|Contact Us | Visit Us | UCAR People Search||Numerics| Assimilation| Turbulence| Statistics|
This is a nearly complete record in R binary format for the monthly weather station data for the continential US from 1895 through 1997. Variables are the monthly average daily minimum temperature, average daily maximum temperature and total precipitation. Temperature units are degree C and precipitation is in millimeters.
The R binary data file RData.USMonthlyMet.bin can be obtained from the directory http://www.image.ucar.edu/public/Data and is 28.2Mb in size. The R script make.RData.USMet.R was used to create these objects from the full data sets that include infilled values. e (244kb) text file USmonthly.names.txt is a table ( station code, place name) that can be used to find the geographic name of a station. Not all the precipitation stations are in this list however.
attach("RData.USMonthlyMet.bin")will attach these data objects to your current session. Use the R function load to add these objects permanently to your R workspace.
The individual data objects in components are two tables of the meta information concerning station locations (UStinfo, USpinfo) and three, 3-dimensional arrays of the actual monthly statistics (UStmax,UStmin, USppt). Note that the temperature and preciptiation stations may differ and that is the reason for two separate "info" objects.
The data is a compendium of different levels of weather data ranging from stations taking regular hourly measurements, such as those at airports, to cooperative observer stations where the records may only include daily values, have gaps in time or might not measure both temperature and precipitation. The original source for the data are the data archives at the National Climatic Data Center (http://www.ncdc.noaa.gov) although these data have been further processesd to combine stations at similar locations and eliminate stations with short records. These data 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 this is an interpolation of the observational data to a 4km grid that takes in account and topography.
# descriptive plots png("fig1.png",width=480, height=360) plot( UStinfo[,3:4], col="red", pch=".", cex=2, xlab="", ylab="", axes=FALSE) US(add=TRUE, col=" blue") title("Temperature stations 1895-1997", cex=2) dev.off() png("fig2.png",width=480, height=360) temp1<- apply( is.na((UStmax+UStmin)[,7,]) , 1, "sum") temp1<- 8125- temp1 temp2<- apply( is.na( (UStmax+UStmin)[,1,]) , 1, "sum") temp2<- 8125- temp2 ppt1<- apply( is.na( (USppt)[,7,]) , 1, "sum") ppt1<- 11918- ppt1 ppt2<- apply( is.na( (USppt)[,1,]) , 1, "sum") ppt2<- 11918- ppt2 matplot( 1895:1997, cbind( temp1, ppt1, temp2,ppt2), type="l", lty=c( 1,1,2,2), col=c("red", "blue"), xlab="year", ylab="number of stations", lwd=1.5, cex=2) title("Number of reporting stations for July (solid) and Jan (dashed) precipitation (blue), temperature (red)") dev.off()
ind<- (UStinfo$lon < -101) & (UStinfo$lon> -109.5) ind<- ind & (UStinfo$lat<41.5) & (UStinfo$lat>36.5) # (3 4 5) (6 7 8) (9 10 11) (12 1 2) CO.tmax.JJA<- apply( UStmax[,6:8,ind],c(1,3), "mean") CO.tmin.JJA<- apply( UStmin[,6:8,ind],c(1,3), "mean") CO.loc<- UStinfo[ind,3:4] CO.elev<- UStinfo$elev[ind] CO.id<- UStinfo$station.id[ind]Plot of 1997 summer maximum temperatures and the 30 year average temperatures against elevation.
png("fig3.png",width=480, height=360) quilt.plot( CO.loc,CO.tmax.JJA[103,] ) US( add=T) title( "Recorded JJA mean daily max temperatures (1997)") dev.off() png("fig4.png",width=480, height=360) ind<- (1990:1961) - 1894 temp1<- apply( CO.tmin.JJA[ind,],2,"mean", na.rm=TRUE) temp2<- apply( CO.tmax.JJA[ind,],2,"mean", na.rm=TRUE) matplot( CO.elev, cbind( temp1,temp2), pch=".", type="p", col=c("red", "blue"), xlab="elevation (m)", ylab="Temperature (C)", cex=2) title( " JJA mean daily max/min temperatures (1961-1990))", cex=2) dev.off()