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Assimilation of S(T) from ARGO

Assimilation of S(T) from ARGO. Keith Haines, Arthur Vidard * , Xiaobing Zhou, Alberto Troccoli * , David Anderson * Environmental Systems Science Centre, (ESSC) Reading University * ECMWF. Surface Freshening. Surface Warming. T/S relations and air-sea fluxes. Bindoff and McDougall (1994).

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Assimilation of S(T) from ARGO

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  1. Assimilation of S(T) from ARGO Keith Haines, Arthur Vidard*, Xiaobing Zhou, Alberto Troccoli*, David Anderson* Environmental Systems Science Centre, (ESSC) Reading University *ECMWF

  2. Surface Freshening Surface Warming T/S relations and air-sea fluxes Bindoff and McDougall (1994) Changes in temperature and salinity on z levels and on isopycnals allow surface forcing signature to be determined. Assimilation induced changes in water masses in OCCAM model with T only assimilated (Fox et al 2003)

  3. Temperature profile assimilation at ECMWF • All T profiles assimilated together, including those from CTD/ARGO data (i.e. where salinity also available) • ΔT innovations spread out horizontally only using gaussian decorrelation function (level by level assimilation) K ~ exp –[(Δx/Rx)2 + (Δy/Ry)2]; Rx= 15°; Ry = 3° equator • Analysed Ta down to deepest observation depth zmax • Model background Tb displaced vertically to match Ta(zmax) to give Ta (z>zmax) • S1 Salinity increment to give Sa consistent with no change in S(T) (Troccoli and Haines; 1999)

  4. New S(T) assimilation scheme • Start with Ta ; Sa = Sb +S1from temperature assimilation. • At CTD/ARGO observation points calculate salinity increments ΔS2 = [So(To) - Sb(To)]at temperature To • ΔS2 is a now direct measure of change in S(T) • Store ΔS2 for several To in a profile. ECMWF store 1 per model level; could have more • How to use ΔS2(To) at distance Δr to influence Sa(Ta)? • Use covariance K ~ exp –[((To – Ta)/ RT)2 + (Δx/Rx)2 + (Δy/Ry)2]; Rx; Ry; RT ? What scales to choose?

  5. ECMWF Seasonal Forecasting Assimilation Aug 2002 – Aug 2003: One year of Temperature … and Salinity data

  6. Salinity increments from ARGO assimilation at ECMWF • New S(T) assimilation leads to 2 increments • Balancing increment S1associated with • T assimilation keeps S(T) unchanged • (already operational at ECMWF for past • 2 years, Troccoli et al 2002) • Salinity assimilation increment S2 • associated with observed S(T) changes • (under test, 1 year assimilation complete) First assimilation increments Aug02 (averaged over upper 300m) S1 S1 + S2 S2 Mean N. Atl. Salinity Top 300m S1 only Aug02 Aug03

  7. Salinity Black= rms (obs-back) Red= rms (obs-anal) Mean Salinity top 300m Trop Pac box Aug02 Aug03 ARGO S1 + S2 S1 only

  8. Covariance scales for salinity S K ~ exp –[((To – Ta)/ RT)2 + (Δx/ Rx)2 + (Δy/Ry)2]; • How to choose Rx= ; Ry = ; RT= ? • Consider To = Ta : then Rx and Ry are clearly correlation scales on T surface • Calculate correlations from model data sets 4 years of OCCAM high ¼ degree data every 5 days 50 years HadCM3 1.25 degree data every month • Scales must represent the right kind of S(T) variability, i.e. variability associated with climatic changes!! (model drift?)

  9. One-point correlation S(12C). Example S(12C) Shear dispersion only Noise Mesoscale One point correlation S(355m) Seasonal cycle not removed! Example S(355m) Different Scale OCCAM ¼ degree model run for 4 years

  10. HadCM3 model: 50 years data S(301m) one pt covariances S(12C) one pt covariances

  11. HadCM3 model run S(301m) one pt covariances S(12C) one pt covariances 50 yrs 4 yrs

  12. HadCM3 model: 50 years data S(301m) one pt covariances S(12C) one pt covariances x exp –[(Δr/R)2 + (ΔT)/ RT)2] S(T) covariances at one location

  13. S(T) Covariances • Covariance scales for S(T) should be larger than covariance scales for S(z)=Mesoscale • Models must be run long enough to have realistic S(T) variability which is not simply model drift • Best illustration would come from a long run of mesoscale model with stable climate! • Tune scales during assimilation based on model-data misfits (common in meteorology)? May require long time period to capture interesting S(T) variations.

  14. Further work • Tuning of S assimilation at ECMWF • Covariance scales from models or by tuning (eg. 2 or OmF stats.) • Compare scales with QC scales cf. Boeme/Send! • 40 year ocean reanalysis (EU ENACT project) • Analyse changes in T/S properties to detect climate signals as in Bindoff and McDougall or Walin • Impact of Salinity assimilation on seasonal/mesoscale forecasting (ECMWF, Met Office)

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