Preprints
https://doi.org/10.5194/amt-2023-237
https://doi.org/10.5194/amt-2023-237
15 Nov 2023
 | 15 Nov 2023
Status: this preprint is currently under review for the journal AMT.

Independent validation of IASI/METOP-A LMD and RAL CH4 products using CAMS model, in situ profiles and ground-based FTIR measurements

Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge

Abstract. In this study, we carried out an independent validation of two methane retrieval algorithms using spectra from the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Meteorological Operational satellite programme-A (MetOp-A) since 2006. Both algorithms, one developed by the Laboratoire de Météorologie Dynamique (LMD), called the non-linear inference scheme (NLISv8.3), the other by the Rutherford Appleton Laboratory (RAL), referred to as RALv2.0, provide longterm global CH4 concentrations using distinctively different retrieval approaches (Neural Network vs. Optimal Estimation, respectively). They also differ with respect to the vertical range covered, where LMD provides mid-tropospheric dry air mole fractions (mtCH4) and RAL provides mixing ratio profiles from which we can derive total column-averaged dry air mole fractions (XCH4) and potentially 2 partial column layers (qCH4).

We compared both CH4 products using the Copernicus Atmospheric Monitoring Service (CAMS) model, in situ profiles (range extended using CAMS model data) and ground-based Fourier transform infrared (FTIR) remote sensing measurements. The average difference in mtCH4 with respect to in situ profiles for LMD ranges between -0.3 and 10.9 ppb while for RAL the XCH4 difference ranges between -10.2 and -4.6 ppb. The standard deviation (stdv) of the observed differences between in situ and RAL retrievals is 14.5–23.0 ppb, which is consistently smaller than that between in situ and LMD retrievals about 15.2–30.6 ppb. By comparing with ground-based FTIR sites, the mean difference is within ±10 ppb for both RAL and LMD retrievals. However, the stdv of the differences at the ground-based FTIR stations show significantly lower values for RAL (11–16 ppb) than those for LMD (about 25 ppb).

The long-term stability and seasonal cycles of CH4 derived from the LMD and RAL products are further investigated and discussed. The seasonal variation of XCH4 derived from RAL is consistent with the seasonal variation observed by the groundbased FTIR measurements. However, the overall 2007–2015 XCH4 trend derived from RAL measurements is underestimated if not adjusted for an anomaly occurring on 16 May 2013 due to a L1 calibration change. For LMD, we see very good agreement at the (sub)tropics (<35° N–35° S), but notice deviations of the seasonal cycle (both in the amplitude and phase) and an underestimation of the long-term trend with respect to the RAL and reference data at higher latitude sites.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2023-237', Anonymous Referee #1, 29 Jan 2024
    • AC1: 'Reply on RC1', Bart Dils, 09 Mar 2024
  • RC2: 'Comment on amt-2023-237', Anonymous Referee #2, 29 Jan 2024
    • AC2: 'Reply on RC2', Bart Dils, 09 Mar 2024
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge
Bart Dils, Minqiang Zhou, Claude Camy-Peyret, Martine De Mazière, Yannick Kangah, Bavo Langerock, Pascal Prunet, Carmine Serio, Richard Siddans, and Brian Kerridge

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Short summary
Here we looked at two very distinct methane products from the IASI instrument onboard the MetOp-A satellite. One (referred to as LMD NLISv8.3) uses a machine learning approach while the other (RALv2.0) uses a more conventional optimal estimation approach. We used a variety of model and independent reference measurement data to assess both product’s overall quality, their differences, and specific aspects of each product that would benefit from further analysis by the product development teams.