Rutherford Appleton Laboratory Requirements Consolidation of the Near-Infrared Channel of the GMES-Sentinel-5 UVNS Instrument: Height-resolved aerosol (summary) & Cloud retrievals for UV/VIS trace-gases. PM2, 28 February 2014, Bremen R.Siddans (RAL),

Study Overview Consolidate requirements for NIR band considering application areas: Height resolved aerosol from O2-A (and B) bands (RAL) Requirement: 0.05 on layer optical depths (NB free-troposphere) Scattering correction for DOAS retrievals UV/VIS/NIR (RAL) Requirements: e.g. O 3 : 20% trop.column; NO 2 : 10% PBL Scattering correction for full-physics retrievals from SWIR+NIR joint retrieval (Univ Leicester) Requirements: CH 4 : 2% column; CO: 25% Water vapour (column) retrievals (Univ Bremen) Requiremenst: 5% (Climate NRT) or 10% Vegetation fluorescence to be taken into account (FU-Berlin) No requirement, not driving

Early priority to trade-off two current instrument concepts: Concept A: 0.39 nm resolution, covering O 2 A,B-bands + H 2 O Concept B: 0.12 nm resolution, covering O 2 A-band Initial trade-off did not result in strong case for MAG to select concept A or B; following awarding of industrial contract, only option A currently considered

InstrumentBand Coverage / nm Resolution / nm Oversampl ing ratio Number of detectors GOME S5P S5- Concept A S5 Specs (concept A) vs GOME & S5P Current issues: Need for B- band/H2O coverage Downlinked spectral range

Height-resolved Aerosol Application RAL OE scheme developed for previous Eumetsat and ESA studies Retrieves aerosol extinction profile, integrated to layer amounts Wavelength calibration, linear surface albedo dependence, spectral response function width & fluorescence all fitted in retrieval Other instrumental errors quantified by linear mapping Aerosol performance very dependent on view / solar geometry due to variations in aerosol phase function, light path for aerosol light-path for O 2 absorption etc. Surface albedo Assumed aerosol type + size (asymmetry, single scatter albedo etc) 0.05 requirement cannot be met under all observing conditions Difficult to concisely summarise performance and optimise inst/L1 requirements without considering many conditions Results presented along S5 orbits based on many individual simulations Use SWIR study scenarios from A. Butz as basis thought NIR study

Retrieval Simulation results Estimated Standard Deviation (ESD) = retrieval precision (random noise) for Free-tropospheric column Concept B Concept A (A Band) Concept A (A+B Bands)

Concept B Concept A (A Band) Concept A (A+B Bands) Retrieval Simulation results 1% error in instrument spectral line-shape (ILS) = spectral response function If not fitted in retrieval

Absolute Radiometric Accuracy (ARA) (MR-LEO-UVN-160) MRTD: At the MAG the requirement was relaxed to apply only over a given signal level (High-latitude dark at 755nm); Here ARA mapped as 2 components: Gain consistent with MRTD (3%) Offset consistent with proposed relaxation

Concept B Concept A (A Band) Concept A (A+B Bands) Retrieval Simulation results ARA relaxation, considered as radiometric offset error (assuming High-Lat Dark limit)

Conclusions (Aerosol) Height resolved aerosol retrievals improve with increasing (finer) spectral resolution, even considering an instrument with fixed total throughput. Dependence on geometry large – no concept compliant over whole swath Concept B clearly preferred but retrieval remains a challenge Better performance over more of swath Option A only competitive if both O 2 A and B bands used Even then sensitivity to instrumental errors larger than concept B Introduces need to model spectral dependence of aerosol optical properties (only limited demonstrations for GOME-2 exist) For option B relaxation of ARA requirement (to HL-dark level) seems acceptable (if mapped as offset); This is not the case for concept A. Now that option B not selected, height-resolved aerosol in terms of layer optical depths meeting requirements very unlikely for S5 and would unrealistically drive requirements for the band With concept A, could aim for less challenging aerosol layer height under high aerosol load (no quantitative user requirement or this but could be useful) – should consider implications of this further

NIR cloud / UV-VIS Application RAL Simulations based on retrieval scheme developed for Eumetsat A- band study Basis of approach is to Define realistic cloud scenarios & simulate measurements Perform cloud retrievals used relatively simple cloud model Determine implied errors in the uv-vis trace gases by quantifying air- mass-factor (AMF) errors from the retrieved cloud representation Eumetsat study concluded A-band cloud-as-reflecting-surface improves AMFs cf VIS/TIR imager A-band scattering profile retrieval improves further For application to characterise AMFs for uv, then A-band with nm resolution, signal to noise ~250 sufficient. High resolution, low error instrument demonstrates superior cloud profile retrieval, however AMFs do not improve significantly

New Simulations Cloud scenarios generated to complement the “SWIR scenarios” for A- Butz – basis is simulations of observations for idealised single day, representative of April conditions. ~2.8 degree lat/lon grid of surface albedo, trace-gas profiles, temperature, aerosol and thin cirrus Thick cloud scenarios constructed to represent range of cloud fractions and realistic cloud profiles for each grid cell Only model data can provide full description of cloud vertical profile, so profiles taken from ECMWF model cloud fields However samples selected to match (a) CALIPSO statistics for cloud top height in the given grid cell (b) ECMWF median thick cloud base height corresponding to clouds with the prescribed cloud top. Individual model profiles selected which match the selected (representative) top and base height – so other cloud parameters are randomly selected from a year of ECMWF data for the given location Range of cloud fractions and range of thick cloud heights spanned in groups of 3x3 grid cells...

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Non linear simulations for cloud/uv A-band measurements + True trace gas AMFs simulated Cloud retrievals based on 4 assumptions 1.Reflecting layer (fraction,height retrieved) 2.Geometrically thin scattering layer (optical depth, height retrieved, assumed fraction from imager, albedo+climatological cloud base) 3.Geometrically extended scattering layer (optical depth, height retrieved, assumed albedo+climatological cloud vertical extent) 4.Geometrically extended scattering layer (optical depth, base height retrieved, top height taken from TIR) 1, 2 and 3 are similar to schemes planned for S5P (different schemes needed as trace gas retrievals use different cloud models); Concept A assumed Schemes applied to A-band and B-band separately (to test benefit of B) Joint retrieval of surface albedo with also 10% prior constraint tested Maximum SNR of 100 or 400 assumed (after noise model) ESD on column AMFs computed + errors due to ISRF width and ARA

“AMFs” Here the term AMF refers to the relative sensitivity of the TOA measurement to the given trace gas column, compared to that ignoring the presence of cloud but calculated for a surface albedo (in the DOAS window) which matches the apparent albedo of the scene (internal closure). Modelling of underlying albedo accounts for effect of multiple scattering above cloud. Despite potential for scattering in-cloud the usually means these relative AMFs are in range = column completely obscured by cloud 1 = effect of cloud negligible

True conditions Imager retrieval results A-band retrieval results (thin scattering layer) A-band retrieval results (reflecting surface model)

True AMF Imager derived AMF A-band derived AMF (thin scattering layer) A-band derived AMF (reflecting surface model)

AMF ESD / % (estimated precision)

Actual errors (retreived/True-1 / %)

Actual errors (Bias / %)

Actual errors (std.dev. / %)

ESD / %

Summary Planned cloud retrieval models for S5 feasible with quite relaxed instrument requirements Signal:noise around 100 sufficient Weak sensitivity to slit width; ARA errors acceptable This application unlikely to drive NIR band requirements There remain cloud representation errors related to vertical scattering profile shape These may be addressed by extended-scattering-layer retrieval models (yet to be simulated) So far there is no obvious benefit of B-band for this application (similar representation errors, worse (but acceptable) ESDs Next steps Simulate extended layer retrieval models Apply modified version of scheme to assess aerosol layer height potential in clear sky scenes (not guaranteed to give useful results in time) Will also review recent studies/literature/s5p atbd for relevant info on layer height retrieval & consider implications for inst reqs (so far as possible). Aerosol layer height could be driving application, but there are no quantitative user requirements for layer height

Retrieval Simulation results “FRESCO” style retrieval (fraction + height of reflecting boundary) Concept A (A-band) with max SNR=50 True cloud fraction = 0.2 True cloud height = median Calipso opaque cloud-top

Retrieval Simulation results “FRESCO” style retrieval (fraction + height of reflecting boundary) Concept A (A-band) with max SNR=50 True cloud fraction = 0.2 True cloud height = median Calipso opaque cloud-top Abs.radiometric accuracy significant error for this cloud retrieval approach

Absolute Radiometric Accuracy (ARA) (MR-LEO-UVN-160)