eof.dmc {clim.pact}R Documentation

Daily common EOF.

Description

Common EOFs for daily December-February 2-meter temperature (T(2m)) and sea level pressure (SLP).

Usage

data(eof.dmc)

Format

EOF EOF patterns.
W Eigen values.
PC Principal components of common PCA.
n.fld Number of different predictors (see mixFields).
tot.var Sum of all W squared.
id.t Time labels for the fields (see catFields) - used in DS.
id.x Spatial labels for the fields (see mixFields) - used in plotEOF.
id.lon Spatial labels for the fields (see mixFields) - used in plotEOF.
id.lat Spatial labels for the fields (see mixFields) - used in plotEOF.
region Describes the region analysed.
tim Time information (usually redundant).
lon Longitudes associated with EOF patterns.
lat Latitudes associated with EOF patterns.
var.eof Fractional variances associated with EOF patterns.
yy years.
mm months.
dd days.
v.name Name of element.
c.mon Month-season information.
f.name File name of original data.

Source

The common EOF was produced using EOF, with the combined December-February (DJF) 2-meter air temperature data field from European Centre for Medium-Range Weather Forecasts (ECMWF; UK) reanalysis ( see URL: http://www.ecmwf.int/) and HIRHAM dynamically dowwnscaled scenarios from the ECHAM4-GSDIO scenario (Max-Planck Institute for Meteorology, Hamburg, Germany; URL: http://www.mpimet.mpg.de/). The region is 5E - 25E, 58N - 65N.

References

Reference to methodology: R.E. Benestad (2001), "A comparison between two empirical downscaling strategies", Int. J. Climatology, vol 210, pp.1645-1668. [DOI 10.1002/joc.703].

Examples

library(clim.pact)
## Not run: 
x.1.dm<-retrieve.nc("/data1/era15/ERA-15_t2m.nc",x.rng=c(5,25),y.rng=c(58,65))
X.1.dm<-retrieve.nc("/data1/hirham/T2M_198001-199912.nc",x.rng=c(5,25),
                    y.rng=c(58,65))
Y.1.dm<-retrieve.nc("/data1/hirham/T2M_203001-204912.nc",x.rng=c(5,25),
                    y.rng=c(58,65))
Y.1.dm$yy <- Y.1.dm$yy + 50
# It is important that demean=FALSE when concatinating the two time slices
# from the model simulations, if a study of climate change is the objective.
xX.1.dm <- catFields(X.1.dm,Y.1.dm,demean=FALSE)
xX.1.dm <- catFields(x.1.dm,xX.1.dm)
x.2.dm<-retrieve.nc("/data1/era15/ERA-15_slp.nc",x.rng=c(5,25),y.rng=c(58,65))
X.2.dm<-retrieve.nc("/data1/hirham/PSL_198001-199912.nc",x.rng=c(5,25),
                    y.rng=c(58,65))
Y.2.dm<-retrieve.nc("/data1/hirham/PSL_203001-204912.nc",x.rng=c(5,25),
                    y.rng=c(58,65))
Y.2.dm$yy <- Y.2.dm$yy + 50
# It is important that demean=FALSE when concatinating the two time slices
# from the model simulations, if a study of climate change is the objective.
xX.2.dm <- catFields(X.2.dm,Y.2.dm,demean=FALSE)
xX.2.dm <- catFields(x.2.dm,xX.2.dm)

xX.dm <- mix.fields(xX.1.dm,xX.2.dm,mon=1)
eof.dmc <- eof(xX.dm,mon=1)
## End(Not run)
# To read the data:
data(eof.dmc)

[Package clim.pact version 2.2-15 Index]