data.frame
(class wux.df
).
"summary"(object, parms = c("perc.delta.precipitation_amount",
"delta.air_temperature"), average.over.gcm.runs = FALSE, ...)
data.frame
(wux.df
object) obtained from models2wux
perc.delta.precipitation_amount
(percentage of precipitation change)
and delta.air_temperature
(air temperature change in K).
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.
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.
## 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)
Run the code above in your browser using DataLab