EastAuClimate {latticeExtra} | R Documentation |
A set of climate statistics for 16 coastal locations along Eastern Australia. These sites were chosen to be approximately equally spaced to cover the whole eastern coast of Australia. For each site, climate statistics were calculated for the standard 30-year period 1971-2000. Only sites with nearly-complete data were chosen.
data(EastAuClimate)
A data frame with the following 10 variables and 5 items of metadata for each of 16 sites.
SummerMaxTemp
SummerMinTemp
WinterMaxTemp
WinterMinTemp
SummerRain
WinterRain
MeanAnnRain
RainDays
ClearDays
CloudyDays
ID
Latitude
Longitude
Elevation
State
The row names of the data frame give the location names. Note: these are not the official names of the climate stations.
Sites were chosen by hand from maps on the Bureau of Meteorology website. The data were extracted manually from web pages under http://www.bom.gov.au/climate/averages/ and processed to extract a subset of statistics. - by Felix Andrews felix@nfrac.org
Bureau of Meteorology, Commonwealth of Australia. Product IDCJCM0026 Prepared at Wed 31 Dec 2008.
Definitions of statistics adapted from http://www.bom.gov.au/climate/cdo/about/about-stats.shtml
data(EastAuClimate) ## Compare the climates of state capital cities EastAuClimate[c("Hobart", "Melbourne", "Sydney", "Brisbane"),] ## A function to plot maps (a Lattice version of maps::map) lmap <- function(database = "world", regions = ".", exact = FALSE, boundary = TRUE, interior = TRUE, projection = "", parameters = NULL, orientation = NULL, aspect = "iso", type = "l", par.settings = list(axis.line = list(col = "transparent")), xlab = NULL, ylab = NULL, ...) { theMap <- map(database, regions, exact = exact, boundary = boundary, interior = interior, projection = projection, parameters = parameters, orientation = orientation, plot = FALSE) xyplot(y ~ x, theMap, type = type, aspect = aspect, par.settings = par.settings, xlab = xlab, ylab = ylab, default.scales = list(draw = FALSE), ...) } ## Plot the sites on a map of Australia if (require("maps")) { lmap(regions = c("Australia", "Australia:Tasmania"), exact = TRUE, xlim = c(130, 170), panel = function(...) { panel.xyplot(...) with(EastAuClimate, { panel.points(Longitude, Latitude, pch = 16) txt <- row.names(EastAuClimate) i <- c(3, 4) panel.text(Longitude[ i], Latitude[ i], txt[ i], pos = 2) panel.text(Longitude[-i], Latitude[-i], txt[-i], pos = 4) }) }) } ## Average daily maximum temperature in July (Winter). xyplot(WinterMaxTemp ~ Latitude, EastAuClimate, aspect = "xy", type = c("p", "a"), ylab = "Temperature (degrees C)") ## (Make a factor with levels in order - by coastal location) siteNames <- factor(row.names(EastAuClimate), levels = row.names(EastAuClimate)) ## Plot temperature ranges (as bars), color-coded by RainDays segplot(siteNames ~ WinterMinTemp + SummerMaxTemp, EastAuClimate, level = RainDays, sub = "Color scale: number of rainy days per year", main = paste("Typical temperature range and wetness", "of coastal Australian cities", sep = "\n")) ## Show Winter and Summer temperature ranges separately segplot(Latitude ~ WinterMinTemp + SummerMaxTemp, EastAuClimate, main = "Average daily temperature ranges \n of coastal Australian sites", ylab = "Latitude", xlab = "Temperature (degrees C)", par.settings = simpleTheme(lwd = 3, alpha = 0.5), key = list(text = list(c("July (Winter)", "February (Summer)")), lines = list(col = c("blue", "red"))), panel = function(x, y, z, ..., col) { with(EastAuClimate, { panel.segplot(WinterMinTemp, WinterMaxTemp, z, ..., col = "blue") panel.segplot(SummerMinTemp, SummerMaxTemp, z, ..., col = "red") }) }) ## Northern sites have Summer-dominated rainfall; ## Southern sites have Winter-dominated rainfall. xyplot(SummerRain + WinterRain ~ Latitude, EastAuClimate, type = c("p", "a"), auto.key = list(lines = TRUE), ylab = "Rainfall (mm / month)") ## Clear days are most frequent in the mid latitudes. xyplot(RainDays + CloudyDays + ClearDays ~ Latitude, EastAuClimate, type = c("p", "a"), auto.key = list(lines = TRUE), ylab = "Days per year")