plotTS | R Documentation |
Creates a temperature-salinity plot for a CTD cast, with labeled isopycnals.
plotTS(
x,
inSitu = FALSE,
type = "p",
referencePressure = 0,
nlevels = 6,
levels,
grid = TRUE,
col.grid = "lightgray",
lty.grid = "dotted",
rho1000 = FALSE,
eos = getOption("oceEOS", default = "gsw"),
cex = par("cex"),
col = par("col"),
pch = par("pch"),
bg = "white",
pt.bg = "transparent",
col.rho = gray(0.5),
cex.rho = 3/4 * par("cex"),
rotate = TRUE,
useSmoothScatter = FALSE,
xlab,
ylab,
Slim,
Tlim,
drawFreezing = TRUE,
trimIsopycnals = TRUE,
gridIsopycnals = c(30, 50),
mgp = getOption("oceMgp"),
mar = c(mgp[1] + 1.5, mgp[1] + 1.5, mgp[1], mgp[1]),
lwd = par("lwd"),
lty = par("lty"),
lwd.rho = par("lwd"),
lty.rho = par("lty"),
add = FALSE,
inset = FALSE,
debug = getOption("oceDebug"),
...
)
x |
a ctd, argo or section object, or a list containing solely ctd objects or argo objects. |
inSitu |
A boolean indicating whether to use in-situ temperature or
(the default) potential temperature, calculated with reference pressure
given by |
type |
representation of data, |
referencePressure |
reference pressure, to be used in calculating
potential temperature, if |
nlevels |
Number of automatically-selected isopycnal levels (ignored if
|
levels |
Optional vector of desired isopycnal levels. |
grid |
a flag that can be set to |
col.grid |
color for grid. |
lty.grid |
line type for grid. |
rho1000 |
if TRUE, label isopycnals as e.g. 1024; if FALSE, label as e.g. 24 |
eos |
equation of state to be used, either |
cex |
character-expansion factor for symbols, as in par |
col |
color for symbols. |
pch |
symbol type, as in par |
bg |
optional color to be painted under plotting area, before
plotting. (This is useful for cases in which |
pt.bg |
inside color for symbols with |
col.rho |
color for isopycnal lines and their labels. |
cex.rho |
size of the isopycnal labels. |
rotate |
if TRUE, labels in right-hand margin are written vertically |
useSmoothScatter |
if TRUE, use |
xlab |
optional label for the x axis, with default "Salinity [PSU]". |
ylab |
optional label for the y axis, with default "Temperature [C]". |
Slim |
optional limits for salinity axis, otherwise inferred from visible data (i.e. the data that have finite values for both salinity and temperature). |
Tlim |
as |
drawFreezing |
logical indication of whether to draw a freezing-point
line. This is based on zero pressure. If |
trimIsopycnals |
logical value ( |
gridIsopycnals |
a parameter that controls how the isopycnals
are computed. This may be NULL, or an integer vector of length 2.
Case 1: the isopycnals are drawn by tracing density
isopleths in salinity-temperature space. This method was
used as the default prior to version 1.7-11, but it was
found to yield staircase-like isopycnal curves for highly
zoomed-in plots (e.g. with millidegree temperature ranges).
Case 2: a grid of density is constructed, with |
mgp |
3-element numerical vector to use for |
mar |
value to be used with par |
lwd |
line width of lines or symbols. |
lty |
line type of lines or symbols. |
lwd.rho |
line width for density curves. |
lty.rho |
line type for density curves. |
add |
a flag that controls whether to add to an existing plot. (It
makes sense to use |
inset |
set to |
debug |
a flag that turns on debugging. Set to 1 to get a moderate amount of debugging information, or to 2 to get more. |
... |
optional arguments passed to plotting functions. |
The isopycnal curves (along which density is constant) are
drawn with drawIsopycnals()
, which also places
labels in the margins showing density minus 1000 kg/m^3
.
If trimIsopycnals
is TRUE
(which is the default), these curves
are trimmed to the region within which the results of density calculation
in the chosen equation of state (eos
) are considered to be reliable.
With eos="unesco"
this region includes
Practical Salinity from 0 to 42 and Potential Temperature
from -2C to 40C, in accordance with Fofonoff and Millard
(1983, page 23).
With eos="gsw"
the lower
limit of Absolute Salinity validity is taken as 0 g/kg,
in accordance with both McDougall et al. (2003 section 3)
and the TEOS-10/gsw Matlab code for the so-called "funnel" of validity.
However, an appropriate upper limit on Absolute Salinity is not as clear.
Here, the value 42 g/kg is chosen to match the "funnel" Matlab code
as of July 2020, but two other choices might have been
made. One is 50 g/kg, since gsw::gsw_SA_from_rho()
returns NA
values
for Absolute Salinities exceeding that value, and another is
40 g/kg, as in McDougall et al. (2003 section 3).
The Conservative Temperature range is set to run from -2C
to 33C, as in McDougall et al. (2003 section 3), even though the
"funnel" imposes no upper limit on this variable.
A list is silently returned, containing xat
and yat
,
values that can be used by oce.grid()
to add a grid to the plot.
Dan Kelley
Fofonoff, N. P., and R. C. Millard.
"Algorithms for Computation of Fundamental Properties of Seawater."
UNESCO Technical Papers in Marine Research. SCOR working group on Evaluation of CTD data;
UNESCO/ICES/SCOR/IAPSO Joint Panel on Oceanographic Tables and Standards, 1983.
https://unesdoc.unesco.org/ark:/48223/pf0000059832
.
McDougall, Trevor J., David R. Jackett, Daniel G. Wright, and Rainer Feistel.
"Accurate and Computationally Efficient Algorithms for Potential Temperature and Density of Seawater."
Journal of Atmospheric and Oceanic Technology 20, no. 5 (May 1, 2003): 730-41.
https://journals.ametsoc.org/jtech/article/20/5/730/2543/Accurate-and-Computationally-Efficient-Algorithms
.
summary,ctd-method()
summarizes the information, while
read.ctd()
scans it from a file.
Other functions that plot oce data:
download.amsr()
,
plot,adp-method
,
plot,adv-method
,
plot,amsr-method
,
plot,argo-method
,
plot,bremen-method
,
plot,cm-method
,
plot,coastline-method
,
plot,ctd-method
,
plot,gps-method
,
plot,ladp-method
,
plot,landsat-method
,
plot,lisst-method
,
plot,lobo-method
,
plot,met-method
,
plot,odf-method
,
plot,rsk-method
,
plot,satellite-method
,
plot,sealevel-method
,
plot,section-method
,
plot,tidem-method
,
plot,topo-method
,
plot,windrose-method
,
plot,xbt-method
,
plotProfile()
,
plotScan()
,
tidem-class
Other things related to ctd data:
CTD_BCD2014666_008_1_DN.ODF.gz
,
[[,ctd-method
,
[[<-,ctd-method
,
as.ctd()
,
cnvName2oceName()
,
ctd
,
ctd-class
,
ctd.cnv.gz
,
ctdDecimate()
,
ctdFindProfiles()
,
ctdFindProfilesRBR()
,
ctdRaw
,
ctdRepair()
,
ctdTrim()
,
ctd_aml.csv.gz
,
d200321-001.ctd.gz
,
d201211_0011.cnv.gz
,
handleFlags,ctd-method
,
initialize,ctd-method
,
initializeFlagScheme,ctd-method
,
oceNames2whpNames()
,
oceUnits2whpUnits()
,
plot,ctd-method
,
plotProfile()
,
plotScan()
,
read.ctd()
,
read.ctd.aml()
,
read.ctd.itp()
,
read.ctd.odf()
,
read.ctd.odv()
,
read.ctd.saiv()
,
read.ctd.sbe()
,
read.ctd.ssda()
,
read.ctd.woce()
,
read.ctd.woce.other()
,
setFlags,ctd-method
,
subset,ctd-method
,
summary,ctd-method
,
woceNames2oceNames()
,
woceUnit2oceUnit()
,
write.ctd()
# 1. ctd object
library(oce)
data(ctd)
plotTS(ctd)
# 2. section object (note the outlier!)
data(section)
plotTS(section)
# 3. argo object
data(argo)
plotTS(handleFlags(argo))
# 4. oxygen-based colormap
marOrig <- par("mar") # so later plots with palettes have same margins
cm <- colormap(section[["oxygen"]])
drawPalette(colormap = cm, zlab = "Oxygen")
plotTS(section, pch = 19, col = cm$zcol, mar = par("mar")) # the mar adjusts for the palette
# 5. waters near Gulf Stream, colour-coded for longitude.
sec <- subset(section, abs(longitude + 71.6) < 1)
cm <- colormap(sec[["longitude", "byStation"]], col = oceColors9B)
par(mar = c(3.3, 3.3, 1, 1.5))
drawPalette(colormap = cm, zlab = "Longitude")
plotTS(sec, type = "n", xaxs = "r", mar = par("mar"))
jnk <- mapply(
function(s, col) {
plotTS(s, type = "o", col = "gray", pt.bg = col, pch = 21, add = TRUE)
},
sec[["station"]],
col = cm$zcol
)
# 6. with added spiciness contours
data(ctd)
plotTS(ctd, eos = "gsw") # MANDATORY so x=SA and y=CT
usr <- par("usr")
n <- 100
SAgrid <- seq(usr[1], usr[2], length.out = n)
CTgrid <- seq(usr[3], usr[4], length.out = n)
g <- expand.grid(SA = SAgrid, CT = CTgrid)
spiciness <- matrix(gsw::gsw_spiciness0(g$SA, g$CT), nrow = n)
contour(SAgrid, CTgrid, spiciness, col = 2, labcex = 1, add = TRUE)
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