diagnose: Diagnose

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

Description

Diagnose and examine combined fields, MVR, and CCA results. applies some tests to check for consistency.

The method diagnose.comb.eof which estimates the difference in the mean for the PCs of the calibration data and GCMs over a common period in addition to the ratio of standard deviations and lag-one autocorrelation. This 'bias correction' is described in Imbert and Benestad (2005), Theor. Appl. Clim. http://dx.doi.org/10.1007/s00704-005-0133-4.

climvar estimates the climatological variance, e.g. how the inter-annual variance varies with seasons.

Usage

diagnose(x,...)
diagnose.default(x,...)
diagnose.comb(x)
diagnose.eof(x)
diagnose.comb.eof(x)
diagnose.mvr(x)
diagnose.cca(x)
diagnose.ds(x,plot=FALSE)
diagnose.station(x,it=NULL,...)
diagnose.dsensemble(x,plot=TRUE,plot.type='target',...)

Arguments

x	data object
it	teporal selection - see subset
plot
plot.type

Value

A 'diag' object containing test results

Author(s)

R.E. Benestad

Examples

t2m <- t2m.NCEP(lon=c(-40,40),lat=c(30,70))
T2m <- t2m.NorESM.M(lon=c(-40,40),lat=c(30,70))
# Combine in time to compute common EOFs:
X <- combine(t2m,T2m)
diagnose(X)

ceof <-EOF(X,it=1)
plot(diagnose(ceof))

slp <- slp.NCEP(lat=c(-40,40),anomaly=TRUE)
sst <- sst.NCEP(lat=c(-40,40),anomaly=TRUE)
eof.1 <- EOF(slp,it=1)
eof.2 <- EOF(sst,it=1)
cca <- CCA(eof.1,eof.2)
diagnose(cca)

metno/esd.test documentation built on May 22, 2019, 7:49 p.m.