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SST Quality Monitor (SQUAM): Focus on Suomi NPP VIIRS

2012 EUMETSAT Meteorological Satellite Conference 3 – 7 September, 2012, Sopot, Poland. SST Quality Monitor (SQUAM): Focus on Suomi NPP VIIRS. www.star.nesdis.noaa.gov/sod/sst/squam. Prasanjit Dash 1,2 and Alexander Ignatov 1 1 NOAA/NESDIS, Center for Satellite Applications & Research (STAR)

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SST Quality Monitor (SQUAM): Focus on Suomi NPP VIIRS

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  1. 2012 EUMETSAT Meteorological Satellite Conference3 – 7 September, 2012, Sopot, Poland SST Quality Monitor (SQUAM):Focus on Suomi NPP VIIRS www.star.nesdis.noaa.gov/sod/sst/squam Prasanjit Dash1,2 and Alexander Ignatov1 1NOAA/NESDIS, Center for Satellite Applications & Research (STAR) 2Colorado State Univ, Cooperative Institute for Research in the Atmosphere (CIRA) Objective: A global, web-based, community, quasi NRT, monitor for SST producers & users !

  2. Contributions/Support • Level-2 SST: VIIRS/AVHRR/MODIS • NESDIS SST Team : ACSPO (GAC: 5 platforms, FRAC: MetOp-A, VIIRS: NPP, MODIS: Terra/Aqua) • P. LeBorgne:O&SI SAF MetOp-A FRAC • D. May, B. McKenzie:NAVO SEATEMP • S. Jackson:IDPS (NPP) • Level-3 SST: AVHRR: • K. Casey, R. Evans, J. Vazquez, E. Armstrong:PathFinder v5.0 • Level 4 SSTs: • R. Grumbine, B. Katz:RTG (Low-Res & Hi-Res) • R. Reynolds, V. Banzon:OISSTs (AVHRR & AVHRR+AMSRE) • M. Martin, J. R. Jones:OSTIA foundation, GHRSST Median Product Ensemble, OSTIA Reanalysis • D. May, B. McKenzie:NAVO K10 • J.-F. Piollé, E. Autret :ODYSSEA • E. Maturi, A. Harris, J. Mittaz:POES-GOES blended • B. Brasnett:Canadian Met. Centre, 0.2 foundation • Y. Chao:JPL G1SST • H. Beggs:ABOM GAMSSA • M. T. Chin, J. Vazquez, E. Armstrong:JPL MUR • L4s in SQUAM pipeline: • J. Hoyer:DMI OISST; S. Ishizaki:MGDSST; • C. Gentemann:RSS products; J. Cummings:NCODA • GHRSST support: • Craig Donlon, Peter Minnett, Alexey Kaplan Definitions of levels: L2: at observed pixels (satellite) L3: gridded with gaps (satellite) L4: gap-free gridded, time-averaged CMC

  3. SST datasets available in community Level 4 • Reynolds (AVHRR; +AMSR-E*) • RTG (Low, High Resolution), GSI • OSTIA, Operational + Retro (UKMO) • ODYSSEA (France) • GMPE (GHRSST) • NAVO K10 • NESDIS POES-GOES Blended • JPL G1SST, JPL MUR • NCODA (NRL) • CMC 0.2 (Canada) • GAMSSA (Australia) • MGDSST (JAXA, Japan) • RSS (MW, MW+MODIS) • DMISST (Danish Met. Inst.) Level 2/3 • Polar • AVHRR (NESDIS, NAVO, O&SI SAF, U. Miami, NODC) • VIIRS (NESDIS, IDPS),MODIS,ATSR, • Microwave • Geostationary • GOES (NESDIS, NAVO, O&SI SAF) • SEVIRI (NESDIS, O&SI SAF) • MTSAT (NESDIS, JAXA) In situ • Sources • GTS, ICOADS, GODAE/FNMOC • Platforms • Drifters, Moorings, Ships, ARGO Floats • Quality Control • May be unavailable or non-uniform • SST community is data-rich • Are these products self-consistent? Cross-consistent?

  4. SQUAM Objectives and Methodology • Cross-evaluate all major global SST products and validate against consistent reference standard, in near-real time • Report summary performance statistics online • SQUAM is organized into three major modules: L2, L3, and L4 • The diagnostics aimed at assessing (relative) performance of • Cloud mask • SST Algorithm • Ice-mask .. • Methodology • Analyze global differences, ΔTS = TSminus expected TR • Evaluate global maps for “uniformity” • Evaluate distributions for Normality (X~N(µ,σ)) • Compare and Trend Gaussian parameters in time

  5. Choice of expected state: In situ or L4? • NPP VIIRS(TS) – Drifters(TR): • Conventional Val wrt. In situ SST: • Sparse (voids), geographically non-uniform • Quality non-uniform & sub-optimal • Number of Match-ups ~2,000/Night • NPP VIIRS(TS) – OSTIA(TR): • Using L4: • Complements traditional in situ VAL • Global snapshot, in near-real time • Number of Match-ups 90,000,000/Night

  6. SQUAM Interface Locate this website: Google: “SST + SQUAM”, the first hit

  7. L2/3 SQUAM • ΔTS (TS - TR) analyzed: • Maps • Histograms • Time series (Gaussian moments, outlier info, double differences) • Dependencies (on geophysical & observational parameters) • Hovmöller Diagrams (Time series of dependencies) (GHRSST ST-VAL) The SST Quality Monitor (SQUAM)Journal of Atmospheric & Oceanic Technology, 27, 1899-1917, 2010

  8. L2/L3 SQUAM: • The Suomi National Polar Partnership (NPP) satellite launched in Oct 2011 • Cryoradiator Doors opened on 18 Jan 2012 • VIIRS Global SST Products produced since 23 Jan 2012 • ACSPO and IDPS: • Two SST processing systems applied to the same satellite data • ACSPO (Advanced Clear-Sky Processor for Oceans) - NOAA • IDPS (Interface Data Processing Segment) – NPOESS Contractor, transitioning to NOAA

  9. L2/L3 SQUAM: NIGHT: ACSPO VIIRS L2 minus OSTIA L4, 13 August 2012 • Deviation from TR is flat & close to 0 • Residual Cloud/Aerosol leakages seen in the Tropics

  10. L2/L3 SQUAM: NIGHT: IDPS VIIRS L2 minus OSTIA L4, 13 August 2012 • More Cloud leakages in IDPS than in ACSPO Two processors applied to the same satellite data More HR Level-2 SST analyses at: http://www.star.nesdis.noaa.gov/sod/sst/squam/HR/

  11. L2/L3 SQUAM: NIGHT: ACSPO VIIRS L2 minus OSTIA L4, 13 August 2012 • Shape close to Gaussian • Domain and performance stats close to expected

  12. L2/L3 SQUAM: NIGHT: IDPS VIIRS L2 minus OSTIA L4, 13 August 2012 • IDPS confidently clear sample ~27% larger • Shape less Gaussian (negative skewness, increased kurtosis) • Increased Std Dev/Robust Std Dev; Larger fraction of outliers

  13. L2/L3 SQUAM: Summary stat of ΔT = “VIIRS minus OSTIA” SST for 13 Aug 2012 (expected ~0) • IDPS SST domain +27% larger than ACSPO • IDPS performance statistics degraded, compared to ACSPO • Gap between Conventional and Robust stats wider in IDPS - More outliers IDPS/ACSPO Analyses routinely performed in SQUAM Comparisons with other AVHRR and MODIS products are also done VIIRS, MODIS, and AVHRR SST products are being improved

  14. L2/L3 SQUAM: Warm-Up Cool-Down Event IDPS shows larger Std Dev Loss of Envisat NPP JPSS • SST Std Dev from OSTIA for VIIRS, AVHRR, MODIS • AVHRR and MODIS closely track each other • ACSPO VIIRS is consistent with MODIS/AVHRR • So far, IDPS VIIRS EDR shows larger Std Dev than ACSPO

  15. L4 intercomparison • Inter-compare L4 SSTs using similar diagnostics: • maps, histograms, time series, Hovmöller • All analyses are done in two modes: • including and excluding ice fields (if ice flags available) • Validate consistently against quality controlled in situ data Group for High Resolution Sea Surface Temperature (GHRSST) analysis fields inter-comparisons —Part 1: A GHRSST multi-product ensemble (GMPE) Deep Sea Research Part II:, 77-80, 21-30, 2012 Group for High Resolution Sea Surface Temperature (GHRSST) analysis fields inter-comparisons —Part 2: Near real time web-based level 4 SST Quality Monitor (L4-SQUAM) Deep Sea Research Part II:, 77-80, 31-43, 2012

  16. L4 SQUAM: http://www.star.nesdis.noaa.gov/sod/sst/squam/L4/

  17. Summary and Future Work • SQUAM currently monitors major global polar L2/3 SST products from VIIRS, MODIS, and AVHRR, and 14 L4 SST products • Two VIIRS SST products were added in Jan 2012: ACSPO and IDPS • ACSPO SST is consistent with AVHRR/MODIS family, IDPS SST is less accurate • Work is underway to improve both VIIRS SST products, and reconcile • Future data additions in SQUAM • Polar: MODIS MOD29/MYD28 and (A)ATSR • Geostationary: MSG, MTSAT, GOES – Preparation for GOES-R • Remaining L4 SSTs • Work with community towards Improved self- and cross-consistency of SST products • Improve cloud masks, SST algorithms, sensor calibration • Explore SST diurnal variability models • Understand relative merit and differences of products, and reconcile • Facilitate blending towards improved analyses, forecast, and climate THANK YOU!

  18. BACK UP Slides

  19. SQUAM web

  20. JPSS Data Products: IDPS – Interface Data Processing Segment • Algorithms: IPO/NPOESS (Northrop Grumman Aerospace Systems) • Operational Products: IPO/NPOESS (Raytheon) IDPS (RDRs, SDRs, EDRs)

  21. L2/L3 SQUAM: • High Res. L2 SST mean differences: • VIIRS, AVHRR, MODIS • ACSPO VIIRS is consistent with MODIS & AVHRR • - IDPS VIIRS EDR shows larger diff (also Std Dev; not shown) Warm-Up Cool-Down Event L2 vs. OSTIA night, ~50-100mi/day NPP JPSS L2 vs. in situ drifters night, ~1500-2000/day

  22. L2/L3 SQUAM: NIGHT STD DEV wrt. OSTIA L4 Warm-Up Cool-Down Event IDPS shows larger STD DEV • AVHRR & MODIS SSTs are consistent • ACSPO VIIRS is consistent with MODIS & AVHRR • IDPS VIIRS EDR shows larger STD DEV

  23. L2/L3 SQUAM: DAY STD DEV wrt. OSTIA L4 Warm-Up Cool-Down Event IDPS shows much larger STD DEV • AVHRR & MODIS SSTs are consistent • ACSPO VIIRS is consistent with MODIS & AVHRR • IDPS VIIRS EDR shows much larger STD DEV

  24. L2/L3 SQUAM: NOAA-17 mid-morning platform - Diurnal warming suppressed Platforms Year Wind Speed (ms-1)

  25. L4 SQUAM: “OISST – CMC” mean zonal difference Diff. in ice mask Year HL issues More combinations at: http://www.star.nesdis.noaa.gov/sod/sst/squam/L4/ Latitude

  26. L4 SQUAM: Too many products busy .. Interactive plots available online Mean Std Dev wrt drifters wrt drifters Year Year Roughly, L4 products form 3 major groups (when compared against GMPE): DOI_AV,DOI_AA,RTG_LR,NAVO K10, G1SST RTG_HR,GOES-POES blended (with seasonal variation between: RTG_HR, RTG_LR) OSTIA,CMC,GAMSSA&GMPE

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