This work presents a study on the sensitivity of two satellite cloud height retrievals to cloud vertical distribution. The difference in sensitivity is exploited by relating the difference in the retrieved cloud heights to cloud vertical extent. The two cloud height retrievals, performed within the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) algorithm, are based on independent measurements and different retrieval techniques. First, cloud top temperature (CTT) is retrieved from Advanced Along Track Scanning Radiometer (AATSR) measurements in the thermal infrared. Second, cloud top pressure (CTP) is retrieved from Medium Resolution Imaging Spectrometer (MERIS) measurements in the oxygen-A absorption band. Both CTT and CTP are converted to cloud top height (CTH) using atmospheric profiles from a numerical weather prediction model. A sensitivity study using radiative transfer simulations in the near- infrared and thermal infrared were performed to demonstrate the larger impact of the assumed cloud vertical extinction profile on MERIS than on AATSR top- of-atmosphere measurements. The difference in retrieved CTH (ΔCTH) from AATSR and MERIS are related to cloud vertical extent (CVE) as observed by ground- based lidar and radar at three ARM sites. To increase the impact of the cloud vertical extinction profile on the MERIS-CTP retrievals, single-layer and geometrically thin clouds are assumed in the forward model. The results of the comparison to the ground-based observations were separated into single-layer and multi-layer cloud cases. Analogous to previous findings, the MERIS-CTP retrievals appear to be close to pressure levels in the middle of the cloud. Assuming a linear relationship, the ΔCTH multiplied by 2.5 gives an estimate on the CVE for single-layer clouds. The relationship is weaker for multi-layer clouds. Due to large variations of cloud vertical extinction profiles occurring in nature, a quantitative estimate of the cloud vertical extent is accompanied with large uncertainties. Yet, estimates of the CVE can contribute to the characterization of a cloudy scene. To demonstrate the plausibility of the approach, an estimate of the CVE was applied to a case study. In light of the follow-up mission Sentinel-3 with AATSR and MERIS like instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and (Ocean and Land Colour Instrument) OLCI, respectively, for which the FAME-C algorithm can be easily adapted, a more accurate estimate of the CVE can be expected. OLCI will have three channels in the oxygen-A absorption band, thus providing more pieces of information on the cloud vertical extinction profile.
