Note:The BOM uses the mean of temperatures in the period 1961–1990 as the ‘baseline’ for anomalies. The NASA data from RSS calculates anomalies as differences from the mean in the period 1979–2008 (for the relevant series). But in this case, the different baselines don’t matter.I’m interested only in whether the BOM claim of a huge anomaly (> 1° celsius) is plausible. It sure doesn’t look that way from space.
The smoothing in the graph is based on a simple, two-sided, moving average over 13 months. It’s unnecessary; only a piece of eye-candy.
Here’s the R script used to create the graph. It should be able to handle future updates to the RSS data. Please note that you’ll need the “Hmisc” library from CRAN for the last step in the script.
Disowner: I’m an R amateur, so…this is a kludge, your milage may vary etc. etc.
# Load S-hemisphere (-70s to -20s) land anomalies
# Smooth them using a two-sided filter (13 years)
# Plot the anomaly time-series and the smoothed series
# for the tick marks on the graph
# get the data: land temperature anomalies
f<-read.table(file, skip=3, fill=TRUE)
# create a time-series
# f$V6 is the vector corresponding to data for 70s - 20s latitude
# Substitute: f$V3 = global; f$V4 = tropics; f$V5 = nth hemisphere
# f$V7 = nth temperate; f$V8 = sth temperate
# a vector of weights
# smooth the anomaly series
A_Smooth<-filter(Anomaly,(k/sum(k))) # filter the anomalies
# the date of the data
# now plot the data
plot(Anomaly, col="darkseagreen", lty=1, xlab="",ylab="degrees c", main="Southern Hemisphere Lower Troposphere (Land) Anomaly", sub=paste("Source: Remote Sensing Systems, to",
my_months[f$V2[length(f$V2)]], f$V1[length(f$V1)], sep=" "), cex.sub=0.7, font.sub=3, cex.axis=0.8)
# overplot the smoothed series
# add a legend
legend("bottomright",c("anomaly","smoothed"), cex=0.8, lwd=2,col=c("darkseagreen","darkorange"),horiz=TRUE, bty="n", inset=0.02)
# and a 'mid-line' to make the anomaly easier to read
# some tick marks