Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project

De Smedt, I., Theys, N., Yu, H., Danckaert, T., Lerot, C., Van Roozendael, M., Richter, A., Hilboll, A., Peters, E., Pedergnana, M., Loyola, D., Beirle, S., Wagner, T., Eskes, H., van Geffen, J., Boersma, F. and Veefkind, P.: 2018,
doi: 10.5194/amt-11-2395-2018
Atmos. Meas. Tech. 11, 2395-2426.

Abstract

On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

   Abstract
   1. Introduction
   2. TROPOMI HCHO algorithm
      2.1 Product requirements
      2.2 Algorithm description
          2.2.1 Formaldehyde slant column retrieval
          2.2.2 Tropospheric air mass factor
          2.2.3 Across-track and zonal reference sector correction
   3. Uncertainty analyses
      3.1 Uncertainty formulation by uncertainty propagation
          3.1.1 Errors on the slant columns
          3.1.2 Errors on air mass factors
          3.1.3 Surface albedo
          3.1.4 Clouds and aerosols
          3.1.5 Profile shape
          3.1.6 Errors on the reference sector correction
      3.2 HCHO error estimates and product requirements
          3.2.1 Precision
          3.2.2 Trueness
   4. Verification
      4.1 Harmonized DOAS fit settings using OMI test data
      4.2 Verification of the operational implementation
   5. Validation
      5.1 Requirements for validation
      5.2 Reference measurement techniques
      5.3 Deployment of validation sites
      5.4 Satellite-satellite intercomparisons
   6. Conclusions
   Appendix A: Acronyms and abbreviations
   Appendix B: High L2 HCHO data product description
   Appendix C: Averaging kernel
   Acknowledgements
   References

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