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

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

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

Climate Operations Model

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

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)

RequirementGCOS(2006)CMUG(2010)URD L3/L4 objective SST CCI plan Accuracy0.25 K0.1 K / 10 km 0.2 K / 1 km 0.01 K / 100 km 0.1 K/1000 km PrecisionNone0.05 K in monthly 0.02 K / 100 km Varies, quantify it Stability0.1 K / decade0.05 K / per decade 0.01 K / per decade; 0.02 K seasonally, diurnally 0.05 K / per decade, seasonally, diurnally Spatial resolution 1 km1 km (re- anal), 10 km 0.05 deg Temporal resolution 3 hourly observing cycle 3 h (re-anal.), daily, monthly 3 hourly (UTC)Day/night on standardized local time (L3) Uncertainty information NoneSSAOB SSEOB Total uncertainty Total, systematic and uncorrelated Type of SSTBlendedSkin & ??Skin & buoy- depth Skin and buoy-depth

Require- ment GCOS(2006)CMUG(2010)URD L3/L4 breakthru SST CCI plan Accuracy0.25 K0.1 K / 10 km 0.2 K / 1 km 0.02 K / 100 km 0.1 K/1000 km PrecisionNone0.05 K in monthly 0.05 K / 100 km Varies, quantify it Stability0.1 K / decade0.05 K / per decade 0.02 K / per decade; 0.05 K seasonally, diurnally 0.05 K / per decade, seasonally, diurnally Spatial resolution 1 km1 km (re-anal), 10 km 0.1 deg0.05 deg Temporal resolution 3 hourly observing cycle 3 h (re-anal.), daily, monthly Day/night (UTC) Day/night on standardized local time (L3) Uncertainty information NoneSSAOB SSEOB Total uncertainty Total, systematic and uncorrelated Type of SST BlendedSkin & ??Skin & buoy- depth Skin and buoy- depth Period~ now

2. Product specification

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

3. Consistency between ECVs

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)

3. Uncertainties in products

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.

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,

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

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

5. Needs for ECMWF data