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MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is amid-infrared limb emission sounder that operated on board the polar satelliteENVISAT from 2002 to 2012. The retrieval algorithm used by the European SpaceAgency to process MIPAS measurements exploits the assumption that theatmosphere is horizontally homogeneous. However, previous studies highlightedhow this assumption causes significant errors on the retrieved profiles ofsome MIPAS target species.In this paper we quantify the errors induced by this assumption and evaluatethe performances of three different algorithms that can be used to mitigatethe problem. We generate synthetic observations with a high spatialresolution atmospheric model and carry out the retrievals with fouralternative methods. The first assumes horizontal homogeneity (1-D retrieval),the second includes a model of the horizontal gradient of atmospherictemperature (1-D plus temperature gradient retrieval), the third accounts foran horizontal gradient of temperature and composition (1-D plus temperatureand composition gradient retrieval), while the fourth is the fulltwo-dimensional (2-D) inversion approach.Our results highlight that the 1-D retrieval implies errors that aresignificant for averages of profiles. Furthermore, for some targets (e.g.T, CH4 and N2O below 10 hPa) the error induced by the 1-Dapproximation also becomes visible in the individual retrieved profiles. Theinclusion of any kind of horizontal variability model improves all thetargets with respect to the horizontal homogeneity assumption. Fortemperature, HNO3 and CFC-11, the inclusion of an horizontal temperaturegradient leads to a significant reduction of the error. For other targets, such asH2O, O3, N2O, CH4, the improvements due to the inclusion of anhorizontal temperature gradient are minor. In these cases, the inclusion of agradient in the target volume mixing ratio leads to significant improvements.Among all the methods tested in this work, the 2-D approach, as expected,implies the smallest errors for almost all the target parameters. Thisresidual error of the 2-D approach is the smoothing caused by the retrievalgrid, which is coarser than that of the atmospheric model

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