Data extraction | Statistics

2.1 Ocean eddies as seen by satellite altimetry:
the Kuroshio current

Altimetry data processing for mesoscale studies.

Mesoscale variability in statistics

Computation of EKE

Using geostrophic current components, mesoscale variability can be measured by Eddy Kinetic Energy (EKE, cm²/s²):

EKE=1/2x(u²+v²)

EKE is commonly used as a key indicator of mesoscale variability, as high EKE values correspond to areas of intense activity (fig 5).

Seasonal SLA variations in the Kuroshio system

Several mean seasonal SLAs can be computed, respectively from January to March, April to June, July to September and October to December:

mean SLA=(1/n)x(Sum SLA(t))

This mean SLA represents the mean seasonal status of mesoscale structures in the Kuroshio and enables us to study variations from one period to another (fig 6).

Computation of RMS

Root Mean Square (RMS, fig 7) is given by:

RMS=[[Sum SLA(t)]/n]^½

fig 5: EKE, Kuroshio area, cm²/s²

fig 6: Seasonal variations of mean SLA for 2002, Kuroshio current, Winter, Spring, Summer, Autumn, cm

fig 7: Seasonal variations of MSLA RMS for 2002, Kuroshio current, Winter, Spring, Summer, Autumn, cm

Observing mesoscale variability using merged data

Combining data from several altimetry missions improves the description of mesoscale structures. The following figures show the comparison between mean EKE computed with only two altimeters (top figure) and mean EKE obtained with merged data from four altimeters (bottom figure). In areas of strong variability, RMS differences between these two configurations can reach 400 cm²/s².

Pascual et al., 2006