ORCID Profile
0000-0001-5418-7657
Current Organisation
University of Reading
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Publisher: Society for Industrial & Applied Mathematics (SIAM)
Date: 2019
DOI: 10.1137/18M1219965
Publisher: IOP Publishing
Date: 02-04-2012
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-7336
Abstract: & & We use large deviation theory to study persistent extreme events of temperature, like heat waves or cold spells. We consider the mid-latitudes of a simplified yet Earth-like general circulation model of the atmosphere and numerically estimate large deviation rate functions of near-surface temperature averages over different spatial scales. We find that, in order to represent persistent extreme events based on large deviation theory, one has to look at temporal averages of spatially averaged observables. The spatial averaging scale is crucial, and has to correspond with the scale of the event of interest. Accordingly, the computed rate functions indicate substantially different statistical properties of temperature averages over intermediate spatial scales (larger, but still of the order of the typical scale), as compared to the ones related to any other scale. Thus, heat waves (or cold spells) can be interpreted as large deviations of temperature averaged over intermediate spatial scales. Furthermore, we find universal characteristics of rate functions, based on the equivalence of temporal, spatial, and spatio-temporal rate functions if we perform a re-normalisation by the integrated auto-correlation.& &
Publisher: The Royal Society
Date: 03-2019
Abstract: We derive Edgeworth expansions that describe corrections to the Gaussian limiting behaviour of slow–fast systems. The Edgeworth expansion is achieved using a semi-group formalism for the transfer operator, where a Duhamel–Dyson series is used to asymptotically determine the corrections at any desired order of the time-scale parameter ε . The corrections involve integrals over higher-order auto-correlation functions. We develop a diagrammatic representation of the series to control the combinatorial wealth of the asymptotic expansion in ε and provide explicit expressions for the first two orders. At a formal level, the expressions derived are valid in the case when the fast dynamics is stochastic as well as when the fast dynamics is entirely deterministic. We corroborate our analytical results with numerical simulations and show that our method provides an improvement on the classical homogenization limit which is restricted to the limit of infinite time-scale separation.
Publisher: Copernicus GmbH
Date: 28-11-2016
Abstract: Abstract. We discuss applications of a recently developed method for model reduction based on linear response theory of weakly coupled dynamical systems. We apply the weak coupling method to simple stochastic differential equations with slow and fast degrees of freedom. The weak coupling model reduction method results in general in a non-Markovian system we therefore discuss the Markovianization of the system to allow for straightforward numerical integration. We compare the applied method to the equations obtained through homogenization in the limit of large timescale separation between slow and fast degrees of freedom. We numerically compare the ensemble spread from a fixed initial condition, correlation functions and exit times from a domain. The weak coupling method gives more accurate results in all test cases, albeit with a higher numerical cost.
Publisher: AIP Publishing
Date: 02-2020
DOI: 10.1063/1.5127272
Abstract: In this paper, we examine the deviations from Gaussianity for two types of a random variable converging to a normal distribution, namely, sums of random variables generated by a deterministic discrete time map and a linearly d ed variable driven by a deterministic map. We demonstrate how Edgeworth expansions provide a universal description of the deviations from the limiting normal distribution. We derive explicit expressions for these asymptotic expansions and provide numerical evidence of their accuracy.
Publisher: Cold Spring Harbor Laboratory
Date: 28-02-2023
Abstract: The GIGYF proteins interact with 4EHP and RNA-associated proteins to elicit transcript-specific translational repression. However, the mechanism by which the GIGYF1/2–4EHP complex is recruited to its target transcripts remain unclear. Here we report the crystal structures of the GYF domains from GIGYF1 and GIGYF2 in complex with proline-rich sequences from miRISC-binding proteins TNRC6C and TNRC6A, respectively. The TNRC6 proline-rich motifs bind to a conserved array of aromatic residues on the surface of the GIGYF1/2 GYF domain, thereby bridging 4EHP to Argonaute–miRNA complexes. Our structures also reveal a phenylalanine residue conserved from yeast to human GYF domains that contributes to GIGYF2 thermostability. The molecular details we outline here are likely to be conserved between GIGYF1/2 and other RNA-binding proteins to elicit 4EHP-mediated repression in different biological contexts.
Publisher: IOP Publishing
Date: 26-10-2009
Publisher: Elsevier BV
Date: 07-2014
Publisher: Physica-Verlag HD
Date: 2006
Publisher: American Geophysical Union (AGU)
Date: 12-2014
DOI: 10.1002/2013RG000446
Publisher: Cold Spring Harbor Laboratory
Date: 20-08-2021
DOI: 10.1101/2021.08.20.457040
Abstract: The GIGYF proteins associate with 4EHP and RNA-associated proteins to elicit transcript-specific translational repression. However, the mechanism by which the GIGYF1/2-4EHP complex is recruited to its target transcripts remain unclear. Here we report the crystal structures of the GYF domains from GIGYF1 and GIGYF2 in complex with proline-rich sequences from miRISC-binding proteins TNRC6C and TNRC6A, respectively. The TNRC6 proline-rich motifs bind to a conserved array of aromatic residues on the surface of the GIGYF1/2 GYF domain, bridging 4EHP to Argonaute-miRNA mRNA targets. Our structures also reveal a phenylalanine residue conserved from yeast to human GYF domains that contributes to GIGYF2 thermostability. The molecular details we outline here are likely to be conserved between GIGYF1/2 and other RNA-binding proteins to elicit 4EHP-mediated repression in different biological contexts.
Publisher: WORLD SCIENTIFIC
Date: 10-2010
Publisher: Wiley
Date: 16-11-2022
Publisher: AIP Publishing
Date: 08-2019
DOI: 10.1063/1.5120509
Publisher: SPIE
Date: 02-03-2006
DOI: 10.1117/12.653081
Publisher: IOP Publishing
Date: 06-03-2012
Publisher: IOP Publishing
Date: 07-08-2017
Publisher: Proceedings of the National Academy of Sciences
Date: 19-12-2017
Abstract: We propose an algorithm to s le rare events in climate models with a computational cost from 100 to 1,000 times less than direct s ling of the model. Applied to the study of extreme heat waves, we estimate the probability of events that cannot be studied otherwise because they are too rare, and we get a huge ensemble of realizations of an extreme event. Using these results, we describe the teleconnection pattern for the extreme European heat waves. This method should change the paradigm for the study of extreme events in climate models: It will allow us to study extremes with higher-complexity models, to make intermodel comparison easier, and to study the dynamics of extreme events with unprecedented statistics.
Publisher: American Physical Society (APS)
Date: 08-07-2013
Publisher: American Physical Society (APS)
Date: 10-05-2013
Publisher: Educational Development Unit, University of Greenwich
Date: 12-05-2022
Abstract: In this article I give a brief overview of some of the challenges in creating accessible documents for STEM education, as well as why and how GNU TeXmacs can be used to address some of these.
Publisher: Springer Science and Business Media LLC
Date: 06-2021
DOI: 10.1007/S40766-021-00020-Z
Abstract: The climate is a complex, chaotic system with many degrees of freedom. Attaining a deeper level of understanding of climate dynamics is an urgent scientific challenge, given the evolving climate crisis. In statistical physics, many-particle systems are studied using Large Deviation Theory (LDT). A great potential exists for applying LDT to problems in geophysical fluid dynamics and climate science. In particular, LDT allows for understanding the properties of persistent deviations of climatic fields from long-term averages and for associating them to low-frequency, large-scale patterns. Additionally, LDT can be used in conjunction with rare event algorithms to explore rarely visited regions of the phase space. These applications are of key importance to improve our understanding of high-impact weather and climate events. Furthermore, LDT provides tools for evaluating the probability of noise-induced transitions between metastable climate states. This is, in turn, essential for understanding the global stability properties of the system. The goal of this review is manifold. First, we provide an introduction to LDT. We then present the existing literature. Finally, we propose possible lines of future investigations. We hope that this paper will prepare the ground for studies applying LDT to solve problems encountered in climate science and geophysical fluid dynamics.
Publisher: Springer Science and Business Media LLC
Date: 02-03-2013
Publisher: Springer Science and Business Media LLC
Date: 24-01-2014
Publisher: AIP
Date: 2009
DOI: 10.1063/1.3131288
Publisher: American Physical Society (APS)
Date: 02-04-2009
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-16406
Abstract: & & Extremes are related to high impact and serious hazard events and hence their study and prediction have been and continue to be highly relevant for all kind of applications in geoscience and beyond. Extreme value theory is promising to be able to predict them reliably and robustly. In the last fifteen years the classical extreme value theory for stochastic processes has been extended to dynamical systems and has been related to properties of physical measure (statistical properties of the system), return and hitting times. We will review what one can say for highly dimensional perfectly chaotic systems.& We will concentrate on relations between the index of the extreme distribution and invariants of the underlying dynamical system which are stable, in the sense that they will continuously depend on changing parameters in the dynamics.& Furthermore, we explore whether there exists a response theory for extremes, that is, whether the change of extremes can be quantitatilvely expressed& in terms of changing parameters.& & & & & & & &
Publisher: American Geophysical Union (AGU)
Date: 04-2023
DOI: 10.1029/2022MS003537
Abstract: We test the application of a rare event simulation (RES) algorithm to accelerate the s ling of extreme winter rainfall over Europe in a climate model. The genealogical particle analysis algorithm, an ensemble method that interrupts the simulation at intermediate times to clone realizations in which an extreme event is developing, is applied to the intermediate complexity general circulation model PlaSim. We show that the algorithm strongly reduces the numerical effort required to estimate probabilities of extremes, demonstrating the potential of RES of seasonal precipitation extremes.
Publisher: Springer Science and Business Media LLC
Date: 28-03-2012
Publisher: Elsevier BV
Date: 09-2016
Publisher: IOP Publishing
Date: 24-08-2016
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2015
End Date: 2018
Funder: European Commission
View Funded ActivityStart Date: 2014
End Date: 2016
Funder: AXA Research Fund
View Funded Activity