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www.atmos-meas-tech-discuss.net/2/1185/2009/
doi:10.5194/amtd-2-1185-2009
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under the Creative Commons Attribution 3.0 License.
Cloud detection for MIPAS using singular vector decomposition
1Atmospheric, Oceanic and Planetary Physics, Clarendon Laboratory, Department of Physics, Parks Road, Oxford, UK
*now at: Centre for Air Transport and the Environment, Manchester Metropolitan University, Oxford Road, Manchester, UK
Abstract. Clouds are increasingly recognised for their influence on the radiative balance of the Earth and the implications that they have on possible climate change, as well as in air pollution and acid-rain production. However, clouds remain a major source of uncertainty in climate models.
Satellite-borne high-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 thick cloud filling more than 30% of the measurement field-of-view (FOV). In order to resolve thin clouds, a new detection method using Singular Vector Decomposition (SVD) is formulated and tested. A rigorous comparison of the current operational and newly-developed detection methods for MIPAS is carried out – and the new SVD detection method has been proven to be much more reliable than the current operational method, and very sensitive even to thin clouds only marginally filling the MIPAS FOV.
Discussion Paper (PDF, 1958 KB) Interactive Discussion (Closed, 4 Comments) Final Revised Paper (AMT)
Citation: Hurley, J., Dudhia, A., and Grainger, R. G.: Cloud detection for MIPAS using singular vector decomposition, Atmos. Meas. Tech. Discuss., 2, 1185-1219, doi:10.5194/amtd-2-1185-2009, 2009. Bibtex EndNote Reference Manager XML
