Atmospheric Measurement Techniques (Nov 2022)

Synergistic retrieval and complete data fusion methods applied to simulated FORUM and IASI-NG measurements

  • M. Ridolfi,
  • C. Tirelli,
  • S. Ceccherini,
  • C. Belotti,
  • U. Cortesi,
  • L. Palchetti

DOI
https://doi.org/10.5194/amt-15-6723-2022
Journal volume & issue
Vol. 15
pp. 6723 – 6737

Abstract

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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, 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 Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) and the Infrared Atmospheric Sounding Interferometer – New Generation (IASI-NG) 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 atmospheres. The target parameters of the inversion are the vertical profiles of temperature, water vapor 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 through 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 an accuracy point of view.