Assimilation of S(T) from ARGO Keith Haines, Arthur Vidard *, Xiaobing Zhou, Alberto Troccoli *, David Anderson * Environmental Systems Science Centre, (ESSC) Reading University * ECMWF
T/S relations and air-sea fluxes Bindoff and McDougall (1994) Surface FresheningSurface Warming 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)
Temperature profile assimilation at ECMWF All T profiles assimilated together, including those from CTD/ARGO data (i.e. where salinity also available) Δ T innovations spread out horizontally only using gaussian decorrelation function (level by level assimilation) K ~ exp –[( Δ x/R x ) 2 + ( Δ y/R y ) 2 ]; R x = 15°; R y = 3° equator Analysed T a down to deepest observation depth z max Model background T b displaced vertically to match T a (z max ) to give T a (z>z max ) S 1 Salinity increment to give S a consistent with no change in S(T) (Troccoli and Haines; 1999)
New S(T) assimilation scheme Start with T a ; S a = S b + S 1 from temperature assimilation. At CTD/ARGO observation points calculate salinity increments Δ S 2 = [S o (T o ) - S b (T o )] at temperature T o Δ S 2 is a now direct measure of change in S(T) Store Δ S 2 for several T o in a profile. ECMWF store 1 per model level; could have more How to use Δ S 2 (T o ) at distance Δ r to influence S a (T a )? Use covariance K ~ exp –[((T o – T a )/ R T ) 2 + ( Δ x/R x ) 2 + ( Δ y/R y ) 2 ]; R x ; R y ; R T ? What scales to choose?
ECMWF Seasonal Forecasting Assimilation Aug 2002 – Aug 2003: One year of Temperature … and Salinity data
Salinity increments from ARGO assimilation at ECMWF First assimilation increments Aug02 (averaged over upper 300m) New S(T) assimilation leads to 2 increments (1)Balancing increment S 1 associated with T assimilation keeps S(T) unchanged (already operational at ECMWF for past 2 years, Troccoli et al 2002) (2)Salinity assimilation increment S 2 associated with observed S(T) changes (under test, 1 year assimilation complete) S1S1 S2S2 Aug02 Aug03 S 1 only S 1 + S 2 Mean N. Atl. Salinity Top 300m
Salinity Black= rms (obs-back) Red= rms (obs-anal) Mean Salinity top 300m Trop Pac box ARGO S 1 + S 2 S 1 only Aug02 Aug03
Covariance scales for salinity S K ~ exp –[((T o – T a )/ R T ) 2 + ( Δ x/ R x ) 2 + ( Δ y/R y ) 2 ]; How to choose R x = ; R y = ; R T = ? Consider T o = T a : then R x and R y 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 HadCM degree data every month Scales must represent the right kind of S(T) variability, i.e. variability associated with climatic changes!! (model drift?)
OCCAM ¼ degree model run for 4 years Example S(12C) Noise Shear dispersion only One-point correlation S(12C). Example S(355m) One point correlation S(355m) Seasonal cycle not removed! Mesoscale Different Scale
HadCM3 model: 50 years data S(301m) one pt covariancesS(12C) one pt covariances
HadCM3 model run S(301m) one pt covariancesS(12C) one pt covariances 50 yrs 4 yrs
HadCM3 model: 50 years data S(301m) one pt covariancesS(12C) one pt covariances x S(T) covariances at one location exp –[(Δr/R) 2 + (ΔT)/ R T ) 2 ]
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. S(T) Covariances
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)