Previous Page

“Hockey Stick - Michael Mann

There has been a lot of controversy about the “hockey stick”, at least in the mass media. Since paleoclimate is outside my knowledge base, I’m going to redirect you to read Dummies guide to the latest “Hockey Stick” controversy at RealClimate. The “problems” with the “hockey stick” are highly mathematical, and I hope it’s written at a level that you can understand.

Galactic Cosmic Rays and Clouds

I don’t know anything about galactic cosmic rays, but Recent Warming But No Trend in Galactic Cosmic Rays might. I’ve reproduced their figure showing temperatures in white, and GCR in red.

Aerosols

You include a brief paragraph on aerosols, but unfortunately it’s mostly wrong (similar to mostly dead, if you’ve seen The Princess Bride). An aerosol is defined as “a suspension of fine solid or liquid particles in a gas, common usage refers to the aerosol as the particulate [solid] component only (Seinfeld and Pandis, 1997). The word ’smog’ is a combination of the words smoke and fog, and results from large amounts of coal burning in an area and is caused by a mixture of smoke and sulphur dioxide. This classic smog is mostly a thing of the past due to clean air acts passed around the world that limit the amount of coal burned, especially in highly populated areas. Today, the word ’smog’ generally refers to photochemical smog. This is a mixture of several compounds, although mostly consisting of tropospheric ozone (O3) and volatile organic compounds (VOCs). Smog is not generally considered an aerosol, even though it has dangerous health effects.

Aerosols, tiny solid particles suspended in the air, can have both direct and indirect effects on climate. First let’s look at the direct effect, because it’s easier to understand. Some aerosols, such as soot, are black. And like an asphalt driveway, they absorb the sun’s radiation and heat up. Other aerosols, like sulfates, are white. They reflect light like a white painted roof. Because these aerosols are near the surface, the black absorbing ones tend to heat the surface, while the white reflecting ones tend to cool the surface.

This leads us to the semi-direct effect. In order for clouds to form, they need cloud condensation nuclei (CCN) upon which to condense. If these CCN are black, they will absorb more radiation than a white CCN. The cloud particle around the black CCN will heat up and possibly evaporate the water surrounding it. The cloud particle with a white CCN will not absorb as much radiation. Therefore, clouds that form around soot and other dark particles have a tendency to “burn off” faster than their lighter colored counterparts.

There are many indirect effects of aerosols on climate; I will only talk of the first one. When a cloud is over the ocean, there are very few CCN for the water to condense onto. This is what is called a CCN-limited environment. In these situation, the water vapor still condenses, but will form fewer, and larger droplets. If a large ship were to pass under this area of CCN-limited clouds and inject it’s exhaust into the cloud, it provides a large number of CCN for the water vapor to condense. This transforms the environment from CCN-limited to water-limited. Because we have the same amount of water, but more CCN, there will be more liquid water droplets that are smaller in size. Because of the radiative properties of droplets in this size range, the smaller, more numerous droplets will have a higher albedo than the larger droplets. This can be seen in “ship tracks”. Because of the higher albedo of these regions, the aerosols tend to cool the surface.

ENSO - Temperature

I’m going to plot the Southern Oscillation Index (SOI) and the average global temperature for the last 150 years. This first plot is what you get when you plot the raw variables. It’s really messy. SOI and temperature change a lot year-to-year.

The correlation between the SOI and global temperature is -0.28, which means that the SOI explains about 8 percent of the variance in the global temperature (R²). When the data is actually plotted on the same graph, and some statistical analysis is done, it’s clear that ENSO is not responsible for the rise in global temperatures. These are the actual data, not “smoothed”, which I show below.

To aquire this graph, I used the SOI and global temperature data above. First I did a 2-year running mean, then a 4-year running mean, and finally an 8-year running mean. If I did just one of the above (ie. the 8-year mean), then the plot looks remarkably different (not shown). I plotted the negative of SOI so it would be easier to see the correlation between the variables. A better way of “smoothing” data is to use a lowpass frequency filter (again not shown). Using a frequency filter with a cutoff that corresponds to about 25-30 year produces a similar, although not exact, plot as shown in the blue curve directly above. This filtered data has a higher correlation with the temperature, both when the temperature is not-filtered (not shown) and filtered (shown above). Even with the filtering, the R² is only 0.33, not a highly significant correlation. The SOI cannot explain the temperature increase from 1920-1950, as it is actually increasing during that time; it should be decreasing if the changes in SOI were causing global warming.

An important thing to remember is that your eye is a good at picking out patterns, but that means that it does not do a good job of estimating the correlation between two time series. The human eye sees all sorts of patterns where there actually are none. Have you ever looked at the clouds and seen an animal? Obviously there isn’t a dog in the cloud, but we see a dog anyway. Another example is from 9/11. Have you seen this picture?

There isn’t a face in the cloud. There appears to be a face because our eyes pick out patterns well. And there happens to be a random pattern, caused by the turbulent eddies in the smoke, that happens to looks somewhat like a face. If that picture had been taken a second earlier or a second later, there would be no face, just smoke. The important thing to remember when comparing two things is to use a statistically rigorous method.

Previous Page

(1 votes, average: 5 out of 5)

 Loading ...

Related Posts:

Trackback URI |