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Download the file, ozmax8.dat, which has the actual ozone measurements (max 8-hr daily average). Units are concentrations in parts per billion (PPB). Also, download the file, ozmax8.info.q, This is a list with information about the data set: station.no, lat, lon, dates. The times are in julian days where day 1 = JAN-01-1960. The actual times start on April 1, 1995. The ozone "season" runs from April through October ( 184 days) over five years (1995 - 1999). Alternatively, if only data from the North Carolina subset is desired, download the file NCdat.R, which has the daily maximum 8-hr average ozone data (ozmax8), the locations for the N.C. subset (loc) and the time points (dates). The standardized data for this subset are also available (NCstdO3.dat).

From an R session, use the following commands to load them into R:

ozmax8 <- matrix( scan("ozmax8.dat"), 920,513) source("ozmax8.info.q") # names( ozmax8.info) # are "stat.no" "lat" "lon" "dates" "loc" # # to plot station locations plot( ozmax8.info$lat, ozmax8.info$lon) # time series plot of first station plot( ozmax8.info$date, ozmax8[,1]) # # # the next example requires the fields package from CRAN # library( fields) corr <- cor( ozmax8, use = "pairwise") up <- col( corr) > row( corr) corr <- corr[ up] dist <- rdist.earth( ozmax8.info$loc)[up] plot( dist, corr, type="n", xlab="distance (miles)", ylab="cor") points( dist, corr, pch=".", col="blue") bplot.xy( dist, corr, add=TRUE) rm( corr, dist, up) # Working with the dates # Sorry yet another R package. I find much of the date stuff # incomprehensible! library( chron) # to extract calendar information start<- c(month = 1, day = 1, year = 1960) month.day.year( ozmax8.info$dates, origin.= start)-> look # look has components of month, day, year # to find the "day of year" necessary to model an annual cycle # first reset so that day 1 of the cycle is Jan 1. day.of.year<- (ozmax8.info$dates- julian( 12,31,1994, origin.=start)) day.of.year<- day.of.year%%365.25The result should look like the plot below.