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www.atmos-meas-tech.net/2/533/2009/
doi:10.5194/amt-2-533-2009
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under the Creative Commons Attribution 3.0 License.
Cloud detection for MIPAS using singular vector decomposition
Atmospheric, Oceanic and Planetary Physics, Clarendon Laboratory, Department of Physics, Parks Road, Oxford, UK
Abstract. Satellite-borne high-spectral-resolution limb sounders, such as the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard ENVISAT, provide information on clouds, especially optically thin clouds, which have been difficult to observe in the past. The aim of this work is to develop, implement and test a reliable cloud detection method for infrared spectra measured by MIPAS.
Current MIPAS cloud detection methods used operationally have been developed to detect cloud effective filling more than 30% of the measurement field-of-view (FOV), under geometric and optical considerations – and hence are limited to detecting fairly thick cloud, or large physical extents of thin cloud. In order to resolve thin clouds, a new detection method using Singular Vector Decomposition (SVD) is formulated and tested. This new SVD detection method has been applied to a year's worth of MIPAS data, and qualitatively appears to be more sensitive to thin cloud than the current operational method.
Final Revised Paper (PDF, 4475 KB) Discussion Paper (AMTD)
Citation: Hurley, J., Dudhia, A., and Grainger, R. G.: Cloud detection for MIPAS using singular vector decomposition, Atmos. Meas. Tech., 2, 533-547, doi:10.5194/amt-2-533-2009, 2009. Bibtex EndNote Reference Manager XML
