Change points of global temperature

Cahill, Niamh; Rahmstorf, Stefan; Parnell, Andrew C.

doi:10.1088/1748-9326/10/8/084002

Cited by 97 publications

(103 citation statements)

References 13 publications

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“…Taken together, the statistical evidence presented here and elsewhere (Cahill et al 2015;Foster and Abraham 2015) shows that the pause period is comparable in statistical terms with other recent fluctuations. Any exceedance of the z score of the pause period compared to other fluctuations, if it exists, is marginal and depends on the details of which dataset is used and precisely what time window is used to assess the pause.…”

supporting

confidence: 88%

“…Two analyses of the GMST time series have failed to find any statistical evidence for a slowdown (Foster and Abraham 2015), or a distinct changepoint in the rate of warming (Cahill et al 2015). There have also been questions about biases in some datasets used to identify a potential pause (Cowtan and Way 2014;Karl et al 2015).…”

mentioning

confidence: 99%

“…The choice of period marking the longer-term trend is necessarily somewhat arbitrary. The year 1970 has been statistically identified as an approximate marker of an upsurge in the rate of global warming on multidecadal time scales (Cahill et al 2015). This longer-term trend has been estimated at 0.17 K decade −1 (Cowtan and Way 2014;Karl et al 2015) or 0.16 K decade −1 [National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies Surface (GISS) Temperature Analysis (GISTEMP; Hansen et al 2010) and the Met Office's Hadley Centre/Climatic Research Unit, version 4 (HadCRUT4; Morice et al 2012)].…”

mentioning

confidence: 99%

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The “Pause” in Global Warming: Turning a Routine Fluctuation into a Problem for Science

Lewandowsky

Risbey

Орескес

2016

Bulletin of the American Meteorological Society

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There has been much recent published research about a putative “pause” or “hiatus” in global warming. We show that there are frequent fluctuations in the rate of warming around a longer-term warming trend, and that there is no evidence that identifies the recent period as unique or particularly unusual. In confirmation, we show that the notion of a pause in warming is considered to be misleading in a blind expert test. Nonetheless, the most recent fluctuation about the longer-term trend has been regarded by many as an explanatory challenge that climate science must resolve. This departs from long-standing practice, insofar as scientists have long recognized that the climate fluctuates, that linear increases in CO2 do not produce linear trends in global warming, and that 15-yr (or shorter) periods are not diagnostic of long-term trends. We suggest that the repetition of the “warming has paused” message by contrarians was adopted by the scientific community in its problem-solving and answer-seeking role and has led to undue focus on, and mislabeling of, a recent fluctuation. We present an alternative framing that could have avoided inadvertently reinforcing a misleading claim.

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supporting

confidence: 88%

mentioning

confidence: 99%

mentioning

confidence: 99%

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The “Pause” in Global Warming: Turning a Routine Fluctuation into a Problem for Science

Lewandowsky

Risbey

Орескес

2016

Bulletin of the American Meteorological Society

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“…The EIV-IGP model was applied to this dataset. To complement results from the EIV-IGP model, we also used change-point analysis (Carlin et al, 1992;Cahill et al, 2015b) The number and timing of change points is estimated quantitatively and with uncertainty from the RSL data. Deviance information criterion (Spiegelhalter et al, 2002) combined with parameter convergence checks were used to detect the appropriate number of change points.…”

mentioning

confidence: 99%

Relative sea-level trends in New York City during the past 1500 years

et al. 2017

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foraminifera, salt marsh, Bayesian transfer function, carbon isotope, The Bronx, sedimentation Abstract: New York City is at risk from 21st century relative sea-level rise because it is likely to experience a regional trend that exceeds the global mean and has high concentrations of low-lying infrastructure and socio economic activity. To provide a long-term context for anticipated future trends, we reconstructed relative sea-level change during the past ~1500 years using a sediment core from a salt marsh at Pelham Bay in The Bronx. Foraminifera and bulk sediment δ13C values were used as sea level indicators, while the history of sediment accumulation was established by radiocarbon dating of plant macrofossils and recognition of pollution and land-use trends of known age in down-core elemental, isotopic, and pollen profiles. The reconstruction was generated within a Bayesian hierarchical model comprised of three modules (calibration, chronology, and process) to accommodate multiple proxies and to provide a unified statistical framework for quantifying uncertainty. We show that relative sea level in New York City rose by ~1.70 m since ~575 CE, of which ~0.38 m occurred after 1850 CE. The rate of relative sea level rise increased markedly between 1852 CE and 1911 CE, which coincides with other reconstructions along the U.S. Atlantic coast. A regional tidal model was used to investigate the possible influence of tidal-range change in Long Island Sound on our reconstruction and we demonstrate that this effect was likely small. However, future tidal-range change could http://mc.manuscriptcentral.com/holocene approximately mean high water (MHW) and mean higher high water (MHHW; e.g., van de Plassche, 1991;Redfield, 1972; Johnson and York, 1915). At the boundary between the salt marsh and surrounding, upland forest is a narrow vegetative zone dominated by Phragmites australis. This zone is found above the MHHW tidal datum. Peat forming in this environment is typically a black, amorphous organic matrix that hosts the rhizomes of Phragmites australis plants (e.g., Niering et al., 1977). Through time these rhizomes are commonly flattened and degraded, resulting in a homogenized peat. The halotype of Phragmites found on and around modern salt marshes in the northeastern United States is invasive, although native haloptypes existed prior to European colonization in this region (Saltonstall, 2002). Elsewhere this uppermost zone of marine influence may also be occupied by Schoeneplectus spp., Typha spp., and/or Iva fructescens. We estimated the great diurnal tidal range (mean lower low water, MLLW to MHHW) at the site to be 2.44 m using the VDatum Harbor and Long Island Sound. METHODS Core collection and levelingThe sediment beneath the Pelham Bay salt marsh was described from hand-driven cores collected along two transects ( Figure 1C, D). Core PBA-4 was selected for detailed analysis because it included the thickest accumulation of peat and was therefore anticipated to provide the longest RSL record and adequate materia...

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“…Other trend models are OLS linear trends with varying sample periods (IPCC, 2013 -Box 2.2, Fig. 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).…”

Section: Appendix A: An Overview Of Trend Methods Applied To Gmst Obmentioning

confidence: 99%

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

et al. 2018

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Abstract. In December 2015, 195 countries agreed in Paris to "hold the increase in global mean surface temperature (GMST) well below 2.0 • C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 • C". Since large financial flows will be needed to keep GMSTs below these targets, it is important to know how GMST has progressed since pre-industrial times. However, the Paris Agreement is not conclusive as regards methods to calculate it. Should trend progression be deduced from GCM simulations or from instrumental records by (statistical) trend methods? Which simulations or GMST datasets should be chosen, and which trend models? What is "pre-industrial" and, finally, are the Paris targets formulated for total warming, originating from both natural and anthropogenic forcing, or do they refer to anthropogenic warming only? To find answers to these questions we performed an uncertainty and sensitivity analysis where datasets and model choices have been varied. For all cases we evaluated trend progression along with uncertainty information. To do so, we analysed four trend approaches and applied these to the five leading observational GMST products. We find GMST progression to be largely independent of various trend model approaches. However, GMST progression is significantly influenced by the choice of GMST datasets. Uncertainties due to natural variability are largest in size. As a parallel path, we calculated GMST progression from an ensemble of 42 GCM simulations. Mean progression derived from GCM-based GMSTs appears to lie in the range of trend-dataset combinations. A difference between both approaches appears to be the width of uncertainty bands: GCM simulations show a much wider spread. Finally, we discuss various choices for pre-industrial baselines and the role of warming definitions. Based on these findings we propose an estimate for signal progression in GMSTs since pre-industrial.

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Change points of global temperature

Cited by 97 publications

References 13 publications

The “Pause” in Global Warming: Turning a Routine Fluctuation into a Problem for Science

The “Pause” in Global Warming: Turning a Routine Fluctuation into a Problem for Science

Relative sea-level trends in New York City during the past 1500 years

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

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