© Crown copyright Met Office The EN4 dataset of quality controlled ocean temperature and salinity profiles and monthly objective analyses Simon Good

© Crown copyright Met Office What is the EN series of datasets? Climate datasets of ocean temperature and salinity profiles. Include: 1.The observed profiles with quality flags. 2.Monthly objective analyses formed from the data. Data are in NetCDF files. Freely available for scientific research and private study.

© Crown copyright Met Office Contents History of the dataset The EN4 dataset Objective analysis uncertainty estimates Ensemble of opportunity Conclusions

© Crown copyright Met Office History of the dataset

© Crown copyright Met Office How did they originate? The first version of the dataset was produced for the ENACT project (ENhanced ocean data Assimilation and Climate predicTion) for global ocean data assimilation. Data were collected from a number of sources. To get consistent quality control, all flags were discarded from the source. Then, all data were run through the Met Office quality control system. The system was shared with real time systems – necessary to have good automated checks.

© Crown copyright Met Office Updates to EN2 and EN3 A new version was produced for the ENSEMBLES project (EN2; Ingleby and Huddleston, 2007, Journal of Marine Systems, 65). Changes were updated data from sources; tweaks to quality control checks; updated background error covariances. EN3 (with various subversions) followed. Updated data again. Revised climatology. Tweaks to quality control checks again. Added some manual rejects.

© Crown copyright Met Office Update to EN4 Targeted development of a duplicate check and new quality control checks to solve specific issues with the dataset. Work done for the ERA-CLIM project (European Reanalysis of Global Climate Observations; Uncertainty estimates produced to accompany the objective analyses. Good et al. (2013), JGR-Oceans, 118.

© Crown copyright Met Office The EN4 dataset

© Crown copyright Met Office Input data Profiles obtained from WOD ASBO (Arctic Synoptic Basinwide Observations) Argo GTSPP Argo and GTSPP are used for monthly updates. Duplicate check applied to remove the multiple versions of profiles. Based on Gronell and Wijffels (2008), JAOT, 25.

© Crown copyright Met Office Number of profiles

© Crown copyright Met Office Thinning of levels CTD profile 50.9°W, 58.2°N July 1995 Original profile: 3596 levels EN3 version: 127 levels (~5m spacing near surface) EN4 version: 390 levels (~1m spacing near surface) Thinned profiles have (if available) EN3: 5m spacing near surface EN4: 1m spacing near surface

© Crown copyright Met Office Monthly processing cycle Quality control Analysis Persistence forecast Output as NetCDF file One month of observations processed per cycle Output as NetCDF file Available from Met Office website Observations

© Crown copyright Met Office Quality control tests Manual exclusions Track check Profile check (spikes etc.) Thinning (informational) Stability check Background checks Buddy check Multi level check Argo delayed mode flags Argo grey list Argo altimetry quality control External quality information Automatic quality checks Bathymetry check Measurement depths check Waterfall check Near surface and deep BTs Range check

© Crown copyright Met Office Background check Quality control examples Measurement depths check

© Crown copyright Met Office Quality control examples Track check Waterfall check Spike check

© Crown copyright Met Office Objective analysis system Uses a iterative scheme equivalent to optimal interpolation. But no need to subselect a limited number of observations close to a grid box. Monthly. Potential temperature and salinity. 1 degree grid, 42 levels in the vertical. Uses a persistence forecast as background. Relaxes to a climatology in the long term absence of observations.

© Crown copyright Met Office Example fields – March 2014 at 5 m

© Crown copyright Met Office Objective analysis uncertainty estimates

© Crown copyright Met Office Method The scheme used to produce the objective analyses makes it impossible to calculate uncertainty using the optimal interpolation equations. These are only valid if background error covariances are well known. Use an analysis quality method instead where observation values are set to 1 and background values to 0 (based on Donlon et al. 2012, Remote Sensing of Environment, 116). All other aspects of the analysis are the same except length scales are shortened. Result is linearly related to analysis error variance.

© Crown copyright Met Office Example of observation influence

© Crown copyright Met Office Example of observation influence Dots are the locations of observations

© Crown copyright Met Office Example of observation influence

© Crown copyright Met Office Example of observation influence

© Crown copyright Met Office Example of observation influence

© Crown copyright Met Office Linear relationship between ‘observation influence’ and analysis error variance Using simulated data points it is possible to show this relationship. Length scales have to be shortened by a factor 1.75 to get a linear relationship. Simulations Line fit

© Crown copyright Met Office Coefficients of the linear relationship For EN4 I developed an empirical scheme to do this. The observations are split into two groups and analyses made from each. The differences between analyses allow the uncertainty to be estimated. The method also allows some checks to be done: Intercept should match the background error variance – method can even be used to improve this Gradients should be negative – some issues with the EN4 analyses were identified

© Crown copyright Met Office Gradients of the linear relationship

© Crown copyright Met Office Example uncertainty estimates

© Crown copyright Met Office Ensembles of opportunity

© Crown copyright Met Office Uncertainty in construction of an ocean dataset There are a number of global ocean profile databases: WOD GTSPP CORA EN4 Etc. These are constructed differently, e.g. Different quality control. Different choices about which profiles to include. Bias adjustments. This tells us about the uncertainty in the data.

© Crown copyright Met Office Example From Lyman et al. (2010), Nature, 465.

© Crown copyright Met Office Conclusions

© Crown copyright Met Office Conclusions The EN series of datasets were originally started for global ocean data assimilation. This has been incrementally updated to the latest version EN4. It is available freely for scientific research and private study from The new version includes objective analysis uncertainty estimates produced using an ‘observation influence’ method.

© Crown copyright Met Office Questions and answers