fss: Fractional Skill Score

In verification: Weather Forecast Verification Utilities

Description

Calculates the fractional skill score for spatial forecasts and spatial observations.

Usage

    fss(obs, pred,w = 0, FUN = mean, ...)
       

Arguments

obs	A matrix of binomial observed values.
pred	A matrix of binomial forecasted values
w	Box width. When w = 0, each pixel is considered alone. w = 2 creates a box with a length of 5 units.
FUN	Function to be applied to each subgrid. By default, the mean of each box is used to calculate the fraction of each subgrid.
...	Optional arguments

Value

Return the fraction skill score.

Note

This function contain several loops and consequently is not particularly fast.

Author(s)

Matt Pocernich

References

Roberts, N.M and H.W. Lean: 2008: Scale-Selective Verification of Rainfall Accumulations from High-Resolution Forecasts of Convective Events. Monthly Weather Review 136, 78-97.

Examples

grid<- list( x= seq( 0,5,,100), y= seq(0,5,,100)) 
obj<-Exp.image.cov( grid=grid, theta=.5, setup=TRUE)
look<- sim.rf( obj)
look[look < 0] <- 0

look2 <- sim.rf( obj)
look2[look2<0] <- 0

fss(look, look2, w=5)


## Not run: 
#  The following example replicates Figure 4 in Roberts and Lean (2008).
####      examples

LAG <- c(1,3,11,21)
box.radius <- seq(0,24,2)

OUT <- matrix(NA, nrow = length(box.radius), ncol = length(LAG) )

for(w in 1:4){

FRCS <- OBS <- matrix(0, nrow = 100, ncol = 100)

obs.id        <- 50
OBS[,obs.id]  <- 1

FRCS[, obs.id + LAG[w]] <- 1

for(i in 1:length(box.radius)){

OUT[i, w] <- fss(obs = OBS, pred = FRCS, w = box.radius[i] )

} ### close i
} ### close w

b <- mean(OBS) ## base rate

fss.uniform  <- 0.5 + b/2
fss.random   <- b

matplot(OUT, ylim = c(0,1), ylab = "FSS", xlab = "grid squares", 
type = "b", lty = 1, axes = FALSE , lwd = 2)

abline(h = c(fss.uniform, fss.random), lty = 2)  
axis(2)
box()
axis(1, at = 1:length(box.radius), lab = 2*box.radius + 1)
grid()

legend("bottomright", legend = LAG, col = 1:4, pch = as.character(1:4), 
 title = "Spatial Lag", inset = 0.02, lwd = 2 )

## End(Not run)

verification documentation built on May 2, 2019, 1:24 a.m.