Preprints

Filtering by Subject: Numerical Analysis and Computation

A Mathematical Representation of Historical Greenhouse Gas Emissions with Rigorous Insights

Rizal Purnawan

Published: 2024-02-25
Subjects: Analysis, Environmental Monitoring, Longitudinal Data Analysis and Time Series, Numerical Analysis and Computation

In this paper, we analyze historical greenhouse gas (GHG) emissions worldwide, leveraging a dataset provided by (Gütschow and Pflüger, 2023). Employing mathematical modeling, a formal theory is developed, describing the growth trajectories of GHG emissions over time. The theory introduces several key concepts, including historical upper bound emission (HUBE), historical peak emission (HPE), and [...]

Open-source approach for reproducible substrate mapping using semantic segmentation on recreation-grade side scan sonar datasets

Cameron Scott Bodine, Daniel David Buscombe, Toby D. Hocking

Published: 2023-12-21
Subjects: Analysis, Artificial Intelligence and Robotics, Databases and Information Systems, Environmental Monitoring, Hydrology, Natural Resources and Conservation, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Programming Languages and Compilers, Software Engineering, Terrestrial and Aquatic Ecology, Water Resource Management

Knowledge of the variation and distribution of substrates at large spatial extents in aquatic systems, particularly rivers, is severely lacking, impeding species conservation and ecosystem restoration efforts. Air and space-borne remote sensing important for terrestrial and atmospheric measurements are limited in benthic environments due to river stage, turbidity, and canopy cover, requiring [...]

A Stability Analysis of Neural Networks and Its Application to Tsunami Early Warning

Donsub Rim, Sanah Suri, Sanghyun Hong, et al.

Published: 2023-05-14
Subjects: Geophysics and Seismology, Hydrology, Numerical Analysis and Computation

Neural networks (NNs) enable precise modeling of complicated geophysical phenomena but are sensitive to small input changes. In this work, we present a new method for analyzing this instability in NNs. We focus our analysis on adversarial examples, test-time inputs with carefully-crafted human-imperceptible perturbations that expose the worst-case instability in a model's predictions. Our [...]

Dampening effect of global flows on Rayleigh-Taylor instabilities: Implications for deep-mantle plumes vis-à-vis hotspot distributions

Arnab Roy, Dip Ghosh, Nibir Mandal

Published: 2023-01-18
Subjects: Earth Sciences, Fluid Dynamics, Numerical Analysis and Computation

It is a well-accepted hypothesis that deep-mantle primary plumes originate from a buoyant source layer at the core-mantle boundary (CMB), where Rayleigh–Taylor (RT) instabilities play a key role in the plume initiation process. Previous studies have characterized their growth rates mainly in terms of the density, viscosity and layer-thickness ratios between the denser overburden and the source [...]

Two-dimensional model of flow and transport in porous media: linking heterogeneous anisotropy with stratal patterns in meandering tidal channel deposits of the Venice Lagoon (Italy)

Elena Bachini, Elena Bellizia, Mario Putti, et al.

Published: 2022-09-08
Subjects: Geomorphology, Hydrology, Numerical Analysis and Computation

Understanding the internal structure of permeable and impermeable sediments (e.g. point-bars and tidal-flat deposits) generated by the evolution of meandering tidal channels is essential for accurate modeling of groundwater flow and contaminant transport in coastal areas. The detailed reconstruction of stratal geometry and hydraulic properties from measurements must be accompanied by depositional [...]

Tidal Turbine Array Modelling using Goal-Oriented Mesh Adaptation

Joseph Gregory Wallwork, Athanasios Angeloudis, Nicolas Barral, et al.

Published: 2022-04-30
Subjects: Civil and Environmental Engineering, Fluid Dynamics, Geophysics and Seismology, Numerical Analysis and Computation, Partial Differential Equations

Purpose: To examine the accuracy and sensitivity of tidal array performance assessment by numerical techniques applying goal-oriented mesh adaptation. Methods: The goal-oriented framework is designed to give rise to adaptive meshes upon which a given diagnostic quantity of interest (QoI) can be accurately captured, whilst maintaining a low overall computational cost. We seek to improve the [...]

A consistent mass-conserving C-staggered method for shallow water equations on global reduced grids

Genilson Schunck de Lima, Pedro da Silva Peixoto

Published: 2022-03-25
Subjects: Numerical Analysis and Computation

The increasing number of cores in modern supercomputers motivated the search for methods with better scalability to model the atmospheric dynamics in global weather forecasting and climate simulations. This objective renewed the interest in grid-point schemes with quasi-uniform spherical grids, with each alternative providing some good properties and some disadvantages. Here, we target reduced [...]

Uncertainty and sensitivity analysis for probabilistic weather and climate risk modelling: an implementation in CLIMADA v.3.1.

Chahan M. Kropf, Alessio Ciullo, Laura Otth, et al.

Published: 2022-02-23
Subjects: Applied Statistics, Climate, Design of Experiments and Sample Surveys, Earth Sciences, Environmental Studies, Natural Resources Management and Policy, Nature and Society Relations, Numerical Analysis and Computation, Numerical Analysis and Scientific Computing, Risk Analysis, Statistical Methodology

Modelling the risk of natural hazards for society, ecosystems, and the economy is subject to strong uncertainties, even more so in the context of a changing climate, evolving societies, growing economies, and declining ecosystems. Here we present a new feature of the climate risk modelling platform CLIMADA which allows to carry out global uncertainty and sensitivity analysis. CLIMADA underpins [...]

Calibration, inversion and sensitivity analysis for hydro-morphodynamic models

Mariana C A Clare, Stephan C Kramer, Colin J Cotter, et al.

Published: 2021-08-03
Subjects: Applied Mathematics, Fluid Dynamics, Geomorphology, Numerical Analysis and Computation, Partial Differential Equations, Programming Languages and Compilers

The development of reliable, sophisticated hydro-morphodynamic models is essential for protecting the coastal environment against hazards such as flooding and erosion. There exists a high degree of uncertainty associated with the application of these models, in part due to incomplete knowledge of various physical, empirical and numerical closure related parameters in both the hydrodynamic and [...]

Assessing erosion and flood risk in the coastal zone through the application of the multilevel Monte Carlo method

Mariana C A Clare, Matthew Piggott, Colin J Cotter

Published: 2021-01-07
Subjects: Applied Mathematics, Earth Sciences, Geomorphology, Hydrology, Numerical Analysis and Computation, Risk Analysis, Statistics and Probability

The risk from erosion and flooding in the coastal zone has the potential to increase in a changing climate. The development and use of coupled hydro-morphodynamic models is therefore becoming an ever higher priority. However, their use as decision support tools suffers from the high degree of uncertainty associated with them, due to incomplete knowledge as well as natural variability in the [...]

Multi-scale hydro-morphodynamic modelling using mesh movement methods.

Mariana C A Clare, Joseph Gregory Wallwork, Stephan C Kramer, et al.

Published: 2020-10-22
Subjects: Applied Mathematics, Geomorphology, Mathematics, Numerical Analysis and Computation, Partial Differential Equations

Hydro-morphodynamic models are an important tool that can be used in the protection of coastal zones. They can be required to resolve spatial scales ranging from sub-metre to hundreds of kilometres and are computationally expensive. In this work, we apply mesh movement methods to a depth-averaged hydro-morphodynamic model for the first time, in order to tackle both these issues. Mesh movement [...]

Robust Q estimation using surface seismic data

Joakim Oscar Blanch

Published: 2020-07-30
Subjects: Applied Mathematics, Computational Engineering, Earth Sciences, Engineering, Geophysics and Seismology, Numerical Analysis and Computation, Physical Sciences and Mathematics

Direct wave arrivals are the most robust signals to determine velocity and consequently they have been used for almost a century in hydrocarbon exploration. The reason is simple as the arrivaltime is explicitly available and provide a direct measurement of the average velocity of the sub-surface ray-path. These signals have not been extensively used to estimate attenuation or Q. One reason may [...]

Modelling an energetic tidal strait: investigating implications of common numerical configuration choices

Lucas Mackie, Paul Evans, Magnus Harrold, et al.

Published: 2020-07-16
Subjects: Applied Mathematics, Civil and Environmental Engineering, Civil Engineering, Engineering, Numerical Analysis and Computation, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Characterising tidal hydrodynamics in the vicinity of submerged features can be demanding given the hostility of the marine environment. Logistical challenges in the measurement of such flows has promoted research on wake studies through physical and numerical modelling. In this study, site measurements and modelled data are combined to provide an insight into the regional hydrodynamics within a [...]

Adjoint-based sensitivity analysis for a numerical storm surge model

Simon Charles Warder, Kevin Horsburgh, Matthew Piggott

Published: 2020-06-29
Subjects: Applied Mathematics, Numerical Analysis and Computation, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Numerical storm surge models are essential to forecasting coastal flood hazard and informing the design of coastal defences. However, such models rely on a variety of inputs, many of which will carry uncertainty, and an awareness and understanding of the sensitivity of the model outputs with respect to those uncertain inputs is necessary when interpreting model results. Here, we use an [...]

A comparison of Bayesian inference and gradient-based approaches for friction parameter estimation

Simon Charles Warder, Athanasios Angeloudis, Stephan C Kramer, et al.

Published: 2020-06-29
Subjects: Applied Mathematics, Numerical Analysis and Computation, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

Numerical tidal models are essential to the study of a variety of coastal ocean processes, but typically rely on uncertain inputs, including a bottom friction parameter which can in principle be spatially varying. Here we employ an adjoint-capable numerical ocean model, Thetis, and apply it to the Bristol Channel and Severn Estuary, using a spatially varying Manning coefficient within the bottom [...]

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