WUWT’s Armagh silliness

One of the silliest posts to be published at WUWT since the “Diatoms…iiiiin spaaaaaaaaaaace!” farce, has to be yesterday’s article by Darko Butina based on his new paper. The paper apparently labours under the title

Should We Worry About the Earth’s Calculated Warming at 0.7°C Over Last the Last 100 Years When the Observed Daily Variations Over the Last 161 Years Can Be as High as 24°C?

in an unidentified “journal that deals with data analysis and pattern recognition of data generated by a physical instrument”. Presumably it is too embarrassing to mention the journal’s name (at least it should be embarrassing for the editor who published this paper). We are told that the paper is 20 pages long – crucial information for evaluating how good it is. Anthony Watts obviously thought it merited promoting and invited Butina’s contribution to WUWT.

The paper uses the Armagh Observatory temperature series (1844-2004) to claim that there is no global warming.

Sou at HotWopper has already discussed much of the madness in the article.

The method is encapsulated by this quote:

So if one wants, for some bizarre reason, to compare two annual patterns then one year can be unequivocally declared as warmer only if each daily reading of that year is larger than each corresponding daily reading of another year

Not surprisingly, Butina finds that there is no year that is hotter on every day than another year. It only takes single cold day in April in an otherwise exceptionally hot year for this test to fail. My question is, how much warming would be required before warming was unequivocal under this test?

The Armagh Observatory data is easy to import into R, and somewhat more difficult to format.

arm<-arm[!is.na(arm\$V2),]
arm<-sapply(0:160,function(i) {
r<-lapply(arm[,-1],function(k){k[(i*31+1):(i*31+31)]})
unlist(r)
})
dim(arm)
arm<-arm[rowSums(f.arm<(-100))<10,]#remove 31th Feb etc.
arm[arm==-888]<-NA
arm[arm==-999]<-NA

The resulting matrix has one column per year, one row per day.

The mean temperature of 2004 (the last year) is 0.8°C warmer than the 1844, but there are over 150 days when the temperature was warmer in 1844. Obviously under Butina’s test, 0.8°C is not enough to declare 2004 unequivocally warmer. How much warmer would 2004 have to have been to be unequivocally warmer? 8.5°C. With Butima’s method, 2004 would have had to have been 9.3°C warmer than 1844 before it could have been declared unequivocally warmer.

Daily maximum temperatures for Armagh Observatory, 1884 (blue) and 2004 (red)

x11();par(mar=c(3,3,1,1), mgp=c(1.5,.5,0))
matplot(1:365,arm[,c(1,161)], type="l", col=c(4,2), lty=1, xaxt="n", xlab="", ylab="Temperature °C")
mo<-cumsum(c(0,31,28,31,30, 31,30,31,31,30,31,30,31))
axis(1, mo, labels=NA)
axis(1, mo[-13]+15, labels=c("J","F","M","A","M","J","J","A","S","O","N","D"), tick=F)
legend("topleft", legend=c(1844,2004), col=c(4,2), lty=1, bty="n")
abline(h=colMeans(arm[,c(1,161)], na.rm=T), col=c(4,2), lty=3)

min(arm[,161]-arm[,1], na.rm=T)
mean(arm[,161]-arm[,1], na.rm=T)
sum(arm[,161]<arm[,1] , na.rm=T)

I could leave it there. But the 1844-2004 comparison could be a fluke. I want to test all combinations of years.

Warming required for year 1 to be declared warmer than year 2, tested for all pairs of years of data from Armagh Observatory.

required.warming<-apply(arm,2,function(y1){
apply(arm,2,function(y2){
if(identical(y1,y2))return(NA)
-min((y1-mean(y1, na.rm=T))-(y2-mean(y2, na.rm=T)), na.rm=T)
})
})

x11(6,6);par(mar=c(3,3,1,1), mgp=c(1.5,.5,0))
hist(required.warming, main="", xlab="warming required °C", col="grey")
quantile(required.warming, na.rm=T)

Typically, one year needs to be 11°C warmer than another before it can be declared warmer with Butina’s method: the method is useless. It is a method that that would struggle to declare that the Holocene is warmer than the preceding interglacial, that Cairo is warmer than Oslo or that summer is warmer than winter in Armagh. This is absurd. Even under the most extreme warming scenarios, it will not be possible to unequivocally declare 2100 warmer than 1900 with this test.

Warming under different scenarios in the IPCC AR4. Figure SPM.5. Solid lines are multi-model global averages of surface warming (relative to 1980–1999) for the scenarios A2, A1B and B1, shown as continuations of the 20th century simulations. Shading denotes the ±1 standard deviation range of individual model annual averages. The grey bars at right indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES marker scenarios.

Butina’s method is a joke. Watts thought this work worth promoting.