Compute \(N^2\), the square of the buoyancy frequency for a seawater profile.
swN2(pressure, sigmaTheta = NULL, derivs, df, eos = getOption("oceEOS",
default = "gsw"), debug = getOption("oceDebug"), ...)either pressure [dbar] (in which case sigmaTheta must
be provided) or an object of class ctd object (in which case
sigmaTheta is inferred from the object.
Surface-referenced potential density minus 1000 [kg/m\(^3\)]
optional argument to control how the derivative \(d\sigma_\theta/dp\) is calculated. This may be a character string or a function of two arguments. See “Details”.
argument passed to smooth.spline if this function is
used for smoothing; set to NA to prevent smoothing.
equation of state, either "unesco" or "gsw".
an integer specifying whether debugging information is
to be printed during the processing. This is a general parameter that
is used by many oce functions. Generally, setting debug=0
turns off the printing, while higher values suggest that more information
be printed. If one function calls another, it usually reduces the value of
debug first, so that a user can often obtain deeper debugging
by specifying higher debug values.
additional argument, passed to smooth.spline, in
the case that derivs="smoothing". See “Details”.
Square of buoyancy frequency [\(radian^2/s^2\)].
Smoothing is often useful prior to computing buoyancy frequency, and so this
may optionally be done with smooth.spline, unless
df=NA, in which case raw data are used. If df is not
provided, a possibly reasonable value computed from an analysis of the
profile, based on the number of pressure levels.
If eos="gsw", then the first argument must be a ctd object,
and processing is done with gsw_Nsquared, based on
extracted values of Absolute Salinity and Conservative Temperature (possibly
smoothed, depending on df).
If eos="unesco", then the processing is as follows. The core of the
method involves differentiating potential density (referenced to median
pressure) with respect to pressure, and the derivs argument is used
to control how this is done, as follows.
if derivs is not supplied, the action is as though it were
given as the string "smoothing"
if derivs equals "simple", then the derivative of
density with respect to pressure is calculated as the ratio of first-order
derivatives of density and pressure, each calculated using
diff. (A zero is appended at the top level.)
if derivs equals "smoothing", then the processing
depends on the number of data in the profile, and on whether df is
given as an optional argument. When the number of points exceeds 4, and
when df exceeds 1, smooth.spline is used to calculate
smoothing spline representation the variation of density as a function of
pressure, and derivatives are extracted from the spline using
predict. Otherwise, density is smoothed using smooth,
and derivatives are calculated as with the "simple" method.
if derivs is a function taking two arguments (first pressure,
then density) then that function is called directly to calculate the
derivative, and no smoothing is done before or after that call.
For deep-sea work, the eos="gsw" option is the best scheme, because
it uses derivatives of density computed with local reference
pressure.
For precise work, it makes sense to skip swN2 entirely, choosing
whether, what, and how to smooth based on an understanding of fundamental
principles as well as data practicalities.
Other functions that calculate seawater properties: T68fromT90,
T90fromT48, T90fromT68,
swAbsoluteSalinity,
swAlphaOverBeta, swAlpha,
swBeta, swCSTp,
swConservativeTemperature,
swDepth, swDynamicHeight,
swLapseRate, swPressure,
swRho, swRrho,
swSCTp, swSTrho,
swSigma0, swSigma1,
swSigma2, swSigma3,
swSigma4, swSigmaTheta,
swSigmaT, swSigma,
swSoundAbsorption,
swSoundSpeed, swSpecificHeat,
swSpice, swTFreeze,
swTSrho,
swThermalConductivity,
swTheta, swViscosity,
swZ
# NOT RUN {
library(oce)
data(ctd)
# Illustrate difference between UNESCO and GSW
p <- ctd[["pressure"]]
ylim <- rev(range(p))
par(mfrow=c(1,3), mar=c(3, 3, 1, 1), mgp=c(2, 0.7, 0))
plot(ctd[["sigmaTheta"]], p, ylim=ylim, type='l', xlab=expression(sigma[theta]))
N2u <- swN2(ctd, eos="unesco")
N2g <- swN2(ctd, eos="gsw")
plot(N2u, p, ylim=ylim, xlab="N2 Unesco", ylab="p", type="l")
d <- 100 * (N2u - N2g) / N2g
plot(d, p, ylim=ylim, xlab="N2 UNESCO-GSW diff. [%]", ylab="p", type="l")
abline(v=0)
# }
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