gsw (version 1.2-0)

gsw_gibbs: Gibbs Energy of Seawater, and its Derivatives

Description

Gibbs Energy of Seawater, and its Derivatives

Usage

gsw_gibbs(ns, nt, np, SA, t, p = 0)

Value

Gibbs energy [ J/kg ] if ns=nt=np=0. Derivative of energy with respect to SA [ J/kg/(g/kg)^ns ] if ns is nonzero and nt=np=0, etc. Note that derivatives with respect to pressure are in units with Pa, not dbar.

Arguments

ns

An integer, the order of the SA derivative. Must be 0, 1, or 2.

nt

An integer, the order of the t derivative. Must be 0, 1, or 2.

np

An integer, the order of the p derivative. Must be 0, 1, or 2.

SA

Absolute Salinity [ g/kg ]. The valid range for most `gsw` functions is 0 to 42 g/kg.

t

in-situ temperature (ITS-90) [ degC ]

p

sea pressure [dbar], i.e. absolute pressure [dbar] minus 10.1325 dbar

Implementation Note

This R function uses a wrapper to a C function contained within the GSW-C system as updated 2022-10-11 at https://github.com/TEOS-10/GSW-C with git commit `657216dd4f5ea079b5f0e021a4163e2d26893371`.

The C function uses data from the library/gsw_data_v3_0.mat file provided in the GSW-Matlab source code, version 3.06-11. Unfortunately, this version of the mat file is no longer displayed on the TEOS-10.org website. Therefore, in the interests of making GSW-R be self-contained, a copy was downloaded from http://www.teos-10.org/software/gsw_matlab_v3_06_11.zip on 2022-05-25, the .mat file was stored in the developer/create_data directory of https://github.com/TEOS-10/GSW-R, and then the dataset used in GSW-R was created based on that .mat file.

Please consult http://www.teos-10.org to learn more about the various TEOS-10 software systems.

Caution

The TEOS-10 webpage for gsw_gibbs does not provide test values, so the present R version should be considered untested.

References

http://www.teos-10.org/pubs/gsw/html/gsw_gibbs.html

Examples

library(gsw)
p <- seq(0, 100, 1)
SA <- rep(35, length(p))
t <- rep(-5, length(p))
## Check the derivative wrt pressure. Note the unit change
E <- gsw_gibbs(0, 0, 0, SA, t, p)
# Estimate derivative from linear fit (try plotting: it is very linear)
m <- lm(E ~ p)
print(summary(m))
plot(p, E)
abline(m)
dEdp1 <- coef(m)[2]
# Calculate derivative ... note we multiply by 1e4 to get from 1/Pa to 1/dbar
dEdp2 <- 1e4 * gsw_gibbs(0, 0, 1, SA[1], t[1], p[1])
## Ratio
dEdp1 / dEdp2