Investigation of the adiabatic assumption for estimating cloud micro- and macrophysical properties from satellite and ground

Abstract

Abstract. In this study we investigate the accuracy of quantities relevant for the first indirect aerosol effect, with focus on the cloud droplet number concentration and cloud geometrical depth. The adiabatic cloud model is commonly applied to retrieve cloud micro- and macrophysical quantities from passive satellite sensors like SEVIRI or MODIS. As reference we use ground-based observations from a cloud radar, a microwave radiometer and a ceilometer. The cloud geometrical depth is obtained directly from these measurements. An optimal estimation technique was developed to retrieve profiles of droplet number concentration. Although the ground-based observations contain detailed information about the cloud vertical structure, there are also large uncertainties. We investigate four different cases of temporally homogeneous and inhomogeneous liquid cloud layers. Considering uncertainties for both ground-based and satellite-based retrievals we found a good agreement for observations under suitable conditions. Overall cloud layers were subadiabatic with values of the subadiabatic factor consistent with previous studies. The best match between satellite and ground perspective is found for one of the homogeneous cases where we obtained a relative mean difference of adiabatic cloud geometrical depth of 15% and a relative mean difference of cloud droplet number concentration of 27%. The estimation of cloud droplet number concentration is especially sensitive to radar reflectivity for the ground-based retrieval and to effective radius for the satellite retrieval.