Post on 06-Jan-2016
description
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A High Resolution Daily SST Analysis
Richard W. Reynolds (NOAA, CICS)
Dudley B. Chelton (Oregon State University)
Thomas M. Smith (NOAA, STAR)
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Background• The Group for High Resolution SST
(GHRSST) supports many high resolution SST products
– 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 which analyses are superior
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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?
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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?
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Results
• RSS has too much variability compared to buoys at middle and high frequencies
• There is no clear correlation between resolution and spatial grid size
• Is there a better way to do analyses?
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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
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MW and IR DATA: 5 July 2003
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25 km MW and IR Daily OI
4.4 km IR Daily OI
Two Stages
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Analysis DifferencesHigh – Low
• Upper panel: No filter of Pathfinder AVHRR
– Note bull’s eyes: especially along 145°E
• Lower panel: Median filter of Pathfinder AVHRR
– Data extremes tossed by eliminating data where the |median – observation| > 0.8°C
– Fewer bull’s eyes
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RMS monthly differences:High – Low
• Upper panel: January 2003
• Lower panel: July 2003
• Note regions with little difference (no AVHRR hi-res signal)
– Gulf Stream in January
– Off Peru/Columbia coast in July
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California Current Region: SST (oC)
• Rest of SST pictures will focus on this region
• The figure shows an unusual day with no clouds
• Note complex interweaving SST patterns
• Coastal upwelling
• If all days were like this SST analysis would be simple
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11 September 2003: Hi-Res & Low-Res OI SST (oC) |Gradient| (oC/100 km)
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11 Sep. ‘03SST Gradient: (°C/100 km)
• Upper panel: Hi-Res- qualitatively similar to
what is expected
• Middle panel: Low-Res
• Lower 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)
• Upper panel: Hi-Res
• Middle panel: Low-Res
• Lower panel: Diff. (Hi-Res – Low-Res)
– With Hi-Res Normalized Error 0.8 Contour
– Note correlation between contour and high gradients
– Highest SST gradients are likely due to cloud contamination
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2-Stage Analysis
• High Resolution Analysis: using 3 days Pathfinder AVHRR data– Shows promise– The high-res analysis resolution is
only improved when high resolution data are available
– Some further tuning needed to improve gradients
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High Resolution SST Analyses
• What have we learned? - SST gradients are a powerful way to
investigate the truth of small-scale features
• Where do we go from here?
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Goldilocks & the 3 Bears
Need to help users find the SST analysis that “is just right”
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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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Is it SST signal or SST noise?
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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
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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
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GHRSST & High Resolution
Signal and Noise must be Balanced in an SST Analysis
GHRSST
Reynolds & Chelton