SMOS L2 Ocean Salinity www.argans.co.uk Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

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SMOS L2 Ocean Salinity Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1

SMOS L2 Ocean Salinity When to apply land-sea correction? 2 L2OS TDS (lsc01/2): Outlier detection (decision tree): apply OTT & LSC. Sets measurement, snapshot & RFI flags. If retrieving A3TEC for OTT computation, do not apply OTT or LSC (A3TEC algorithm retrieves OTT) Compute OTT correction per model M1/2/3 (ottTB in AUX_DTBXY: mean forward model OTT TB for all measurements in each snapshot FOV sub-zone, can be compared to modelTB/deltaTB) – not used in retrievals If A3TEC for retrievals, apply OTT & LSC (A3TEC does not retrieve OTT), & compute outlier detection again using new TEC. For each retrieval (M1/2/3 & Acard), apply OTT & LSC per grid point

SMOS L2 Ocean Salinity Design for land-sea correction 3 4 x retrievals in v62x: SSS1/2/3 & Acard 4 threads gives ~12:1 reprocessing performance Convergence algorithm ~28% of processing time Max RAM ~ 6G Land-sea LUT (containing ascending & descending LUTs) is ~2.2G Could split into 2, but no performance advantage Reading land-sea LUT takes ~ 30 seconds, applying LUT very fast. Land-sea LUT is applied at the same time as OTT, before running A3TEC retrieval, measurement selection, & convergence (per forward model). Land-sea LUT adds ~0.9G (not scene dependent).

SMOS L2 Ocean Salinity Options for land-sea correction 4 A.4 x retrievals with land-sea correction applied to SSS1/2/3 & Acard (or a selection of these) (same as May 2011 lsc01/2 TDS) No UDP/DAP format changes required No significant impact on processing performance B.Retrieve SSS with & without land-sea correction: which model? UDP will contain 2 x SSS & Acard Faster processing (only 3 retrievals): 14:1 (M1) or better C.6 x retrievals with & without land-sea correction applied to SSS1/2/3, & Acard UDP will contain 6 x SSS, & Acard Processing performance degraded to 10:1 Best for users: UDP with 1 SSS selected from several (<4) retrievals, & 1 Acard DAP can contain anything – ie all retrieval results All retrievals with land-sea correction applied (via config switch) Need criteria to select which SSS to write into UDP…

SMOS L2 Ocean Salinity SSS1/2/3 are similar due to OTT & land-sea correction 5 SSS1

SMOS L2 Ocean Salinity SSS1/2/3 are similar due to OTT & land-sea correction 6 SSS2

SMOS L2 Ocean Salinity SSS1/2/3 are similar due to OTT & land-sea correction 7 SSS3

SMOS L2 Ocean Salinity Criteria to select a single SSS for UDP 8 Need results from ESL analysis (& JLV T1.3) Criteria could include: Best (lowest) Dg_quality_SSSx Best Dg_chi2/chi2P No poor_retrieval flags raised Classification of geophysical conditions: do some models perform better eg in cold waters or high winds? Or average of all 3 SSS (if no poor quality flags & Dg_quality < 150)?

SMOS L2 Ocean Salinity UDP design n x grid points: Grid point data (6) ID, latitude, longitude, footprint, time, x_swath Science flags (4 x 22) land, rain, ice, sea state, hi/lo wind/SST/SSS Geophysical retrievals (10) SSS1, SSS2, SSS3, Acard & sigmas, WS, SST TB42.5 (8) modelled BTs & sigmas at surface & antenna Product confidence (33) quality index, chi2, chi2P, nIter for SSS1/2/3/Acard Dg_xxx counters (17) Control flags (4 x 30) ignored, valid, range, sigma, chi2, chi2P, sun/moon/gal glint, maxiter, meas min/low, outliers, marq, rough, foam, ecmwf, poor geophysical/retrieval, rfi v62x (208 flags & 58 fields) v63x (54 flags & 59 fields) n x grid points: Grid point data (6) ID, latitude, longitude, footprint, time, x_swath Science flags (1 x 22) land, rain, ice, sea state, hi/lo wind/SST/SSS Geophysical priors & retrievals (4 x 5) SSS, WS, SST, TEC, Acard & sigmas TB42.5 (8) modelled BTs & sigmas at surface & antenna Product confidence (25) quality index, chi2, chi2P, nIter for SSS/Acard Dg_xxx counters (17) Control flags (1 x 32) ignored, valid, range, sigma, chi2, chi2P, sun/moon/gal glint, maxiter, meas min/low, outliers, marq, rough, foam, ecmwf, poor geophysical/retrieval, rfi, model

SMOS L2 Ocean Salinity UDP/DAP format changes: decisions & actions 10 Always apply land-sea correction? Single SSS in UDP? Run all 3 models in convergence algorithm, select ‘best’ SSS?