RMprecip {fields} | R Documentation |
RMprecip
is a useful spatial data set of moderate size consisting of 865
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.)
The data set RMprecip
is a list containing the following components:
The data sets
PRISMelevation
and
RMelevation
are lists
in the usual R grid format for images and contouring
They have the following components:
These elevations and the companion grid formed the basis for the 103-Year High-Resolution Precipitation Climate Data Set for the Conterminous United States ftp://ftp.ncdc.noaa.gov/pub/data/prism100 archived at the National Climate Data Center. This work was primarily authored by Chris Daly www.prism.oregonstate.edu and his PRISM group but had some contribution from the Geophysical Statistics Project at NCAR. and is an interpolation of the observational data to a 4km grid that takes into account topography such as elevation and aspect.
# 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)) 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) par( save.par) image.plot(RMelevation, col=topo.colors(256)) US( add=TRUE, col="grey", lwd=2) title("PRISM elevations (m)")