Shingle 2.0: generalising self-consistent and automated domain discretisation for multi-scale geophysical models

The approaches taken to describe and develop spatial discretisations of the domains required for geophysical simulation models are commonly ad hoc, model or application specific and under-documented. This is particularly acute for simulation models that are flexible in their use of multi-scale, anisotropic, fully unstructured meshes where a relatively large number of heterogeneous parameters are required to constrain their full description. As a consequence, it can be difficult to reproduce simulations, ensure a provenance in model data handling and initialisation, and a challenge to conduct model intercomparisons rigorously. This paper takes a novel approach to spatial discretisation, considering it much like a numerical simulation model problem of its own. It introduces a generalised, extensible, self-documenting approach to carefully describe, and necessarily fully, the constraints over the heterogeneous parameter space that determine how a domain is spatially discretised. This additionally provides a method to accurately record these constraints, using high-level natural language based abstractions, that enables full accounts of provenance, sharing and distribution. Together with this description, a generalised consistent approach to unstructured mesh generation for geophysical models is developed, that is automated, robust and repeatable, quick-to-draft, rigorously verified and consistent to the source data throughout. This interprets the description above to execute a self-consistent spatial discretisation process, which is automatically validated to expected discrete characteristics and metrics.Comment: 18 pages, 10 figures, 1 table. Submitted for publication and under revie

Subgrid scale modelling of transport processes.

Consideration of stabilisation techniques is essential in the development of physical models if they are to faithfully represent processes over a wide range of scales. Careful application of these techniques can significantly increase flexibility of models, allowing the computational meshes used to discretise the underlying partial differential equations to become highly nonuniform and anisotropic, for example. This exibility enables a model to capture a wider range of phenomena and thus reduce the number of parameterisations required, bringing a physically more realistic solution. The next generation of fluid flow and radiation transport models employ unstructured meshes and anisotropic adaptive methods to gain a greater degree of flexibility. However these can introduce erroneous artefacts into the solution when, for example, a process becomes unresolvable due to an adaptive mesh change or advection into a coarser region of mesh in the domain. The suppression of these effects, caused by spatial and temporal variations in mesh size, is one of the key roles stabilisation can play. This thesis introduces new explicit and implicit stabilisation methods that have been developed for application in fluid and radiation transport modelling. With a focus on a consistent residual-free approach, two new frameworks for the development of implicit methods are presented. The first generates a family of higher-order Petrov-Galerkin methods, and the example developed is compared to standard schemes such as streamline upwind Petrov-Galerkin and Galerkin least squares in accurate modelling of tracer transport. The dissipation generated by this method forms the basis for a new explicit fourth-order subfilter scale eddy viscosity model for large eddy simulation. Dissipation focused more sharply on unresolved scales is shown to give improved results over standard turbulence models. The second, the inner element method, is derived from subgrid scale modelling concepts and, like the variational multiscale method and bubble enrichment techniques, explicitly aims to capture the important under-resolved fine scale information. It brings key advantages to the solution of the Navier-Stokes equations including the use of usually unstable velocity-pressure element pairs, a fully consistent mass matrix without the increase in degrees of freedom associated with discontinuous Galerkin methods and also avoids pressure filtering. All of which act to increase the flexibility and accuracy of a model. Supporting results are presented from an application of the methods to a wide range of problems, from simple one-dimensional examples to tracer and momentum transport in simulations such as the idealised Stommel gyre, the lid-driven cavity, lock-exchange, gravity current and backward-facing step. Significant accuracy improvements are demonstrated in challenging radiation transport benchmarks, such as advection across void regions, the scattering Maynard problem and demanding source-absorption cases. Evolution of a free surface is also investigated in the sloshing tank, transport of an equatorial Rossby soliton, wave propagation on an aquaplanet and tidal simulation of the Mediterranean Sea and global ocean. In combination with adaptive methods, stabilising techniques are key to the development of next generation models. In particular these ideas are critical in achieving the aim of extending models, such as the Imperial College Ocean Model, to the global scale

Efficient unstructured mesh generation for marine renewable energy applications

Renewable energy is the cornerstone of preventing dangerous climate change whilst maintaining a robust energy supply. Tidal energy will arguably play a critical role in the renewable energy portfolio as it is both predictable and reliable, and can be put in place across the globe. However, installation may impact the local and regional ecology via changes in tidal dynamics, sediment transport pathways or bathymetric changes. In order to mitigate these effects, tidal energy devices need to be modelled in order to predict hydrodynamic changes. Robust mesh generation is a fundamental component required for developing simulations with high accuracy. However, mesh generation for coastal domains can be an elaborate procedure. Here, we describe an approach combining mesh generators with Geographical Information Systems. We demonstrate robustness and efficiency by constructing a mesh with which to examine the potential environmental impact of a tidal turbine farm installation in the Orkney Islands. The mesh is then used with two well-validated ocean models, to compare their flow predictions with and without a turbine array. The results demonstrate that it is possible to create an easy-to-use tool to generate high-quality meshes for combined coastal engineering, here tidal turbines, and coastal ocean simulations

The Oceanographic Multipurpose Software Environment (OMUSE v1.0)

In this paper we present the Oceanographic Multipurpose Software Environment (OMUSE). OMUSE aims to provide a homogeneous environment for existing or newly developed numerical ocean simulation codes, simplifying their use and deployment. In this way, numerical experiments that combine ocean models representing different physics or spanning different ranges of physical scales can be easily designed. Rapid development of simulation models is made possible through the creation of simple high-level scripts. The low-level core of the abstraction in OMUSE is designed to deploy these simulations efficiently on heterogeneous high-performance computing resources. Cross-verification of simulation models with different codes and numerical methods is facilitated by the unified interface that OMUSE provides. Reproducibility in numerical experiments is fostered by allowing complex numerical experiments to be expressed in portable scripts that conform to a common OMUSE interface. Here, we present the design of OMUSE as well as the modules and model components currently included, which range from a simple conceptual quasi-geostrophic solver to the global circulation model POP (Parallel Ocean Program). The uniform access to the codes' simulation state and the extensive automation of data transfer and conversion operations aids the implementation of model couplings. We discuss the types of couplings that can be implemented using OMUSE. We also present example applications that demonstrate the straightforward model initialization and the concurrent use of data analysis tools on a running model. We give examples of multiscale and multiphysics simulations by embedding a regional ocean model into a global ocean model and by coupling a surface wave propagation model with a coastal circulation model

Water motion and vegetation control the pH dynamics in seagrass-dominated bays

info:eu-repo/semantics/publishe

A Population Genetic Approach to Mapping Neurological Disorder Genes Using Deep Resequencing

Deep resequencing of functional regions in human genomes is key to identifying potentially causal rare variants for complex disorders. Here, we present the results from a large-sample resequencing (n = 285 patients) study of candidate genes coupled with population genetics and statistical methods to identify rare variants associated with Autism Spectrum Disorder and Schizophrenia. Three genes, MAP1A, GRIN2B, and CACNA1F, were consistently identified by different methods as having significant excess of rare missense mutations in either one or both disease cohorts. In a broader context, we also found that the overall site frequency spectrum of variation in these cases is best explained by population models of both selection and complex demography rather than neutral models or models accounting for complex demography alone. Mutations in the three disease-associated genes explained much of the difference in the overall site frequency spectrum among the cases versus controls. This study demonstrates that genes associated with complex disorders can be mapped using resequencing and analytical methods with sample sizes far smaller than those required by genome-wide association studies. Additionally, our findings support the hypothesis that rare mutations account for a proportion of the phenotypic variance of these complex disorders

Neptune Odyssey: A Flagship Concept for the Exploration of the Neptune–Triton System

The Neptune Odyssey mission concept is a Flagship-class orbiter and atmospheric probe to the Neptune-Triton system. This bold mission of exploration would orbit an ice-giant planet to study the planet, its rings, small satellites, space environment, and the planet-sized moon Triton. Triton is a captured dwarf planet from the Kuiper Belt, twin of Pluto, and likely ocean world. Odyssey addresses Neptune system-level science, with equal priorities placed on Neptune, its rings, moons, space environment, and Triton. Between Uranus and Neptune, the latter is unique in providing simultaneous access to both an ice giant and a Kuiper Belt dwarf planet. The spacecraft - in a class equivalent to the NASA/ESA/ASI Cassini spacecraft - would launch by 2031 on a Space Launch System or equivalent launch vehicle and utilize a Jupiter gravity assist for a 12 yr cruise to Neptune and a 4 yr prime orbital mission; alternatively a launch after 2031 would have a 16 yr direct-to-Neptune cruise phase. Our solution provides annual launch opportunities and allows for an easy upgrade to the shorter (12 yr) cruise. Odyssey would orbit Neptune retrograde (prograde with respect to Triton), using the moon's gravity to shape the orbital tour and allow coverage of Triton, Neptune, and the space environment. The atmospheric entry probe would descend in ~37 minutes to the 10 bar pressure level in Neptune's atmosphere just before Odyssey's orbit-insertion engine burn. Odyssey's mission would end by conducting a Cassini-like "Grand Finale,"passing inside the rings and ultimately taking a final great plunge into Neptune's atmosphere

Shingle example self-consistent source datasets

<p>Self-consistent source datasets for the Shingle project -- an approach and software library for the generation of boundary representation from arbitrary geophysical fields and initialisation for anisotropic, unstructured meshing (see https://www.shingleproject.org for more information).</p