Scientific Results

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

Year: 2016

Authors: Castelli E., Ridolfi M., Carlotti M., Sinnhuber BM.; Kirner O.; Kiefer M.; Dinelli BM.

Autors Affiliation: CNR, ISAC, Bologna, Italy
Univ Bologna, Dipartimento Fis & Astron, Bologna, Italy
Univ Bologna, Dipartimento Chim Ind Toso Montanari, Bologna, Italy;
Karlsruhe Inst Technol, IMK ASF, Karlsruhe, Germany;
Karlsruhe Inst Technol, Steinbuch Ctr Comp, Karlsruhe, Germany;
CNR, IFAC, Ist Fis Applicata Nello Carrara, Florence, Italy

Abstract: 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. 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. Our results highlight that the 1-D retrieval implies errors that are significant for averages of profiles. Furthermore, for some targets (e.g. T, CH4 and N2O below 10 hPa) the error induced by the 1-D approximation also becomes visible in the individual retrieved profiles. The inclusion of any kind of horizontal variability model improves all the targets with respect to the horizontal homogeneity assumption. For temperature, HNO3 and CFC-11, the inclusion of an horizontal temperature gradient leads to a significant reduction of the error. For other targets, such as H2O, O-3, N2O, CH4, the improvements due to the inclusion of an horizontal temperature gradient are minor. In these cases, the inclusion of a gradient 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. This residual error of the 2-D approach is the smoothing caused by the retrieval grid, which is coarser than that of the atmospheric model.

Journal/Review: ATMOSPHERIC MEASUREMENT TECHNIQUES

Volume: 9 (11)      Pages from: 5499  to: 5508

More Information: This work was performed under ESA-ESRIN Contract no. 21719/08/I-OL. The authors gratefully acknowledge Richard Siddans (RAL) for proofreading the manuscript and ECMWF for access to data.
KeyWords: LIMB; TEMPERATURE; MODEL
DOI: 10.5194/amt-9-5499-2016

Citations: 3
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2021-10-17
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