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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