PlotVsLTime: Plots A Score Along The Forecast Time With Its Confidence...

In s2dverification: Set of Common Tools for Forecast Verification

Plots A Score Along The Forecast Time With Its Confidence Interval

Description

Plots The Correlation (Corr()) or the Root Mean Square Error (RMS()) between the forecasted values and their observational counterpart or the slopes of their trends (Trend()) or 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 = "output_plotvsltime.eps",
  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. Default = 'output_plotvsltime.eps'
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.

Author(s)

History:
0.1 - 2011-03 (V. Guemas) - Original code
0.2 - 2013-03 (I. Andreu-Burillo) - Introduced parameter sizetit
0.3 - 2013-10 (I. Andreu-Burillo) - Introduced parameter show_conf
1.0 - 2013-11 (N. Manubens) - Formatting to CRAN

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
dim_to_smooth <- 4  # Smooth along lead-times
smooth_ano_exp <- Smoothing(ano_exp, runmean_months, dim_to_smooth)
smooth_ano_obs <- Smoothing(ano_obs, runmean_months, dim_to_smooth)
dim_to_mean <- 2  # Mean along members
required_complete_row <- 3  # Discard startdates for which there are NA leadtimes
leadtimes_per_startdate <- 60
corr <- Corr(Mean1Dim(smooth_ano_exp, dim_to_mean), 
            Mean1Dim(smooth_ano_obs, dim_to_mean), 
            compROW = required_complete_row, 
            limits = c(ceiling((runmean_months + 1) / 2), 
                       leadtimes_per_startdate - floor(runmean_months / 2)))
 
PlotVsLTime(corr, toptitle = "correlations", ytitle = "correlation", 
           monini = 11, limits = c(-1, 2), listexp = c('CMIP5 IC3'), 
           listobs = c('ERSST'), biglab = FALSE, hlines = c(-1, 0, 1), 
           fileout = 'tos_cor.eps')
 

s2dverification documentation built on April 20, 2022, 9:06 a.m.