Guest post by Steve Goddard
I tried an experiment which some of the null questioners may find convincing. I took all of the monthly data from 1978 to 1997, removed the volcanic affected periods, and calculated the mean. Interestingly, the mean anomaly was positive (0.03) i.e. above the mean anomaly for the 30 year period.
This provides more evidence that normalizing to null is conservative. Had I normalized to 0.03, the slope would have been reduced further.
Yesterday’s discussion raised a few questions, which I will address today.
We are all personally familiar with the idea that reduced atmospheric transparency reduces surface temperatures. On a hot summer day, a cloud passing overhead can make a marked and immediate difference in the temperature at the ground. A cloudy day can be tens of degrees cooler than a sunny day, because there is less SW radiation reaching the surface, due to lower atmospheric transparency.
Similarly, an event which puts lots of dust in the upper atmosphere can also reduce the amount of SW radiation making it to the surface. It is believed that a large meteor which struck the earth at the end of the Cretaceous, put huge amounts of dust and smoke in the upper atmosphere that kept the earth very cold for several years, leading to the extinction of the dinosaurs. Carl Sagan made popular the idea of “nuclear winter” where the fires and dust from nuclear war would cause winter temperatures to persist for several years.
Large volcanic eruptions can have a similar effects. This was observed in 1981 and 1992, when volcanic eruptions caused large drops in the measured atmospheric transmission of shortwave radiation at the Mauna Loa observatory. These eruptions lowered atmospheric transmission for several years, undoubtedly causing a significant cooling effect at the surface. At one point in late 1991, atmospheric transmission was reduced by 15%. An extended period like that would lead to catastrophically cold conditions on earth.
In recent years, there has been a lot of interest in measuring how much warming of the earth has occurred due to increased CO2 concentrations from burning fossil fuels. This is difficult to measure, but one thing we can do to improve the measurements is to filter out events which are known to be unrelated to man’s activities. Volcanoes are clearly in that category. In yesterday’s analysis, I chose to null out the years where atmospheric transparency was affected by volcanic eruptions, as seen in the image below. Atmospheric transmission is in green, and UAH satellite temperatures are in blue.
Atmospheric transmission in green. Monthly temperature deviation in blue, with overlap periods nulled out.
The question was raised, why did I null out those periods?
I made that decision because the null level is the mean deviation for the period, and because that is the most conservative approach. As you can see in the image below, there is a large standard deviation and variance from month to month, which makes other approaches extremely problematic. There were also corresponding El Ninos during both of the null periods, which would have been expected to raise the temperature significantly in the absence of the the volcanic dust. Had I attempted to adjust for the El Nino events, the reduction in slope (degrees per century) would have been greater than what I reported. This is because the temperature anomaly during each El Nino would have been greater than zero (above the null line.)
Due to the large standard deviation and large monthly variance, any attempt to calculate what the temperature “should have been” in the absence of the volcanic dust would likely introduce unsupportable error into the calculation. One can play all sorts of games based on their belief system about what the temperature should have been. I chose not to do that, and instead used the mean as the most conservative approach.
There is no question that the volcanic dust lowered temperatures during those periods, and because of that the 1.3C/century number is too high. My approach came up with 1.0. A reasonable ENSO based approach would have come up with a number much less than that. If you take nothing else away from this discussion, that is the important point.
UAH, with non-nulled temperatures in green.
Furthermore, it is also important to realize that the standard approach of reporting temperature trends as linear slopes is flawed. Climate is not linear, which is why Dr. Roy Spencer fits his UAH curves with a fourth or fifth order function, rather than a line.