Articles | Volume 9, issue 5
https://doi.org/10.5194/amt-9-1981-2016
https://doi.org/10.5194/amt-9-1981-2016
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

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Cited articles

Baldridge, A. M., Hook, S. J., Grove, C. I., and Rivera, G.: The ASTER spectral library ver. 2.0, Remote Sens. Environ., 113, 711–715, 2009.
Chahine, M. T.: Remote Sounding of Cloudy Atmospheres 1, Single Cloud Layer, J. Atmos. Sci., 31, 233–243, 1974.
Chang, F. L., Minnis, P., Lin, B., Khaiyer, M. M., Palikonda, R., and Spangenberg, D. A.: A modified method for inferring upper troposphere cloud top height using the GOES 12 imager 10.7 and 13.3 µm data, J. Geophys. Res.-Atmos., 115, D06208, https://doi.org/10.1029/2009jd012304, 2010.
Clough, S. A., Shephard, M. W., Mlawer, E., Delamere, J. S., Iacono, M., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, 2005.
Gero, P. J., Knuteson, R. O., Shiomi, K., Kuze, A., Kataoka, F., Revercomb, H. E., Tobin, D. C., Taylor, J. K., and Best, F. A.: GOSAT TANSO FTS TIR band calibration: a five year review, Proc. SPIE, 9263, 926316, 2014.
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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.