IMK/IAA MIPAS temperature retrieval version 8: nominal measurements

Abstract

Abstract. A new global set of atmospheric temperature profiles is retrieved from recalibrated radiance spectra recorded with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Changes with respect to previous data versions include a new radiometric calibration considering the time-dependency of the detector non-linearity, and a more robust frequency calibration scheme. Temperature is retrieved using a smoothing constraint, while tangent altitude pointing information is constrained using optimal estimation. ECMWF ERA-Interim is used as temperature a priori below 43 km. Above, a priori data is based on data from the Whole Atmosphere Community Climate Model Version 4 (WACCM4). Bias-corrected fields from specified dynamics runs, sampled at the MIPAS times and locations, are used, blended with ERA-Interim between 43 and 53 km. Horizontal variability of temperature is considered by scaling an a priori 3D temperature field in the orbit plane in a way that the horizontal structure is provided by the a priori while the vertical structure comes from the measurements. Additional microwindows with better sensitivity at higher altitudes are used. The background continuum is jointly fitted with the target parameters up to 58 km altitude. The radiance offset correction is strongly regularized towards an empirically determined vertical offset profile. In order to avoid the propagation of uncertainties of O3 and H2O a priori assumptions, the abundances of these species are retrieved jointly with temperature. The retrieval is based on HITRAN 2016 spectroscopic data, with a few amendments. Temperature-adjusted climatologies of vibrational populations of CO2 states emitting in the 15 micron region are used in the radiative transfer modelling in order to account for non-local thermodynamic equilibrium. Numerical integration in the radiative transfer model is now performed at higher accuracy. The random component of the temperature uncertainty typically varies between 0.4 and 0.8 K, with occasional excursions up to 1.3 K above 60 km altitude. The leading sources of the random component of the temperature error are measurement noise, gain calibration uncertainty, spectral shift, and uncertain CO2 mixing ratios. The systematic error is caused by uncertainties in spectroscopic data and line shape uncertainties. It ranges from 0.2 K at 24 km altitude for northern midlatitude nighttime conditions to 2.3 K at 12 km for tropical nighttime conditions. The estimated total uncertainty amounts to values between 0.5 K at 24 km and northern polar winter conditions to 2.3 K at 12 km and northern midlatitude day conditions. The vertical resolution varies around 3 km for altitudes below 50 km. The long-term drift encountered in the previous temperature product has been largely reduced. The consistency between high spectral resolution results from 2002–2004 and the reduced spectral resolution results from 2005–2012 has been largely improved. As expected, most pronounced temperature differences between version 8 and previous data versions are found in elevated stratopause situations. The fact that the phase of temperature waves seen by MIPAS is not locked to the wave phase found in ECMWF analyses demonstrates that our retrieval provides independent information and does not merely reproduce the prior information.

An optimal estimation-based retrieval of upper atmospheric oxygen airglow and temperature from SCIAMACHY limb observations

“…We use the nominal temperature profiles from version 8 of MIPAS Level 2 data retrieved by the European Space Agency (ESA; Dinelli et al, 2021). Version 8 data from the other modes are obtained through the Institute of Meteorology and Climate Research in cooperation with the Instituto de Astrofísica de Andalucía (IMK/IAA) retrieval algorithm (García-Comas et al, 2012;Kiefer et al, 2021). The typical total errors are 0.5-2 K below 70 km and 2-7 K above (for MA, UA, and NLC modes).…”

Level 2 processor and auxiliary data for ESA Version 8 final full mission analysis of MIPAS measurements on ENVISAT

“…The end of the mission did not stop the work on improving the data, and two sets of full mission reprocessing were performed: one with the MIPAS Level 2 Processor Prototype (ML2PP) code Version 6 (V6; Raspollini et al, 2013) using L1b V5 data, and the second with ML2PP V7 (De Laurentis et al, 2016;Valeri et al, 2017) with L1b V7 data. These two sets of ESA reprocessing were performed with improvements to the original NRT algorithm, but other independent L2 reprocessing was also performed (Dinelli et al, 2010;Dudhia, 2008;Kiefer et al, 2021).…”

The ESA MIPAS/Envisat level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22

“…Over the years, the code has been improved both to follow the evolution of the measurement strategies and to adopt new strategies suggested by the analysis of the quality of the retrieved products (Raspollini et al, 2006. Besides ESA data, there is a series of independent level-2 databases produced with MIPAS observations, at Oxford University (Dudhia and Piccolo, 2007), at the Karlsruhe Institute of Technology (von Clarmann et al, 2009a(von Clarmann et al, , 2003Milz et al, 2005;Kiefer et al, 2021), and at ISAC-CNR Bologna (Dinelli et al, 2010), which include different targets and use different analysis strategies. Recently, a new version of ORM, ORM v8.22 , has been developed for processing the final release of MIPAS level-1b data and producing the final version of the ESA level-2 MIPAS products.…”