Comparison of the GOSAT TANSO-FTS TIR CH4 volume mixing ratio vertical profiles with those measured by ACE-FTS, ESA MIPAS, IMK-IAA MIPAS, and 16 NDACC stations
Abstract. The primary instrument on the Greenhouse gases Observing SATellite (GOSAT) is the Thermal And Near infrared Sensor for carbon Observations (TANSO) Fourier transform spectrometer (FTS). TANSO-FTS uses three short-wave infrared (SWIR) bands to retrieve total columns of CO2 and CH4 along its optical line of sight and one thermal infrared (TIR) channel to retrieve vertical profiles of CO2 and CH4 volume mixing ratios (VMRs) in the troposphere. We examine version 1 of the TANSO-FTS TIR CH4 product by comparing co-located CH4 VMR vertical profiles from two other remote-sensing FTS systems: the Canadian Space Agency's Atmospheric Chemistry Experiment FTS (ACE-FTS) on SCISAT (version 3.5) and the European Space Agency's Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat (ESA ML2PP version 6 and IMK-IAA reduced-resolution version V5R_CH4_224/225), as well as 16 ground stations with the Network for the Detection of Atmospheric Composition Change (NDACC). This work follows an initial inter-comparison study over the Arctic, which incorporated a ground-based FTS at the Polar Environment Atmospheric Research Laboratory (PEARL) at Eureka, Canada, and focuses on tropospheric and lower-stratospheric measurements made at middle and tropical latitudes between 2009 and 2013 (mid-2012 for MIPAS). For comparison, vertical profiles from all instruments are interpolated onto a common pressure grid, and smoothing is applied to ACE-FTS, MIPAS, and NDACC vertical profiles. Smoothing is needed to account for differences between the vertical resolution of each instrument and differences in the dependence on a priori profiles. The smoothing operators use the TANSO-FTS a priori and averaging kernels in all cases. We present zonally averaged mean CH4 differences between each instrument and TANSO-FTS with and without smoothing, and we examine their information content, their sensitive altitude range, their correlation, their a priori dependence, and the variability within each data set. Partial columns are calculated from the VMR vertical profiles, and their correlations are examined. We find that the TANSO-FTS vertical profiles agree with the ACE-FTS and both MIPAS retrievals' vertical profiles within 4 % (± ∼ 40 ppbv) below 15 km when smoothing is applied to the profiles from instruments with finer vertical resolution but that the relative differences can increase to on the order of 25 % when no smoothing is applied. Computed partial columns are tightly correlated for each pair of data sets. We investigate whether the difference between TANSO-FTS and other CH4 VMR data products varies with latitude. Our study reveals a small dependence of around 0.1 % per 10 degrees latitude, with smaller differences over the tropics and greater differences towards the poles.
