the sst quality monitor (squam) : an overview

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 !


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


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………..


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


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)


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


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/


Tabs for analyzing ΔTS (sat SST – L4):

Maps

Histograms


Dependencies


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L2/L3 SQUAM


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)



Maps

Histograms


Dependencies


L2/L3 SQUAM

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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


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!)



Maps

Histograms


Dependencies


L2/L3 SQUAM

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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



Maps

Histograms


Dependencies


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L2/L3 SQUAM


“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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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/


“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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“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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“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


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


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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the sst quality monitor (squam) : an overview

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