The Experimental Cloud Lidar Pilot Study (ECLIPS) was initiated to obtain statistics on cloud-base height, extinction, optical depth, cloud brokenness, and surface fluxes. Two observational phases have taken place, in October-December 1989 and April-July 1991, with intensive 30-day periods being selected within the two time intervals. Data are being archived at NASA Langley Research Center and, once there, are readily available to the international scientific community. This article describes the scale of the study in terms of its international involvement and in the range of data being recorded. Lidar observations of cloud height and backscatter coefficient have been taken from a number of ground-based stations spread around the globe. Solar shortwave and infrared longwave fluxes and infra-red beam radiance have been measured at the surface wherever possible. The observations have been tailored to occur around the overpass times of the NOAA weather satellites. This article describes in some detail the various retrieval methods used to obtain results on cloud-base height, extinction coefficient, and infrared emittance, paying particular attention to the uncertainties involved. The above methods are then illustrated by both model simulations and by selected results from various laboratories. The ECLIPS data are shown to represent a valuable resource for cloud parameter-izations in models and for model validations.

The operation of an airborne lidar intended for the detection of fish schools is numerically simulated by the Monte Carlo method. The calculations are performed for schools located at small depths in order to study the regularities in the shaping of the lidar return accurately. Three models of the phase function of scattering of laser radiation in sea water are used. The signals reflected from surface waters that contain a school of fish are determined as a function of the lidar parameters, light scattering and absorption coefficients in the water, stratification of light scattering layers, and fish-school depth. The results obtained can be used for interpreting the signals of the fish-detection lidar.

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