1. Introduction
According to the IPCC, “It is extremely likely that human influence has been the dominant cause of the observed increase in global temperatures since the mid-20th century “(IPCC, 2013, p. 17 ). As early as 2001, the science academies of Australia, Belgium, Brazil, Canada, the Caribbean, China, France, Germany, India, Indonesia, Ireland, Italy, Malaysia, New Zealand, Sweden, Turkey, and the United Kingdom all endorsed the IPCC’s Third Assessment ( Australian Academy of Sciences et al., 2001).A more recent list of scientific academies that have accepted this view includes the science academies in Japan, Russia, and the USA. ( National Academies of Science, 2005). These institutes are not indicating that human activity is only partly responsible for climate change. Instead, they have indicated that human activity is the dominant driver.
In the United States, a country in which a nontrivial number of climate deniers hold powerful elected positions, a group of 18 highly respected scientific organizations explicitly endorsed the scientific consensus on climate change in a 2009 letter to U.S. policymakers (American Association for the Advancement of Science, 2009). This Letter was released again in 2016 by a larger group of 31 scientific organizations (American Association for the Advancement of Science, 2016). The updated Letter makes the following point:
“Observations throughout the world make it clear that climate change is occurring, and rigorous scientific research concludes that the greenhouse gases emitted by human activities are the primary driver. This conclusion is based on multiple independent lines of evidence and the vast body of peer-reviewed science.” AAAS, 2016
This paper’s starting point is the observation that the survey data does not fully reflect the scientific consensus. This paper applies methods developed to address issues in economics and finance to assess whether the temperature data at the Barrow Atmospheric Observatory in northern Alaska supports this view. While some might sharply question the approach employed in this paper because the methodology is “unorthodox” relative to the conventional meteorological framework, it may be worth noting that the methodology applied in this paper has revolutionized the analysis in other sectors when the data are found to be autoregressive and heteroskedastic in nature. One modest example of this is Forbes and Zampelli (2019), who analyzed CO2emissions from the Irish power grid using the methods presented in this paper after observing that the emission levels had autoregressive and heteroskedastic properties. These properties will be shown to be highly relevant when modeling hourly temperature. Ignoring these properties makes extracting CO2’s “signal” from the “noisy” data almost impossible.
In terms of organization, section 2 of the paper discusses the survey data. Section 3 summarizes the views of individuals identified as being climate deniers within the scientific community. Section 4 discusses the data used in the analysis. To provide context, the trends in hourly temperature, downward total solar irradiance, and CO2concentrations at the Barrow Atmospheric Observatory are reported. In response to an assertion about a lack of recent warming relative to the pre-1940 period by Lindzen ( 2020, pp. 12-13), the annual temperature at the nearby Barrow Airport from 1921 through 2020 is reported. The time-series nature of hourly temperature at Barrow is also discussed to facilitate the modeling discussion in the remaining sections of the paper. Section 5 introduces a modeling framework to examine the possible association between CO2 concentrations and hourly temperature. Section 6 discusses the estimation process and also presents the results. Section 7 evaluates the model. The paper’s findings are discussed in section 8.