Model_stability_boot: Test the model stability: 2. empirical extreme value plot

In timokelder/UNSEEN: Evaluate Large ensemble simulations

Description

We plot the density distribution of the different leadtimes using ggplot. We want to show the confidence interval of the distribution of all lead times pooled together, and test whether the individual lead times fall within these confidence intervals. Therefore we bootstrap the pooled leadtimes into series with equal length of the individual leadtimes (875), with n=10000.

Usage

Model_stability_boot(
  ensemble,
  var_name = "tprate",
  ld_name = "leadtime",
  lab = var_name,
  fontsize = 11
)

Arguments

ensemble	The UNSEEN ensemble. This function expects an dataframe with variables leadtime, precipitation.
var_name	The column name containing the variable to be analyzed. Defaults to "tprate".
ld_name	The column name containing the leadtimes. Defaults to "leadtime".
lab	The y-label. Defaults to the variable name (var_name).
fontsize	The font size. Defaults to 11.

Value

a plot with the empirical return values of the pooled ensemble including confidence intervals. Individual lead times are plotted on top.

Source

Evaluation explaned in more detail in Kelder et al. 2020

Colorblind friendly palette http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/#a-colorblind-friendly-palette

timokelder/UNSEEN documentation built on June 1, 2021, 2:30 a.m.