The horizontal resolution of MIPAS

Abstract

Abstract. Limb remote sensing from space provides atmospheric composition measurements at high vertical resolution while the information is smeared in the horizontal domain. The horizontal components of two-dimensional (altitude and along-track coordinate) averaging kernels of a limb retrieval constrained to horizontal homogeneity can be used to estimate the horizontal resolution of limb retrievals. This is useful for comparisons of measured data with modeled data, to construct horizontal observation operators in data assimilation applications or when measurements of different horizontal resolution are intercompared. We present these averaging kernels for retrievals of temperature, H2O, O3, CH4, N2O, HNO3 and NO2 from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) high-resolution limb emission spectra. The horizontal smearing of a MIPAS retrieval in terms of full width at half maximum of the rows of the horizontal averaging kernel matrix varies typically between about 200 and 350 km for most species, altitudes and atmospheric conditions. The range where 95% of the information originates from varies from about 260 to 440 km for these cases. This information spread is smaller than the MIPAS horizontal sampling, i.e. MIPAS data are horizontally undersampled, and the effective horizontal resolution is driven by the sampling rather than the smearing. The point where the majority of the information originates from is displaced from the tangent point towards the satellite by typically less than 10 km for trace gas profiles and about 50 to 100 km for temperature, with a few exceptions for uppermost altitudes. The geolocation of a MIPAS profile is defined as the tangent point of the middle line of sight in a MIPAS limb scan. The majority of the information displacement with respect to this nominal geolocation of the measurement is caused by the satellite movement and the geometrical displacement of the actual tangent point as a function of the elevation angle.

Tomographic retrieval approach for mesoscale gravity wave observations by the PREMIER Infrared Limb-Sounder

“…In this form, the full-width at half-max of the vertical and horizontal direction can be calculated (e.g. Steck et al, 2005;von Clarmann et al, 2009). Figure 8 shows exemplarily the estimated horizontal and vertical resolution.…”

Harmonisation and diagnostics of MIPAS ESA CH<sub>4</sub> and N<sub>2</sub>O profiles using data assimilation

“…Figure 6 shows the evolution of the cost function at the analysis point J (x a ) weighted by the number of observations p, for the period April-November 2008. If the error statistics used in the assimilation system are consistent with the O-F residuals then the value of J (x a )/p should be close to 1/2 (Talagrand, 2010). Note that this is a necessary but not sufficient condition.…”

“…However, the latitude and longitude of the tangent point are used in the observation operator instead of the average latitude and longitude of the profile. This provides most of the correction given by the horizontal AKs (von Clarmann et al, 2009).…”

The MIPAS2D database of MIPAS/ENVISAT measurements retrieved with a multi-target 2-dimensional tomographic approach

“…MIPAS limb-scans are individually analysed by ORM, using the geolocation of the tangent points to define the retrieval grid. As a consequence, the retrieved profiles are calculated on a sparse horizontal and vertical grid, and the horizontal resolution is implicitly defined by the separation between adjacent scans (see von Clarmann et al, 2009b).…”