Articles | Volume 9, issue 5
Research article
03 May 2016
Research article |  | 03 May 2016

A development of cloud top height retrieval using thermal infrared spectra observed with GOSAT and comparison with CALIPSO data

Yu Someya, Ryoichi Imasu, Naoko Saitoh, Yoshifumi Ota, and Kei Shiomi

Abstract. An algorithm based on CO2 slicing, which has been used for cirrus cloud detection using thermal infrared data, was developed for high-resolution radiance spectra from satellites. The channels were reconstructed based on sensitivity height information of the original spectral channels to reduce the effects of measurement errors. Selection of the reconstructed channel pairs was optimized for several atmospheric profile patterns using simultaneous studies assuming a cloudy sky. That algorithm was applied to data by the Greenhouse gases Observing SATellite (GOSAT). Results were compared with those obtained from the space-borne lidar instrument on-board Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Monthly mean cloud amounts from the slicing generally agreed with those from CALIPSO observations despite some differences caused by surface temperature biases, optically very thin cirrus, multilayer structures of clouds, extremely low cloud tops, and specific atmospheric conditions. Comparison of coincident data showed good agreement, except for some cases, and revealed that the improved slicing method is more accurate than the traditional slicing method. Results also imply that improved slicing can detect low-level clouds with cloud top heights as low as approximately 1.5 km.

Short summary
This article presents an algorithm for cloud detection using TIR radiance spectra based on the CO2 slicing technique for improvement of GHG observation from space. The key techniques of the algorithm are channel reconstruction and their optimization for increasing sensitivity and accuracy. The analysis results using GOSAT data show general agreement with those from CALIPSO. It can be expected that this algorithm would improve the accuracy of cloud screening and gas retrievals from GOSAT data.