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

In this paper we quantify the errors induced by this assumption and evaluate the performances of three different algorithms that can be used to mitigate the problem. We generate synthetic observations with a high spatial resolution atmospheric model and carry out the retrievals with four alternative methods. The first assumes horizontal homogeneity (1-D retrieval), the second includes a model of the horizontal gradient of atmospheric temperature (1-D plus temperature gradient retrieval), the third accounts for an horizontal gradient of temperature and composition (1-D plus temperature and composition gradient retrieval), while the fourth is the full two-dimensional (2-D) inversion approach.

MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) is a mid-infrared limb emission sounder that operated on board the polar satellite ENVISAT from 2002 to 2012. The retrieval algorithm used by the European Space Agency to process MIPAS measurements exploits the assumption that the atmosphere is horizontally homogeneous. However, previous studies highlighted how this assumption causes significant errors on the retrieved profiles of some MIPAS target species.