Well-estimated global surface warming in climate projections selected for ENSO phase

Risbey, James S.; Lewandowsky, Stephan; Langlais, Clothilde; Monselesan, Didier; O’Kane, Terence J.; Орескес, Наоми

doi:10.1038/nclimate2310

Cited by 104 publications

(93 citation statements)

References 32 publications

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“…Such timescales are also important for those studying sea ice and other aspects of the climatology. However, on such decadal time scales future change will be dominated by natural variability of the climate system which is challenging to predict with the current climate modeling tools (Meehl et al, 2009;O'Kane et al, 2013;Risbey et al, 2014). This results in a mismatch in temporal scale between what the models can deliver and the relevant time-window for ecological considerations (Massom and Stammerjohn, 2010;Macias et al, 2013;Supplementary Table 1).…”

Section: Key Challenges and Recommendationsmentioning

confidence: 99%

“…However, Figures 3B, 4B illustrate that this narrower range is maintained in the projected sea ice spatial distribution in the late twentyfirst century. This emphasizes that model-projected future sea ice distributions (and associated variables) are highly dependent on the match between simulated and observed climatological SIE conditions (Risbey et al, 2014;Bracegirdle et al, 2015).…”

Section: Effect Of Sub-setting On Historical and Future Cmip5-derivedmentioning

confidence: 99%

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A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

et al. 2017

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Increasing concern about the impacts of climate change on ecosystems is prompting ecologists and ecosystem managers to seek reliable projections of physical drivers of change. The use of global climate models in ecology is growing, although drawing ecologically meaningful conclusions can be problematic. The expertise required to access and interpret output from climate and earth system models is hampering progress in utilizing them most effectively to determine the wider implications of climate change. To address this issue, we present a joint approach between climate scientists and ecologists that explores key challenges and opportunities for progress. As an exemplar, our focus is the Southern Ocean, notable for significant change with global implications, and on sea ice, given its crucial role in this dynamic ecosystem. We combined perspectives to evaluate the representation of sea ice in global climate models. With an emphasis on ecologically-relevant criteria (sea ice extent and seasonality) we selected a subset of eight models that reliably reproduce extant sea ice distributions. While the model subset shows a similar mean change to the full ensemble in sea ice extent (approximately 50% decline in winter and 30% decline in summer), there is a marked reduction in the range. This improved the precision of projected future sea ice distributions by approximately one third, and means they are more amenable to ecological interpretation. We conclude that careful multidisciplinary evaluation of climate models, in conjunction with ongoing modeling advances, should form an integral part of utilizing model output.

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Section: Key Challenges and Recommendationsmentioning

confidence: 99%

Section: Effect Of Sub-setting On Historical and Future Cmip5-derivedmentioning

confidence: 99%

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

et al. 2017

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“…We argue that to put potential trend discrepancies into appropriate context, all overlapping trends over the longest available record of tropical tropospheric temperatures must 10.1002/2017GL073798 be analyzed [Thorne et al, 2007;Risbey et al, 2014;Marotzke and Forster, 2015]. Radiosonde-based data sets offer the longest available record and therefore are used in our study.…”

Section: Introductionmentioning

confidence: 99%

Internal variability in simulated and observed tropical tropospheric temperature trends

Suárez-Gutiérrez

Thorne

et al. 2017

Geophysical Research Letters

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We explore the extent to which internal variability can reconcile discrepancies between observed and simulated warming in the upper tropical troposphere. We compare all extant radiosonde‐based estimates for the period 1958–2014 to simulations from the Coupled Model Intercomparison Project phase 5 multimodel ensemble and the 100 realization Max Planck Institute large ensemble. We consider annual mean temperatures and all available 30‐and 15‐year trends. Most observed trends fall within the ensemble spread for most of the record, and trends calculated over 15‐year periods show better agreement than 30‐year trends, with generally larger discrepancies for the older observational products. The simulated amplification of surface warming aloft in the troposphere is consistent with observations, and the linear correlation between surface and simultaneous tropospheric warming trends decreases with trend length. We conclude that trend differences between observations and simulations of tropical tropospheric temperatures are dominated by observational uncertainty and chaotic internal variability rather than by systematic errors in model performance.

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“…These range from a high, business-as-usual, scenario (RCP8.5), two intermediate scenarios with maximum emissions occurring around 2080 (RCP6.0) and 2040 (RCP4.5), and a low-emission scenario (RCP2.6). RCP2.6 is constructed to be in line with the so-called two-degree target (Rijsberman and Swart 1990;Jaeger and Jaeger 2011). The observed CO 2 -emissions indicate that we are currently tracking the RCP 8.5 scenario (Quéré et al 2014).…”

Section: Global Temperature Variationsmentioning

confidence: 99%

“…This paradox has generated a lot of attention among researchers (e.g., Easterling and Wehner 2009;Foster and Rahmstorf 2011;Katsman and van Oldenborgh 2011;Santer et al 2011Santer et al , 2014Trenberth and Fasullo 2013;Huber and Knutti 2014;Maher et al 2014;Risbey et al 2014;Watanabe et al 2014) and the general public (Tollefson 2014). It has also been used to cast doubts about the reliability of climate research in general and climate models in particular (Showstack 2014) since the ensemble mean of the models do not reproduce the so-called surface temperature hiatus.…”

Section: Motivationmentioning

confidence: 99%

Global and regional surface cooling in a warming climate: a multi-model analysis

Medhaug

Drange

2015

Clim Dyn

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to variations in global surface temperature. The likelihood of decadal-scale non-warming periods decrease with global warming, firstly at the low latitude region stretching eastward from the tropical Atlantic towards the western Pacific. The North Atlantic and Southern Oceans have largest likelihood of non-warming decades in a warming world. Keywords Hiatus · CMIP5 · Global warming · Decadal variability MotivationA central issue in climate research in recent years has been the apparent paradox that global surface temperature has not been increasing in tandem with increasing emissions of human-induced greenhouse gases. This paradox has generated a lot of attention among researchers (e.g., Easterling and Wehner 2009;Foster and Rahmstorf 2011;Katsman and van Oldenborgh 2011;Santer et al. 2011Santer et al. , 2014Trenberth and Fasullo 2013;Huber and Knutti 2014;Maher et al. 2014;Risbey et al. 2014;Watanabe et al. 2014) and the general public (Tollefson 2014). It has also been used to cast doubts about the reliability of climate research in general and climate models in particular (Showstack 2014) since the ensemble mean of the models do not reproduce the so-called surface temperature hiatus.A large suite of possible factors influencing the recent hiatus in the global surface temperature have been identified, including: the possibility of too-high model sensitivity to increased greenhouse gas (GHG) forcing (Flato et al. 2013); decadal-scale ocean uptake and storage of heat in the Pacific Ocean (e.g., Meehl et al. 2011;Kosaka and Xie 2013;Meehl et al. 2013;Trenberth and Fasullo 2013;England et al. 2014;Hu et al. 2015), in the Atlantic Ocean Abstract Instrumental temperature records show that the global climate may experience decadal-scale periods without warming despite a long-term warming trend. We analysed 17 global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5), identifying the likelihood and duration of periods without warming in the four Representative Concentration Pathway (RCP) scenarios RCP2.6, RCP4.5, RCP6.0 and RCP8.5, together with the preindustrial control and historical simulations. We find that non-warming periods may last 10, 15 and 30 years for RCP8.5, RCP6.0 and RCP4.5, respectively. In the models, anomalous ocean heat uptake and storage are the main factors explaining the decadalscale surface temperature hiatus periods. The low-latitude East Pacific Ocean is a key region for these variations, acting in tandem with basin-scale anomalies in the sea level pressure. During anomalously cold decades, roughly 35-50 % of the heat anomalies in the upper 700 m of the ocean are located in the Pacific Ocean, and 25 % in the Atlantic Ocean. Decadal-scale ocean heat anomalies, integrated over the upper 700 m, have a magnitude of about 7.5 × 10 21 J. This is comparable to the ocean heat uptake needed to maintain a 10 year period without increasing surface temperature under global warming. On sub-decadal time scales the Atlantic, Pacific and Southern Oceans all have the a...

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Well-estimated global surface warming in climate projections selected for ENSO phase

Cited by 104 publications

References 32 publications

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

A Synergistic Approach for Evaluating Climate Model Output for Ecological Applications

Internal variability in simulated and observed tropical tropospheric temperature trends

Global and regional surface cooling in a warming climate: a multi-model analysis

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