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Overview

Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: Plans for Task 2 R.Siddans MTR: Estec, 1 October 2013. Overview. Time scale for project to have impact on industrial contracts is very short

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Overview

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  1. Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument:Plans for Task 2R.SiddansMTR: Estec, 1 October 2013

  2. Overview • Time scale for project to have impact on industrial contracts is very short • Only minor refinements to current “T1” simulations possible • Include assessment of NO2 AMFs for cloud sensitivity • Explicitly evaluate 30% co-registration error • Consolidation of ESRA (?) • Scope of Task 2 remains to be defined • Remaining requirements from T2 plan are • Non-linear cloud retrievals from more realistic cloud profiles • Intra-band co-registration error for cloud SWIR & H2O retrieval • Realistic model of co-registration wavelength dependence needed • Requirement for HSS data • Effort should be reserved for issues raised by industry • Are there any of these already ?

  3. Approach for cloud/trace-gases • These to be non-linear retrievals based on “realistic” cloud/aerosol conditions as in earlier Eumetsat study • Starting point can be the SWIR scenarios. However optically thick cloud needs to be added (to the existing thin cirrus). • Propose to add optically thick (>1) cloud with varying profile and area-fraction based on a statistical sampling of the CALIPSO 5km layer product within regions on the map (details tbc). • Cloud-fractions vary over range where gas retrievals (in lower troposphere) possible, i.e. <0.5 (tbc). This will lead to two maps (i) as SWIR study with no thick cloud (ii) map with thick cloud of varying cloud. height, fraction and geometric thickness •  SWIR scenarios extended over sea (othewise fixed properties) • but emphasis over land is justified as trace gases primarily required over land even if retrieval over sea possible. •  Errors in trace gases simulated via AMF errors. No need to define trace-gas profiles explicitly.

  4. Consolidation of ESRA • Previously defined requirements on Relative Spectral Radiometric Accuracy (RSRA) have been found difficult to meet. • Effective relative Spectral Radiometric Accuracy has now been adopted: • ESRA is the error at L2 determined using a retrieval gain matrix to propagate a particular L1 error spectrum; this is required to be smaller than 50% of the corresponding L2 user requirement. • Industry expected to apply provided gain matrices to demonstrate compliance • In addition a relaxed RSRA requirement is retained (for NIR 0.25%, relaxed from 0.05%). • This is sufficient for cloud/uv application • Gain matrices have been provided for most species by relevant groups for ESA and industry to use to assess compliance. • For most species only one gain matrix is supplied. • Concerns raised over how representative this approach is, in particular for the NIR band aerosol and cloud retrievals.

  5. Consolidation of ESRA • For the NIR band, RAL have provided a set of gain matrices for aerosol column amounts, for the high-resolution band option (older instrument parameters). • No matrices have been provided for water vapour, cloud or sensitivity of SWIR to NIR. • NB gain matrix approach is unsuitable for cloud retrievals as • (a) the cloud retrieval is highly non-linear and so unlikely to be well represented by a single gain matrix • (b) there are no user requirements on cloud properties (only on the trace-gas retrievals which rely on the cloud retrieval).

  6. Consolidation of ESRA • Within this study, task of deriving requirements for certain errors which dominate the RSRA budget (diffuser structure, spectrally structured stray-light) is replaced by a task to consolidate the ESRA approach. • Tasks involved are: • Provide gain matrices for H2O (IUP) • Provide gain matrices to map NIR band errors to error in SWIR CH4 (Leicester, if not covered by SWIR study) • For each NIR application except cloud/UV, assess representativeness of the gain matrices for selected cases compared to the range of geophysical scenarios (RAL, IUP, Leicester) • Comparing linearly mapped errors for some “generic” errors (e.g. spectrally uniform radiometric offset, spectral shift, 1% spectral response function width), based on gain matrices for the specific geophysical/geometric scenario to the selected conditions. • Optimise gain matrices provided to smallest possible set to capture necessary sensitivities

  7. High Spatial Sampling Data (MR-LEO-SYS-39) • Recently completed S4 Study considered impact of scene inhomogeneity on A-band aerosol retrieval from inhomogeneity in ground scene. • Noveltis simulated impact of inhomogeneity using 3 cloud-free scenes • RAL linearly mapped provided error spectra onto profile retrieval • Error was very large, but mitigation approach based on HSS data leads to effect being negligible • Conclusion not directly transferrable to S5 as number of HSS samples will be significantly fewer (6 for S4) • Performance of mitigation for reduced number of HSS samples could be important to assess, but this can only be done if Noveltis contribution to the study can be arranged. • Noveltis contacted and open to conducting such a task, but funds would need to be found… • Noveltis have already simulated S5 SWIR in context of S4 study so should be well set-up to do necessary work.

  8. Schedule MTR (ESTEC) 1 Oct; PM2 (Bremen) 25 Jan

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