datasets: Spatial Forecast Verification Methods Inter-Comparison...

In SpatialVx: Spatial Forecast Verification

Spatial Forecast Verification Methods Inter-Comparison Project (ICP) Test Cases and other example verification sets

Description

Test cases used for the ICP. In particular, those actually analyzed in the special collection of the journal, Weather and Forecasting. Includes the nine “real” cases, five simple geometric cases, and the seven perturbed “real” cases.

Usage

data( "obs0601" )
data( "wrf4ncar0531" )
data( "geom000" )
data( "geom001" )
data( "geom002" )
data( "geom003" )
data( "geom004" )
data( "geom005" )
data( "ICPg240Locs" )

Format

The format is: num [1:601, 1:501] 0 0 0 0 0 0 0 0 0 0 ...

The format is: num [1:301101, 1:2] -110 -110 -110 -110 -110 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "lon" "lat"

Details

One of the nine ICP “real” cases is from one version of the Weather Research Forecast (WRF) model denoted wrf4ncar (see Kain et al. 2008; Ahijevych et al., 2009 for complete details), and the corresponding “observed” field is stage II reanalyses denoted here by “obs”. The model is a 24-h forecast so that the valid time is for the next day (e.g., obs0531 corresponds with obs0601).

These data are a subset from the 2005 Spring Program of the Storm Prediction Center/National Severe Storms Laboratory (SPC/NSSL, cf. Weiss et al., 2005; Kain et al., 2008). Units for the real cases are in mm/h, and are on the NCEP g240 grid (~4-km resolution) with 601 X 501 grid points. Both SPC and NSSL should be cited as sources for these cases, as well as Weiss et al. (2005) and possibly also Kain et al. (2008). The data were made available to the ICP by M. E. Baldwin.

The five geometric cases are simple ellipses (each with two intensities) that are compared against the verification case (geom000) on the same NCEP g240 grid as the nine real cases. See Ahijevych et al. (2009) for complete details. Case geom001 is exactly the same as geom000, but is displaced 50 grid points to the right (i.e., ~200 km too far east). Case geom002 is also identical to geom000, but displaced 200 grid points to the right. case geom003 is displaced 125 grid points to the right, and is also too big 9i.e., has a spatial extent, or coverage, bias). Case geom004 is also displaced 125 grid points to the right, but also has a different orientation (note, however, that it is not a true rotation of geom000). Case geom005 is displaced 125 grid points to the right, and has a huge spatial extent bias. This last case is also the only one that actually overlaps with geom000, and therefore may be regarded by some as the best case. It is certainly the case that comes out on top by the traditional verification statistics that are calculated on a grid point by grid point basis. Ahijevych et al. (2009) should be cited if these geometric cases are used for publications, etc.

The longitude and latitude information for each grid (the NCEP g240 grid) is contained in the ICPg240Locs dataset.

Other data sets for the ICP can be obtained from the ICP web site (https://projects.ral.ucar.edu/icp/). MesoVICT data sets are also available there. All of the ICP test cases used to be available in this package, but had to be removed because of space concerns on CRAN.

Source

https://projects.ral.ucar.edu/icp/

References

Ahijevych, D., Gilleland, E., Brown, B. G. and Ebert, E. E. (2009) Application of spatial verification methods to idealized and NWP gridded precipitation forecasts. Wea. Forecasting, 24 (6), 1485–1497.

Kain, J. S., Weiss, S. J., Bright, D. R., Baldwin, M. E. Levit, J. J. Carbin, G. W. Schwartz, C. S. Weisman, M. L. Droegemeier, K. K. Weber, and D. B. Thomas, K. W. (2008) Some Practical Considerations Regarding Horizontal Resolution in the First Generation of Operational Convection-Allowing NWP. Wea. Forecasting, 23, 931–952.

Weiss, S., Kain, J. Levit, J. Baldwin, M. E., Bright, D. Carbin, G. and Hart, J. (2005) NOAA Hazardous Weather Testbed. SPC/NSSL Spring Program 2005 Program Overview and Operations Plan. 61pp.

Examples

## Not run: 
data( "obs0601" )
data( "wrf4ncar0531" )
data( "ICPg240Locs" )
## Plot verification sets with a map.
## Two different methods.

# First way does not preserve projections.
locr <- c( range( ICPg240Locs[,1]), range( ICPg240Locs[,2]))
zl <- range( c( c(obs0601), c( wrf4ncar0531) ) )
par( mfrow=c(2,1), mar=rep(0.1,4))
image( obs0601, axes=FALSE, col=c("grey", tim.colors(256)), zlim=zl)
par( usr=locr)
# if( map.available) map( add=TRUE, database="state") # from library( "maps" )
image( wrf4ncar0531, axes=FALSE, col=c("grey", tim.colors(256)), zlim=zl)
par( usr=locr)
# if( map.available) map( add=TRUE, database="state")
image.plot( obs0601, legend.only=TRUE, horizontal=TRUE, 
		col=c("grey", tim.colors(256)), zlim=zl)

# Second way preserves projections, but values are slighlty interpolated.
zl <- range( c( c(obs0601), c( wrf4ncar0531) ) )
par( mfrow=c(2,2), mar=rep(2.1,4))
image(as.image(c(t(obs0601)), x=ICPg240Locs, nx=601, ny=501, na.rm=TRUE), zlim=zl,
        col=c("grey", tim.colors(64)), axes=FALSE, main="Stage II Reanalysis 4/26/05 0000 UTC")
# map(add=TRUE, lwd=1.5)
# map(add=TRUE, database="state", lty=2)
image(as.image(c(t(wrf4ncar0531)), x=ICPg240Locs, nx=601, ny=501, na.rm=TRUE), zlim=zl,
        col=c("grey", tim.colors(64)), axes=FALSE, main="WRF NCAR valid 4/26/05 0000 UTC")
image.plot(obs0601, col=c("grey", tim.colors(64)), zlim=zl, legend.only=TRUE, horizontal=TRUE)

## End(Not run)

SpatialVx documentation built on Nov. 10, 2022, 5:56 p.m.