A tropopause-related climatological a priori profile for IASI-SOFRID ozone retrievals: improvements and validation

Abstract

Abstract. The MetOp/Infrared Atmospheric Sounding Interferometer (IASI) instruments have provided data for operational meteorology and document atmospheric composition since 2007. IASI ozone (O3) data have been used extensively to characterize the seasonal and interannual variabilities and the evolution of tropospheric O3 at the global scale. SOftware for a Fast Retrieval of IASI Data (SOFRID) is a fast retrieval algorithm that provides IASI O3 profiles for the whole IASI period. Until now, SOFRID O3 retrievals (v1.5 and v1.6) were performed with a single a priori profile, which resulted in important biases and probably a too-low variability. For the first time, we have implemented a comprehensive dynamical a priori profile for spaceborne O3 retrievals which takes the pixel location, time and tropopause height into account for SOFRID-O3 v3.5 retrievals. In the present study, we validate SOFRID-O3 v1.6 and v3.5 with electrochemical concentration cell (ECC) ozonesonde profiles from the global World Ozone and Ultraviolet Radiation Data Centre (WOUDC) database for the 2008–2017 period. Our validation is based on a thorough statistical analysis using Taylor diagrams. Furthermore, we compare our retrievals with ozonesonde profiles both smoothed by the IASI averaging kernels and raw. This methodology is essential to evaluate the inherent usefulness of the retrievals to assess O3 variability and trends. The use of a dynamical a priori profile largely improves the retrievals concerning two main aspects: (i) it corrects high biases for low-tropospheric O3 regions such as the Southern Hemisphere, and (ii) it increases the retrieved O3 variability, leading to a better agreement with ozonesonde data. Concerning upper troposphere–lower stratosphere (UTLS) and stratospheric O3, the improvements are less important and the biases are very similar for both versions. The SOFRID tropospheric ozone columns (TOCs) display no significant drifts (<2.5 %) for the Northern Hemisphere and significant negative ones (9.5 % for v1.6 and 4.3 % for v3.5) for the Southern Hemisphere. We have compared our validation results to those of the Fast Optimal Retrievals on Layers for IASI (FORLI) retrieval software from the literature for smoothed ozonesonde data only. This comparison highlights three main differences: (i) FORLI retrievals contain more theoretical information about tropospheric O3 than SOFRID; (ii) root mean square differences (RMSDs) are smaller and correlation coefficients are higher for SOFRID than for FORLI; (iii) in the Northern Hemisphere, the 2010 jump detected in FORLI TOCs is not present in SOFRID.

Recent ozone trends in the Chinese free troposphere: role of the local emission reductions and meteorology

“…Some individual studies exist but once again they do not allow one to conclude. Indeed, Boynard et al (2018) noticed a significant negative drift in the Northern Hemisphere in the IASI-FORLI product, which is not detected in the most recent IASI-SOFRID product (Barret et al, 2020). The OMI/MLS product shows a small positive drift when compared to ozonesondes but not significant when based upon a difference t-test (Ziemke et al, 2019).…”

Recent ozone trends in the Chinese free troposphere: role of the local emission reductions and meteorology

“…Some individual studies exist, but once again, they do not allow one to draw conclusions concerning the role of the drifts in the trend discrepancies. Indeed, Boynard et al (2018) noticed a significant negative drift in the North- ern Hemisphere in the IASI-FORLI product, which is not detected in the most recent IASI-SOFRID product (Barret et al, 2020). The OMI/MLS product shows a small positive drift when compared to ozonesondes but not significant when based upon a difference t test (Ziemke et al, 2019).…”

“…Further information on the instrument is available in other articles (see Thouret et al, 1998;Nédélec et al, 2015). Long-term quality and consistency have been assessed by Blot et al (2021).…”

“…4). Note that Barret et al (2020) also discussed the interest in the consideration of raw and smoothed data in satellite data procedures. Spatial distribution and spatial gradients of ozone are in good agreement for the four partial columns.…”

Remote sensing study of ozone, NO2, and CO: some contrary effects of SARS-CoV-2 lockdown over India

“…2 ). The tropospheric ozone column is also derived utilizing IASI and GOME-2 observations by integrating ozone profiles from surface to tropopause, where the thermal tropopause height was taken from IASI observations (Barret et al 2020 ).

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