22 May 2023
 | 22 May 2023
Status: this preprint is currently under review for the journal AMT.

Tropospheric ozone column dataset from OMPS-LP/OMPS-NM limb-nadir matching

Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, Annette Ladstätter-Weißenmayer, John P. Burrows, Anne M. Thompson, Ryan M. Stauffer, and Debra E. Kollonige

Abstract. A Tropospheric Ozone Column (TrOC) dataset from the Ozone Mapping and Profiler Suite (OMPS) observations was generated by combining the retrieved total ozone column from OMPS - Nadir Mapper (OMPS-NM) and limb profiles from OMPS - Limb Profiler (OMPS-LP) data. All datasets were generated at the University of Bremen, and the TrOC product was obtained by applying the Limb-Nadir Matching technique (LNM). The retrieval algorithm and a comprehensive analysis of the uncertainty budget are presented here. The OMPS-LNM-TrOC dataset (2012–2018) is analysed and validated by comparing with ozonesondes, tropospheric ozone residual (TOR) data from the combined Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) observations, and the TROPOspheric Monitoring Instrument (TROPOMI) Convective Cloud Differential technique (CCD) dataset. The OMPS-LNM TrOC is generally lower than the other datasets. The average bias with respect to ozonesondes is −1.7 DU with no significant latitudinal dependence identified. The mean difference with respect to OMI/MLS TOR and TROPOMI CCD is −3.4 and −1.8 DU, respectively. The seasonality and inter-annual variability are in good agreement with all comparison datasets.

Andrea Orfanoz-Cheuquelaf et al.

Status: open (until 26 Jun 2023)

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Andrea Orfanoz-Cheuquelaf et al.

Andrea Orfanoz-Cheuquelaf et al.


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Short summary
Valuable information on the tropospheric ozone column (TrOC) can be obtained globally by combining space-borne limb and nadir measurements (limb-nadir matching, LNM). This study describes the retrieval of TrOC from the OMPS instrument (since 2012) using the LNM technique. The OMPS-LNM TrOC was compared with ozonesondes and other satellite measurements, showing a good agreement with a negative bias within 1 to 4 DU. This new dataset is suitable for pollution studies.