Probing the timescale dependency of local and global variations in surface air temperature from climate simulations and reconstructions of the last millennia

Ellerhoff, Beatrice; Rehfeld, Kira

doi:10.1103/physreve.104.064136

Cited by 7 publications

(25 citation statements)

References 105 publications

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“…Our results provide crucial insights into the discrepancy between modeled and reconstructed local, long‐term variability (Ellerhoff & Rehfeld, 2021; Laepple & Huybers, 2014a). Internal variability dominates the local temperature variance on annual to decadal scales (Goosse et al., 2005), but contributions from natural forcing are detectable beyond decadal timescales (Figure 3), increasing variance on longer timescales.…”

Section: Discussionmentioning

confidence: 86%

“…Including natural forcing in simulations improved model‐data agreement of local variability on multidecadal and multicentennial scales (Figure 4). This is perhaps surprising given that the forcing has no centennial scale variability (Ellerhoff & Rehfeld, 2021). There is no change in agreement from interannual to decadal timescales, implying that the gain from forcing on local temperatures is small on these short timescales.…”

Section: Discussionmentioning

confidence: 99%

“…We use variance ratios, as in Laepple and Huybers (2014b), Rehfeld et al. (2018) and Ellerhoff and Rehfeld (2021), to compare model simulations and observational data. First, observation and proxy data are interpolated onto an equidistant time axis of the same mean resolution as the raw signal.…”

Section: Methodsmentioning

confidence: 99%

“…The paleoclimate record is crucial to assess whether a colder planet is more sensitive to natural forcing than a warmer one. Yet, temperature variability shows a mismatch between paleoclimate simulations and proxy data on the decadal‐to‐multicentennial scale (Ellerhoff & Rehfeld, 2021; Laepple & Huybers, 2014a). Despite major efforts, such as the Paleoclimate Modeling Intercomparison Project (PMIP; Braconnot et al., 2012; Kageyama et al., 2018), this discrepancy remains unresolved.…”

Section: Introductionmentioning

confidence: 99%

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Contrasting State‐Dependent Effects of Natural Forcing on Global and Local Climate Variability

Ellerhoff

Kirschner

Ziegler

et al. 2022

Geophysical Research Letters

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Climate variability, that is variations in the statistics of climate parameters, characterizes Earth's dynamical system and is the primary influence on extreme events (Katz & Brown, 1992). Variability arises from unforced processes, internal to the climate system, and from forced processes, caused by external natural and anthropogenic drivers. Natural drivers include volcanic and solar forcing, contributing significantly to climate variability (Crowley & Unterman, 2013b). Due to anthropogenic activities, the recent trend of global mean surface temperature (GMST) and other variables has clearly emerged beyond the range of natural variability (

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Section: Discussionmentioning

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Contrasting State‐Dependent Effects of Natural Forcing on Global and Local Climate Variability

Ellerhoff

Kirschner

Ziegler

et al. 2022

Geophysical Research Letters

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“…External sources include changes in radiative forcing, for example, from solar irradiance, volcanic eruptions, and greenhouse gases. Despite a general agreement of the total simulated and observed GMST variability over the Common Era (0-2000 CE) 2,3 , uncertainties remain about the mechanisms and magnitude of internal and external variations [4][5][6] , especially on decadal to centennial timescales 3,7 .…”

Section: Introductionmentioning

confidence: 99%

Separating internal and externally-forced contributions to global temperature variability using a Bayesian stochastic energy balance framework

Schillinger,

Ellerhoff,

Scheichl

et al. 2022

Preprint

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The 2021 “Complex Systems” Nobel Prize: The Climate, With and Without Geocomplexity

Lovejoy

2022

AGU Advances

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This year's physics Nobel prize marks history as the first for geophysics since 1947 when Edward Appleton won it for ionospheric research. Half-shared by statistical physicist Georgio Parisi and half by climate scientists Syukoro Manabe and Klauss Hasselmann, the prize was nominally for "complex systems," yet the two halves of the work were so disparate that at least one of the winners (Manabe) reportedly confessed to never having heard of another (Parisi). Ironically, Parisi's important contribution to multifractals was not even mentioned in the committee's 18 page report (Nobel Committee for Physics, 2021) in spite of its significant atmospheric and climate applications (see below). In addition, nonagenarians Manabe and Hasselmann were honored primarily for work in the 1960s and 1970s-before the Nonlinear revolution and before complexity science even existed. In this commentary, I focus on the climate half of the prize giving a succinct update on complexity applied to geoscience: geocomplexity.Complexity science in general-and geocomplexity in particular-emerged in the wake of the 1980s nonlinear revolution: notably deterministic chaos, fractals, nonlinear waves, self organized criticality and somewhat later, network theory. Complexity physics took shape in the 1990s (see the review, Nicolis & Nicolis, 2012) whereas nonlinear geoscience can be roughly dated from the workshops on Nonlinear VAriability in Geophysics (NVAG 1-4, 1986(NVAG 1-4, -1997, the establishment of the Nonlinear Processes division at the European Geophysical Society (now European Geophysical Union, EGU, 1989), the Nonlinear Geophysics focus group at the American Geophysical Union (AGU, 1997) and in 2009, an AGU session with accompanying geocomplexity workshop (Lovejoy et al., 2009). Recently, a group of AGU and EGU geocomplexity scientists collaborated in the establishment of the ongoing Climate Variability Across-Scales working group of PAGES (

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Probing the timescale dependency of local and global variations in surface air temperature from climate simulations and reconstructions of the last millennia

Cited by 7 publications

References 105 publications

Contrasting State‐Dependent Effects of Natural Forcing on Global and Local Climate Variability

Contrasting State‐Dependent Effects of Natural Forcing on Global and Local Climate Variability

Separating internal and externally-forced contributions to global temperature variability using a Bayesian stochastic energy balance framework

The 2021 “Complex Systems” Nobel Prize: The Climate, With and Without Geocomplexity

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