Abstract
Current trends in Northern Hemisphere and Central England temperatures are estimated using a variety of statistical signal extraction and filtering techniques and their extrapolations are compared with the pre dictions from coupled atmospheric-ocean general circulation models. Ear lier warming trend epochs are also analysed and compared with the current warming trend, suggesting that the long-run patterns of temperature trends should also be considered alongside the current emphasis on global warming.
Highlights
Global warming and climate change are currently topics of major importance, with the publication of the Stern Review on the Economics of Climate Change (Stern, 2007) and the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (IPCC, 2007)
There are many ways of estimating trends, we focus here on the ’classic’ signal extraction and filtering approach of estimating the unobserved
An obvious response to such calculations is to invoke the ‘perils of extrapolation’ argument and to ask the question ‘have there been past warming patterns similar to that being observed currently that haven’t led to a continuing upward trend in temperatures?’ The NH temperature record does appear to be currently undergoing an unprecedented warming trend, so that there are no earlier periods of similarity with which to compare our current trend estimates with
Summary
Global warming and climate change are currently topics of major importance, with the publication of the Stern Review on the Economics of Climate Change (Stern, 2007) and the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (IPCC, 2007). Climate modelling and long-run temperature prediction are typically done using large scale computer simulations (see, for example, Cubasch and Meele, 2001, and Covey et al, 2003), an interesting statistical problem is to estimate recent and current trend levels of temperature using statistical signal extraction and filtering techniques. We emphasise that this approach is purely statistical and avoids the need to identify potential covariates, but as such it has the benefit of providing independent results that may be useful in informing quantitative debate on global warming.
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