-sky cooling rate profiles propagates into cooling rate profile knowledge. The formulation of a cooling rate profile error budget is presented for clear-sky scenes given temperature, water vapor, and ozone profile uncertainty. Using linear propagation of error analysis, an expression for the cooling rate profile covariance matrix is given. Some of the features of the cooling rate covariance matrix are discussed, and it is found that nonzero error correlations in the temperature, water vapor, and ozone retrieval profiles must be considered to produce an unbiased estimate of cooling rate profile variance and the covariance structure. To that end, the exclusion of the details of this error correlation leads to an underestimation of the cooling rate profile uncertainty. This work then examines the assumptions made in the course of deriving the expression for the cooling rate covariance matrix by using ERA-40 Reanalysis data. It is established that the assumptions of linear error propagation and Gaussian statistics are generally tenable. Next, the information content of thermal infrared spectra with respect to clear-sky cooling rate profiles is investigated. Several formerly- and currently-operational spectrometers are compared with different spectral coverage, resolution, signal-to-noise ratio. Among these, IASI is found to have the ability to provide the greatest amount of information on the cooling rate profile. Also, it may be scientifically useful to develop far-infrared missions in terms of cooling rate profile analysis.

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