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1
High Resolution Daily Sea Surface Temperature
Analysis Errors
Richard W. Reynolds (NOAA, CICS)
Dudley B. Chelton (Oregon State University)
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GHRSST & High Resolution
SST Analysis: Must be a balance between Signal and Noise
GHRSST
Reynolds & Chelton
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Background• GHRSST (The Group for High
Resolution SST) includes many high resolution SST analyses
– There are differences in input data, grid resolution, analysis procedures
– There are important differences in analyzed SSTs and analysis resolution
• Reynolds and Chelton compared 6 SST analyses for 2006-08 to try to identify analysis problems and determine whether any of the analyses are superior
4
SST Analyses, 1 January 2007• RSS OI
– (~1/11)° grid
• NCEP RTG-HR– (1/12)° grid
• UK OSTIA– (1/20)° grid
• NCDC Daily OI: (AMSR + AVHRR) – (1/4)° grid
• Spatial scales differ
• Differences can exceed 5°C off coast
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Random + Sampling Error
• OI Derived– Top panel: Top panel:
AVHRR-only– Bottom panel: Bottom panel:
AMSR+AVHRRAMSR+AVHRR• Sampling errors
are larger than random errors
• Sampling and random error reduced by observations– Lower for
AMSR+AVHRR
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SST Analyses, 1 January 2007• RSS OI
– (~1/11)° grid
• NCEP RTG-HR– (1/12)° grid
• UK OSTIA– (1/20)° grid
• NCDC Daily OI: (AMSR + AVHRR) – (1/4)° grid
• This is a daily average– What spatial
scales are justified?
7
Results
• There is no clear correlation between resolution and spatial grid size
• If the analysis resolution is pushed beyond the spatial and temporal resolution of the data: the apparent SST signal is simply just noise
• Is there a better way to do analyses?
8
Two Stage Analysis
1. Low Resolution (25 km) analysis using microwave and infrared satellite data plus in situ data
2. High Resolution (4.4 km) analysis using infrared satellite data only
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Why Two Stages?
• Both microwave (MW) and infrared (IR) satellite data are now available
– Microwave has better coverage than infrared
– Infrared has higher resolution than microwave
• “2-Stage Analysis” allows processing to take advantage of both types of data
10
Analysis DifferencesHigh – Low
• Top panel: Top panel: No filter of Pathfinder AVHRR
– Note bull’s eyes: especially along 145°E
• Bottom panel:Bottom panel: Median filter of Pathfinder AVHRR
– Data extremes tossed by eliminating data where the |median – observation| > 0.8°C
– Fewer bull’s eyes
11
RMS monthly differences:High – Low
• Top panel: Top panel: January 2003
• Bottom panel: Bottom panel: July 2003
• Note regions with little difference (no AVHRR hi-res signal)
– Gulf Stream in January
– Off Peru/Columbia coast in July
12 130W 125W 120W 115W 130W 125W 120W 115W 130W 125W 120W 115W 130W 125W 120W 115W
SST Gradient Magnitudes Castelao, et al. (2006), hourly averages: 2001-4
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11 Sep. ‘03SST Gradient: (°C/100 km)
• Top panel: Top panel: Hi-Res
• Middle panel: Middle panel: Low-Res
• Bottom panelBottom panel: OI Hi-Res Normalized Error
– Norm. Error ~1.0 if no Hi-Res Data
– Norm. Error < 0.8 with Hi-Res Data
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11 Sep. ‘03SST Gradient: (°C/100 km)
• Top panel: Top panel: Hi-Res
• Middle panel: Middle panel: Low-Res
• Bottom panelBottom panel: Difference (Hi-Res – Low-Res)
– With Hi-Res Normalized Error 0.8 Contour
– Indicator of data edge: e.g., cloud cover, swath edge
– Note correlation between contour and high gradients
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Input Data
• Pathfinder AVHRR Data with respect to AMSR+AVHRR– Data for 10 Sept. 2003
analysis shown– Data for 11 Sept. 2003
Analysis uses 10-12 Sept. 2003 data
• no data for 12 Sept.
• The only useful field for 10 and 11 Sept. analysis is AVHRR day data for 10 Sept. 2003
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Day Pathfinder10 Sept. 2003
• TopTop: Median filtered observations
• BottomBottom: Additional gradient filtering using climatology if missing box in 3x3– Large 1°C data to
AMSR+AVHRR difference near data edge
– Gradient filtering reduces but can’t eliminate it
– Gradient filtering does reduce other gradients at date edge
17
Analysis11 Sept. 2003
• TopTop: Median filtered analysis
• BottomBottom: Median + gradient filtering near data edge: 3x3 box with at least 1 missing ob– Some improvement– Gradients are
unrealistic showing where analysis resolution changes
– May need to reduce analysis resolution at data edge
3x3 edge with large gradient
19
Why are there Data Edge Biases?
• Retrievals are from NOAA-17, a morning satellite: bias is unlikely to be a diurnal signal; also same positive bias seen at night on another several other days
• Median and gradient filtering not adequate
• Are the biases due to cloud detection problems?
• How should these biases be corrected?• Can the Pathfinder team help?
20
Low-Res Analysis
11 Sept. 2003
• Top: Top: AVHRR-only• Middle: Middle:
AMSR+AVHRR• Bottom: Bottom: Difference:
AVHRR-only warmer than AMSR+AVHRR by more than 1°C
• AMSR dominates AVHRR due to better sampling
21
Filtering for High-Res Data
• Large-scale bias correction (15 day, ~1000 km): to correct satellite data with respect to in situ data
• Median Filtering: To eliminate 1 pixel extremes
• Gradient Filtering: To eliminate errors near data (or cloud) edges
• ADD ?? Small-scale bias correction (3 day, ~100 km): to correct AVHRR data with respect to AMSR data
22
Is it Real or is it Memorex?
Advertisement from the 1990s implying that a live and a Memorex taped performance were the same
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Suggestions for Improving SST Analyses - 1
• Intercompare the input data– Look for and reduce isolated extremes
• Consider median filtering
– Be careful at boundaries between regions with and without data
• Computing an analysis is a bit like making sausage– The input impacts the
output
25
Suggestions for Improving SST Analyses - 2
• Compute several versions– Do intercomparsions among these versions
and with other analysis products to uncover problems
• Compute gradients– Look for large gradients at the boundaries
between regions with and without data
• Share results with others
27
One page summary-1“Truth in Advertising”
• SST Stats: Grid resolution, data used, temporal resolution, and period of analysis, provider, …..• This is easily available• We need to also provide “more
difficult” information
28
One page summary-2“Truth in Advertising”
• SST AnalysisAnalysis Resolution: Explain that the resolution changes in time and space with data changes– Example: For 2 stage analysis
• With AVHRR data: 10 km • Without AVHRR: 100 km • Flag regions with/without AVHRR data
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One page summary-3“Truth in Advertising”
• SST Bias Correction: Explain why corrections needed – For 2 stage analysis
• Ship SSTs reduced by 0.14°C to better match buoys
• Satellite data adjusted with respect to buoy and corrected ship data: 15 day, ~1000 km
• AVHRR data adjusted with respect to AMSR data: 3 day, ~100 km ??
30
One page summary-4“Truth in Advertising”
• Error Estimates: Verification needed by analysis and by data intercomparions– For 2 stage analysis
• Bias, random & sampling error estimated• Relative values useful• Absolute values may be too small
especially near the coast
31
One page summary-5“Truth in Advertising”
• Additional Data Processing– For 2 stage analysis
• Satellite data median filtered to eliminate grid scale bull’s eyes
• Satellite data near data edges eliminated when gradients large
• Other information– For 2 stage analysis
• Two stages allow useful separation of IR and MW resolution and sampling