Publications
98 results found
Cotter C, Crisan D, Holm D, et al., 2020, Data Assimilation for a Quasi-Geostrophic Model with Circulation-Preserving Stochastic Transport Noise, Publisher: SPRINGER
Gibson T, Mitchell L, Ham D, et al., 2020, Slate: extending Firedrake's domain-specific abstraction to hybridized solvers for geoscience and beyond, Geoscientific Model Development, Vol: 13, Pages: 735-761, ISSN: 1991-959X
Within the finite element community, discontinuous Galerkin (DG) and mixed finite element methods have becomeincreasingly popular in simulating geophysical flows. However, robust and efficient solvers for the resulting saddle-point andelliptic systems arising from these discretizations continue to be an on-going challenge. One possible approach for addressingthis issue is to employ a method known as hybridization, where the discrete equations are transformed such that classic staticcondensation and local post-processing methods can be employed. However, it is challenging to implement hybridization as performant parallel code within complex models, whilst maintaining separation of concerns between applications scientistsand software experts. In this paper, we introduce a domain-specific abstraction within the Firedrake finite element library thatpermits the rapid execution of these hybridization techniques within a code-generating framework. The resulting frameworkcomposes naturally with Firedrake’s solver environment, allowing for the implementation of hybridization and static condensa-tion as runtime-configurable preconditioners via the Python interface to PETSc, petsc4py. We provide examples derived from second order elliptic problems and geophysical fluid dynamics. In addition, we demonstrate that hybridization shows greatpromise for improving the performance of solvers for mixed finite element discretizations of equations related to large-scalegeophysical flows.
Wimmer GA, Cotter CJ, Bauer W, 2020, Energy conserving upwinded compatible finite element schemes for the rotating shallow water equations, JOURNAL OF COMPUTATIONAL PHYSICS, Vol: 401, ISSN: 0021-9991
Melvin T, Benacchio T, Shipway B, et al., 2019, A mixed finite-element, finite-volume, semi-implicit discretisation for atmospheric dynamics: Cartesian geometry, Quarterly Journal of the Royal Meteorological Society, Vol: 145, Pages: 2835-2853, ISSN: 0035-9009
To meet the challenges posed by future generations of massively parallel supercomputers a reformulation of the dynamical core for the Met Office’s weather and climate model is presented. This new dynamical core uses explicit finite‐volume type discretisations for the transport of scalar fields coupled with an iterated‐implicit, mixed finite‐element discretisation for all other terms. The target model aims to maintain the accuracy, stability and mimetic properties of the existing Met Office model independent of the chosen mesh while improving the conservation properties of the model. This paper details that proposed formulation and, as a first step towards complete testing, demonstrates its performance for a number of test cases in (the context of) a Cartesian domain. The new model is shown to produce similar results to both the existing semi‐implicit semi‐Lagrangian model used at the Met Office and other models in the literature on a range of bubble tests and orographically forced flows in two and three dimensions.
Bendall TM, Cotter CJ, Shipton J, 2019, The 'recovered space' advection scheme for lowest-order compatible finite element methods, JOURNAL OF COMPUTATIONAL PHYSICS, Vol: 390, Pages: 342-358, ISSN: 0021-9991
Cotter C, Crisan D, Holm DD, et al., 2019, A Particle Filter for Stochastic Advection by Lie Transport (SALT): A case study for the damped and forced incompressible 2D Euler equation, Publisher: arXiv
In this work, we apply a particle filter with three additional procedures(model reduction, tempering and jittering) to a damped and forcedincompressible 2D Euler dynamics defined on a simply connected bounded domain.We show that using the combined algorithm, we are able to successfullyassimilate data from a reference system state (the ``truth") modelled by ahighly resolved numerical solution of the flow that has roughly $3.1\times10^6$degrees of freedom for $10$ eddy turnover times, using modest computationalhardware. The model reduction is performed through the introduction of a stochasticadvection by Lie transport (SALT) model as the signal on a coarser resolution.The SALT approach was introduced as a general theory using a geometricmechanics framework from Holm, Proc. Roy. Soc. A (2015). This work follows onthe numerical implementation for SALT presented by Cotter et al, SIAMMultiscale Model. Sim. (2019) for the flow in consideration. The modelreduction is substantial: The reduced SALT model has $4.9\times 10^4$ degreesof freedom. Forecast reliability and estimated asymptotic behaviour of the particlefilter are also presented.
Cotter CJ, Cullen MJP, 2019, PARTICLE RELABELLING SYMMETRIES AND NOETHER'S THEOREM FOR VERTICAL SLICE MODELS, Publisher: AMER INST MATHEMATICAL SCIENCES-AIMS
Cotter CJ, Cullen MJP, 2019, Particle relabelling symmetries and Noether's theorem for vertical slice models, Journal of Geometric Mechanics, Vol: 11, Pages: 139-151, ISSN: 1941-4889
We consider the variational formulation for vertical slice models introduced in Cotter and Holm (Proc RoySoc, 2013). These models have a Kelvin circulation theorem that holds on all materially-transported closedloops, not just those loops on isosurfaces of potential temperature. Potential vorticity conservation can bederived directly from this circulation theorem. In this paper, we show that this property is due to these modelshaving a relabelling symmetry for every single diffeomorphism of the vertical slice that preserves the density, notjust those diffeomorphisms that preserve the potential temperature. This is developed using the methodologyof Cotter and Holm (Foundations of Computational Mathematics, 2012).
Cotter C, Cotter S, Russell P, 2019, Ensemble transport adaptive importance sampling, SIAM/ASA Journal on Uncertainty Quantification, Vol: 7, Pages: 444-471, ISSN: 2166-2525
Markov chain Monte Carlo methods are a powerful and commonly used family ofnumerical methods for sampling from complex probability distributions. As applications of thesemethods increase in size and complexity, the need for efficient methods increases. In this paper, wepresent a particle ensemble algorithm. At each iteration, an importance sampling proposal distri-bution is formed using an ensemble of particles. A stratified sample is taken from this distributionand weighted under the posterior, a state-of-the-art ensemble transport resampling method is thenused to create an evenly weighted sample ready for the next iteration. We demonstrate that thisensemble transport adaptive importance sampling (ETAIS) method outperforms MCMC methodswith equivalent proposal distributions for low dimensional problems, and in fact shows better thanlinear improvements in convergence rates with respect to the number of ensemble members. We alsointroduce a new resampling strategy, multinomial transformation (MT), which while not as accurateas the ensemble transport resampler, is substantially less costly for large ensemble sizes, and canthen be used in conjunction with ETAIS for complex problems. We also focus on how algorithmicparameters regarding the mixture proposal can be quickly tuned to optimise performance. In partic-ular, we demonstrate this methodology’s superior sampling for multimodal problems, such as thosearising from inference for mixture models, and for problems with expensive likelihoods requiring thesolution of a differential equation, for which speed-ups of orders of magnitude are demonstrated.Likelihood evaluations of the ensemble could be computed in a distributed manner, suggesting thatthis methodology is a good candidate for parallel Bayesian computations.
Cotter CJ, Crisan D, Holm DD, et al., 2019, Numerically modelling stochastic lie transport in fluid dynamics, SIAM Journal on Scientific Computing, Vol: 17, Pages: 192-232, ISSN: 1064-8275
We present a numerical investigation of stochastic transport in ideal fluids.According to Holm (Proc Roy Soc, 2015) and Cotter et al. (2017), the principlesof transformation theory and multi-time homogenisation, respectively, imply aphysically meaningful, data-driven approach for decomposing the fluid transportvelocity into its drift and stochastic parts, for a certain class of fluidflows. In the current paper, we develop new methodology to implement thisvelocity decomposition and then numerically integrate the resulting stochasticpartial differential equation using a finite element discretisation forincompressible 2D Euler fluid flows. The new methodology tested here is foundto be suitable for coarse graining in this case. Specifically, we performuncertainty quantification tests of the velocity decomposition of Cotter et al.(2017), by comparing ensembles of coarse-grid realisations of solutions of theresulting stochastic partial differential equation with the "true solutions" ofthe deterministic fluid partial differential equation, computed on a refinedgrid. The time discretization used for approximating the solution of thestochastic partial differential equation is shown to be consistent. We includecomprehensive numerical tests that confirm the non-Gaussianity of the streamfunction, velocity and vorticity fields in the case of incompressible 2D Eulerfluid flows.
Goss ZL, Piggott MD, Kramer SC, et al., 2019, Competition effects between nearby tidal turbine arrays—optimal design for alderney race, Pages: 255-262
© 2019 Taylor & Francis Group, London. Tidal renewable energy can be described as a fledgling industry, with the world’s pilot tidal stream turbine array only recently installed. Full-sized arrays will be developed if they prove their economic, engineering and environmental viability. Reliable numerical tools are needed to optimise power yields in arrays of potentially hundreds of turbines and assess viability of new sites and designs. To demonstrate our capability to optimise the number of turbines and their spatial distribution in a region, we focus on a test case based upon the Alderney Race. The site contains the majority of the Channel Islands resource with plans from both France and Alderney to develop adjacent arrays that could impact on each other. We present a shallow-water model of the English Channel using the Thetis ocean model. Together with the hydrodynamics modelling we employ adjoint technology to optimise the micrositing of turbines for a set of scenarios.
Gibson T, McRae ATT, Cotter C, et al., 2019, Compatible finite element methods for geophysical flows: Automation and implementation using Firedrake, Publisher: Springer International Publishing, ISBN: 9783030239565
This book introduces recently developed mixed finite element methods for large-scale geophysical flows that preserve essential numerical properties for accurate simulations. The methods are presented using standard models of atmospheric flows and are implemented using the Firedrake finite element library. Examples guide the reader through problem formulation, discretisation, and automated implementation.The so-called “compatible” finite element methods possess key numerical properties which are crucial for real-world operational weather and climate prediction. The authors summarise the theory and practical implications of these methods for model problems, introducing the reader to the Firedrake package and providing open-source implementations for all the examples covered.Students and researchers with engineering, physics, mathematics, or computer science backgrounds will benefit from this book. Those readers who are less familiar with the topic are provided with an overview of geophysical fluid dynamics.
Budd CJ, McRae ATT, Cotter CJ, 2018, The scaling and skewness of optimally transported meshes on the sphere, Journal of Computational Physics, Vol: 375, Pages: 540-564, ISSN: 0021-9991
In the context of numerical solution of PDEs, dynamic mesh redistribution methods (r-adaptive methods) are an important procedure for increasing the resolution in regions of interest, without modifying the connectivity of the mesh. Key to the success of these methods is that the mesh should be sufficiently refined (locally) and flexible in order to resolve evolving solution features, but at the same time not introduce errors through skewness and lack of regularity. Some state-of-the-art methods are bottom-up in that they attempt to prescribe both the local cell size and the alignment to features of the solution. However, the resulting problem is overdetermined, necessitating a compromise between these conflicting requirements. An alternative approach, described in this paper, is to prescribe only the local cell size and augment this an optimal transport condition to provide global regularity. This leads to a robust and flexible algorithm for generating meshes fitted to an evolving solution, with minimal need for tuning parameters. Of particular interest for geophysical modelling are meshes constructed on the surface of the sphere. The purpose of this paper is to demonstrate that meshes generated on the sphere using this optimal transport approach have good a-priori regularity and that the meshes produced are naturally aligned to various simple features. It is further shown that the sphere's intrinsic curvature leads to more regular meshes than the plane. In addition to these general results, we provide a wide range of examples relevant to practical applications, to showcase the behaviour of optimally transported meshes on the sphere. These range from axisymmetric cases that can be solved analytically to more general examples that are tackled numerically. Evaluation of the singular values and singular vectors of the mesh transformation provides a quantitative measure of the mesh anisotropy, and this is shown to match analytic predictions.
Shipton J, Gibson TH, Cotter CJ, 2018, Higher-order compatible finite element schemes for the nonlinear rotating shallow water equations on the sphere, Journal of Computational Physics, Vol: 375, Pages: 1121-1137, ISSN: 0021-9991
We describe a compatible finite element discretisation for the shallow waterequations on the rotating sphere, concentrating on integrating consistentupwind stabilisation into the framework. Although the prognostic variables are velocity and layer depth, the discretisation has a diagnostic potentialvorticity that satisfies a stable upwinded advection equation through aTaylor-Galerkin scheme; this provides a mechanism for dissipating enstrophy at the gridscale whilst retaining optimal order consistency. We also use upwind discontinuous Galerkin schemes for the transport of layer depth. These transport schemes are incorporated into a semi-implicit formulation that is facilitated by a hybridisation method for solving the resulting mixed Helmholtz equation. We illustrate our discretisation with some standard rotating sphere test problems.
Cotter CJ, Graber PJ, Kirby RC, 2018, Mixed finite elements for global tide models with nonlinear damping, Numerische Mathematik, Vol: 140, Pages: 963-991, ISSN: 0029-599X
We study mixed finite element methods for the rotating shallow waterequations with linearized momentum terms but nonlinear drag. By means of anequivalent second-order formulation, we prove long-time stability of the systemwithout energy accumulation. We also give rates of damping in unforced systemsand various continuous dependence results on initial conditions and forcingterms. \emph{A priori} error estimates for the momentum and free surfaceelevation are given in $L^2$ as well as for the time derivative and divergenceof the momentum. Numerical results confirm the theoretical results regardingboth energy damping and convergence rates.
Bendall TM, Cotter CJ, Statistical properties of an enstrophy conserving finite element discretisation for the stochastic quasi-geostrophic equation, Geophysical and Astrophysical Fluid Dynamics, Vol: 113, Pages: 491-504, ISSN: 0309-1929
A framework of variational principles for stochastic fluid dynamics was presented by Holm (2015), and these stochastic equations were also derived by Cotter et al. (2017). We present a conforming finite element discretisation for the stochastic quasi-geostrophic equation that was derived from this framework. The discretisation preserves the first two moments of potential vorticity, i.e. the mean potential vorticity and the enstrophy. Following the work of Dubinkina and Frank (2007), who investigated the statistical mechanics of discretisations of the deterministic quasi-geostrophic equation, we investigate the statistical mechanics of our discretisation of the stochastic quasi-geostrophic equation. We compare the statistical properties of our discretisation with the Gibbs distribution under assumption of these conserved quantities, finding that there is agreement between the statistics under a wide range of set-ups.
Bauer W, Cotter CJ, 2018, Energy-enstrophy conserving compatible finite element schemes for the rotating shallow water equations with slip boundary conditions, Journal of Computational Physics, Vol: 373, Pages: 171-187, ISSN: 0021-9991
We describe an energy-enstrophy conserving discretisation for the rotatingshallow water equations with slip boundary conditions. This relaxes theassumption of boundary-free domains (periodic solutions or the surface of asphere, for example) in the energy-enstrophy conserving formulation of McRaeand Cotter (2014). This discretisation requires extra prognostic vorticityvariables on the boundary in addition to the prognostic velocity and layerdepth variables. The energy-enstrophy conservation properties hold for anyappropriate set of compatible finite element spaces defined on arbitrary mesheswith arbitrary boundaries. We demonstrate the conservation properties of thescheme with numerical solutions on a rotating hemisphere.
Melvin T, Benacchio T, Thuburn J, et al., 2018, Choice of function spaces for thermodynamic variables in mixed finite-element methods, Quarterly Journal of the Royal Meteorological Society, Vol: 144, Pages: 900-916, ISSN: 0035-9009
We study the dispersion properties of three choices for the buoyancy space in a mixed finite‐element discretization of geophysical fluid flow equations. The problem is analogous to that of the staggering of the buoyancy variable in finite‐difference discretizations. Discrete dispersion relations of the two‐dimensional linear gravity wave equations are computed. By comparison with the analytical result, the best choice for the buoyancy space basis functions is found to be the horizontally discontinuous, vertically continuous option. This is also the space used for the vertical component of the velocity. At lowest polynomial order, this arrangement mirrors the Charney–Phillips vertical staggering known to have good dispersion properties in finite‐difference models. A fully discontinuous space for the buoyancy corresponding to the Lorenz finite‐difference staggering at lowest order gives zero phase velocity for high vertical wavenumber modes. A fully continuous space, the natural choice for scalar variables in a mixed finite‐element framework, with degrees of freedom of buoyancy and vertical velocity horizontally staggered at lowest order, is found to entail zero phase velocity modes at the large horizontal wavenumber end of the spectrum. Corroborating the theoretical insights, numerical results obtained on gravity wave propagation with fully continuous buoyancy highlight the presence of a computational mode in the poorly resolved part of the spectrum that fails to propagate horizontally. The spurious signal is not removed in test runs with higher‐order polynomial basis functions. Runs at higher order also highlight additional oscillations, an issue that is shown to be mitigated by partial mass‐lumping. In light of the findings and with a view to coupling the dynamical core to physical parametrizations that often force near the horizontal grid scale, the use of the fully continuous space should be avoided in favour of the horizontally discontinuous, vertically co
Natale A, Cotter CJ, 2018, Corrigendum to: A variational H(div) finite-element discretization approach for perfect incompressible fluids, IMA Journal of Numerical Analysis, Vol: 38, Pages: 1084-1084, ISSN: 0272-4979
This is a correction to:IMA Journal of Numerical Analysis, Volume 38, Issue 3, 17 July 2018, Pages 1388–1419, https://doi.org/10.1093/imanum/drx033
McRae ATT, Cotter CJ, Budd CJ, 2018, Optimal-transport-based mesh adaptivity on the plane and sphere using finite elements, SIAM Journal on Scientific Computing, Vol: 40, Pages: A1121-A1148
In moving mesh methods, the underlying mesh is dynamically adapted withoutchanging the connectivity of the mesh. We specifically consider the generationof meshes which are adapted to a scalar monitor function throughequidistribution. Together with an optimal transport condition, this leads to aMonge-Amp\`ere equation for a scalar mesh potential. We adapt an existingfinite element scheme for the standard Monge-Amp\`ere equation to this meshgeneration problem; this is a mixed finite element scheme, in which an extradiscrete variable is introduced to represent the Hessian matrix of secondderivatives. The problem we consider has additional nonlinearities over thebasic Monge-Amp\`ere equation due to the implicit dependence of the monitorfunction on the resulting mesh. We also derive the equivalentMonge-Amp\`ere-like equation for generating meshes on the sphere. The finiteelement scheme is extended to the sphere, and we provide numerical examples.All numerical experiments are performed using the open-source finite elementframework Firedrake.
Gregory ACA, Cotter CJ, 2017, A seamless multilevel ensemble transform particle filter, SIAM Journal on Scientific Computing, Vol: 39, Pages: A2684-A2701, ISSN: 1095-7197
This paper presents a seamless algorithm for the application of the multilevel MonteCarlo (MLMC) method to the ensemble transform particle filter (ETPF). The algorithm uses a combi-nation of optimal coupling transformations between coarse and fine ensembles in difference estimatorswithin a multilevel framework, to minimise estimator variance. It differs from that of Gregory et al.(2016) in that strong coupling between the coarse and fine ensembles is seamlessly maintained duringall stages of the assimilation algorithm, instead of using independent transformations to equal weightsfollowed by recoupling with an assignment problem. This modification is found to lead to an increasedrate in variance decay between coarse and fine ensembles with level in the hierarchy, a key componentof MLMC. This offers the potential for greater computational cost reductions. This is shown, alongsideevidence of asymptotic consistency, in numerical examples.
van Sebille E, Griffies SM, Abernathey R, et al., 2017, Lagrangian ocean analysis: fundamentals and practices, Ocean Modelling, Vol: 121, Pages: 49-75, ISSN: 1463-5003
Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.
Cotter CJ, Gottwald G, Holm DD, 2017, Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 473, ISSN: 1364-5021
In Holm (Holm 2015 Proc. R. Soc. A 471, 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow.
Natale A, Cotter CJ, 2017, A variational H (div) finite-element discretization approach for perfect incompressible fluids, IMA Journal of Numerical Analysis, Vol: 38, Pages: 1388-1419, ISSN: 0272-4979
We propose a finite-element discretization approach for the incompressible Euler equations which mimicstheir geometric structure and their variational derivation. In particular, we derive a finite-element methodthat arises from a nonholonomic variational principle and an appropriately defined Lagrangian, where finite-elementH(div)vector fields are identified with advection operators; this is the first successful extensionof the structure-preserving discretization ofPavlovet al.(2009) to the finite-element setting. The resultingalgorithm coincides with the energy-conserving scheme proposed byGuzm ́anet al.(2016). Through thevariational derivation, we discover that it also satisfies a discrete analogous of Kelvin’s circulation theorem.Further, we propose an upwind-stabilized version of the scheme that dissipates enstrophy while preservingenergy conservation and the discrete Kelvin’s theorem. We prove error estimates for this version of thescheme, and we study its behaviour through numerical tests.
Natale A, Cotter CJ, 2017, Scale-selective dissipation in energy-conserving finite element schemes for two-dimensional turbulence, Quarterly Journal of the Royal Meteorological Society, Vol: 143, Pages: 1734-1745, ISSN: 0035-9009
We analyze the multiscale properties of energy-conserving upwind-stabilized finite-element discretizations of the two-dimensional incompressible Euler equations. We focus our attention on two particular methods: the Lie derivative discretization introduced by Natale and Cotter and the Streamline Upwind/Petrov–Galerkin (SUPG) discretization of the vorticity advection equation. Such discretizations provide control on enstrophy by modelling different types of scale interactions. We quantify the performance of the schemes in reproducing the non-local energy backscatter that characterizes two-dimensional turbulent flows.
Yamazaki H, Shipton J, Cullen MJP, et al., 2017, Vertical slice modelling of nonlinear Eady waves using a compatible finite element method, Journal of Computational Physics, Vol: 343, Pages: 130-149, ISSN: 1090-2716
A vertical slice model is developed for the Euler–Boussinesq equations with a constant temperature gradient in the direction normal to the slice (the Eady–Boussinesq model). The model is a solution of the full three-dimensional equations with no variation normal to the slice, which is an idealised problem used to study the formation and subsequent evolution of weather fronts. A compatible finite element method is used to discretise the governing equations. To extend the Charney–Phillips grid staggering in the compatible finite element framework, we use the same node locations for buoyancy as the vertical part of velocity and apply a transport scheme for a partially continuous finite element space. For the time discretisation, we solve the semi-implicit equations together with an explicit strong-stability-preserving Runge–Kutta scheme to all of the advection terms. The model reproduces several quasi-periodic lifecycles of fronts despite the presence of strong discontinuities. An asymptotic limit analysis based on the semi-geostrophic theory shows that the model solutions are converging to a solution in cross-front geostrophic balance. The results are consistent with the previous results using finite difference methods, indicating that the compatible finite element method is performing as well as finite difference methods for this test problem. We observe dissipation of kinetic energy of the cross-front velocity in the model due to the lack of resolution at the fronts, even though the energy loss is not likely to account for the large gap on the strength of the fronts between the model result and the semi-geostrophic limit solution.
Gregory ACA, Cotter CJ, 2017, On the Calibration of Multilevel Monte Carlo Ensemble Forecasts, Quarterly Journal of the Royal Meteorological Society, Vol: 143, Pages: 1929-1935, ISSN: 1477-870X
The multilevel Monte Carlo method can efficiently compute statistical estimates ofdiscretized random variables for a given error tolerance. Traditionally, only a certainstatistic is computed from a particular implementation of multilevel Monte Carlo. Thisarticle considers the multilevel case in which one wants to verify and evaluate a singleensemble that forms an empirical approximation to many different statistics, namely anensemble forecast. We propose a simple algorithm that, in the univariate case, allows oneto derive a statistically consistent single ensemble forecast from the hierarchy of ensemblesthat are formed during an implementation of multilevel Monte Carlo. This ensembleforecast then allows the entire multilevel hierarchy of ensembles to be evaluated usingstandard ensemble forecast verification techniques. We demonstrate the case of evaluatingthe calibration of the forecast.
Natale A, Shipton J, Cotter CJ, 2016, Compatible finite element spaces for geophysical fluid dynamics, Dynamics and Statistics of the Climate System, Vol: 1, ISSN: 2059-6987
Compatible finite elements provide a framework for preserving important structures in equations of geophysical uid dynamics, and are becoming important in their use for building atmosphere and ocean models. We survey the application of compatible finite element spaces to geophysical uid dynamics, including the application to the nonlinear rotating shallow water equations, and the three-dimensional compressible Euler equations. We summarise analytic results about dispersion relations and conservation properties, and present new results on approximation properties in three dimensions on the sphere, and on hydrostatic balance properties.
McRae ATT, Mitchell L, Bercea, et al., 2016, Automated Generation and Symbolic Manipulation of Tensor Product Finite Elements, SIAM Journal on Scientific Computing, Vol: 38, Pages: S25-S47, ISSN: 1095-7197
We describe and implement a symbolic algebra for scalar and vector-valued finite elements, enabling the computer generation of elements with tensor product structure on quadrilateral, hexahedral, and triangular prismatic cells. The algebra is implemented as an extension to the domain-specific language UFL, the Unified Form Language. This allows users to construct many finite element spaces beyond those supported by existing software packages. We have made corresponding extensions to FIAT, the FInite element Automatic Tabulator, to enable numerical tabulation of such spaces. This tabulation is consequently used during the automatic generation of low-level code that carries out local assembly operations, within the wider context of solving finite element problems posed over such function spaces. We have done this work within the code-generation pipeline of the software package Firedrake; we make use of the full Firedrake package to present numerical examples.
Abolghasemi M, Piggott MD, Spinneken J, et al., 2016, Simulating tidal turbines with multi-scale mesh optimisation techniques, Journal of Fluids and Structures, Vol: 66, Pages: 69-90, ISSN: 1095-8622
Embedding tidal turbines within simulations of realistic large-scale tidal flows is a highly multi-scale problem that poses significant computational challenges. Here this problem is tackled using actuator disc momentum (ADM) theory and Reynolds-averaged Navier-Stokes (RANS) with, for the first time, dynamically adaptive mesh optimisation techniques. Both k-ω and k-ω SST RANS models have been developed within the Fluidity framework, an adaptive mesh CFD solver, and the model is validated against two sets of experimental flume test results. A brief comparison against a similar OpenFOAM model is presented to portray the benefits of the finite element discretisation scheme employed in the Fluidity ADM model. This model has been developed with the aim that it will be seamlessly combined with larger numerical models simulating tidal flows in realistic domains. This is where the mesh optimisation capability is a major advantage as it enables the mesh to be refined dynamically in time and only in the locations required, thus making optimal use of limited computational resources.
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