SMOS L2 Ocean Salinity Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS &...

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

Transcript of SMOS L2 Ocean Salinity Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS &...

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

SMOS L2 Ocean Salinity

www.argans.co.uk

Level 2 Ocean Salinity

v63x product design evolution

22 April 2015

ARGANS & SMOS L2OS ESL

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

SMOS L2 Ocean Salinity

www.argans.co.uk

When to apply land-sea correction?

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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

Page 3: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

Design for land-sea correction

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• 4 x retrievals in v62x: SSS1/2/3 & Acard4 threads gives ~12:1 reprocessing performanceConvergence algorithm ~28% of processing timeMax RAM ~ 6G

• Land-sea LUT (containing ascending & descending LUTs) is ~2.2GCould 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).

Page 4: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

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Options for land-sea correction

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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 requiredNo significant impact on processing performance

B. Retrieve SSS with & without land-sea correction: which model?UDP will contain 2 x SSS & AcardFaster processing (only 3 retrievals): 14:1 (M1) or better

C. 6 x retrievals with & without land-sea correction applied to SSS1/2/3, & AcardUDP will contain 6 x SSS, & AcardProcessing performance degraded to 10:1

Best for users:UDP with 1 SSS selected from several (<4) retrievals, & 1 AcardDAP can contain anything – ie all retrieval resultsAll retrievals with land-sea correction applied (via config switch)Need criteria to select which SSS to write into UDP…

Page 5: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

SSS1/2/3 are similar due to OTT & land-sea correction

5SSS1

Page 6: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

SSS1/2/3 are similar due to OTT & land-sea correction

6SSS2

Page 7: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

SSS1/2/3 are similar due to OTT & land-sea correction

7SSS3

Page 8: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

Criteria to select a single SSS for UDP

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Need results from ESL analysis (& JLV T1.3)

Criteria could include:Best (lowest) Dg_quality_SSSxBest Dg_chi2/chi2PNo poor_retrieval flags raisedClassification 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)?

Page 9: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

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/AcardDg_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/AcardDg_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

Page 10: SMOS L2 Ocean Salinity  Level 2 Ocean Salinity v63x product design evolution 22 April 2015 ARGANS & SMOS L2OS ESL 1.

SMOS L2 Ocean Salinity

www.argans.co.uk

UDP/DAP format changes: decisions & actions

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• Always apply land-sea correction?

• Single SSS in UDP?

• Run all 3 models in convergence algorithm, select ‘best’ SSS?