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GHRSST Joint DVWG, HL-TAG & ST-VAL workshop 28 Feb – 02 Mar, 2011, Boulder, CO. The SST Quality Monitor (SQUAM) : an overview. 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) - PowerPoint PPT Presentation
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GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20111
GHRSST Joint DVWG, HL-TAG & ST-VAL workshop
28 Feb – 02 Mar, 2011, Boulder, CO
The SST Quality Monitor (SQUAM) :an overview
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 !
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20112
Contributions/Support
AVHRR Level 2 SSTs:- J. Sapper, Y. Kihai, B. Petrenko, J. Stroup: NESDIS ACSPO- P. LeBorgne: O&SI SAF MetOp-A FRAC- D. May, B. McKenzie: NAVO SEATEMP
AVHRR Level 3 SST:- K. Casey, T. Brandon, R. Evans, J. Vazquez, E. Armstrong: PathFinder v5.0
Level 4 SSTs:- R. Grumbine, Xu Li, B. Katz: RTG (Low-Res & Hi-Res), GSI- R. Reynolds: OISSTs (AVHRR & AVHRR+AMSRE)- M. Martin: OSTIA foundation, GHRSST Median Product Ensemble- D. May, B. McKenzie: NAVO K10- E. Autret, J.-F. Piollé: ODYSSEA- E. Maturi, A. Harris, J. Mittaz: POES-GOES blended- B. Brasnett: Canadian Met. Centre, 0.2 foundation- Y. Chao: JPL G1SST
L4s in SQUAM pipeline:- H. Beggs: ABOM GAMSSA- C. Gentemann: MISST- M. T. Chin, J. Vazquez, E. Armstrong: JPL MUR- M. Martin, J. Roberts-Jones: OSTIA reanalysis extended history (1985-2007)
GHRSST support: - Craig Donlon, Matt Martin, Andrea Kaiser-Weiss And the ORGANIZERS: 2x-Gary, Sandra
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20113
Objectives of SQUAM
Initial:
Monitor NESDIS MUT and ACSPO SSTs for stability, self-consistency, cross-consistency (platform, product)
Evaluate satellite SST products daily in global domain, against global L4 fields (complements the validation against in situ SSTs)
Quickly facilitate product diagnostics (e.g., identify anomalies due to sensor malfunction, cloud mask, or SST algorithm)
Subsequent:
Other L2 (e.g., NAVO, O&SI SAF), L3 (PFv5.0) & L4 SSTs were includedand consequently now………..
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20114
Current list of SSTs included in SQUAM
In pipeline:• L2 : SEVIRI (ACSPO & NESDIS operational)• L4: ABOM GAMSSA, REMSS MISST, JPL MUR
Locate this website:• Google: “NESDIS + SQUAM”, the first hit
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20115
SQUAM approach: Premises of comparing against L4
In situ measurements have limitations :
Sparse and geographically biased (HL even worse)
Quality non-uniform and suboptimal Not available in NRT in sufficient numbers (ISAR presentation, AATSR, SEVIRI)
Jan 2011 global insitu data, ~ 45K/dy, src: http://www.star.nesdis.noaa.gov/sod/sst/iquam/
SQUAM complements heritage VAL against in situ: ΔTS = SST to be monitored (TS) – reference L4 SST (TR)
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
L2/3 SQUAM
Tabs for analyzing ΔTS (sat SST – L4): Maps
Histograms
Time series (Gaussian moments, outlier info, & double differences)
Dependencies (on geophysical and observational parameters)
Hovmöller & alike (as is applicable)
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The SST Quality Monitor (SQUAM)Journal of Atmospheric & Oceanic Technology, 27, 1899-1917, 2010
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20117
L2/L3 SQUAM: Maps of ΔTS (TS-TR)
Maps are used to assess satellite SST globally “at a glance”
NESDIS ACSPO MetOp-A FRAC - OSTIA
O&SI SAF MetOp-A FRAC – OSTIA
More FRAC analyses at:http://www.star.nesdis.noaa.gov/sod/sst/squam/FRAC/
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
Tabs for analyzing ΔTS (sat SST – L4):
Maps
Histograms
Time series (Gaussian moments, outlier info, & double differences)
Dependencies
Hovmöller & alike (as is applicable)
8
L2/L3 SQUAM
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-20119
Gaussian parameters and outlier info are used in time-series plots
NESDIS MUT NOAA-19 - OISST
NAVO SEATEMP NOAA-19 - OISST
More MUT analyses at:http://www.star.nesdis.noaa.gov/sod/sst/squam/MUT/
More NAVO analyses at:http://www.star.nesdis.noaa.gov/sod/sst/squam/NAVO/
L2/L3 SQUAM: Histograms of ΔTS (TS-TR)
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
Tabs for analyzing ΔTS (sat SST – L4):
Maps
Histograms
Time series (Gaussian moments, outlier info, & double differences)
Dependencies
Hovmöller & alike (as is applicable)
L2/L3 SQUAM
10
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-201111
L2/L3 SQUAM: Timeseries of ΔTS (TS-TR)
SST val against in situnighttime, each point ~5K
NESDIS MUT AVHRR
SST vs. Reynoldsnighttime, each point ~0.5mi
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-201112
L2/L3 SQUAM: Double differences of ΔTS
DD can alleviate the issue of space-time mismatch by using a third transfer standard
SSTDay-Night = (SSTDay – L4) – (SSTNight – L4)
• If the L4s are compensated for DV corresponding to SST (x,t), then one would expect the curves to flatten out: Global Validation of DV models
• similar technique for cross-platform consistency (see SQUAM web!)
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
Tabs for analyzing ΔTS (sat SST – L4):
Maps
Histograms
Time series (Gaussian moments, outlier info, & double differences)
Dependencies
Hovmöller & alike (as is applicable)
L2/L3 SQUAM
13
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-201114
Such ‘retrieval-space’ dependent biases are difficult to uncover using customary validation (will take a long time) (as to why customary validation is inadequate!)
The SQUAM diagnostics helped uncover a bug in the MUT SST which was causing across-swath bias >0.7K.
After correction, bias reduced to ~0.2K and symmetric with respect to nadir.
L2/L3 SQUAM: Artifical dependency detection
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
Tabs for analyzing ΔTS (sat SST – L4):
Maps
Histograms
Time series (Gaussian moments, outlier info, & double differences)
Dependencies
Hovmöller & alike (as is applicable)
15
L2/L3 SQUAM
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
“Pathfinder v5.0 (Day) - OISST” vs. Wind SpeedPla
tform
sYear
Wind Speed (ms-1)
NOAA-17 mid-morning platform – Diurnal warming suppressed
http://www.star.nesdis.noaa.gov/sod/sst/squam/PF/
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GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
L4-SQUAM
Inter-compare L4 SSTs via similar diagnostics (maps, histograms …)
Validate consistently against quality controlled in situ data
IC-TAG
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GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011 18
http://www.star.nesdis.noaa.gov/sod/sst/squam/L4/
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
“OISST – CMC” mean zonal differenceYear
Latitude
HL issues, calls for consensus between the L4 developersMore combinations at: http://www.star.nesdis.noaa.gov/sod/sst/squam/L4/
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GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
“L4s – drifters”: time series statistics
More time-series at: www.star.nesdis.noaa.gov/sod/sst/squam/L4/l4_delsst_timeseries.htm
DOI_AVDOI_AARTG_HRRTG_LRGOESPOESOSTIACMC 0.2NAVO K10ODYSSEAGMPEG1SST
Reynolds OISST (AVHRR)Reynolds OISST (+ AMSR-E)Real Time Global high resolutionRTG low resolutionBlended POES and GOESOperational SST and Sea ice analysisCanadian Met. Centre 0.2 degreeNAVOCEANO 1/10 degreeMERSEA IFREMER/CERSATGHRSST Median Ensemble ProductJPL 1km G1SST
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, & GMPE
Mean
Year
Std
Dev
Year
wrt drifters wrt drifters
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GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-201121
“L4 val against drifters: summary stats”Type/resolution
InputMean Bias (K)
(27Feb11, # ~31K)
Std Dev (K)
Robust Conv.
Reynolds (AVHRR)Bulk, 0.25°
IR (PF till `05, then NAVO), & in situ-0.01 0.23 0.33
Reynolds (+AMSR-E)Bulk 0.25°
AVHRR IR, AMSR-E MW, & in situ-0.06 0.41 0.48
RTG low resolutionBulk, 0.5°
AVHRR IR, & in situ-0.04 0.35 0.45
NAVO K10Bulk, 0.1°
AVHRR, VISSR, AMSR-E, JPL cli.-0.08 0.30 0.51
POESGOES blendedBulk, 0.1°
AVHRR, GOES-0.04 0.35 0.43
RTG high resolutionBulk, 1/12°
AVHRR IR physical retr., & in situ-0.03 0.33 0.45
G1SST 1-kmBulk, 1/100°
AVHRR, AATSR, SEVIRI, AMSRE, TMI, insitu-0.06 0.22 0.35
OSTIAFoundation, 0.05°
IR: AVHRR, AATSR, SEVIRIMW: AMSR-E, TMI, SSMI ice, & in situ
-0.03 0.23 0.33
CMCFoundation, 0.2°
IR: AVHRR, AATSRMW: AMSR-E, & in situ & CMC sea/ice
-0.01 0.25 0.37
GMPEEnsemble, 0.25°
Most other L4s come in-0.03 0.22 0.36
ODYSSEASubskin, 0.1°
IR: AATSR, AVHRR, VISSR, SEVIRI, MW: AMSR-E, TMI
-0.08 0.36 0.46
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
L4-SQUAM highlights
• Add remaining L4s
• DV model val (for foundation
SSTs)
• Transfer processing from STAR
(mimicking ops) to operational
facility. Any volunteer ??
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Planned community publications in Deep-Sea Res-II, Special Issue (proposed abstracts accepted; manuscripts are due in June 2011):
1. Group for High Resolution SST (GHRSST) Analysis Fields Inter-Comparisons: Part 1. A Multi-Product Ensemble of Sea Surface Temperature Analyses
Matthew Martin1, Prasanjit Dash2,3, Alexander Ignatov2, Craig Donlon4, Alexey Kaplan5, Robert Grumbine6, Bruce Brasnett7, Bruce McKenzie8, Jean-Francois Cayula9, Yi Chao10, Helen Beggs11, Eileen Maturi2, Chelle Gentemann12, James Cummings13, Viva Banzon14, Shiro Ishizaki15, Emmanuelle Autret16, David Poulter17
2. Group for High Resolution SST (GHRSST) Analysis Fields Inter-Comparisons: Part2. Near real time web-based Level 4 SST Quality Monitor (L4-SQUAM)
Prasanjit Dash1,2, Alexander Ignatov1, Matthew Martin3, Craig Donlon4, Robert Grumbine5, Bruce Brasnett6, Doug May7, Bruce McKenzie7, Jean-Francois Cayula8, Yi Chao9, Helen Beggs10, Eileen Maturi1, Andy Harris1,11, John Sapper12, Toshio M. Chin9, Jorge Vazquez9, Edward M. Armstrong9
GHRSST, Joint DVWG, HL-TAG & ST-VAL workshop, 02-Mar-2011
Summary and Future Work
SQUAM currently monitors all “major Global” L2 AVHRR SST, L3 PF v5.0, and ~11 L4 SST products
They mostly show cross-platform and day-night consistency but there is room for improvement
Double Diff. may be useful for global Val of DV models
Highlights the HL discrepancies between various L4 products
Future plans Include remaining L4 SSTs
Add in situ val in SQUAM page for L2/L3 (done for L4)
Include Geostationary capabilities (prototype)
Include non-AVHRR polar products (MODIS, AATSR ….)
Find a way to link to HR-DDS (vice versa) – spoke with Dave P.
THANK YOU!SQUAM: http://www.star.nesdis.noaa.gov/sod/sst/squam
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