A statistical model for dating uncertainties in Greenland ice core records

2021 ◽  
Author(s):  
Eirik Myrvoll-Nilsen ◽  
Niklas boers ◽  
Martin Rypdal ◽  
Keno Riechers
Keyword(s):  
Statistical Model ◽  
Gaussian Process ◽  
Ice Core ◽  
Depth Interval ◽  
Physical Processes ◽  
Proxy Records ◽  
Gaussian White Noise Process ◽  
Multivariate Gaussian ◽  
Multivariate Gaussian Process ◽  
Ice Core Records

<p>Most layer-counting based paleoclimate proxy records have non-negligible uncertainties that arise from both the proxy measurement and the dating processes. Proper knowledge of the dating uncertainties in paleoclimatic ice core records is important for a rigorous propagation to further analyses; for example for identification and dating of stadial-interstadial transitions during glacial intervals, for model-data comparisons in general, or to provide a complete uncertainty quantification of early warning signals. We develop a statistical model that incorporates the dating uncertainties of the Greenland Ice Core Chronology 2005 (GICC05), which includes the uncertainty associated with layer counting. We express the number of layers per depth interval as the sum of a structural component that represents both underlying physical processes and biases in layer counting, described by a linear regression model, and a noise component that represents the internal variation of the underlying physical processes, as well as residual counting errors. We find the residual components to be described well by a Gaussian white noise process that appear to be largely uncorrelated, allowing us to represent the dating uncertainties using a multivariate Gaussian process. This means that we can easily produce simulations as well as incorporate tie-points from other proxy records to match the GICC05 time scale to other chronologies. Moreover, this multivariate Gaussian process exhibits Markov properties which grants a substantial gain in computational efficiency.</p>

scholarly journals Quantifying dating uncertainties in layer-counted paleoclimate proxy archives

2021 ◽  
Author(s):  
Eirik Myrvoll-Nilsen ◽  
Keno Riechers ◽  
Martin Wibe Rypdal ◽  
Niklas Boers
Keyword(s):  
Ice Core ◽  
Ice Cores ◽  
Depth Interval ◽  
Physical Processes ◽  
Noise Component ◽  
Proxy Records ◽  
Complete Uncertainty ◽  
Multivariate Gaussian Process ◽  
Depth Relationship ◽  
Paleoclimate Proxy

Abstract. Paleoclimate proxy records have non-negligible uncertainties that arise from both the proxy measurement and the dating processes. Knowledge of the dating uncertainties is important for a rigorous propagation to further analyses; for example for identification and dating of stadial-interstadial transitions in Greenland ice core records during glacial intervals, for comparing the variability in different proxy archives, and for model-data comparisons in general. In this study we develop a statistical framework to quantify and propagate dating uncertainties in layer-counted proxy archives using the example of the Greenland Ice Core Chronology 2005 (GICC05). We express the number of layers per depth interval as the sum of a structured component that represents both underlying physical processes and biases in layer counting, described by a regression model, and a noise component that represents the fluctuations of the underlying physical processes, as well as unbiased counting errors. The age-depth relationship of the joint dating uncertainties can then be described by a multivariate Gaussian process from which realizations of the chronology can be sampled. We show how the effect of an unknown counting bias can be incorporated in our framework and present refined estimates of the occurrence times of Dansgaard-Oeschger events evidenced in Greenland ice cores together with a complete uncertainty quantification of these timings.

Multi-model multivariate Gaussian process modelling with correlated noises

2017 ◽  
Vol 58 ◽  
pp. 11-22 ◽  
Author(s):  
Xiaodan Hong ◽  
Biao Huang ◽  
Yongsheng Ding ◽  
Fan Guo ◽  
Lei Chen ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Process Modelling ◽  
Multivariate Gaussian ◽  
Multivariate Gaussian Process ◽  
Correlated Noises

Simulation Optimization for Computer Models With Multivariate Output

2017 ◽  
Author(s):  
Raed Kontar ◽  
Shiyu Zhou ◽  
John Horst
Keyword(s):  
Gaussian Process ◽  
Manufacturing Systems ◽  
Performance Metrics ◽  
Simulation Optimization ◽  
Process Models ◽  
Manufacturing Performance ◽  
Gaussian Process Models ◽  
Multivariate Gaussian ◽  
Potential Applicability ◽  
Multivariate Gaussian Process

This paper explores the potential of Gaussian process based Metamodels for simulation optimization with multivariate outputs. Specifically we focus on Multivariate Gaussian process models established through separable and non-separable covariance structures. We discuss the advantages and drawbacks of each approach and their potential applicability in manufacturing systems. The advantageous features of the Multivariate Gaussian process models are then demonstrated in a case study for the optimization of manufacturing performance metrics.

scholarly journals Multivariate Gaussian Process Emulators With Nonseparable Covariance Structures

Technometrics ◽  
2012 ◽  
Vol 55 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Thomas E. Fricker ◽  
Jeremy E. Oakley ◽  
Nathan M. Urban
Keyword(s):  
Gaussian Process ◽  
Covariance Structures ◽  
Multivariate Gaussian ◽  
Multivariate Gaussian Process

scholarly journals Connecting the Greenland ice-core and U / Th timescales via cosmogenic radionuclides: Testing the synchronicity of Dansgaard-Oeschger events

2018 ◽  
Author(s):  
Florian Adolphi ◽  
Christopher Bronk Ramsey ◽  
Tobias Erhardt ◽  
R. Lawrence Edwards ◽  
Hai Cheng ◽  
...  
Keyword(s):  
Climate Changes ◽  
Ice Core ◽  
Cosmogenic Radionuclides ◽  
Last Glacial Period ◽  
Temperature Changes ◽  
Proxy Records ◽  
Atmospheric Fronts ◽  
Absolute Dating ◽  
The Last Glacial ◽  
Ice Core Records

Abstract. During the last glacial period Northern Hemisphere climate was characterized by extreme and abrupt climate changes, so-called Dansgaard-Oeschger (DO) events. Most clearly observed as temperature changes in Greenland ice-core records, their climatic imprint was geographically widespread. However, the temporal relation between DO-events in Greenland and other regions is uncertain due to the chronological uncertainties of each archive, limiting our ability to test hypotheses of synchronous change. On the contrary, the assumption of direct synchrony of climate changes forms the basis of many timescales. Here, we use cosmogenic radionuclides (10Be, 36Cl, 14C) to link Greenland ice-core records to U / Th-dated speleothems, quantify offsets between both timescales, and improve their absolute dating back to 45 000 years ago. This approach allows us to test the assumption that DO-events occurred synchronously between Greenland ice-core and tropical speleothem records at unprecedented precision. We find that the onset of DO-events occurs within synchronization uncertainties in all investigated records. Importantly, we demonstrate that there remain local discrepancies in the temporal development of rapid climate change for specific events and speleothems. These may be either related to the location of proxy records relative to the shifting atmospheric fronts or to underestimated U / Th-dating uncertainties. Our study thus highlights the potential for misleading interpretations of the Earth system when applying the common practice of climate wiggle-matching.

scholarly journals A multivariate Gaussian process factor model for hand shape during reach-to-grasp movements

2015 ◽  
Author(s):  
Lucia Castellanos ◽  
Vincent Q. Vu ◽  
Sagi Perel ◽  
Andrew B. Schwartz ◽  
Robert E . Kass
Keyword(s):  
Gaussian Process ◽  
Factor Model ◽  
Reach To Grasp ◽  
Process Factor ◽  
Hand Shape ◽  
Multivariate Gaussian ◽  
Multivariate Gaussian Process

scholarly journals Isotopic diffusion in polar firn: implications for interpretation of seasonal climate parameters in ice-core records, with emphasis on central Greenland

1998 ◽  
Vol 44 (147) ◽  
pp. 273-284 ◽  
Author(s):  
Kurt M. Cuffey ◽  
Eric J. Steig
Keyword(s):  
Accumulation Rate ◽  
A Priori ◽  
Ice Core ◽  
Published Data ◽  
High Accumulation ◽  
Proxy Records ◽  
New Information ◽  
Isotopic Records ◽  
Diffusive Mixing ◽  
Ice Core Records

AbstractIf it were possible to properly extract seasonal information from ice-core isotopic records, paleoclimate researchers could retrieve a wealth of new information concerning the nature of climate changes and the meaning of trends observed in ice-core proxy records. It is widely recognized, however, that the diffusional smoothing of the seasonal record makes a “proper extraction" very difficult. In this paper, we examine the extent to which seasonal information (specifically the amplitude and shape of the seasonal cycle) is irrecoverably destroyed by diffusion in the firn. First, we show that isotopic diffusion firn is reasonably well understood. We do this by showing that a slightly modified version of the Whillans and Grootes (1985) theory makes a tenable a priori prediction of the decay of seasonal isotopic amplitudes with depth at the GISP2 site, though a small adjustment to one parameter significantly improves the prediction. Further, we calculate the amplitude decay at various other ice-core sites and show that these predictions compare favorably with published data from South Pole and locations in southern and central Greenland and the Antarctic Peninsula. We then present numerical experiments wherein synthetic ice-core records are created, diffused, sampled, reconstituted and compared to the original. These show that, alter diffusive mixing in the entire fini column, seasonal amplitudes can be reconstructed to within about 20% error in central Greenland but that all information about sub-annual signals is permanently lost there. Furthermore, most of the error in the amplitude reconstructions is due to the unknowable variations in the sub-annual signal. Finally, we explore how these results can be applied to other locations and suggest that Dye 3 has a high potential for meaningful seasonal reconstructions, while Siple Dome has no potential at all. An optimal ice-core site for seasonal reconstructions has a high accumulation rate and a low temperature.

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