ocean (surface) salinity an in situ perspective g. reverdin locean, umr cnrs/upmc/ird, paris, france...
DESCRIPTION
What do we measure Measured with respect to a standard water (more or less since 1900) -first by measuring Chlorinity; -more recently, conductivity Lost in Fathom: LondonTRANSCRIPT
Ocean (surface) salinity an in situ perspective
G. ReverdinLOCEAN, UMR CNRS/UPMC/IRD, Paris, France
(indebted to numerous colleagues in France, US, Spain…)
Salinity
• Water with anions and cations in fixed’ ratios (Dittmar, 40 samples from the Challenger Expedition1874-1877)
• Thus, to 0-order S=fn(C,T), and density=fn(T,S,P)(small increase 0(0.003 psu) due to increase
DIC; small overall decrease due to glacial melt/change of ocean mass)
S evolves with E-P+R, ocean circulation, mixing
What do we measure
• Measured with respect to a standard water (more or less since 1900)- first by measuring Chlorinity; - more recently, conductivity
Lost in Fathom: London
How do we measure it
• Discrete samples 110 y (0.1 psu)
• Thermosalinographs 40 y (ships, drifters) (0.02 psu)
• Argo floats (0.01 psu) (and other profilers)
Different networks
SO SSSG. Alory, T. DelcroixSOCAT, GOSUD, SAMOS
(all require careful validation)
Surface drifters (SPURS)L. Centurioni, V. HormannJ. Font, G. Reverdin
Requires also careful validation)
Mapping of climatology
Sufficient data: Last 40 yearsReverdin et al, 2007; Delcroix et al., 2005
Gordon and Giulivi, 2014
Examples of variability
Subpolar gyre : TSGs (20 years)earlier sampling 100 years
NAC
LC
Binning in boxes or along tracks…
Subpolar gyre
Binning data 1°x1 month :scales resolved a few degrees and a few monthsLarge spatial coherence : modulation of gyre
Larger signal : circulation
West Greenland / Nfld shelves
Larger seasonal modulation on shelves; harder to interpret(for example, expectation of huge melt in 2011-2012, and no low S)Possible phase opposition West Greenland/ Newfoundland shelf
Spatial mapping of individual fields (~10 years)
April-June 1997
300-500 km scales can be retrieved (away from fronts),even with the spare Argo sampling (and surface TSG sampling)ISAS (Gaillard, 2009); Reverdin et al., 2002; Reverdin et al., 2007
Displacement of the fresh poolwestern equatorial Pacific
(binning Delcroix et al., 2011; scales 1000 km*100km*3 months)
Singh et al., 2012, but also Delcroix and Picaut, 1998, Maes et al, 2006
Displacements advected by zoal currents + P influence
ENSO/El Niño
Singh et al., 2011Different flavors of ENSO (EP, CP)With SSS patterns that relate to currents/P
Warm pool
(Cravatte et al, 2007) Trends in PDO and SSS
Trends– natural variabilityA climate change perspective
Trend SSS/century in climate models(compared to obs 1970-2002)Terray et al 2012; Delcroix et al., 2011
Pacific seems to be robust, but N. Atlantic within natural variability
Longer time series(feasible in NE subpolar gyre with some data adjustments over the last 120 years)
Reverdin et al., 2010
T and S correlated, but present also differencesLow-frequency S presents weak seasonal dependencyrelated to modulation of westerlies (NAO) with 0-4 years lag (0.63)Studies on the 1990s transition indicates that in winter it is related mostly to changes in ocean circulation/inputs to the gyre (and E-P)
Multi-decadal filter
Fresh
Salty
Fresh
Further southThe worse sampling
Better sampling further northBut gaps remain
In all cases: issues of corrections/qualification of data(particularly in the 1920s) (requires adjustment of data)There is often a need to bin in ‘big’ boxes (and interannual smoothing+ averaging different seasons)
Trends
No relation (in phase) between NATLAnd NASG (possible delayed phase)45-50°N, already signal characteristicof NASG (2 years earlier)
NA
TA
IG
Meso-scales need to be resolved to study higher
frequency variability (seasonal or less)even on the large scales
Examples from SPURS (1-year survey of NA subtropical gyre)
Feature associated with transport of fresh/warm anomaly from south(Busecke et al., 2014)
R. SchmittA. Gordon
The largest scales haveRms =0.14 (cor=0.5 with SMOS)
The smaller meso-scalescan have 0.2 psu signals asMuch as large scales over 1000 km…Thus possible strong fronts and vertical circulations…(but in some areas/seasons T and S Compensated, whichis scale-dependent)Kolodziejczyk et al., 2014
Meso-scaleSSS variability
100 km
20 km
SPURS SSS seasonal signalinfluence of the eddy and meso-scale structures to d(V’S’)/dy
80 0.10
Gordon et al, 2014(SODA reanalysis)
Local SPURS budget evaluated100 km x 100 km box
Estimates of dSSS/dt from driftersNear SPURS moring (red)Compared to Aquarius+Aviso estimateCenturioni et al., 2015
Farrar
Near surface stratification
The low wind; high SW case (Asher et al., 2014)
Gradients day-time, a few percents of the surface of the oceans
Rainfall-induced stratificationS(15-cm) – S(45-cm)
17 events SVP-BS / Surplas (ITCZ/SPCZ)
Individual rain events : 25% more at 15-cm, but for less than an hour(also, T decrease and stratification); wind estimated ‘SSMI’, not measured
Extreme rain event!
No wind! (means no wave energy in 20 cm – 1m wave length domain)Little S gradient between 4cm and 50 cm (~1 unit) thus at least 12 cmRain in 90 minutes, but should be more as decrease below 50 cm...Strong T-gradient (implies probably ~100 W/m2 cooling); secondary drops?
1 h
Conclusions & Perspectives- In situ data can be used to have long time series, but issues on some old data remain
and cast doubts on some results
- No identification of Atlantic basin-scale SSS trends over the last 118 years
- When data density high enough, spatial patterns of low frequency modes of variability can be investigated (from 2-D to 3-D in the last 10y)
- Dedicated surveys/instrumentation to test certain balances on smaller spatial scales: example of SPURS1 (but also COARE)
V’S’ ~ 1 E-3 from SSS (smoothed 200 km/1 month) + Aviso current V’S’ ~ 3 E-3 from drifter SSS + velocitiesThus 22-30 cm of equivalent rainfall (compared to 130 cm for E-P)
- Complementarity with satellite data to be developed both in SSS and improved surface current products