Summary of a WUX data.frame

Description

Prints a screen summary of a WUX data.frame (class wux.df).

Usage

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## S3 method for class 'wux.df'
summary(object, parms = c("perc.delta.precipitation_amount",
"delta.air_temperature"), average.over.gcm.runs = FALSE, ...)

Arguments

object

WUX data.frame (wux.df object) obtained from models2wux

parms

String vector specifying the parameters to be evaluated. Default is perc.delta.precipitation_amount (percentage of precipitation change) and delta.air_temperature (air temperature change in K).

average.over.gcm.runs

Boolean. Should the runs of the same GCM be averaged out? This is recommended, as same GCMs tend to behave very similarly when run with different initial conditions and would thus lead to biased statistics when regarding as independent. Only available for GCM analysis.

...

Further optional arguments. Not active now.

Details

summary.wux.df gives an overview of model frequenzy and calculates statistics for each meteorological parameter within each season in each subregion for all emission scenarios.

print.summaryWuxdf prints the result to the screen.

Value

Returns a summaryWuxdf object, which is a list, but will be printed in a special way. The list has two elements, namely overall.stats and parms.stats. Both are lists again. overall.stats stores all categorical statistics (climate model counts, emmission scenarios, rcm-gcm crosstables, ...). parms.stats is a list with statistics of continuous climate change signals (mean, standard deviation, coeficent of variation and quantiles) split by season, emission scenario, meteorological parameters and subregions.

Author(s)

Thomas Mendlik thomas.mendlik@uni-graz.at

Examples

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## ENSEMBLES data summary
data(ensembles)
summary(ensembles)

## CMIP3 data summary
data(cmip3_2100)
summary(cmip3_2100, average.over.gcm.runs = TRUE) # Average GCMs with different 
                                                      # initial conditions
                                                      
## structure of summaryWuxdf object
data(ensembles_gcms)
ensembles.gcms.summary <- summary(ensembles_gcms)
ensembles.gcms.summary  # summary of 8 GCMs
str(ensembles.gcms.summary)

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