The WUX package is a toolbox to analyze climate change uncertainties
projected by numerical model simulations.
The package provides methods to calculate and interpret climate change
signals and time series from entire multi-model ensembles. Climate
model output in binary NetCDF format is read in and aggregated to a
data.frame for statistical analysis with tools provided by the R
environment. The NetCDF format is not restricted to any specific type
of climate model. Global circulation models (GCMs), as the CMIP5 or
CMIP3 simulations, can be read in the same way as Regional Climate
Models (RCMs), as e.g. the CORDEX or ENSEMBLES simulations.
Details
This package can currently perform following actions:
Reading output of climate model simulations from NetCDF
files, processing it, and writing it to a data.frame (the
so-called WUX data frame).
Various plotting options and summarizing utilities for a
descriptive analysis of the projected climate change signals.
Performing an Analysis of Variance (ANOVA) in order to
estimate variance components.
Performing a simple two-way linear data reconstruction, in
order to fill the missing values of a simulation matrix as e.g. the
GCM-RCM simulation matrix of ENSEMBLES.
I. Reading, processing, and writing of climate model ouput
Functions:
models2wux
Reads NetCDF climate model output,
processes it, and writes the results to a data.frame which
is the backbone of all further WUX analyses
CMIP5fromESGF
Automated downloading of the
CMIP5 multi-model climate ensemble
read.wux.table
Reads in wux csv file obtained from
models2wux from harddisk and creates a data frame from
it (same data.frame as models2wux returns interactively)
AverageWuxDataFrame
WUX data frame averaging function
Datasets:
userinput_CMIP5_changesignal,
userinput_CMIP5_timeseries,
modelinput_test
Example config
files for models2wux
ensembles, ensembles_gcms,
cmip3_2050, cmip3_2100,
cmip5_2050, cmip5_2100,
CMIP5_example_changesignal,
CMIP5_example_timeseries,
alpinesummer
Example data frames
calculatated by models2wux
II. Descriptive analysis of climate change signals
Descriptive analysis of multiple climate model simulations.
summary.wux.df
Summary statistics of the WUX
data frame (wux.df class)
plot.wux.df
Scatter Plot
hist.wux.df
Density Plot
plotAnnualCycle
Annual Cycle Plot
III. Analysis of variance components
Extracts variance components of multiple climate model simulations
using an ANOVA.
aovWux
ANOVA for WUX data.frame
plot.wux.aov
Barplot for aovWux
output
IV. Reconstruction tools
Tools for filling missing values of an unbalanced climate model
simulation matrix (e.g. missing RCM-GCM combinations of ENSEMBLES) in
order to avoid biased ensemble estimates. Currently, the underlying
linear reconstrtuction technique is based on
solving the linear equation system (LES) of the ANOVA design matrix
(method = "LES"), or iterative linear
reconstruction based on an ANOVA (method = "Iterative") or
Leave-one-out
cross-calculation (method = "IterativeCC").
reconstruct
Linear reconstruction of missing
RCM-GCM combinations
providing 
.