Implements the 12th and 13th generations of the International Geomagnetic Reference Field (IGRF), based on a reworked version of a Fortran program downloaded from a NOAA website (see “References”).
magneticField(longitude, latitude, time, version = 13)
longitude in degrees east (negative for degrees west), as a number, a vector, or a matrix.
latitude in degrees north, as a number, vector, or matrix.
The shape (length or dimensions) must conform to the dimensions of longitude
.
The time at which the field is desired. This may be a
single value or a vector or matrix that is structured to match
longitude
and latitude
. The value may a decimal year,
a POSIXt time, or a Date time.
an integer that must be either 12 or 13, to specify
the version number of the formulae. Note that 13 became the default
on 2020 March 3, so to old code will need to specify version=12
to work as it did before that date.
A list containing declination
, inclination
, and
intensity
.
The code (subroutines igrf12syn
and igrf13syn
) seem to have
been written by Susan Macmillan of the British Geological Survey. Comments
in the source code igrf13syn
(the current default used here)
indicate that its coefficients were agreed to in
December 2019 by the IAGA Working Group V-MOD. Other comments in that code
suggest that the proposed application time interval is from years 1900 to 2025, inclusive,
but that only dates from 1945 to 2015 are to be considered definitive.
For about a decade, magneticField
used the version 12 formulae provided
by IAGA, but the code was updated on March 3, 2020, to version 13. Example
3 shows that the differences in declination are typically under 2 degrees
(with 95 percent of the data lying between -1.7 and 0.7 degrees).
The underlying Fortran code for version 12 is from igrf12.f
, downloaded the NOAA
website (https://www.ngdc.noaa.gov/IAGA/vmod/igrf.html
) on June 7,
That for version 13 is igrf13.f
, downloaded from the NOAA website
(https://www.ngdc.noaa.gov/IAGA/vmod/igrf.html
on March 3, 2020.
Witze, Alexandra. “Earth's Magnetic Field Is Acting up and Geologists Don't Know Why.” Nature 565 (January 9, 2019): 143. doi:10.1038/d41586-019-00007-1
Alken, P., E. Thébault, C. D. Beggan, H. Amit, J. Aubert, J. Baerenzung, T. N. Bondar, et al. "International Geomagnetic Reference Field: The Thirteenth Generation." Earth, Planets and Space 73, no. 1 (December 2021): 49. doi:10.1186/s40623-020-01288-x .
Other things related to magnetism:
applyMagneticDeclination()
,
applyMagneticDeclination,adp-method
,
applyMagneticDeclination,adv-method
,
applyMagneticDeclination,cm-method
,
applyMagneticDeclination,oce-method
library(oce)
# 1. Today's value at Halifax NS
magneticField(-(63 + 36 / 60), 44 + 39 / 60, Sys.Date())
#> $declination
#> [1] -16.39477
#>
#> $inclination
#> [1] 66.45537
#>
#> $intensity
#> [1] 51234.46
#>
# 2. World map of declination in year 2000.
# \donttest{
data(coastlineWorld)
par(mar = rep(0.5, 4)) # no axes on whole-world projection
mapPlot(coastlineWorld, projection = "+proj=robin", col = "lightgray")
# Construct matrix holding declination
lon <- seq(-180, 180)
lat <- seq(-90, 90)
dec2000 <- function(lon, lat) {
magneticField(lon, lat, 2000)$declination
}
dec <- outer(lon, lat, dec2000) # hint: outer() is very handy!
# Contour, unlabelled for small increments, labeled for
# larger increments.
mapContour(lon, lat, dec,
col = "blue", levels = seq(-180, -5, 5),
lty = 3, drawlabels = FALSE
)
mapContour(lon, lat, dec, col = "blue", levels = seq(-180, -20, 20))
mapContour(lon, lat, dec,
col = "red", levels = seq(5, 180, 5),
lty = 3, drawlabels = FALSE
)
mapContour(lon, lat, dec, col = "red", levels = seq(20, 180, 20))
mapContour(lon, lat, dec, levels = 180, col = "black", lwd = 2, drawlabels = FALSE)
mapContour(lon, lat, dec, levels = 0, col = "black", lwd = 2)
# }
# 3. Declination differences between versions 12 and 13
# \donttest{
lon <- seq(-180, 180)
lat <- seq(-90, 90)
decDiff <- function(lon, lat) {
old <- magneticField(lon, lat, 2020, version = 13)$declination
new <- magneticField(lon, lat, 2020, version = 12)$declination
new - old
}
decDiff <- outer(lon, lat, decDiff)
decDiff <- ifelse(decDiff > 180, decDiff - 360, decDiff)
# Overall (mean) shift -0.1deg
t.test(decDiff)
#>
#> One Sample t-test
#>
#> data: decDiff
#> t = -21.794, df = 65340, p-value < 2.2e-16
#> alternative hypothesis: true mean is not equal to 0
#> 95 percent confidence interval:
#> -0.10399320 -0.08683188
#> sample estimates:
#> mean of x
#> -0.09541254
#>
# View histogram, narrowed to small differences
par(mar = c(3.5, 3.5, 2, 2), mgp = c(2, 0.7, 0))
hist(decDiff,
breaks = seq(-180, 180, 0.05), xlim = c(-2, 2),
xlab = "Declination difference [deg] from version=12 to version=13",
main = "Predictions for year 2020"
)
print(quantile(decDiff, c(0.025, 0.975)))
#> 2.5% 97.5%
#> -1.6695352 0.7159345
# Note that the large differences are at high latitudes
imagep(lon, lat, decDiff, zlim = c(-1, 1) * max(abs(decDiff)))
lines(coastlineWorld[["longitude"]], coastlineWorld[["latitude"]])
# }