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SPIE 2014 conference, Ocean Sensing and Monitoring 5–9 May, 2014, Baltimore Convention Center, MD

SPIE 2014 conference, Ocean Sensing and Monitoring 5–9 May, 2014, Baltimore Convention Center, MD. Towards Cal/Val of Sentinel-3 SST in NOAA SST quality monitor (SQUAM): initial evaluation of (A) ATSR reprocessing for climate (ARC) http://www.star.nesdis.noaa.gov/sod/sst/squam. SPIE 2014

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SPIE 2014 conference, Ocean Sensing and Monitoring 5–9 May, 2014, Baltimore Convention Center, MD

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  1. SPIE 2014 conference, Ocean Sensing and Monitoring5–9 May, 2014, Baltimore Convention Center, MD Towards Cal/Val of Sentinel-3 SST in NOAA SST quality monitor (SQUAM): initial evaluation of (A)ATSR reprocessing for climate (ARC)http://www.star.nesdis.noaa.gov/sod/sst/squam SPIE 2014 Ocean Sensing and Monitoring Sensing Sea Surface Temperature Paper 9111-20, 6 May 2014, 5:10-5:30 PM P. Dash1,2, A. Ignatov1, B. Petrenko1,3, Y. Kihai1,3 1NOAA NESDIS, NCWCP College Park, MD 2 Colorado State Univ, CIRA 3 GST, Inc, MD, USA (Emails: FirstName.LastName@noaa.gov) SQUAM objective: A global, web-based, community, quasi NRT, monitor for SST producers & users !

  2. Acknowledgments • Level-2 SST: VIIRS/AVHRR/MODIS • NESDIS SST Team :ACSPO (GAC: 5 platforms, FRAC: Metop-A & B, VIIRS: NPP, MODIS: Terra/Aqua) • P. LeBorgne, H. Roquet :O&SI SAF Metop-A FRAC • D. May, B. McKenzie : NAVO SEATEMP • S. Jackson :IDPS (NPP) • Level-3 SST: AVHRR/(A)ATSR: • K. Casey, R. Evans, J. Vazquez, E. Armstrong:PathFinder v5.0 • C. Merchant, Owen Embury:ARC (ongoing effort – current presentation) • 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 • J Hoyer :DMI OISST • M. T. Chin, J. Vazquez, E. Armstrong :JPL MUR • GHRSST support:Peter Minnett, Craig Donlon, Alexey Kaplan Definitions of levels: L2: at observed pixels (satellite) L3: gridded with gaps (satellite) L4: gap-free gridded, time-averaged CMC

  3. Outline

  4. 1. Space-based SST products Schematic overview of the space-based GOS (source: http://www.wmo.int/pages/prog/sat/globalplanning_en.php) Many SST products (see www.ghrsst.org for more details) (overview of SST products; next slide) Operational producers of global satellite SST CMC

  5. 1. SST datasets Level 4 • Reynolds (AVHRR; +AMSR-E*) • RTG (Low, High Resolution) • OSTIA, Opr+ Retro (UKMO) • ODYSSEA (France) • GMPE (GHRSST) • NAVOK10 • NESDIS POES-GOES Blended • JPL G1SST, JPL MUR • NCODA (NRL) • CMC 0.2, Opr+Reproc • GAMSSA (ABoM) • MGDSST (JAXA, Japan) • RSS (MW, MW+MODIS) • DMISST (Danish Met. Inst.) Level 2/3 • Polar • AVHRR (NESDIS, NAVO, O&SISAF, U. Miami, NODC) • VIIRS (NESDIS, IDPS,NAVO),MODIS,ATSR, • Microwave • Geostationary • GOES (NESDIS, NAVO, O&SISAF) • SEVIRI (NESDIS, O&SISAF) • MTSAT (NESDIS, JAXA) In situ • Sources • GTS, ICOADS, GODAE/FNMOC • Platforms • Drifters, Moorings, Ships, ARGO Floats • Quality Control • May be unavailable or non-uniform To monitor and cross-evaluate these products, SQUAM was set-up, as a community online tool.

  6. 2. SQUAM objective and overview • Cross-evaluate all major global SST products and validate against a consistent reference standard, in NRT • Report their summary 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” • Distributions for Normality (X~N(µ,σ)) • Compare and Trend parameters in time

  7. 2. SQUAM – web interface Locate this website: Google: “SST + SQUAM” L2: The SST Quality Monitor (SQUAM), J.Tech, 27, 1899-1917, 2010 L4: GHRSST Analysis fields intercomparison, DSR-2, 77–80, 31–43, 2012

  8. 3. Sentinel-3 (S3) mission • Sentinel-3 (source: www.esa.int) • Scheduled: early 2015. builds on the ERS-2/Envisat heritage • SLSTR instrument (Donlon et al., GHRSST XIII ST meeting, Tokyo, 2012): • aims at continuity of SST as good as (A)ATSR or better; SLSTR~ATSR4 • Key improvements over AATSR: increased # of bands, swath and spatial res. for VIS/SWIR, improved coverage < 4 days global ocean • Role of NOAA and SQUAM • NOAA and ESA partnership for sharing L2 data. We will monitor SLSTR SSTs and evaluate it for anchoring (less accurate) ACSPO SST • (A)ATSR Reprocessing for Climate (ARC) data as a test-bed • ARC L2P data is analyzed in SQUAM as prep. for S3 SST. [QF GE 3] • Main objective is to establish a set-up for S3 data; in the process, ARC is being compared with other high-resolution products in HR-SQUAM • Data src.: ftp://ats-ftp-ds.eo.esa.int (search www.esa.int for more info)

  9. 4. ARC SST in HR-SQUAM – preliminary analysis Night: ACSPO MetopAminus OSTIA L4, 30-Mar-2012 • Deviation from TR is flat & close to 0 • Residual Cloud/Aerosol leakages seen in the Tropics, and some in mid-latitudes

  10. 4. ARC SST in HR-SQUAM – preliminary analysis Night: ARC AATSRminus OSTIA L4, 30-Mar-2012 • Deviation from TR is flat & close to 0 • Much narrower swath and lesser coverage (known)

  11. 4. ARC SST in HR-SQUAM – preliminary analysis “ACSPO MetopA– OSTIA” - Night 30-Mar-2012 - Ref. = OSTIA - Metop-A-AVHRR FRAC t(op) ARC AATSR (bottom) “ARC AATSR – OSTIA” • ~Gaussian (both) • Comparable stats (values ~expected) • factor pf ~4 fewer NOBS in ARC

  12. 4. ARC SST in HR-SQUAM – preliminary analysis • Dailyvalidation wrt. Drifters (night) • - Comparable performances (mean & Std dev wrt drifters) for all products • ATSR1 (pink) had sensor issues and should be used with caution • Similar plots available against gap-free L4 fields and will be shown online after further discussions (next time)

  13. 4. ARC SST in HR-SQUAM – preliminary analysis

  14. 5. Summary and Future Work • Preliminary comparisons against high-quality L4 fields and QC’ed drifters from iQuam (www.star.nesdis.noaa.gov/sod/sst/iquam/) show that ARC data performance is comparable with other high resolution products (Metop-A FRAC, S-NPP VIIRS) • Global coverage and number of observations is factor of ~3 to ~6 smaller for (A)ATSR, because of its narrow swath • This work is preliminary and not conclusive. We are in touch with ARC data producers to improve our analyses • Future Work: The major objective of this ARC set-up SQUAM is preparing towards analyses of Sentinel-3 SLSTR SST product, soon after it becomes available. THANK YOU!

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