cascadePlot: Cascade plot to visualize the climate change modelling...

In SantanderMetGroup/visualizeR: Visualizing climate4R data and Communicating Uncertainty in Seasonal Climate Prediction

Cascade plot to visualize the climate change modelling uncertainty cascade.

Description

Cascade plot to decompose modelling uncertainty down to individual future climate projections.

Usage

cascadePlot(
  x,
  factors,
  stages = NULL,
  labels = FALSE,
  label.names = NULL,
  colors = NULL,
  title = NULL,
  line.width = NULL,
  plot.density = TRUE,
  density.offset = 0,
  density.reverse = TRUE
)

Arguments

x	Numeric vector with the values of the individual projections.
factors	List with several factors classifying the data in x.
stages	String vector with the names of the factors to be plotted from bottom to top.
labels	Logical (default = FALSE). Whether to plot individual labels for each line. See label.names.
label.names	Character vector with the names to be given to each line. If NULL (default) names are taken from x.
colors	Color vector to be used in the last aggregating step and all lines leading to each main branch. If NULL (default) an appropriate rainbow scale is used. Its length should be length(levels(factors[[rev(stages)[1]]])).
title	Title of the plot
line.width	Width of the lines.
plot.density	Logical (default = TRUE). Add an estimate of the probability density function (PDF).
density.offset	A vector indicating how much the PDF should be shifted relative to the bottom part of the plot. Default is 0.
density.reverse	Logical (default = TRUE). If TRUE plot the PDF upside down.

Author(s)

J. Fernández [e-mail] and M.D. Frías based on the visualization proposed by Ed Hawkins on his Climate Lab Book http://www.climate-lab-book.ac.uk/2014/cascade-of-uncertainty

References

Hawkins E. 2014. Climate Lab Book. http://www.climate-lab-book.ac.uk/2014/cascade-of-uncertainty

Fernández, J., Frías, M.D., Cabos, W.D. et al. 2018. Consistency of climate change projections from multiple global and regional model intercomparison projects. Clim Dyn. https://doi.org/10.1007/s00382-018-4181-8

See Also

Other visualization functions: bubblePlot(), climagram(), reliabilityCategories(), spreadPlot(), tercileBarplot(), tercilePlot()

Examples

## Not run: 
# This code reproduces Figure 4 (top) from Fernandez et al. (2018)
load(url("http://meteo.unican.es/work/visualizeR/data/multimip_sdelta_es.rda"), verbose=T)
cat(multimip.README)
filter.members <- multimip.factors[["Method"]]=="GCM" & ! multimip.factors[["GCM"]] %in% c("CNRM-CM5-r8", "EC-EARTH-r3")
sdeltas <- multimip.prtas.sdeltas["tas",filter.members]
factors <- lapply(multimip.factors, function(x) factor(x[filter.members]))
title <- "Delta T (K)"
cascadePlot(sdeltas, factors, multimip.stages, title=title, density.offset=2)

## End(Not run) 

SantanderMetGroup/visualizeR documentation built on Oct. 28, 2023, 6:11 a.m.