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Role of surface fluxes from in situ marine platforms in SURFA Elizabeth Kent National Oceanography Centre, Southampton, UK. Outline. Sources of in situ flux data OceanSITES (Moorings) SAMOS (Research Vessels) VOS (WWW/GOS routine weather observations) Summary of data characteristics

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  1. Role of surface fluxes from in situ marine platforms in SURFAElizabeth KentNational Oceanography Centre, Southampton, UK

  2. Outline • Sources of in situ flux data • OceanSITES (Moorings) • SAMOS (Research Vessels) • VOS (WWW/GOS routine weather observations) • Summary of data characteristics • Questions and concerns

  3. OceanSITES • www.oceansites.org • Variety of station types, some measure all flux components • Ocean Reference Stations - fluxes, WHOI Upper Ocean Processes

  4. Stratus buoy - Eastern Tropical Pacific 30-day running mean applied Statistics based on daily means ---------------------------------------------------------------------- QNETQLH+QSHQSW+QLW ---------------------------------------------------------------------- Buoys 50 -110 160 OAFlux&ISCCP 54 ( +4) -113 ( -3) 168 ( +8) NCEP1 -14 (-64) -144 (-34) 130 (-30) ERA40 47 ( -3) -124 (-14) 171 (+11) ---------------------------------------------------------------------- NTAS buoy, Northwest tropical Atlantic Thanks to Al Plueddemann and Bob Weller at WHOI

  5. Atlantic Basin - WHOI Mooring Comparisons Thanks to Bob Weller and Lisan Yu at WHOI

  6. CLIMODE (Gulf Stream) • Region of high variability and strong fluxes • Differences between NWP and buoy measurements in all key variables • NWP underestimate contrasts in cold air outbreaks (not shown) • SST patterns poorly represented, spurious variability in NCEP Thanks to Sebastien Bigorre at WHOI

  7. Data from Research Vessels & SAMOS • Shipboard Automated Meteorological and Oceanographic System Initiative • http://samos.coaps.fsu.edu/html/ • Mostly research vessels Thanks to Shawn Smith at COAPS

  8. Advantages of SAMOS data • Operate in all parts of the ocean, including regions of extreme conditions (e.g., polar latitudes, high wind regimes). • Science systems provide • High sampling rates (typically 1-min interval between samples) • Research data quality (on par with delayed mooring data) • Instruments monitored by onboard technicians • Additional measurements not provided in bridge reports (radiation, precipitation, direct fluxes, etc.) • Radiation and precipitation are critical components to air-sea fluxes Courtesy NOAA OCO

  9. Reanalysis Flux Validation • Quality processed SAMOS data are ideal for evaluation of global flux products (e.g., Smith et al., 2001, J. Climate) • R/V sampling rates allow accurate estimation of 6-hr integrated fluxes

  10. Flux Validation with SAMOS • Conducting R/V to model comparisons must carefully consider differences in flux algorithms • Results differ for the NCEPR1 flux algorithm (triangles) versus Smith (1988) algorithm run with NCEPR1 meteorological data (circles) • How do we handle movements of vessels over 6-hour model interval in comparisons?

  11. Voluntary Observing Ship data • Routine weather reports collected in support of NWP - only regular source of in situ flux information over much of the ocean • Contain meteorological variables from which all the components of the flux can be calculated (or estimated) • Archived in the International Comprehensive Ocean-Atmosphere Dataset (ICOADS) • Extensively used in climate research • But not fully exploited for NWP validation (rather than assimilation) • Not all data of high quality - but can they be useful for flux validation?

  12. Can we improve the quality of the observations? • Errors in air temperature due to platform heating have been modelled • Anemometer-measured winds are adjusted for (usually) known measurement height • Beaufort-estimated winds adjusted for biases in operational scale used • Effect of air-flow distortion being quantified • Studying SST differences for different measurement methods on ships and for ship-buoy differences • Humidity corrections depend on ventilation rate (need measurement method)

  13. Metadata • Metadata is necessary to analyse bias and apply corrections • Measurement heights • Measurement methods • Need identifiable observations to link to metadata (ship security concerns) • Metadata availability is patchy • VOS metadata is collected in Pub. 47 (1955-present) • Historical ODAS metadata can be hard to get hold of • Research Vessel metadata ranges from excellent to non-existent

  14. Flux datasets from VOS data • Used Optimal Interpolation (Lorenc MWR 1981, Reynolds J. Clim 1988) • Analyse daily fields • Better isolate noise from synoptic variability • Gives estimate of sampling error in monthly fields • Still need to correct for bias, improve estimation of suitable time and space scales and QC • Estimate fluxes and their uncertainties Thanks to David Berry at NOCS

  15. Met Office Model Output from David Acreman

  16. Reduction in number of VOS observations = poorer flux estimates • Flux datasets rely on data collected for NWP • Numbers of observations declining • Plot shows increasing uncertainty in latent heat flux over the past 20 years in all ocean regions

  17. Summary and Questions: OceanSITES • OceanSITES • Manageable number of sites • Fixed locations, easy to incorporate into SURFA • Should be high quality data (use models to detect sensor failure?) • Fairly good coverage, especially in the Tropics • Subset of data available in real time • 1 minute data available, in delayed mode (statistics of variability?) • Compare all available parameters (isolate problems with data fields from parameterisation problems)

  18. Summary and Questions: Research Vessels • SAMOS and other R/V data • High quality data, may include direct turbulent flux measurements • Often available only with delay • Routes variable • Can sample in v. data sparse regions • High time resolution data in delayed mode • How best to use this data? • Archive fluxes for target cruises notified? • Select scientifically interesting regions with regular R/V traffic (e.g. Drake Passage, Labrador Sea …. )? • Keep global model output?

  19. Summary and Questions: VOS gridded data • Flux data (and uncertainty) available with short delay • Only regular source of flux data away from mooring sites • Selection of comparison sites: • Every 10˚? • In selected well-sampled regions? • Co-located with OceanSITES and R/V • Other data of interest? • Cloud cover and cloud type statistics • Weather code information • Waves

  20. Concerns • Model output needs to be delivered and archived in a manageable way • Who will keep track of changes in all the different models? • Who will make the comparisons? • Will comparisons be timely enough to be of interest to NWP? • What about reanalyses?

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