Global variability in submesoscale density variability from...
Transcript of Global variability in submesoscale density variability from...
1. Thermosalinograph ( TSG) data from ships
Where does temperature vs. salinity drive density variations? De�ne the ”Density variability ratio”,
3. Regional–seasonal patterns
References & Acknowledgements Callies & Ferrari (2013). Interpreting energy and tracer spectra of upper-ocean turbulence in the submesoscale range (1–200 km). J. Phys. Oceanogr.,
43(11), 2456–2474.
Callies, J., Ferrari, R., Klymak, J. M., & Gula, J. (2015). Seasonality in submesoscale turbulence. Nature communications.
Rudnick and Ferrari (1999). Compensation of horizontal temperature and salinity gradients in the ocean mixed layer. Science, 283(5401), 526–529.
Support from NASA is gratefully acknowledged (NNX14AQ54GW).
Data sources (thank you!): GOSUD project, http://www.gosud.org/. LEGOS Sea Surface Salinity Observation Service, http://sss.sedoo.fr/. PANGAEA Data Publisher for Earth and Environmental Science, https://pangaea.de/. SAMOS (Shipboard Automated Meterological and Oceanographic System), http://samos.coaps.fsu.edu/html/. Sophie Clayton. NOAA Ship of Oppor-tunity Program, http://www.aoml.noaa.gov/phod/tsg/soop/index.php (QC by Cli�ord Hoang). Australian Integrated Marine Observing System, https://imos.aodn.org.au/.
Global variability in submesoscale density variabilityfrom historical thermosalinograph data
σρ, kg/m3Fig. 1: Number of 2-km-spacing TSG datapoints per 3°x3° box
Fig. 4: Density variability ratio for regions with strong variabilityTEMPERATURE
DOMINATES DENSITY
VARIABILITY
SALINITY DOMINATES
DENSITYVARIABILITY
Fig. 2: TSG data from an example ship transectTemperatureSalinity
Density
Standard deviation calculatedover each 100 km segment: σρ
(Averaged over 3°x3° boxes to produce Fig 3)
Fig. 3: Binned σρ (computed over 100-km TSG segments)
AUSTRALIA
Regions with strong currents and mean
SST gradients
Tropics & high-latitudes (river out-
�ow & ice melt)
Sources: LEGOS, GOSUD, SAMOS, pangaea.de, IMOS, NOAA75 ships, 103 transects, 106 total good datapoints (T and S)
2. Submesoscale density variability
Strongest in regions with: – strong currents or background gradients – river out�ow, ice melt Same spatial patterns if computed over segments 10–100 km long
4. Spectral slopesFig. 7: Slope of surface density wavenumber spectrum
(�t over 20-100 km wavelength)
slope
Summer ice-melt increases submesoscale
density variability
σρ, kg/m3
Fig. 5: South of Greenland: ice melt
Winter Summer
Fig. 6: Eastern tropical Atlantic: river out�ows from West Africa
April-May-June-July Aug-Sept-Oct-Nov
SSS, psu
GREENLAND
WEST AFRICA
Mean sea surface salinity
Submesoscale density variability
σρ, kg/m3
April-May-June-July Aug-Sept-Oct-Nov
Mean sea surface salinity
Submesoscale density variability
SSS, psu
Winter Summer
River out�ow increases submesoscale density
variability
Kyla DrushkaApplied Physics Laboratory, University of Washington.
Liège Colloquium on Submesoscale Processes – 23 -27 May 2016 – Liège, Belgium
–5/3
Expect a slope of –5/3 from surface QG theory (Callies & Ferrari, 2013) Globally, we observe: – shallower in the subtropics – steeper in the tropics
Fig 5
Fig 6
Fig 2
Expect a seasonal cycle in submesoscale energy (Callies et al., 2015: k –3 in summer, k –2 in winter )
pow
er sp
ectr
al d
ensi
ty
inverse wavenumber, km-1
5/3
South of Greenland (i.e., Fig. 5), we observe a shallower slope in summer than in winter – due to energetic small-scale surface variability?