Modelling current trends in Northern Hemisphere temperatures

Abstract

Fitting a trend is of interest in many disciplines, but it is of particular importance in climatology, where estimating the current and recent trend in temperature is thought to provide a major indication of the presence of global warming. A range of ad hoc methods of trend fitting have been proposed, with little consensus as to the most appropriate techniques to use. The aim of this paper is to consider a range of trend extraction techniques, none of which require 'padding' out the series beyond the end of the available observations, and to use these to estimate the trend of annual mean Northern Hemisphere (NH) temperatures. A comparison of the trends estimated by these methods thus provides a robust indication of the likely range of current trend temperature increases and hence inform, in a timely quantitative fashion, arguments based on global temperature data concerning the nature and extent of global warming and climate change. For the complete sample 1856-2003, the trend is characterised as having long waves about an underlying increasing level. Since around 1970, all techniques display a pronounced warming trend. However, they also provide a range of trend functions so that extrapolation far into the future would be a hazardous exercise.

A moving windows visual approach to analysing spatial variation in temperature trends on the Spanish mainland 1951–2010

“…All these arguments were summarized years before by Kendall et al . (), section 45.12), quoted in Mills (), when indicating that (speaking of trend) ‘… ‘long’… is a relative term, and what is long for one purpose may be short for another’. Among others, Loehle (), Liebmann et al .…”

“…Thus, de Elía et al (2014) suggest that the different spatiotemporal timescale at which climate change takes place would eventually have serious consequences for adaptation requirements, and they explored alternative ways of defining the timescale of climate change. All these arguments were summarized years before by Kendall et al (1983), section 45.12), quoted in Mills (2006), when indicating that (speaking of trend) ' … 'long'... is a relative term, and what is long for one purpose may be short for another'. Among others, Loehle (2009), Liebmann et al (2010, and Santer et al (2011) suggest that a minimum length of around 20 years should be used in climate trend analyses, because the signal/noise ratio is small (<1) in short timescales and becomes larger over longer periods (Santer et al, 2011).…”

1963: The break point of the Northern Hemisphere temperature trend during the twentieth century

“…Conventionally, it is treated as a deterministic straight line, but a number of authors investigate this issue more profoundly. The results are contradictory and vary from purely deterministic through long-memory processes to a purely stochastic nature of the non-stationarity (Gordon, 1991;Woodward and Gray, 1995;Lanzante, 1996;Rodionov, 2004;Stern and Kaufmann, 1999;Zheng and Basher, 1999;Karl et al, 2000;Fomby and Vogelsang, 2002;Seidel and Lanzante, 2004;Tomé and Miranda, 2004;Cohn and Lins, 2005;Gao and Hawthorne, 2006;Mills, 2006Mills, , 2007Gil-Alana, 2008a, 2008b.…”

Signal detection in global mean temperatures after “Paris”: an uncertainty and sensitivity analysis

“…1a; Karl et al, 2015;Rajaratnam et al, 2015), linear trends with change points (Cahill et al, 2015), binomial filters (Morice et al, 2012), splines (IPCC, 2013 -Box 2.2, Fig. b), EEMD decomposition (Wei et al, 2015;Yao et al, 2015), structural time series models (Visser and Molenaar, 1995;Mills, 2006Mills, , 2010 and long-memory trend models (Lennartz and Bunde, 2009;Rea et al, 2011). …”