Impact of temperature field inhomogeneities on the retrieval of atmospheric species from MIPAS IR limb emission spectra

Abstract

We examine volume mixing ratios (vmr) retrieved from limb emission spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on board Envisat. In level 2 (L2) data products of three different retrieval processors, which perform one dimensional (1-D) retrievals, we find significant differences between species' profiles from ascending and descending orbit parts. The relative differences vary systematically with time of the year, latitude, and altitude. In the lower stratosphere their monthly means can reach maxima of 20% for CFC-11, CFC-12, HNO<sub>3</sub>, H<sub>2</sub>O, 10% for CH<sub>4</sub> and N<sub>2</sub>O. Relative differences between monthly means of 1-D retrieval results and of the true atmospheric state can be expected to reach half of these percentage values, while relative differences in single vmr profiles might well exceed those numbers. Often there are no physical or chemical reasons for these differences, so they are an indicator for a problem in the data processing. The differences are generally largest at locations where the meridional temperature gradient of the atmosphere is strong. On the contrary, when performing the retrieval with a tomographic two dimensional (2-D) retrieval, L2 products generally do not show these differences. This suggests that inhomogeneities in the temperature field, and possibly in the species' fields, which are accounted for in the 2-D algorithm and not in standard 1-D processors, may cause significant deviations in the results. Inclusion of an externally given adequate temperature gradient in the forward model of a 1-D processor helps to reduce the observed differences. However, only the full tomographic 2-D approach is suitable to resolve the horizontal inhomogeneities. Implications for the use of the 1-D data, e.g. for validation, are discussed. The dependence of the ascending/descending differences on the observation strategy suggests that this problem may affect 1-D retrievals of infrared limb sounders, if the line of sight of the instrument has a significant component in the direction of the horizontal temperature variation

Position error in profiles retrieved from MIPAS observations with a 1-D algorithm

“…In this case the 2-D retrieval grid is fully independent from the measurement grid; the 2-D grid (typically profiles are retrieved at the average position of each limb-scan) is used to model the horizontal structures of the atmosphere. The MIPAS2D database of level 2 products ) generated with the GMTR analysis system has proven to be capable of properly representing the horizontal structures of the atmosphere that are cause of errors when neglected in 1-D algorithms (Kiefer et al, 2010).…”

“…The size of the possible geo-location error qualifies the retrieval products but it is not considered to be of concern within the retrieval process because, thanks to the horizontal homogeneity assumption, the profile position is not relevant within the portion of atmosphere spanned by the observations. However, the profile geo-location becomes relevant when it is used to identify coincidence with independent measurements or to calculate average distributions within predefined latitudinal bands (Kiefer et al, 2010).…”

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

“…In particular, we selected the geolocation of MIPAS measurements in the orbits 47 349 and 47 350 for 21 March, 48 671 and 48 672 for 21 June, 49 964 and 49 965 for 21 September and 51 301 and 51 302 for 21 December. Figure 1 shows an example of temperature, O 3 , HNO 3 and CH 4 EMAC distri- The results of Kiefer et al (2010) are based on the assumption that the average atmosphere in a given latitude band should not depend on longitude. Indeed, those averages are computed using several days of measurements allowing for an almost equal longitudinal distribution of ascending and descending profiles.…”

“…Comparing MIPAS/ENVISAT CFC-11 profiles with ACE (Atmospheric Chemistry Experiment) matching measurements, Höpfner et al (2007) discovered unrealistic differences between MIPAS nightside and dayside CFC-11 VMRs. These discrepancies were thoroughly investigated by Kiefer et al (2010) and were attributed to the unmodelled horizontal variability of the atmosphere in the ESA Level 2 processor. Similar horizontal gradients of temperature or composition are sounded by the instrument line of sight with the opposite sign in the ascending and the descending parts of the orbit.…”

“…geofit multi-target retrieval (GMTR, Carlotti et al, 2006) MIPAS Orbital Retrieval using Sequential Estimation (MORSE, Dudhia et al, 2005), 2-D retrieval code (RET2D, von Clarmann et al, 2003) and the 2-D option of the retrieval control programme (RCP, Steck et al, 2005), for SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) (Puķīte et al, 2008) and for MLS (Microwave Limb Sounder) (Livesey et al, 2006). Given the complexity of the 2-D retrieval models, von Clarmann et al (2009) and Kiefer et al (2010) evaluated the representation of the horizontal variability of the atmosphere with a temperature (T ) horizontal gradient model in the MIPAS 1-D retrieval codes. However, to date, the impact of neglecting the horizontal variability of the atmosphere and the relative improvements that can be achieved including a horizontal gradient model are still to be quantified.…”