Terence Mills has a "white paper" on the Global Warming Policy Foundation Website. It predicts little future increase in temperature. Not surprisingly, The Australian has published a totally positive article about it. I commented in the comments there:
"Mills assumes that past fluctuations in temperature are purely random and of unknown causes and ignores greenhouse gases, or the sun, or volcanic eruptions, or any other specific factor that might drive climate change. He then fits simple statistical models based on this assumption to the data. Not surprisingly, if you assume that there isn't any specific factor driving the climate, your best forecast for the future is for not much change because you don't know what random shocks will show up to change the climate in the future. A more sensible approach is to test which of the various proposed drivers might actually have an effect and how large that effect has been. There are a lot of refereed academic papers that do just that including some I published myself. It's pretty easy to show that greenhouse gases have an effect on the climate, it's quite big (but fairly uncertain how big), and if emissions continue on a business as usual path there will be a lot of increase in temperature."
More technically: Mills fits univariate ARIMA models to HADCRUT, RSS global lower troposphere series (only available since 1980) and Central England Temperature series. These include models with no deterministic component (an ARIMA(0,1,3) model of HADCRUT) and a model with a deterministic trend with breakpoints chosen based on "eyeballing" the temperature graph. None of these models predicts any future warming, because there is no trend in the trendless model and because the "hiatus" means there is no recent trend in the segmented trend model. Of course, a model with just a single linear deterministic trend fitted to HADCRUT data would forecast a lot of warming in the 21st Century, though with a very wide forecast error envelope. But that model isn't estimated, for some reason...
This is a prime case of "mathiness" I think - lots of math that will look sophisticated to many people used to build a model on silly assumptions with equally silly conclusions.
In other news, my paper coauthored with Luis Sanchez on drivers of greenhouse gas emissions is now published in Ecological Economics. It is open access till 12th April.
P.S. This post was cited in the Daily Mail.
"Mills assumes that past fluctuations in temperature are purely random and of unknown causes and ignores greenhouse gases, or the sun, or volcanic eruptions, or any other specific factor that might drive climate change. He then fits simple statistical models based on this assumption to the data. Not surprisingly, if you assume that there isn't any specific factor driving the climate, your best forecast for the future is for not much change because you don't know what random shocks will show up to change the climate in the future. A more sensible approach is to test which of the various proposed drivers might actually have an effect and how large that effect has been. There are a lot of refereed academic papers that do just that including some I published myself. It's pretty easy to show that greenhouse gases have an effect on the climate, it's quite big (but fairly uncertain how big), and if emissions continue on a business as usual path there will be a lot of increase in temperature."
More technically: Mills fits univariate ARIMA models to HADCRUT, RSS global lower troposphere series (only available since 1980) and Central England Temperature series. These include models with no deterministic component (an ARIMA(0,1,3) model of HADCRUT) and a model with a deterministic trend with breakpoints chosen based on "eyeballing" the temperature graph. None of these models predicts any future warming, because there is no trend in the trendless model and because the "hiatus" means there is no recent trend in the segmented trend model. Of course, a model with just a single linear deterministic trend fitted to HADCRUT data would forecast a lot of warming in the 21st Century, though with a very wide forecast error envelope. But that model isn't estimated, for some reason...
This is a prime case of "mathiness" I think - lots of math that will look sophisticated to many people used to build a model on silly assumptions with equally silly conclusions.
In other news, my paper coauthored with Luis Sanchez on drivers of greenhouse gas emissions is now published in Ecological Economics. It is open access till 12th April.
P.S. This post was cited in the Daily Mail.
Not surprisingly, there are a lot of conferences and United Nations Framework Conventions on Climate Change conducted annually, according to a schedule! You may even read http://bigessaywriter.com/blog/climate-changing-or-main-problem-of-the-21st-century to see how significant and important this topic is!
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