Preprints
https://doi.org/10.5194/amt-2022-82
https://doi.org/10.5194/amt-2022-82
 
08 Jun 2022
08 Jun 2022
Status: this preprint is currently under review for the journal AMT.

Synergistic retrieval and Complete Data Fusion methods applied to FORUM and IASI-NG simulated measurements

Marco Ridolfi1,, Cecilia Tirelli2,, Simone Ceccherini2, Claudio Belotti1, Ugo Cortesi2, and Luca Palchetti1 Marco Ridolfi et al.
  • 1Istituto Nazionale di Ottica del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
  • 2Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019 Sesto Fiorentino, Italy
  • These authors contributed equally to this work.

Abstract. In the frame of Earth observation remote sensing data analysis, Synergistic Retrieval (SR) and Complete Data Fusion (CDF) are techniques used to exploit the complementarity of the information carried by different measurements sounding the same air mass and / or ground pixel. While more difficult to implement due to the required simultaneous access to measurements originating from different instruments / missions, the SR method is sometimes preferred over the CDF method as the latter relies on a linear approximation of the retrieved states as functions of the true atmospheric and / or surface state.

In this work, we study the performance of the SR and CDF techniques when applied to simulated measurements of the FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) and the IASI-NG (Infrared Atmospheric Sounding Interferometer - New Generation) missions that will be operational in a few years, from two polar orbiting satellites. The study is based on synthetic measurements generated for the two missions, in clear-sky Antarctic atmospheres. The target parameters of the inversion are the vertical profiles of temperature, water vapour and ozone mixing ratios, surface temperature and spectral emissivity.

We find that for exact matching of the measurements, the results of the SR and CDF techniques differ by less than 1/10 of their errors estimated trough the propagation of measurement noise. For measurements with a realistic mismatch in space and time, the two methods provide more different results. Still in this case, however, the differences between the results are within the error bars due to measurement noise. We conclude that, when applied to FORUM and IASI-NG missions, the two methods are equivalent from the accuracy point of view.

Marco Ridolfi et al.

Status: open (until 13 Jul 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-82', Anonymous Referee #2, 24 Jun 2022 reply
  • RC2: 'Comment on amt-2022-82', Joern Ungermann, 28 Jun 2022 reply

Marco Ridolfi et al.

Marco Ridolfi et al.

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Short summary
Synergistic Retrieval (SR) and Complete Data Fusion (CDF) methods exploit the complementarity of coincident remote sensing measurements. We assess the performance of the SR and CDF methods on the basis of synthetic measurements of the FORUM and IASI-NG missions. In case of perfectly matching measurements, SR and CDF results differ by less than 1/10 of the error due to measurement noise. In case of a realistic mismatch, the two methods show differences of the order of their error bars.