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Global 1-km Sea Surface Temperature (G1SST)

for Real-Time Research and Applications

Yi Chao

Jet Propulsion Laboratory, California Institute of Technology

Pasadena, California, USA

4-Year (FY10-FY13) Project funded by NASA Physical Oceanography Program

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Global 1-km SST (G1SST) for:

• Real-time applications (< 24 hours)

• Regional and coastal users (1-km, comparable to model resolution & observational data sets such as coastal radar, glider etc)

• Less sophisticated users with limited resources/bandwidth to produce their own GHRSST SST at 1-km resolution over their region of interests

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Real-time coastal forecasting with a 1-km model: Data assimilation & model validation

Chao, Y., Z. Li, J. D. Farrara, and P. Huang, 2009: Blended sea surface temperatures from multiple satellites and in-situ

observations for coastal oceans. J. Atmos. Oceanic

Technology, 10.1175/2009JTECHO592.1.

Why global?• Request for other regions

• If we can do for the California coast, we can do

the global ocean

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A few notes from this morning’s discussion: I hear both sides of the story

• Who are the targeted users? What are the processes of interests? (e.g., modelers for data assimilation, feature tracking, real-time synoptic regional/coastal vs CDR low-frequency large-scale)

• Recommendations: Data flag (dynamic) to indicate input data sets (1-, 5-, 25-km); Estimated errors

• Let “Goldilocks” to pick the right product; no single product meets everyone’s needs (one-page summary should help!)

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Two sides of the story: not enough 1-km data; ~50% of the world ocean has 1-km data on the daily basis

25-km

5-km

1-km

1-km product & including a data flag

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Input Data Sets: Microwave (25-km)

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Input Data Sets: Geostationary Infrared (5-km)

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Input Data Sets: Polar-Orbitin

g Infrared (1-km)

AVHRRAATSR

(not shown)

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In Situ SST Measurements

Ships, moorings, surface drifters, profiling floats

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How to combine multi-satellite and in situ SST daily to meet users’ needs?

1. Each pixel is measured multiple times by the same or different sensors

• To use all data that provide independent information

2. Each pixel is measured by sensors with different resolutions

• To combine data that provide information on different scales (e.g., 25-km MW, 5-km Geostationary, 1-km IR)

3. Different satellite and sensors have different errors including instrument error or representation error

• To weight data differently according to their errors

4. The spatial interpolation/extrapolation cannot be uniform

• To specify spatial varying de-correlation scales (e.g., open vs coastal ocean, along-shore vs cross-shore)

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Multi-Scale 2DAVR Algorithm

€

T = TL +TM +TH L: 25-km; M: 5-km; H: 1-km

€

J(δT ) =1

2δT T B−1δT +

i

∑ 1

2(Hsiδ

s

∑ Ti −δTsio)T Rsi

−1(HsiδTi −δTsio)

i: L, M, H S: input data sets

€

T a = T guess + δT

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Multi-Scale 2DAVR Algorithm: Gradient Control

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G1SST: version 1 in Sept 2008http://ourocean.jpl.nasa.gov/SST

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Data-Void (24-hour period) Masked

G1SST: version 2 in May 2010http://ourocean.jpl.nasa.gov/SST

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Validation: 20% In Situ SST Data reserved as

Independent

Data Points: 3856Bias = -0.06RMS = 0.59

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G1SST Data Distribution

CF-Compliant netCDF

OPeNDAP/THREDDS

G1SST data are also available in netCDF formatfrom GHRSST GDAC @ PO.DAAC

http://ourocean.jpl.nasa.gov/SST

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G1SST for Applications: Congo River Outflow Survey by Chervon

CongoRiver

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Future Work for G1SST (FY11-FY13)

• G1SST version 3 release projected in late 2011– Systematic bias correction (-0.1o)

– Data flag for input data used in blending (e.g., 25-km, 5-km, 1-km)

– Estimated errors (propagating errors from L2P to L4)

• G1SST version 4 and beyond– Diurnal warming correction (e.g., KPP mixed layer model)– More input data sets: AVHRR (HRPT)

– Include all data errors and co-variances

– Improved spatial-varying error co-variances

• Retrospective analysis (before Sept. 2008) – Computational cost– G1SST production is 2x faster than real-time on 16-processor cluster ($10K);

reprocessing takes $5K*(data-year/time-year), e.g., $5K*(10 data-year/0.5 time-year) = $100K

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Global 1-km Sea Surface Temperature (G1SST)

for Real-Time Research and ApplicationsQuestions?

Yi.Chao@jpl.nasa.gov

Thanks to

The G1SST Team: Zhijin Li, Peggy Li, Benyang Tang, Quoc Vu

Jet Propulsion Laboratory, California Institute of Technology

Pasadena, California, USA

4-Year (FY10-FY13) Project funded by NASA Physical Oceanography Program