Analysis of 4.3-μm CO2 radiance data from the MSX (Midcourse Space Experiment) satellite has shown that gravity waves dominate the fluctuations of radiance at 4.3 μm for both earthlimb (above-the-horizon) and downlooking (below-the-horizon) lines-of-sight under a broad class of conditions. We review previous work on the spectra of known sources of gravity waves and on wave filtering mechanisms by M. J. Alexander and others, as well as the characteristics of gravity-wave power spectra. We then consider the power spectra of line-of-sight radiance fluctuations emitted and self-absorbed by an atmosphere perturbed by gravity waves, discussing the shape of the spectrum and the spectral slopes. We show examples of radiance spectra from gravity-wave-perturbed atmospheres that have two different slopes, with a steeper slope at large wavenumber, and discuss mechanisms that can account for this effect. The effect of latitude and season on the 4.3-μm fluctuations will also be considered.
An extensive database on spatial structure in the infrared radiance of the middle and upper atmosphere has been collected by the Mid-Course Space Experiment (MSX). The observed radiance contains spatial structure down to the scale of hundreds of meters. This spatial structure results from local fluctuations in the temperature and densities of the radiating states of the emitting molecular species as well as fluctuations in radiation transport from the emitting regions to the observer. A portion of this database has been analyzed to obtain statistical parameters characterizing stochastic spatial structure in the observed radiance. Using simple models, the observed statistics have been shown to agree with prior observations and theoretical models of stochastic spatial structure generated by gravity waves for special viewing geometries. The SHARC model has been extended to predict the statistics of stochastic fluctuations in infrared radiance from the statistics characterizing temperature fluctuations in the middle and upper atmosphere for arbitrary viewing geometries. SHARC model predictions have been compared with MSX data and shown to be in generally good agreement. Additional work is in progress to account for the statistics characterizing small spatial scale fluctuations.
Modem optical sensors can provide high quality multi/hyperspectral data at high spatial resolution, permitting the application of diverse and sophisticated algorithms for remote sensing of the terrain and atmosphere. With global coverage of perceptible cloud exceeding seventy-five percent [Wylie & Menzel, 1999], it is important that the effects of intervening cloud be anticipated and minimized to realize the full potential of such systems. Cloud contamination also bears on the more general issue of "information content" in a HSI data stream. This paper will describe the application of the Vis-LWIR scene simulation tools CLDSIM / GENESSIS / MOSART for assessing spectral/spatial matched-filter algorithms for the detection and classification of features-of-interest against terrain, with and without thin clouds. Following a review of the methodology, the sensitivity of matched-filter SNR to cloud-cover, vs GSD, as captured in sequential subsets of the primary principal-components will be presented. The potential for mis-classification due to undetected thin-clouds will also be described.
Radiation transport modulates the spatial frequencies of atmospheric structures, acting as a low pass filter, which causes the power spectra of the accumulated radiance to have different power spectral slopes than the underlying atmospheric structure. Additional effects arise because of the non-stationarity of the atmosphere. The SHARC atmospheric radiance code is used to model both non- stationarity of the atmosphere. The SHARC atmospheric radiance code is used to model both equilibrium and non- equilibrium radiance and radiance fluctuation statistics. It predicts two dimensions. Radiance spatial covariance functions and power spectral densities, PSDs. Radiance power spectral slopes for paths through isotropic Kolmogorov turbulence are predicted to vary from -5/3 to -8/3 depending on the length of the path through the turbulence. The input gravity wave 3D covariances and PSDs of atmospheric temperature are consistent with current gravity wave theory, having vertical and horizontal power spectral indices of -3 and -5/3, respectively. Altitude profiles of variances and correlation lengths account of the non-stationary of the gravity wave structure in the atmosphere. The radiance covariance and PSD power spectral slopes differ from the atmospheric gravity wave temperature model values of -3 and -5/3. These modulations depend on LOS orientations, and scale lengths of the sampled altitudes along the LOS.