RainIbk | R Documentation |

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.

data("RainIbk")

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.

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

Reforecasts: http://www.esrl.noaa.gov/psd/forecasts/reforecast2/

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.

## Spread skill relationship ## ## load and prepare data data(RainIbk) ## 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")

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