1. Climate quality data and datasets from VOS and VOSClim Elizabeth Kent and David Berry National Oceanography Centre, Southampton

2. The requirement for climate-quality data  GCOS implementation plan  Climate datasets (e.g. Hadley Centre, NOAA)  Satellite bias adjustment  Flux datasets (includes visual observations of cloud and weather codes)  SURFA NWP flux validation project  NWP/reanalysis validation  Satellite cal/val

3. Adequacy of what are we collecting now?  Difficult to assess adequacy, need to know: Number of observations Distribution of sampling in space and time Platform information and number of reports from each platform Natural variability Autocorrelation time and space scales Random uncertainty in observations (intra-platform uncertainty) Bias uncertainty between observation types (inter-platform uncertainty) Overall bias User requirement: target and useable accuracies, time and space scales  Only the first 2 are easy to calculate

4. How do we assess uncertainty?  Comparisons of co-located observations  Comparison with a common standard Approach taken with VOSClim Common standard is Met Office NWP model output Also have co-located data and model output for all VOS, drifters and moored buoys Need to partition uncertainty between model and forecast (very basic approach taken so far)

5. What data do we need?  Lots of data in high variability regions  Smaller amounts of high quality data in lower variability regions  Sampling in space and time Far apart to increase representivity Co-locations to perform quality assurance  Data from lots of different platforms OR data from single platform with small bias Identifiable platforms with metadata and quantified uncertainty  Sampling of the diurnal cycle Either fully sampled or randomly sampled (to avoid aliasing)

6. Uncertainty estimates: Air Temp, Feb 07 intra-platform (random)inter-platform (bias) samplingtotal

7. Data quality: impact on uncertainty

8. How does VOSClim help?  VOSClim ships overall are typically better than average  For each country VOSClim ships are typically better than the average for the country  Some exceptions, e.g. UK VOSClim pressure data is worse than their VOS pressure data (but still better than the overall average)

9. How does VOSClim help?  VOSClim shows that operators are aware of factors that indicate which ships provide the best data.  In what way are the VOSClim data better? Data are very much more consistent among the VOSClim ships than among the VOS generally Improvements in random uncertainty for an individual ship are less dramatic but still important  Does the improved monitoring for VOSClim help? Not sure how to demonstrate this - depends on response to monitoring  Do the extra parameters in delayed mode help? Pretty sure they will (based on previous VSOP-NA), but data availability until recently was not good  Do the photos help? Yes, we have used them to relate air temperature sensor exposure to the characteristics of the data from the sensor.

10. Conclusions  VOSClim data are better than average  Improvements are mainly in the consistency of the data  Many "good" ships aren't in VOSClim  A few "bad" ships are  Sampling uncertainty is still a major problem in many regions - we need more data (improved data quality doesn't really help here)  All VOS should report delayed mode parameters  Now have useful information which we can feed back to ship operators (how?)  With improved data flow and volumes we are now poised to exploit the information in the VOSClim dataset

11. SOOP update  Met 16-21 April 2007; new chair: Gustavo Goni, NOAA/AOML  Working on UOT 1999 guidelines 24% of routes not sampled at all in 2005 33% undersampled in 2005  Firm feedback on the non-feasibility of some routes IX-09S (Freemantle-Sri Lanka) no ships PX-21 California - Chile - not serviced by offshore long- routes PX-35 (Melbourne-Dunedin) no ships PX-81 (Hawaii-Chile) difficulty in identifying a reliable ship on this route, but will search (Scripps and Japan)  Routes restarted IX-08 (Mumbai-Mauritius) NIO (India) with support from NOAA/AOML PX-11 (Australia-Japan) has been restarted by Australia

12. SOOP update  Routes with prospects: AX-11 (Europe-Cape of Good Hope) NOAA/AOML has contact with Spanish ship with a TSG on this route AX-25 (Cape of Good Hope - Antarctica) being done by U. Cape Town with support of NOAA/AOML PX-36 (Christchurch-McMurdo) possibility of getting Palmer to do this sampling  XBT fall rate equations German, US, and Italian groups have been doing intercomparisons realize the need for more work - organized a subgroup to pursue this with Sippican, the research community, and a subset of the operators recommendation to operators that extensive metadata (probe type, serial number, date of manufacture) is recorded in the data files

13. SOOP update  Quality Control group will adopt a common real-time QC standard based on Argo QC procedures GTSPP realized need for common delayed-mode quality control and Charles Sun (NODC) and Ann Thresher (CSIRO) among others will work on this  Other variables SOOP will try to work with IOCCP for near-real-time GTS insertion of temperature and salinity from TSG, and with Ferrybox project for real-time insertion on the GTS  SCOR panel on observing techniques from merchant marine (Tom Rossby)  Desire for OOPC to revisit UOT