regrid: Regrid

In metno/esd: Climate analysis and empirical-statistical downscaling (ESD) package for monthly and daily data

Regrid

Description

Fast transform data from one longitude-latitude grid to another through bi-linear interpolation. The regridding is done by first calculating a set of weights. This is a "QUICK & DIRTY" way of getting approximate results. More sophisticated methods exist (e.g. Kriging - LatticeKrig).

Usage

regrid(x, is = NULL, ...)

Arguments

x	a field object.
is	A list holding the coordinates xn and yn, a field object, an eof object, or a station object - for the latter three, the field x is interpolated to the longitude/latitude held by is.
xo	Old x-coordinates (longitudes)
yo	Old y-coordinates (latitudes)
xn	New x-coordinates (longitudes)
yn	New y-coordinates (latitudes)
beta	The matrix of interpolation weights
approach	'station' or 'pca2station'. If 'pca2station', the stations are turned into PCAs before regridding and then converted back to station objects.
verbose	If TRUE, print out diagnostics

Details

Let X(i,j) be a i-j matrix containing the data on a grid with i logitudes and j latitudes. We want to transform this to a different grid with k longitudes and l latitudes:

X(i,j) -> Y(k,l)

First the routine computes a set of weight, then performs a matrix multiplication to map the original data onto the new grid. The weights are based on the distance between points, taking longitude & latitude and use distAB() to estimate the geographical distance in km.

The matrix operation is: Y = beta X

beta is a matrix with dimensions (i*j,k*l)

( Y(1,1) ) (beta(1,1), beta(2,1), beta(3,1), ... ) ( X(1,1) ) ( Y(1,2) ) = (beta(1,2), beta(2,2), beta(3,2), ... ) ( X(1,2) ) ( ..... ) (beta(1,3), beta(2,3), beta(3,3), ... ) ( X(1,3) )

Most of the elements in Beta are zero!

Value

A field object

Author(s)

R.E. Benestad and A. Mezghani

See Also

aggregate.grid

Examples

# Use regrid to interpolate to station location:
t2m <- t2m.DNMI()
data(Oslo)
z.oslo <- regrid(t2m,is=Oslo)
plot(Oslo)
lines(z.oslo)

# Regrid t2m onto the grid of the gcm
gcm <- t2m.NorESM.M()
Z <- regrid(t2m,is=gcm)
map(Z)

# Example using regrid on a matrix object:
t2m.mean <- as.pattern(t2m,FUN='mean')
z <- regrid(t2m.mean,is=list(seq(min(lon(t2m)),max(lon(t2m)),by=0.5),
                             seq(min(lat(t2m)),max(lat(t2m),by=0.5))))
image(lon(z),lat(z),z)
# Add land borders on top
data(geoborders)
lines(geoborders)

## Not run: 
## Regrid station data using weights defined by the distance of the 4
## nearest stations: quick and dirty method
if (!file.exists("stationsVALUE_exp1a.rda")) {
  download.file("http://files.figshare.com/2085591/value_predictands4exp1a.R",
                "value_predictands4exp1a.R")
  source("value_predictands4exp1a.R")
}
   
load("stationsVALUE_exp1a.rda")
TX <- regrid(Tx,is=list(lon=seq(-8,30,by=1),lat=seq(40,60,by=0.5)))
map(TX)

## End(Not run)

metno/esd documentation built on March 9, 2024, 11:21 a.m.