1. Rutherford Appleton Laboratory Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: FP, 25 April 2014, ESTEC Conclusions and Recommendations R.Siddans (RAL), L. Vogel, H. Boesch (Univ. Leicester) K.Weigel, H. Bovensmann (Univ. Bremen) L. Guanter (FUB)

2. Concept A vs Concept B Concept B is clearly preferred for height-resolved aerosol – Even with concept B, meeting the 0.05 layer AOD requirements is challenging: – There is limited heritage from previous satellite observations. – Algorithm need consolidation including non-instrumental limits to errors (forward model errors, need for auxiliary / prior information etc) – The requirement cannot be met (without averaging) over whole swath, only in favorable geometry (low sun / view elevations) Height resolved aerosol retrieval (distinct layer optical depths) should not be planned operational product if concept A selected. – More appropriate to consider aerosol layer height (but no quantitative user requirement for this) NIR/SWIR and Cloud/UV found to have similar performance in both cases Fluorescence also possible from both concepts Only concept A can provide NIR water vapour retrievals. – SWIR also offers column water vapour information but the NIR has potential value over sea – NIR (and SWIR) potentially offer additional near-surface information cf IASI – NIR water vapour continues 25 year record from GOME / SCIA.

3. L1 Requirements (Concept A) NIR-1 and NIR-2 bands should both be measured. – NIR-2 needed for cloud/uv and NIR/SWIR, – NIR-1 needed for water vapour. – Using NIR-1 and NIR-2 also beneficial for NIR/SWIR and may improve cloud/uv and aerosol. Driving applications do not use range 702-710nm. Recommend to downlink – NIR1: 685-702nm (instead of 685-710nm) – NIR2: 745-773nm (instead of 753-773nm) – This would then enable vegetation fluorescence to be confidently retrieved. NESR is not limiting error for cloud/UV or H2O. Representation errors (profile shape, scattering correction, residual cloud) are larger than most instrumental errors considered for cloud/uv and water vapour 0.25% RSRA requirement is sufficient (factor 2 margin) for cloud/UV but not for H2O, so should be retained. – Preferable to (also) apply ESRA for water vapour, using supplied gains

4. L1 Requirements (Concept A) Cloud-as-layer (CAL) and cloud as reflecting boundary (CRB) assumptions (both used for (GOME/SCIAMACHY/GOME-2/OMI/S5P), show very similar sensitivity to instrumental errors are similar. – CAL gives more accurate and precise representation of cloud if the cloud geometric fraction and vertical extent is known – Recommended to make use of co-located imager data to constrain these – Fraction could also come from higher spatial resolution data from S5 itself ARA errors are only just acceptable for cloud/UV and NIR/SWIR applications. It should be a priority to minimise these errors. Achieving the goal requirement of 2% would be a distinct step forward. Scene inhomogeneity errors are shown to have small impact on all retrievals. Errors could be negligible if information at least on the along-track gradient in scene radiance could be acquired. 2-3x spatial oversampling along-track probably sufficient. ISRF errors simulated lead to small errors in most applications. Most significant cf requirement for CH4 (2%), for which relaxation to refer to 2% of the peak value (rather than 1% of the peak) acceptable. Inter-band/Intra-band co-registration errors (20%/10% of the field of view) lead to dominant errors for the cloud/UV and H2O applications, so should not be relaxed.

5. Further Work Consider user requirements for aerosol layer height and fluorescence as operational products. – Consolidate related retrieval schemes and assess S5 ability to meet user requirements. Further consolidate “advanced” schemes (not so far used operationally) so they can be applied from “day-1” of S5: – Use of both oxygen A+B bands together for aerosol and cloud – Use of information on cloud vertical and horizontal distribution from imagers in cloud/UV applications Approaches to minimise the effects of scene inhomogeneity for S5 should be consolidated via more detailed studies.