int.scale.verify: Intensity-Scale Verification Model

Description

For a spatial forecast, evaluates the forecast skill as a function of precipitaion rate intesity and spatial scale of the error.

Usage

int.scale.verify(frcs, obs, thres = quantile(frcs, p = seq(0,0.9,0.1)),  ... )

Arguments

frcs

Forecast matrix. Must be of $2^n$ dimensions.

obs

Observation matrix. Must be of $2^n$ dimensions.

thres

A vector of thresholds to be considered. By default, the percentiles 0, 90 are used.

...

Optional arguments may be passed to the image plot

Value

SSulSkill score as matrix. The rownames are the thresholds, the colnames are $n$ where $2^n$ is the spatial scale of the skill score decomposition.
MSEA matrix with the mean squared error of the forecast
l.frcsNumber of rows in forecast. Used in plotting routine.
thresThresholds used in model

References

B.Casati, D.B. Stephenson, G. Ross. A new intensity-scale approach for the verification of spatial precipitation forecasts. Meteorological Application (RMS), in press.

Examples

Run this code

## simulated example
n<- 5
set.seed(10)
forecast1 <- matrix( log(rlnorm(n = (2^n *2^n) )) , nrow = 2^n)
obs1      <- matrix(log( rlnorm(n = (2^n *2^n) )) , nrow = 2^n)
int.scale.verify(forecast1, obs1, main = "Test Case")  

## real example.  Data source referenced below.


data(analysis.dat)
data(forecast.dat)

require(waveslim)
require(fields)


A<- int.scale.verify(forecast.dat, analysis.dat,
thres = c(0, 2^seq(-5,6)),  main = "NIMROD example" )

plot(A)