Measurements of atmospheric brightness temperature fluctuations and their implications on passive remote sensing

Probability theory for 3-layer remote sensing radiative transfer model: univariate case

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics.

Impact of atmospheric boundary layer turbulent temperature fluctuations on remote detection of vapors by passive infrared spectroscopy

A computational model to simulate the effects of boundary layer isotropic atmospheric turbulence on the radiative transfer process is presented. We perform a large number of simulations with stochastic ambient conditions to estimate the statistics necessary to predict the detection limit of a given trace gas. We find that the radiance and transmittance variability are primarily determined by the optical depth of the emitting atmosphere, and that the relative variability of the transmittance is an order of magnitude smaller than that of the radiance. We estimate that the atmospheric detection limit of a DMMP vapor cloud at 30 meters altitude for a ground-based observer ranges from 3.5 to 12 ppb-m, depending on the horizontal range to the cloud. Addition of uncorrelated detector noise has a disproportionate effect on the detection limit over the spectrally correlated turbulence noise. These calculations appear to be the first predictions of vapor detection limits that explicitly incorporate the effects of turbulence.