Articles | Volume 9, issue 11
Atmos. Meas. Tech., 9, 5499–5508, 2016
https://doi.org/10.5194/amt-9-5499-2016
Atmos. Meas. Tech., 9, 5499–5508, 2016
https://doi.org/10.5194/amt-9-5499-2016

Research article 18 Nov 2016

Research article | 18 Nov 2016

Errors induced by different approximations in handling horizontal atmospheric inhomogeneities in MIPAS/ENVISAT retrievals

Elisa Castelli et al.

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Cited articles

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Carlotti, M., Brizzi, G., Papandrea, E., Prevedelli, M., Ridolfi, M., Dinelli, B. M., and Magnani, L.: GMTR: Two-dimensional geofit multitarget retrieval model for Michelson Interferometer for Passive Atmospheric Sounding/Environmental Satellite observations, Appl. Opt., 45, 716–727, 2006.
Carlotti, M., Arnone, E., Castelli, E., Dinelli, B. M., and Papandrea, E.: Position error in profiles retrieved from MIPAS observations with a 1-D algorithm, Atmos. Meas. Tech., 6, 419–429, https://doi.org/10.5194/amt-6-419-2013, 2013.
Dudhia, A., Jay, V. L., and Rodgers, C. D.: MIPAS Orbital Retrieval using Sequential Estimation, Earth Observation Data Group, Department of Physics, University of Oxford, available at: http://www.atm.ox.ac.uk/MORSE/ (last access: 14 November 2016), 2005.
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Short summary
MIPAS is a satellite-borne limb emission sounder. The algorithm used to infer atmospheric composition from its measurements exploits the assumption that the atmosphere is horizontally homogeneous. This assumption can cause significant errors. We use synthetic observations to quantify these errors. Furthermore we show that the inclusion of any kind of horizontal variability model improves all the retrieval targets and that the two-dimensional approach implies the smallest errors.