fields (version 10.3)

RMprecip: Monthly total precipitation (mm) for August 1997 in the Rocky Mountain Region and some gridded 4km elevation data sets (m).

Description

RMprecip is a useful spatial data set of moderate size consisting of 806 locations. 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.)

Format

The data set RMprecip is a list containing the following components:

x

Longitude-latitude position of monitoring stations. Rows names are station id codes consistent with the US Cooperative observer network. The ranges for these coordinates are [-111, -99] for longitude and [35,45] for latitude.

elev

Station elevation in meters.

y

Monthly total precipitation in millimeters. for August, 1997

The data sets PRISMelevation and RMelevation are lists in the usual R grid format for images and contouring

They have the following components:

x

Longitude grid at approximately 4km resolution

y

Latitude grid at approximately 4km resolution

z

Average elevation for grid cell in meters

These elevations and the companion grid formed the basis for the 103-Year High-Resolution Precipitation Climate Data Set for the Conterminous United States ( see http://www.prism.oregonstate.edu/documents/PRISM_downloads_FTP.pdf and also archived at the National Climate Data Center. This work is authored by Chris Daly http://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.

Details

Contact Doug Nychka for the binary file RData.USmonthlyMet.bin and information on its source.

# 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")

Examples

# NOT RUN {
# 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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