Monte Carlo modeling of multiply scattered laser ceilometer returns

Abstract

Initial analysis of the data from the laser ceilometer used during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) and Atlantic Stratocumulus Transition Experiment (ASTEX) programs indicated that clouds were sometimes not reported even though clouds were visible over the ceilometer. In order to understand this inconsistency, a model using Monte Carlo techniques has been refined to study the effect that multiple scattering and other physical processes have on near infrared laser ceilometer returns. The model traces photon paths through three orders of scattering within various scattering media and determines the photon's probability of returning to the receiver at each scattering point. The Monte Carlo model allows for a limited number of horizontal and vertical inhomogeneities in the extinction coefficient and scattering phase function within the scattering media. Clear air and background aerosol scattering, based on published standards are also introduced within the model. Results from the current model are compared with previously published results. Specific atmospheric media and laser ceilometer parameters are modeled, and a factor, a, is defined to measure the effects of each. Results from the model indicate that precipitation and extinction by the subcloud layer have the most significant impact upon the return signal. For clouds with the same optical depth, those with an increasing extinction with depth exhibited a flatter, smaller magnitude return signal than those with a constant or decreasing extinction. Rayleigh scattering and background aerosols in the subcloud layer decrease the return signal from the cloud and introduce a background level of return from below the cloud. Rain in the subcloud layer lowers the return signal from the cloud, but increases the signal from the subcloud layer due to its relatively large extinction, while realistic levels of absorption have no significant impact. Lastly, a quantitative assessment of detectability for clouds is made, based on amin as a threshold. Model results indicate that conditions can exist where a cloud may not be identified by the laser ceilometer.