RainIbk: Precipitation Observations and Forecasts for Innsbruck

In crch: Censored Regression with Conditional Heteroscedasticity

Precipitation Observations and Forecasts for Innsbruck

Description

Accumulated 5-8 days precipitation amount for Innsbruck. Data includes GEFS reforecasts (Hamill et al. 2013) and observations from SYNOP station Innsbruck Airport (11120) from 2000-01-01 to 2013-09-17.

Usage

data("RainIbk", package = "crch")

Format

A data frame with 4977 rows. The first column (rain) are 3 days accumulated precipitation amount observations, Columns 2-12 (rainfc) are 5-8 days accumulated precipitation amount forecasts from the individual ensemble members.

Source

Observations: https://www.ogimet.com/synops.phtml.en

Reforecasts: https://psl.noaa.gov/forecasts/reforecast2/

References

Hamill TM, Bates GT, Whitaker JS, Murray DR, Fiorino M, Galarneau Jr TJ, Zhu Y, Lapenta W (2013). NOAA's Second-Generation Global Medium-Range Ensemble Reforecast Data Set. Bulletin of the American Meteorological Society, 94(10), 1553-1565.

Examples

## Spread skill relationship ##

## load and prepare data
data("RainIbk", package = "crch")

## mean and standard deviation of square root transformed ensemble forecasts
RainIbk$sqrtensmean <- 
  apply(sqrt(RainIbk[,grep('^rainfc',names(RainIbk))]), 1, mean)
RainIbk$sqrtenssd <- 
  apply(sqrt(RainIbk[,grep('^rainfc',names(RainIbk))]),  1, sd)

## quintiles of sqrtenssd
sdcat <- cut(RainIbk$sqrtenssd, c(-Inf, quantile(RainIbk$sqrtenssd, 
  seq(0.2,0.8,0.2)), Inf), labels = c(1:5))

## mean forecast errors for each quintile
m <- NULL
for(i in levels(sdcat)) {
  m <- c(m, mean((sqrt(RainIbk$rain)[sdcat == i] -
  RainIbk$sqrtensmean[sdcat == i])^2, na.rm = TRUE))
}

## plot
boxplot((sqrt(rain) - sqrtensmean)^2~sdcat, RainIbk, 
  xlab = "Quintile of ensemble standard deviation", 
  ylab = "mean squared error", main = "Spread skill relationship")

crch documentation built on Sept. 30, 2024, 9:22 a.m.