This function is intended to provide a bridge to
predict.tidem(), enabling tidal predictions based
on published tables of harmonic fits.
as.tidem(tRef, latitude, name, amplitude, phase, debug = getOption("oceDebug"))
a POSIXt value indicating the mean time of the
observations used to develop the harmonic model. This is rounded
to the nearest hour in
Numerical value indicating the latitude of the
observations that were used to create the harmonic model. This
is needed for nodal-correction procedures carried out
character vector holding names of constituents.
Numeric vector of constituent amplitudes.
Numeric vector of constituent Greenwich phases.
an integer specifying whether debugging information is
to be printed during the processing. This is a general parameter that
is used by many
An object of tidem, with only minimal contents.
Note that only constituent names known to
tidem() are handled.
The permitted names are those listed in Foreman (1978), and
data(tidedata) data.frame(name=tidedata$const$name, freq=tidedata$const$freq)
Warnings are issued for any constituent name that is not in this list; as
of the late summer of 2019, the only example seen in practice is
M1, which according to Wikipedia (2019) has frequency 0.0402557, which
is very close to that of
NO1, i.e. 0.04026859, perhaps explaining
why Foreman (1978) did not handle this constituent. A warning is
issued if this or any other unhandled constituent is provided
name argument to
There are two known differences between
tidem() and the Matlab
T_TIDE package, as listed in references 3 and 4. Work on these
issues is planned for the summer of 2020.
Foreman, M. G. G., 1978. Manual for Tidal Currents Analysis and Prediction. Pacific Marine Science Report. British Columbia, Canada: Institute of Ocean Sciences, Patricia Bay.
Wikipedia, "Theory of Tides." https://en.wikipedia.org/wiki/Theory_of_tides Downloaded Aug 17, 2019.
Github issue 1653: tidem() and t_tide do not produce identical results https://github.com/dankelley/oce/issues/1653
Github issue 1654: predict(tidem()) uses all constituents, unlike T_TIDE https://github.com/dankelley/oce/issues/1654
# Simulate a tide table with output from tidem(). data(sealevelTuktoyaktuk) # 'm0' is model fitted by tidem() m0 <- tidem(sealevelTuktoyaktuk)#> Note: the tidal record is too short to fit for constituents: SA SSA MSM MF SIG1 RHO1 TAU1 BET1 CHI1 PI1 P1 S1 PSI1 PHI1 THE1 SO1 OQ2 2N2 NU2 GAM2 H1 H2 MKS2 LDA2 T2 R2 K2 MSN2 SO3 MK4 SK4 2MK6 MSK6p0 <- predict(m0, sealevelTuktoyaktuk[["time"]]) m1 <- as.tidem(mean(sealevelTuktoyaktuk[["time"]]), sealevelTuktoyaktuk[["latitude"]], m0[["name"]], m0[["amplitude"]], m0[["phase"]]) # Test agreement with tidem() result, by comparing predicted sealevels. p1 <- predict(m1, sealevelTuktoyaktuk[["time"]]) expect_lt(max(abs(p1 - p0), na.rm=TRUE), 1e-10) # Simplified harmonic model, using large constituents # > m0[["name"]][which(m[["amplitude"]]>0.05)] #  "Z0" "MM" "MSF" "O1" "K1" "OO1" "N2" "M2" "S2" h <- " name amplitude phase Z0 1.98061875 0.000000 MM 0.21213065 263.344739 MSF 0.15605629 133.795004 O1 0.07641438 74.233130 K1 0.13473817 81.093134 OO1 0.05309911 235.749693 N2 0.08377108 44.521462 M2 0.49041340 77.703594 S2 0.22023705 137.475767" coef <- read.table(text=h, header=TRUE) m2 <- as.tidem(mean(sealevelTuktoyaktuk[["time"]]), sealevelTuktoyaktuk[["latitude"]], coef$name, coef$amplitude, coef$phase) p2 <- predict(m2, sealevelTuktoyaktuk[["time"]]) expect_lt(max(abs(p2 - p0), na.rm=TRUE), 1) par(mfrow=c(3, 1)) oce.plot.ts(sealevelTuktoyaktuk[["time"]], p0) ylim <- par("usr")[3:4] # to match scales in other panels oce.plot.ts(sealevelTuktoyaktuk[["time"]], p1, ylim=ylim) oce.plot.ts(sealevelTuktoyaktuk[["time"]], p2, ylim=ylim)