Tuesday, October 20, 2009

Antarctic Ice Melt Lowest Ever Measured

That's the sensational headline anyway. Is it part of a significant downward trend though? Here's a graph of ice melt anomaly from the paper: An updated Antarctic melt record through 2009 and its linkages to high-latitude and tropical climate variability

You can use the g3data software to pull data points (that's what I did) if you want to run your own analysis with R. Does a simple statistical analysis support the claim that "there seems to be a downward trend"?

The R to generate the above graph is shown below.

melt = read.table("melt.dat")
attach(melt)

m.1 = lm(V2 ~ V1)

# Make confidence and prediction intervals
m.1.cinterval = predict(m.1, level=0.95, interval="confidence")
m.1.pinterval = predict(m.1, level=0.95, interval="prediction")

# plot the data and the fits/intervals to a png file
png("melt.png", width=640, height=480)

plot(V1, V2, ylab="Melting Anomaly", xlab="Year")
lines(V1, m.1.cinterval[,1], lty=1)
lines(V1, m.1.cinterval[,2], lty=2)
lines(V1, m.1.cinterval[,3], lty=2)
lines(V1, m.1.pinterval[,2], lty=2)
lines(V1, m.1.pinterval[,3], lty=2)
title("Antarctic Summer Melt Anomaly")
dev.off()

And here's the summary table for the linear model.

Call:
lm(formula = V2 ~ V1)

Residuals:
Min 1Q Median 3Q Max
-1.7507 -0.7252 -0.1028 0.7953 2.2894

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 60.54322 42.88214 1.412 0.169
V1 -0.03035 0.02150 -1.412 0.169

Residual standard error: 0.983 on 28 degrees of freedom
Multiple R-squared: 0.06646, Adjusted R-squared: 0.03312
F-statistic: 1.993 on 1 and 28 DF, p-value: 0.1690

What does that model summary output mean? There really is NOT a significant downward trend of melt anomaly with years (there's no first order trend in fact). It's not measurably different from noise. How does this square with the recent reports of runaway melting though?

Whether the ice is melting to much or too little,
The public is not well served by this constant drumbeat of false alarms fed by computer models manipulated by advocates.
-- DR. DAVID WOJICK, UN IPCC expert reviewer, PhD in Philosophy of Science, co-founded Department of Engineering and Public Policy at Carnegie-Mellon University


These recent posts about climate change stuff were inspired by a post I read about climate change skeptics, which I found because of my Google alerts on things related to 'computational fluid dynamics'. In the post she mentions Freeman Dyson, he's a pretty smart guy.

Concerning the climate models, I know enough of the details to be sure that they are unreliable. They are full of fudge factors that are fitted to the existing climate, so the models more or less agree with the observed data.

It is much easier for a scientist to sit in an air-conditioned building and run computer models, than to put on winter clothes and measure what is really happening outside in the swamps and the clouds. That is why the climate model experts end up believing their own models.
-- Dr. Freeman Dyson, Professor Emeritus of Physics at the Institute for Advanced Study at Princeton, fellow of the American Physical Society, member of the US National Academy of Sciences, and a fellow of the Royal Society of London


My favourite quote on the whole mess, a level-headed engineer from MIT quoted in a short article:
Mort Webster, assistant professor of engineering systems, warned that public discussion over climate change policies gets framed as a debate between the most extreme views on each side. "The world is ending tomorrow, versus it's all a myth," he said. "Neither of those is scientifically correct or socially useful."

1 comment:

  1. Accelerated Antarctic ice loss from satellite gravity measurements
    http://www.nature.com/ngeo/journal/v2/n12/abs/ngeo694.html

    ftp://ftp.csr.utexas.edu/pub/ggfc/papers/ngeo694.pdf

    Natural variations in gravity and sunspots are the real cause. Idiots.

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