The SST CCI: Scientific Approaches

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Presentation transcript:

The SST CCI: Scientific Approaches

The SST CCI: Scientific Approaches OUTLINE

What are we aiming for in a satellite SST CDR? What do current techniques give? What will we try in SST CCI? External involvement in SST CCI

The SST CCI: scientific approaches WHAT ARE WE AIMING FOR?

Requirements for SST CDR Property GCOS (2006) statement CCI survey 2010 Accuracy 0.25 K 0.1 K on 100 km scales Stability 0.1 K / decade Random uncertainty -- 0.1 K Spatial resolution 1 km 0.1o (<1 km) Temporal resolution 3 hourly Daily (3 hourly) Uncertainty information Total uncertainty in every cell. Error covariance information. Quality information Simple: probability of “bad” SST meaning Skin and depth required Independence Preferred by 60%

Independence Two meanings of independence Retrievals not tied to in situ observations Information for SST in retrieval near 100%

WHAT DO CURRENT TECHNIQUES GIVE? The SST CCI: scientific approaches WHAT DO CURRENT TECHNIQUES GIVE?

Pathfinder v5 NLSST 1 year Metop-A >200000 drifter night-time matches Single pixel Located at buoy MAD time 1h20

Derive coefficients and bias BTs, y Least squares regression MD SSTs, x Coefficients, a Map Predicted SST, ,given y and a

Regional annual biases

“Random” uncertainty

Dependence on prior Algorithm Sensitivity to true SST, x Fraction of information from prior

Imperfect sensitivity to SST Change in NLSST for a 1 K change in SST

Stability Zero mean bias against drifting buoy sample Prior error depends on mean of matches Stability could depend on buoy distribution Needs to be assessed

Issues with NLSST for CDR Empirically tied to drifting buoys Neither skin nor depth SST Not independent Dependence of bias on evolving match-up? Biases and “random” errors exceed user requirements Dependence: (5% to 60%) of result supplied by implicit prior

How to improve on NLSST? Use 3.7 um when available Improves on bias, precision and prior dependence But introduces day-night inconsistencies Banding of coefficients Latitude, TCWV Bias correction by simulation Le Borgne, 2011, doi:10.1016/j.rse.2010.08.004 Optimal estimation

ATSR Reprocessing for Climate >15 years global coverage, 0.1 deg Accuracy < 0.1 K Stability of 0.05 K per decade Both skin and depth SSTs Diurnal cycle removed Comprehensive error characterization Independent of other records

Radiative transfer modeling and inverse theory Probabilistic, physically based Physical models of skin and stratification 18

ARC SST mean v. drifters N2 (b) N3 (c) D2 (d) D3

ARC SST RSD v. drifters

ARC dependence on prior N2 (b) N3 (c) D2 (d) D3

ARC stability (provisional) Global oceans (data gaps filled) Provisional homogeneity ATSR2/AATSR Trend uncertainty magnitude displayed relative to end of time-series

The SST CCI: scientific approaches WHAT WILL WE TRY NEXT?

Bringing AVHRR and ATSR together Tie AVHRR to ATSR instead of buoys Basis for independence, traceable to physics of radiative transfer Not merely adjusting AVHRR SST bias to ATSR Use common Optimal Estimation retrieval for IR Overcome information deficit in single view Meet 0.1 K bias target Information content / prior dependence known

(Sub) System for Long-term CCI SST

Development logic for AVHRR optimal estimate retrieval (“OE2”) Multi-sensor match-up data set Development logic for AVHRR optimal estimate retrieval (“OE2”)

Mean diurnal cycle

AVHRR orbit drift

AVHRR orbit drift

Characteristics of Long Term CCI SST PATHFINDER ARC CCI SST Sensors AVHRR ATSR AVHRR + ATSR Tied to Drifting buoys Independent Homogenized No Yes Accounting for diurnal effects Meets GCOS accuracy (0.25 K) Meets ARC target accuracy (0.1 K) Mostly Yes/mostly Retrieval method Coefficients Optimal Meets GCOS stability ? Likely Stability quantified Clearly defined SST SST-skin & depth Stable during strat. aerosol Quantified uncertainties Spatial resolution 4 km 0.1o 1 km to 0.05o

EXTERNAL INVOLVEMENT IN SST CCI The SST CCI: scientific approaches EXTERNAL INVOLVEMENT IN SST CCI

Ways to get involved Augment Multi-sensor Match-up Dataset Talk to us now! Algorithm selection round robin August 2011 to November 2011 Climate Data Research Package January 2013

THANK YOU FOR YOUR ATTENTION. QUESTIONS? The SST CCI: scientific approaches THANK YOU FOR YOUR ATTENTION. QUESTIONS?