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Forbes co2 and temperature presentation for earth day at cua april 22 2015 ...
Forbes co2 and temperature presentation for earth day at cua april 22 2015 ...Kevin Forbes
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Extended Abstract
Introduction
While the vast majority of climate scientists have concluded that the changes in the climate over the past few decades can be attributed to human activity [Doran and Zimmerman, 2009], there has been a degree of reluctance to attribute specific weather events to elevated CO2 concentrations. For example, Coumou and Rahmstorf [2012] have noted that there has been an exceptionally high incidence of extreme weather events over the past decade and that some of the events can be linked to climate change but nevertheless concede that particular events cannot be directly attributed to global warming. Moreover, the World Meteorological Organization has noted that the incidence of extreme weather events matches IPCC projections, but qualifies this conclusion by stating that it is impossible to say that an individual weather or climate event was caused by climate change. [World Meteorological Organization, 2011, p 15]. This claim of attribution impossibility is not a minor shortcoming; it leaves the causes of extreme events open to question, allowing climate skeptics to attribute the increased incidence of extreme events to so-called natural variability. In the United States, this has undermined the political consensus necessary to adopt robust, cost-effective policies to reduce CO2 emissions.
This paper explores the relationship between CO2 and weather by addressing whether there is a causal relationship between the atmospheric concentration level of carbon dioxide and hourly temperature. The analysis begins by noting that traditional correlation analysis is not capable of addressing whether there is a causal relationship between CO2 and temperature because statistical methods alone cannot render results that establish or reject causality between two variables that are contemporaneously correlated. Nevertheless, it is possible to address the issue of causality by using more advanced statistical techniques.
An Approach to Establishing Causality
This paper addresses the issue of causality between CO2 and temperature by following the research of the Nobel Laureate Clive Granger [1969], who defined causality in terms of whether lagged values of a variable lead to more accurate predictions of some other variable. In his words, The definition of causality is based entirely on the predictability of the some series, say Xt. If some other series Yt, contains information in past terms that helps in the prediction of Xt then Yt is said to cause Xt. [Granger, 1969, p 430]. This study embraces this view of causality by examining whether lagged values of CO2 lead to more accurate forecasts of temperature. The specific approach adopted here is to exploit the diurnal nature of the variation in the hourly CO2 concentration levels by using the CO2 concentration level in hour t 24 as an explanatory variable. This variable has a 0.96 correlation with the CO2 level in hour t but i
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