PlotVsLTime {s2dv}

Plot a score along the forecast time with its confidence interval

Description

Plot the correlation (Corr()), the root mean square error (RMS()) between the forecast values and their observational counterpart, the slope of their trend (Trend()), the InterQuartile range, maximum-mininum, standard deviation or median absolute Deviation of the ensemble members (Spread()), or the ratio between the ensemble spread and the RMSE of the ensemble mean (RatioSDRMS()) along the forecast time for all the input experiments on the same figure with their confidence intervals.

Usage

PlotVsLTime(
  var,
  toptitle = "",
  ytitle = "",
  monini = 1,
  freq = 12,
  nticks = NULL,
  limits = NULL,
  listexp = c("exp1", "exp2", "exp3"),
  listobs = c("obs1", "obs2", "obs3"),
  biglab = FALSE,
  hlines = NULL,
  leg = TRUE,
  siglev = FALSE,
  sizetit = 1,
  show_conf = TRUE,
  fileout = NULL,
  width = 8,
  height = 5,
  size_units = "in",
  res = 100,
  ...
)

Arguments

var

Matrix containing any Prediction Score with dimensions:
(nexp/nmod, 3/4 ,nltime)
or (nexp/nmod, nobs, 3/4 ,nltime).

toptitle

Main title, optional.

ytitle

Title of Y-axis, optional.

monini

Starting month between 1 and 12. Default = 1.

freq

1 = yearly, 12 = monthly, 4 = seasonal, ... Default = 12.

nticks

Number of ticks and labels on the x-axis, optional.

limits

c(lower limit, upper limit): limits of the Y-axis, optional.

listexp

List of experiment names, optional.

listobs

List of observation names, optional.

biglab

TRUE/FALSE for presentation/paper plot. Default = FALSE.

hlines

c(a,b, ..) Add horizontal black lines at Y-positions a,b, ...
Default = NULL.

leg

TRUE/FALSE if legend should be added or not to the plot. Default = TRUE.

siglev

TRUE/FALSE if significance level should replace confidence interval.
Default = FALSE.

sizetit

Multiplicative factor to change title size, optional.

show_conf

TRUE/FALSE to show/not confidence intervals for input variables.

fileout

Name of output file. Extensions allowed: eps/ps, jpeg, png, pdf, bmp and tiff. The default value is NULL.

width

File width, in the units specified in the parameter size_units (inches by default). Takes 8 by default.

height

File height, in the units specified in the parameter size_units (inches by default). Takes 5 by default.

size_units

Units of the size of the device (file or window) to plot in. Inches ('in') by default. See ?Devices and the creator function of the corresponding device.

res

Resolution of the device (file or window) to plot in. See ?Devices and the creator function of the corresponding device.

...

Arguments to be passed to the method. Only accepts the following graphical parameters:
adj ann ask bg bty cex.sub cin col.axis col.lab col.main col.sub cra crt csi cxy err family fg fig font font.axis font.lab font.main font.sub lheight ljoin lmitre mar mex mfcol mfrow mfg mkh oma omd omi page pch plt smo srt tck tcl usr xaxp xaxs xaxt xlog xpd yaxp yaxs yaxt ylbias ylog
For more information about the parameters see 'par'.

Details

Examples of input:
Model and observed output from Load() then Clim() then Ano() then Smoothing():
(nmod, nmemb, nsdate, nltime) and (nobs, nmemb, nsdate, nltime)
then averaged over the members
Mean1Dim(var_exp/var_obs, posdim = 2):
(nmod, nsdate, nltime) and (nobs, nsdate, nltime)
then passed through
Corr(exp, obs, posloop = 1, poscor = 2) or
RMS(exp, obs, posloop = 1, posRMS = 2):
(nmod, nobs, 3, nltime)
would plot the correlations or RMS between each exp & each obs as a function of the forecast time.

Examples

# Load sample data as in Load() example:
example(Load)
clim <- Clim(sampleData$mod, sampleData$obs)
ano_exp <- Ano(sampleData$mod, clim$clim_exp)
ano_obs <- Ano(sampleData$obs, clim$clim_obs)
runmean_months <- 12
smooth_ano_exp <- Smoothing(data = ano_exp, runmeanlen = runmean_months)
smooth_ano_obs <- Smoothing(data = ano_obs, runmeanlen = runmean_months)
dim_to_mean <- 'member'  # mean along members
required_complete_row <- 'ftime'  # discard startdates for which there are NA leadtimes
leadtimes_per_startdate <- 60
corr <- Corr(MeanDims(smooth_ano_exp, dim_to_mean), 
            MeanDims(smooth_ano_obs, dim_to_mean), 
            comp_dim = required_complete_row, dat_dim = 'dataset', 
            limits = c(ceiling((runmean_months + 1) / 2), 
                       leadtimes_per_startdate - floor(runmean_months / 2)))
# Combine corr results for plotting
corr_combine <- abind::abind(corr$conf.lower, corr$corr, corr$conf.upper, corr$p.val, 
                            along = 0)
corr_combine <- Reorder(corr_combine, c(2, 3, 1, 4))

PlotVsLTime(corr_combine, toptitle = "correlations", ytitle = "correlation", 
           monini = 11, limits = c(-1, 2), listexp = c('CMIP5 IC3'), 
           listobs = c('ERSST'), biglab = FALSE, hlines = c(-1, 0, 1))