Intercomparisons of cloud-top and cloud-base heights from ground-based Lidar, CloudSat and CALIPSO measurements

Abstract

This study presents results of the intercomparison of cloud-top height (CTH) and cloud-bottom height (CBH) obtained from a space-borne active sensor Cloud Profiling Radar (CPR), the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), the space-borne passive sensor Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based Lidar measurements. Three selected cases (one daytime and two night-time cases) involving various cloud conditions such as semi-transparent thin cirrus, opaque thick tropospheric clouds and multi-layered clouds are studied, with special attention to CBH. The space-based CALIOP provides reliable heights of thin high-altitude cirrus clouds containing small ice particles, but the 94 GHz CPR has low sensitivity to these clouds. The CTHs retrieved from the CPR and CALIOP for thick tropospheric clouds are in good agreement with each other. Discrepancies between the CPR and the CALIOP values of the CBH for thick opaque clouds arise from strong Lidar signal attenuations. In cloud-overlap conditions (i.e. multi-layered clouds are present), the CALIOP has difficulties in determining the cloud vertical structure (CVS) for thick clouds underlying thin cirrus clouds due to signal attenuations, whereas the CPR detects the CTH and CBH of both the cloud layers. This fact is also confirmed by the comparison of seasonal variations of occurrences of CBH and CTH retrieved from 1 year measurements. The CBHs derived from the CPR and ground-based Lidar are generally in good agreement with each other. Especially, comparison of CBH between the ground-based Lidar and CPR retrieved from June 2006 to October 2008 shows an excellent linear relationship (coefficient of determination, R ² ∼ 0.996).

Acknowledgements

This study was supported by the Korea Meteorological Administration R&D programs under the grant CATER 2006–4104 and the BK 21 Program of the School of Earth and Environmental Sciences (SEES), Seoul National University (SNU). We are extremely grateful to the entire CloudSat, CALIPSO and MODIS Science Teams for providing the data.