RMprecip
is a useful spatial data set of moderate size consisting of 806
locations. See www.image.ucar.edu/Data for the source of these data.
PRISMelevation
and RMelevation
are gridded elevations for the
continental US and Rocky Mountain region at 4km resolution.
Note that the gridded elevations from the PRISM data product are
different than the exact station elevations. (See example below.)RData.USmonthlyMet.bin
can be downwloaded from
# explicit source code to create the RMprecip data dir <- "" # include path to data file load(paste(dir, "RData.USmonthlyMet.bin", sep="/") #year.id<- 1963- 1895 year.id<- 103 #pptAUG63<- USppt[ year.id,8,] loc<- cbind(USpinfo$lon, USpinfo$lat) xr<- c(-111, -99) yr<- c( 35, 45) station.subset<- (loc[,1]>= xr[1]) & (loc[,1] <= xr[2])="" &="" (loc[,2]="">= yr[1]) & (loc[,2]<= yr[2])="" ydata<-="" usppt[="" year.id,8,station.subset]="" ydata="" <-="" ydata*10="" #="" cm="" -=""> mm conversion xdata<- loc[station.subset,] dimnames(xdata)<- list( USpinfo$station.id[station.subset], c( "lon", "lat")) xdata<- data.frame( xdata) good<- !is.na(ydata) ydata<- ydata[good] xdata<- xdata[good,] test.for.zero.flag<- 1 test.for.zero( unlist(RMprecip$x), unlist(xdata), tag="locations") test.for.zero( ydata, RMprecip$y, "values")
# this data set was created the
# historical data taken from
# Observed monthly precipitation, min and max temperatures for the coterminous US
# 1895-1997
# NCAR_pinfill
# see the Geophysical Statistics Project datasets page for the supporting functions
# and details.
# plot
quilt.plot(RMprecip$x, RMprecip$y)
US( add=TRUE, col=2, lty=2)
# comparison of station elevations with PRISM gridded values
data(RMelevation)
interp.surface( RMelevation, RMprecip$x)-> test.elev
plot( RMprecip$elev, test.elev, xlab="Station elevation",
ylab="Interpolation from PRISM grid")
abline( 0,1,col="blue")
# some differences with high elevations probably due to complex
# topography!
#
# view of Rockies looking from theSoutheast
save.par<- par(no.readonly=TRUE)
par( mar=c(0,0,0,0))
# fancy use of persp with shading and lighting.
persp( RMelevation, theta=75, phi= 15,
box=FALSE, axes=FALSE, xlab="", ylab="",
border=NA,
shade=.95, lphi= 10, ltheta=80,
col= "wheat4",
scale=FALSE, expand=.00025)
# reset graphics parameters and a more conventional image plot.
par( save.par)
image.plot(RMelevation, col=topo.colors(256))
US( add=TRUE, col="grey", lwd=2)
title("PRISM elevations (m)")
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