Research Papers: Julien Emile-Geay

Climate models can correctly simulate the continuum of global-average temperature variability

By Feng Zhu, Julien Emile-Geay, Nicholas P. McKay, Gregory J. Hakim, Deborah Khider, Toby R. Ault, Eric J. Steig, Sylvia Dee, James W. Kirchner

Proceedings of the National Academy of Sciences of the United States of America


Measures of climate are known to exhibit scaling behavior with large exponents, resulting in larger fluctuations at longer timescales. It has been suggested that climate models underestimate these fluctuations [1-4], casting doubt on their ability to predict the amplitude of climate variability over coming decades and centuries. Using the latest simulations and data syntheses, as well as spectral methods tailored to scaling estimation, we find agreement for spectra derived from observations and models on timescales ranging from interannual to multi-millennial. Our results confirm the existence of a regime transition between orbital and annual peaks [5], occurring around millennial periodicities. That both simple and comprehensive ocean-atmosphere models can reproduce these features suggests that long-range persistence is a consequence of the oceanic integration of both gradual and abrupt climate forcings. The result implies that decadal to millennial variability over the Holocene is partly a consequence of the climate system’s integrated memory of orbital forcing. While climate models imperfectly depict some aspects of spatiotemporal variability, we find that they appear contain the essential physics to correctly simulate the temperature continuum. We hypothesize that the deep ocean plays a key role in integrating forcings, keeping a long memory of past events, and having the ability to strongly influence climate states. We therefore suggest that a critical element of successful simulations at sub-orbital scales are initial conditions of the deep ocean state that are consistent with observations of the recent past. Failing to provide such initial conditions sets the models up for failure.

Last Millennium Hurricane Activity Linked to Endogenous Climate Variability

By Julien Emile-Geay et al.

Nature Communications


Despite increased Atlantic hurricane risk, projected trends in hurricane frequency in the warming climate are still highly uncertain, mainly due to short instrumental record that limits our understanding of hurricane activity and its relationship to climate. Here we extend the record to the last millennium using two independent estimates: a reconstruction from sedimentary paleohurricane records and a statistical model of hurricane activity using sea surface temperatures (SSTs). We find statistically significant agreement between the two estimates and the late 20th century hurricane frequency is within the range seen over the past millennium. Numerical simulations using a hurricane-permitting climate model suggest that hurricane activity was likely driven by endogenous climate variability and linked to anomalous SSTs of warm Atlantic and cold Pacific. Volcanic eruptions can induce peaks in hurricane activity, but such peaks would likely be too weak to be detected in the proxy record due to large endogenous variability.

Detecting Paleoclimate Transitions With Laplacian Eigenmaps of Recurrence Matrices (LERM)

By Julien Emile-Geay et al.

Paleoceanography and Paleoclimatology


Paleoclimate records can be considered low-dimensional projections of the climate system that generated them. Understanding what these projections tell us about past climates, and changes in their dynamics, is a main goal of time series analysis on such records. Laplacian eigenmaps of recurrence matrices (LERM) is a novel technique using univariate paleoclimate time series data to indicate when notable shifts in dynamics have occurred. LERM leverages time delay embedding to construct a manifold that is mappable to the attractor of the climate system; this manifold can then be analyzed for significant dynamical transitions. Through numerical experiments with observed and synthetic data, LERM is applied to detect both gradual and abrupt regime transitions. Our paragon for gradual transitions is the Mid-Pleistocene Transition (MPT). We show that LERM can robustly detect gradual MPT-like transitions for sufficiently high signal-to-noise (S/N) ratios, though with a time lag related to the embedding process. Our paragon of abrupt transitions is the “8.2 ka” event; we find that LERM is generally robust at detecting 8.2 ka-like transitions for sufficiently high S/N ratios, though edge effects become more influential. We conclude that LERM can usefully detect dynamical transitions in paleogeoscientific time series, with the caveat that false positive rates are high when dynamical transitions are not present, suggesting the importance of using multiple records to confirm the robustness of transitions. We share an open-source Python package to facilitate the use of LERM in paleoclimatology and paleoceanography.

Links between tropical Pacific seasonal, interannual, and orbital variability during the Holocene

By Julien Emile-Geay, Kim M. Cobb, Matthieu Carré, Pascale Braconnot, Julie Leloup, Y. Zhou, S. P. Harrison, Thierry Corrège, H. V. Mcgregor, Matthew Collins, R. Driscoll, M. Elliot, B. Schneider, A. Tudhope

Nature Geocience


The El Niño/Southern Oscillation (ENSO) is the leading mode of interannual climate variability. However, it is unclear how ENSO has responded to external forcing, particularly orbitally induced changes in the amplitude of the seasonal cycle during the Holocene. Here we present a reconstruction of seasonal and interannual surface conditions in the tropical Pacific Ocean from a network of high-resolution coral and mollusc records that span discrete intervals of the Holocene. We identify several intervals of reduced variance in the 2 to 7 yr ENSO band that are not in phase with orbital changes in equatorial insolation, with a notable 64% reduction between 5,000 and 3,000 years ago. We compare the reconstructed ENSO variance and seasonal cycle with that simulated by nine climate models that include orbital forcing, and find that the models do not capture the timing or amplitude of ENSO variability, nor the mid-Holocene increase in seasonality seen in the observations; moreover, a simulated inverse relationship between the amplitude of the seasonal cycle and ENSO-related variance in sea surface temperatures is not found in our reconstructions. We conclude that the tropical Pacific climate is highly variable and subject to millennial scale quiescent periods. These periods harbour no simple link to orbital forcing, and are not adequately simulated by the current generation of models.

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