Eddy kinetic energy

The kinetic energy carried by the departure of the flow from its mean:

Usage

eke(env_dat, u = "UO", v = "VO", reference = "record", name = "EKE")

Arguments

env_dat

an sf POINT object with one row per location and time step, as datamatch's access functions return

u

name of the eastward velocity column, in m/s

v

name of the northward velocity column, in m/s

reference

"record", "climatology", or a positive integer number of time steps for a centred rolling mean

name

name for the new column

Value

env_dat with an EKE column added, in m^2/s^2

Details

$$EKE = \tfrac{1}{2}(u'^2 + v'^2), \quad u' = u - \bar{u}$$

High EKE marks an energetic, variable region — meanders, rings, and eddies — as distinct from a strong but steady current, which carries high total kinetic energy but little eddy energy.

What the anomaly is measured against

EKE is only defined relative to a mean, and the choice of mean decides what counts as an "eddy". This is a scientific decision, not an implementation detail, so it is an argument with no silently-correct default:

• "record" (the default) subtracts the mean over the whole time series at each location. This is the textbook definition. Because the seasonal cycle of the mean circulation is left in the anomaly, a region whose currents merely strengthen every summer will register as energetic.

• "climatology" subtracts a separate mean for each calendar month, so the repeatable seasonal cycle is removed and only departures from the usual conditions for that month count. Use this when the question is about anomalous years rather than about which places are energetic.

• An integer subtracts a centred rolling mean over that many time steps, so slow drift in the mean state is removed and only variability faster than the window survives.

Means are computed per location, so a spatially varying mean circulation is removed correctly rather than being smeared into the anomaly.

Examples

if (FALSE) { # \dontrun{
env <- eke(env)                             # against the record mean
env <- eke(env, reference = "climatology")  # seasonal cycle removed
env <- eke(env, reference = 12)             # 12-step rolling mean

# If the fetch used Copernicus codes rather than catalog names
env <- eke(env, u = "uo", v = "vo")
} # }