Development of a global cloud model for simulating earth-viewing space missions.

Abstract

Existing global cloud models are improved and expanded so that they might be more effectively used in planning and evaluating potential earth-viewing space missions. A relationship is developed between the ground and satellite-derived cloud-amount frequency distributions. This relationship is used to improve internal consistency between the ground-observed unconditional statistics and the satellite-derived conditional statistics as tabulated in previous models. A statistical technique is developed which permits the scaling of the conditional statistics to time and distance separations other than those for which the data base is tabulated. A new technique to increase or decrease the representative area size of the statistical data base is developed. Both the scaling and area adjustment techniques are shown to represent significant improvements over the techniques previously employed.