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4 June 2009 GHRSST-X STM - SQUAM 1
The SST Quality Monitor (SQUAM)
10th GHRSST Science Team Meeting1-5 June 2009, Santa Rosa, CA
Alexander “Sasha” Ignatov*, Prasanjit Dash*, John Sapper**, Yury Kihai*
NOAA/NESDIS
*Center for Satellite Applications & Research (STAR)**Office of Satellite Data Processing & Distribution (OSDPD)
4 June 2009 GHRSST-X STM - SQUAM 2
NESDIS Operational AVHRR SST Products
Heritage Main Unit Task (MUT)- 1981 - present (McClain et al., 1985; Walton et al., 1998).
New Advanced Clear-Sky Processor for Oceans (ACSPO)- May 2008 – present
http://www.star.nesdis.noaa.gov/sod/sst/squam/
Employ L4 SSTs (Reynolds, RTG, OSTIA, ODYSSEA, ..) to
Evaluate MUT and ACSPO SST products in near-real time
for self-, cross-platform and cross-product consistency
Identify product anomalies & help diagnose their causes (e.g.,
sensor malfunction, cloud mask, or SST algorithm)
Objective of the SST Quality Monitor (SQUAM)
4 June 2009 GHRSST-X STM - SQUAM 3
Customarily, satellite SSTs are validated against in situ SSTs
However, in situ SSTs have limitations
They are sparse and geographically biased (cover retrieval
domain not fully and non-uniformly).
Have non-uniform and suboptimal quality (often comparable to
or worse than satellite SSTs).
Not available in near real time in sufficient numbers to cover the
full geographical domain and retrieval space.
4 June 2009 GHRSST-X STM - SQUAM 4
AVHRR SST MetOp-A GAC, 3 January 2008 (Daytime)
Heritage MUT SST product ACSPO SST product
SST imagery is often inspected visually for quality and artifacts.
Large-scale SST background dominates making it not easy to discern “signal” from “noise”.
4 June 2009 GHRSST-X STM - SQUAM 5
Heritage MUT SST product
Mapping deviations from a global reference field constrains the SST “signal” and emphasizes “noise”.
This helps reveal artifacts in SST product (cold stripes at swath edges).
Removing large-scale SST background (daily 0.25º Reynolds) emphasizes ‘noise’
ACSPO SST product
4 June 2009 GHRSST-X STM - SQUAM 6
View angle dependence of‘MUT - daily Reynolds SST’ (NOAA-17)
Such ‘retrieval-space’ dependent biases are difficult to uncover and quantify using customary validation against in situ data, which do not fully cover the retrieval space.
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.
4 June 2009 GHRSST-X STM - SQUAM 7
Use global L4 SST products to quantitatively evaluate satellite SST
Satellite & reference SSTs are subject to near-Gaussian errors
TSAT = TTRUE + εSAT ; εSAT = N(μsat,σsat2)
TREF = TTRUE + εREF; εREF = N(μref,σref2)
where μ’s and σ’s are global mean and standard deviations of ε‘s
The residual is distributed near-normally
ΔT = TSAT - TREF = εSAT - εREF; εΔT = N(μΔT,σΔT2)
where μΔT = μsat - μref ; σΔT2 = σsat
2 + σref2 (if εSAT and εREF are
independent)
If TREF = Tin situ, then it is customary ‘validation’. If (μref, σref) are comparable to (μin situ, σin situ), and if εSAT and εREF are not too strongly correlated, then TREF can be used to monitor TSAT
4 June 2009 GHRSST-X STM - SQUAM 8
Global Histograms of TSAT - TREF (Nighttime MUT)
4 June 2009 GHRSST-X STM - SQUAM 9
Histogram of SST residualReference SST: In situ
30 days of data: ~6,500 match-ups with in situ SST
Median = -0.04 K; Robust Standard Deviation = 0.27 K
4 June 2009 GHRSST-X STM - SQUAM 10
8 days of data: ~483,500 match-ups with OSTIA SST
Median = 0.00 K; Robust Standard Deviation = 0.30 K
Histogram of SST residualReference SST: OSTIA
4 June 2009 GHRSST-X STM - SQUAM 11
8 days of data: ~483,700 match-ups with daily Reynolds SST
Median = +0.08 K; Robust Standard Deviation = 0.44 K
Histogram of SST residualReference SST: Daily Reynolds
4 June 2009 GHRSST-X STM - SQUAM 12
Global histograms of TSAT - TREF are close to Gaussian,
against all TREF including Tin situ
Normal distribution is characterized by location (median) and scale (robust standard deviation, RSD)
Reduced number/magnitude of outliers with respect to L4 TREF compared to Tin situ
For some TREF (e.g., OSTIA), VAL statistics is closer to
Tin situ than for others (e.g., Reynolds).
* More histograms (ACSPO/MUT, day/night, other platforms / reference SSTs) are found at SQUAM page
Observationsfrom global histograms analyses
4 June 2009 GHRSST-X STM - SQUAM 13
Time SeriesGlobal Median Biases of (TSAT - TREF)
4 June 2009 GHRSST-X STM - SQUAM 14
Global Median Biases TSAT – Tin situ
1 data point = 1 month match-up with in situ Median Bias within ~0.1 K (except for N16 - sensor problems) MetOp-A and N17 fly close orbits but show a cross-platform bias
of ~0.1 K
4 June 2009 GHRSST-X STM - SQUAM 15
1 data point = 1 week match-up with OSTIA SST Patterns reproducible yet crisper (finer temporal resolution) Cross-platform biases: Slightly differ from Val (diurnal cycle) OSTIA artifacts observed in early period (2006-2007)
Global Median Biases TSAT – TOSTIA
4 June 2009 GHRSST-X STM - SQUAM 16
1 data point = 1 week match-up with Reynolds SST Patterns reproducible but noisier than with respect to OSTIA Artifacts also observed but different from OSTIA
Global Median BiasesTSAT – TReynolds
4 June 2009 GHRSST-X STM - SQUAM 17
Number of match-ups is more than two orders of magnitude larger against L4 TREF than against Tin situ
Major trends & anomalies in TSAT are captured well against
all TREF. More detailed and crisper than against Tin situ
Some TREF are “noisier” for VAL purposes than others.
Different artifacts are seen in different TREF
Nevertheless, time series of (TSAT – TREF) can be used to
monitor TSAT for cross-platform & cross-product consistency
* More time series (ACSPO/MUT, other reference SSTs) are available from SQUAM page
Observationsfrom time series of global biases
4 June 2009 GHRSST-X STM - SQUAM 18
Cross-platform consistency of TSAT can be evaluated from
time series of TSAT -TREF overlaid for different platforms
For more quantitative analyses, one ‘reference’ platform can be selected & subtracted from all other (TSAT -TREF)
N17 was selected as ‘reference’, because it is available for the full SQUAM period, and its AVHRR is stable
Double-differences (DD) were calculated as
DD = (TSAT -TREF) - (TN17 -TREF)
for SAT=N16, N18, and MetOp-A
Cross-Platform Consistency Using Double-Differences (TSAT – TSAT_REF)
4 June 2009 GHRSST-X STM - SQUAM 19
Global Median Biases TSAT – Tin situ
Same as slide 14
4 June 2009 GHRSST-X STM - SQUAM 20
In situ Double-Differences (TSAT – Tin situ ) - (TN17 – Tin situ )
Biases are due to errors in TSAT and TSAT /Tin situ skin/bulk differences
Before mid-2006, all SSTs agree to within ~0.01 K In 2006, N16 develops a low bias up to ~-0.7 K, and N18 and MetOp-A
a warm bias up to ~+0.1 K
4 June 2009 GHRSST-X STM - SQUAM 21
OSTIA Double-Differences (TSAT – TOSTIA ) - (TN17 – TOSTIA )
DD’s with respect to global reference fields: Errors in TSAT + Missing diurnal signal in TREF (TREF do not resolve diurnal cycle)
N16: sensor problems. MetOp-A: suboptimal regression coefficients Diurnal correction to TREF is needed to rectify inconsistencies in TSAT
4 June 2009 GHRSST-X STM - SQUAM 22
Reynolds Double-Differences (TSAT – TReynolds ) - (TN17 – TReynolds )
DD’s are consistent for different TREF (biases/noises in TREF largely cancel out in calculating DD’s)
4 June 2009 GHRSST-X STM - SQUAM 23
In situ DD’s are close to ‘true’ cross-platform bias in TSAT
(bulk Tin situ partially accounts for diurnal cycle in skin TSAT)
DD’s with respect to global TREF additionally include diurnal
signal (current L4 TREF do not resolve diurnal cycle)
Employing diurnal-cycle resolved TREF in DD’s (or adding
diurnal correction on the top of existing TREF) should rectify
the ‘true’ cross-platform inconsistency in TSAT
The DD’s provide quick global ‘validation’ of the diurnal cycle model (e.g., Gentemann et al, 2003; Kennedy et al, 2007; Filipiak and Merchant, 2009)
Observationsfrom Satellite-to-Satellite Double Differences
4 June 2009 GHRSST-X STM - SQUAM 24
Day-Night consistency of TSAT can be evaluated as
DD = (TDAY -TREF) - (TNIGHT -TREF)
Day-Night Consistency Using Double-Differences TDAY – TNIGHT
4 June 2009 GHRSST-X STM - SQUAM 25
In situ Day-Night Double-Differences (TDAY – Tin situ ) - (TNIGHT – Tin situ )
During daytime, all platforms show a warmer ~+(0.1±0.1) K bias (except for N16 – sensor problem)
Seasonal structure seen in DD’s Different capturing of diurnal cycle by skin TSAT and bulk Tin situ
4 June 2009 GHRSST-X STM - SQUAM 26
OSTIA Day-Night Double-Differences (TDAY – TOSTIA ) - (TNIGHT – TOSTIA )
Day-Night DD’s wrt OSTIA show biases due to diurnal warming Seasonal variability seen in all DD’s For N17 and MetOp-A (~10am/pm), diurnal signal is (+0.1±0.1) K For N18 (~2am/pm), diurnal signal is (+0.3±0.1) K
4 June 2009 GHRSST-X STM - SQUAM 27
Reynolds Day-Night Double-Differences (TDAY – TReynolds ) - (TNIGHT – TReynolds )
DD’s are closely reproducible for all TREF (biases/noise in TREF largely cancel out in calculating DD’s)
4 June 2009 GHRSST-X STM - SQUAM 28
DD’s wrt in situ data more closely represent cross-platform inconsistencies in TSAT, less difference in the diurnal
If global TREF is used, then DD’s additionally include diurnal
signal (currently, TREF‘s do not resolve diurnal cycle)
Employing diurnal-cycle resolved TREF in DD’s is expected
to improve cross-platform consistency
The DD’s provide quick global ‘validation’ of the diurnal cycle model (e.g., Gentemann et al, 2003; Kennedy et al, 2007; Filipiak and Merchant, 2009)
Observationsfrom Day-Night Double Differences
4 June 2009 GHRSST-X STM - SQUAM 29
Validation against global reference fields is currently employed in SQUAM to monitor two NESDIS operational AVHRR SST products, in near-real time
It helps quickly uncover SST product anomalies and diagnose their root causes (SST algorithm, cloud mask, or sensor performance), and leads to corrections
Summary and Future Work
Work is underway to reconcile AVHRR & reference SSTs - Improve AVHRR sensor calibration- Adjust TREF for diurnal cycle (e.g., Kennedy et al., 2007)- Improve SST product (cloud screening, SST algorithms)- Provide feedback to TREF producers
Objective is to have a single “benchmark” SST in NPOESS era
Add NOAA-19 and eventually MetOp-B, -C and VIIRS to SQUAM
We are open to integration with GHRSST and collaboration (to test other satellite & reference SSTs, diurnal correction, ..)
4 June 2009 GHRSST-X STM - SQUAM 30
SQUAM page http://www.star.nesdis.noaa.gov/sod/sst/squam/ Real time maps, histograms, time series (including double differences), dependencies
CALVAL page http://www.star.nesdis.noaa.gov/sod/sst/calval/ Cal/Val of MUT and ACSPO data against in situ SST (currently, password protected but will be open in 2-3 months)
MICROS page http://www.star.nesdis.noaa.gov/sod/sst/micros/ (Monitoring of IR Clear-sky Radiances over Oceans for SST) Validation of SST Radiances against RTM calculations with Reynolds SST and NCEP GFS input
NESDIS NRT SST analyses on the web