This package includes a single function, bscm to perform a statistical interpolation using Bratseth’s Successive Correction Method. It is designed specifically for marine data, and it uses bottom depth to calculate the similiarity among the interpolation points. The code is adapted from a MATLAB routine developed by Kjell Arne Mork.
The function bscm uses objective analysis with a Gaussian correlation function. The effective distance r between the observation points and the nodes of the interpolation grid is defined based on the difference in bottom depths, as follows:
where rx and ry is the geographic distance in the zonal and meridional directions, and Ha and Ho are the bottom depths at the analysis and observation points, respectively (Skagseth and Mork, 2012).
To install the package, do the following
library(devtools)
install_github("jmburgos/bscm")
The package includes two datasets. aragonite is a data frame containing the near-bottom aragonite saturation state in 90 locations around Iceland. iceland_depth is a named list with the analysis grid.
library(bscm)
data(aragonite)
data(iceland_depth)
interp <- bscm(fo = aragonite$arag,
xo = aragonite$lon,
yo = aragonite$lat,
dypobs = aragonite$depth,
x = iceland_depth$lon,
y = iceland_depth$lat,
dypxy = iceland_depth$depth
)
Bratseth, A. M. (1986). Statistical interpolation by means of succesive corrections. Tellus A 38A(5), 439-447.
Mork, K. A., Ø. Skagseth, V. Ivshin, V. Ozhigin, S. L. Hughes, and H. Valdimarsson (2014), Advective and atmospheric forced changes in heat and fresh water content in the Norwegian Sea, 1951–2010, Geophys. Res. Lett., 41, 6221–6228, doi:10.1002/ 2014GL061038.
Skagseth, Ø., and K. A. Mork (2012), Heat content in the Norwegian Sea, 1995–2010, ICES J. Mar. Sci., 69(5), 826–832.