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sst_cci

sst_cci. Chris Merchant The University of Edinburgh. 1. User requirements analysis. User requirements survey. Methods literature review lessons learned review web-based discussions / interviews questionnaire Analysis of 108 completed questionnaire respondents.

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sst_cci

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  1. sst_cci Chris Merchant The University of Edinburgh

  2. 1. User requirements analysis

  3. User requirements survey • Methods • literature review • lessons learned review • web-based discussions / interviews • questionnaire • Analysis of 108 completed questionnaire respondents

  4. Approach to analysis of user requirements: e.g., spatial resolution Threshold Breakthrough Objective

  5. User Requirements Summary • SST records longer than 30 years (breakthrough) • Phase 1 will cover 1991 – 2010 • L4 SSTs available within 1 week, 99% reliable • Homogeneous record always available, upgrades • Will carry into system specification for operations • Proper uncertainties and simple quality information • Pixel/cell flags • NetCDF available by ftp, CF compliant • Yes + GHRSST compatibility • Simple documentation … that describes all steps in product development (!) • Certainly algorithm and uncertainty information readily obtainable

  6. Climate Operations Model

  7. User Requirements Summary • SST records longer than 30 years (breakthrough) • Phase 1 will cover 1991 – 2010 • L4 SSTs available within 1 week, 99% reliable • Homogeneous record always available, upgrades • Will carry into system specification for operations • Proper uncertainties and simple quality information • NetCDF available by ftp, CF compliant • Yes + GHRSST compatibility • Simple documentation … that describes all steps in product development (!) • Certainly algorithm and uncertainty information readily obtainable

  8. User Requirements for SST • Skin SST retrievals and buoy-depth SST estimates • As planned • GCOS (2006) supports blending skin and “bulk”/in situ • 3 hourly analyses at 10 km resolution or better • Daily at 0.05 deg • Fundamental research for sub-daily analyses proposed as option • Bias: 0.01 K over 100 km scales • SST CCI target is to demonstrate 0.1 K over 1000 km scales • GCOS (2006) states 0.25 K with no indication of applicable scale • Stability 0.01 K, per decade, seasonally, diurnally • Our aim is 0.05 K • GCOS (2006) presents only 0.1 K per decade • Mix of L4 (analyses), L3 (regridded) and L2 (native)

  9. 2. Product specification

  10. Product Specification Process • Prepared by someone with EO experience within the CRG, advised by Science Team • Covering • file metadata • discovery metadata • document revision control • file format • file naming • Input constraints: GHRSST, CMIP5, CF and Guidance • “Data and Metadata Requirements for CMIP5 Observational Datasets“ • GDS2.0 takes precedence over CMIP5 where in conflict • Such conflicts will be debated within GHRSST • GHRSST community for international review

  11. 3. Consistency between ECVs

  12. Consistency of ECVs: two aspects • Spatio-temporal consistency • Compatibility with • CLOUDS at L1B/L2 levels from same sensors • SEA ICE at L2/L3/L4 • COLOUR at L3/L4 – want to be able to co-analyse • SEA-LEVEL? • Estimation consistency • Use compatible auxiliary info: aerosol, winds … • Mutual benefit from joint retrieval (in principle) • CLOUDS (e.g., thin and/or subpixel allowing SST) • AEROSOL (correlations in geophysics and errors)

  13. 3. Uncertainties in products

  14. Starting point • Uncertainty estimation is part of retrieval • (Some) users need to know about variability of uncertainty – need an uncertainty for every SST • Components of uncertainty have different correlation properties. Propagation of uncertainty from L2 to L3 and L4 needs to address each component appropriately.

  15. Uncertainty Characterisation • Six components to uncertainty • Random (precision / uncorrelated) • E.g., Radiometric noise: ~Gaussian NEDT, uncorrelated • Estimate by propagation through retrieval • Pseudo-random (precision / corr. sub-synoptic) • Algorithmic inadequacy • Correlated on synoptic space-time scales • Can simulate • Systematic (accuracy / correlated) • Forward model bias, calibration bias… • Prior error Merchant C J, Horrocks L A, Eyre J and O'Carroll A G (2006), Retrievals of SST from infra-red imagery: origin and form of systematic errors, Quart. J. Royal Met. Soc., 132, 1205-1223.

  16. Uncertainty Characterisation • Contaminant (precision, accuracy) • Non-Gaussian, asymmetric, sporadic • E.g., Failure to detect cloud; retrieval error from aerosol • Various space-time scales • Sampling • Random: scattered gaps because of cloud • Systematic: clear-sky effect?, biased false cloud detection • Stability • Time variation of any systematic effect • Approach: model / quantify each element • Aim: reconcile modelled and observed uncertainty

  17. Uncertainty estimation in Round Robin • SST uncertainty estimation is the reasoned attribution of uncertainty information to an estimate of SST • Algorithms for SST to include SST uncertainty • SST uncertainty estimates will be assessed for • BIAS • INDEPENDENCE • GENERALITY • IMPROVABILITY • DIFFICULTY

  18. 5. Needs for ECMWF data

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