Evaluating of passive cloud-type classification using active-passive EarthCARE measurements

Observations from CloudSat and CALIPSO have demonstrated that the interpretation of cloud radiances derived from passive measurements must be reconsidered in light of vertically resolved profile information. The ESA Cloud, Aerosol and Radiation Explorer (EarthCARE) mission provides a unique opportunity to continue this reinterpretation by combining active and passive measurements from a single satellite platform, enabling a direct linkage between nadir profiling observations and swath-based imagery.

EarthCARE carries an active backscatter lidar (ATLID) and a cloud profiling radar (CPR), which provide high–spatial-resolution vertical profiles of cloud and aerosol properties along the satellite track. These active instruments operate in nadir view, while the passive multispectral imager (MSI) observes a 150 km wide swath with a spatial resolution of 500 m. In combination with the broadband radiometer (BBR), the passive MSI measurements enable the assessment of cloud radiative impacts and cloud feedbacks through their influence on radiative fluxes at the top of the atmosphere. The active radar–lidar synergy provides complementary information on cloud vertical structure, including cloud base altitude and estimates of liquid and ice water content, thereby contributing to the characterization of vertical profiles of cloud changes. To quantify the representation of cloud types from passive observations, the cloud classification framework introduced by the International Satellite Cloud Climatology Project (ISCCP) is applied. Cloud types are characterized using radiometric brightness temperature, interpreted as cloud-top height, and visible reflectance, interpreted as optical thickness, as retrieved from MSI. This cloud type histogram is analysed using vertically resolved cloud information from active measurements. The availability of active profile measurements makes it possible to augment the traditional two-dimensional ISCCP cloud-type histograms with vertically resolved cloud information. This combined perspective allows a more detailed understanding of how specific cloud types and regimes contribute to radiative fluxes at the top of the atmosphere and how changes in cloud vertical structure influence cloud feedbacks.