Article
Geography, Physical
Sasan Tavakoli, Alexander V. Babanin
Summary: Theoretical models are introduced for predicting the decay rate and dispersion process of gravity waves in an integrated ice cover. Wet beam models, incorporating water-based damping and added mass forces, are used. These models accurately predict the decay rate compared to a dry beam model.
Article
Engineering, Marine
M. R. Belmont
Summary: The study introduced a simple nonlinear phase operator to better describe extreme waves in sea wave models. By incorporating a second nonlinear operator to transfer energy from the original wave spectrum into more uniform real valued transient spectra, the research provided insights into the nonlinear mechanisms of extreme wave events.
Article
Environmental Sciences
William Perrie, Bechara Toulany, Michael Casey
Summary: A generalized formulation of the two-scale approximation (TSA) is presented in this study, which allows for multiple peaked spectra, sheared spectra, sea-swell combinations, etc. The TSA is implemented in the operational wave model WAVEWATCHIII (TM) and has shown significant improvement over the standard discrete interaction approximation (DIA) used in wave models. Tests involving simulation of waves generated in Hurricane Teddy (2020) further support the effectiveness of TSA.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Engineering, Multidisciplinary
Ahmad Amer, Fotis P. Kopsaftopoulos
Summary: A novel statistical framework for active-sensing SHM based on ultrasonic guided waves is proposed in this study, with three methods and corresponding statistical quantities experimentally evaluated for damage detection, showing increased sensitivity and robustness compared to conventional approaches, as well as better tracking capability of damage evolution.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2022)
Article
Mechanics
Matthew N. Crowe
Summary: The meridional component of the earth's rotation, often neglected in geophysical contexts, plays an important role in governing frontal dynamics in the ocean. Ocean fronts, regions of strong horizontal buoyancy gradient, may exhibit non-traditional rotation effects leading to the generation of jets and modification of frontal circulation and vertical transport.
JOURNAL OF FLUID MECHANICS
(2021)
Review
Oceanography
Brian K. Arbic
Summary: This article reviews an emerging class of high-resolution global models that consider the effects of both atmospheric fields and astronomical tidal potentials, and can simulate various oceanic phenomena. These models have numerous applications in satellite oceanography, operational oceanography, boundary forcing, tidal-cryosphere interactions, and assessment of the impact of tidal changes on future coastal flooding hazards.
PROGRESS IN OCEANOGRAPHY
(2022)
Article
Environmental Sciences
Andrea Storto, Chunxue Yang
Summary: Advancing the representation of uncertainties in ocean general circulation numerical models is crucial for various applications. The main uncertainty source in these models is the atmospheric forcing. In this study, different approaches to perturb the air-sea fluxes used in atmospheric boundary conditions are formulated and revised. The schemes are implemented and tested in the NEMO4 ocean model, and the results show that they can improve verification skill scores and enhance certain oceanic features. The choice of scheme depends on the specific application.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Mechanics
Ray Chew, Mark Schlutow, Rupert Klein
Summary: The traditional approximation neglects the cosine components of the Coriolis acceleration, and this approximation has been widely used in the study of geophysical phenomena. However, the validity of this approximation is questionable under certain circumstances, such as dynamics with substantial vertical velocities or geophysical phenomena in the tropics. This study investigates the effect of using the full Coriolis acceleration on a meridionally homogeneous flow in an isothermal, hydrostatic, and compressible atmosphere. The results show that experiments considering the full Coriolis terms exhibit an exponentially growing instability, while experiments subjected to the traditional approximation remain stable.
JOURNAL OF FLUID MECHANICS
(2023)
Article
Multidisciplinary Sciences
Joan Villalonga, Angel Amores, Sebastia Monserrat, Marta Marcos, Damia Gomis, Gabriel Jorda
Summary: The Hunga Tonga-Hunga Ha'apai volcano eruption in January 2022 caused a global atmospheric and oceanic response that was recorded by a significant number of sensors. The eruption created an atmospheric disturbance that traveled around the Earth multiple times, and its effects were observed by numerous barographs worldwide. The disturbance produced complex patterns of amplitude and spectral energy in the atmosphere, with most of the energy concentrated in the 2-120 minute band. Additionally, strong sea level oscillations were recorded by tide gauges globally, indicating a global meteotsunami phenomenon.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Analytical
Shabbir Ahmed, Fotis Kopsaftopoulos
Summary: This study rigorously investigates and models the stochastic nature of guided wave propagation in the context of active-sensing guided-wave-based acousto-ultrasound structural health monitoring. The identified RML-TAR model is used to analyze the uncertainty in guided wave propagation, including time-varying model parameters and modal properties such as natural frequencies and damping ratios. Additionally, Monte Carlo simulations on a high-fidelity finite element model are conducted to understand the effect of small temperature perturbation on guided wave signals.
Article
Mechanics
Goezde Oezden, Marcel Oliver
Summary: The model derives a semi-geostrophic variational balance model for the three-dimensional Euler-Boussinesq equations on the nontraditional f-plane under the rigid lid approximation. It allows for a fully non-hydrostatic flow and maintains the balance relation elliptic under the assumption of stable stratification and sufficiently small fluctuations in all prognostic fields.
Article
Astronomy & Astrophysics
Giacomo Ferrante, Gabriele Franciolini, Antonio Junior Iovino, Alfredo Urbano
Summary: We present a comprehensive formalism for computing the abundance of primordial black holes (PBHs) with local non-Gaussianity (NG) in the curvature perturbation field. We go beyond the traditional quadratic and cubic approximations and consider a generic functional form for NG. Our approach considers both narrow and broad power spectra. We show that the conventional perturbative approach is only reliable for narrow spectra, while for broad spectra, nonperturbative computations are necessary to obtain accurate results.
Article
Oceanography
Bertrand L. Delorme, Leif N. Thomas, Patrick Marchesiello, Jonathan Gula, Guillaume Roullet, M. Jeroen Molemaker
Summary: Recent theoretical work suggests that reflection of equatorially trapped waves off the seafloor can lead to strong vertical shear and intensified bottom mixing, potentially playing a significant role in driving diapycnal upwelling in AMOC. However, these findings were derived under idealized conditions, and it remains to be seen how they hold up in more realistic oceanic simulations.
JOURNAL OF PHYSICAL OCEANOGRAPHY
(2021)
Article
Meteorology & Atmospheric Sciences
Yuhong Zhang, Yan Du
Summary: This study examines the relationship between downwelling Rossby waves in the South Indian Ocean and the Indian Ocean dipole (IOD) event. The results show that these waves play a crucial role in influencing sea surface temperature (SST) in the Seychelles thermocline dome and the southeastern tropical Indian Ocean. The study also highlights the importance of the intensity and type of downwelling Rossby waves in shaping the development of the IOD event.
JOURNAL OF CLIMATE
(2022)
Article
Mechanics
Eytan Meisner, Mariano Galvagno, David Andrade, Dan Liberzon, Raphael Stuhlmeier
Summary: We have developed a new deterministic forecasting methodology for ocean surface waves using nonlinear frequency corrections. These corrections, pre-computed based on measured energy density spectra, do not require additional computational cost compared to linear theory. The methodology outperforms linear forecasts consistently, as demonstrated in testing with highly nonlinear synthetically generated seas of varying average steepness and directional spreading.
Article
Social Sciences, Mathematical Methods
David Bolin, Vilhelm Verendel, Meta Berghauser Pont, Ioanna Stavroulaki, Oscar Ivarsson, Erik Hakansson
Summary: The study proposed a functional ANOVA model to analyze the relationship between pedestrian flows and the structure of the city based on a large-scale cross-country pedestrian survey. The results indicated that the model works well in predicting pedestrian flows, but there is still room for improvement in capturing the variability in the data.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY
(2021)
Article
Chemistry, Medicinal
Sandra Barman, Cecilia Fager, Magnus Roding, Niklas Loren, Christian von Corswant, Eva Olsson, David Bolin, Holger Rootzen
Summary: This study introduced a new measure, geodesic channel strength, to capture a different type of bottleneck effect caused by many paths coinciding in the same pore, along with the development of new variants of pore size measures. The combination of new and existing measures provided important insights into connectivity and anisotropies in pore structures, which were visualized using a new method of layered images.
JOURNAL OF PHARMACEUTICAL SCIENCES
(2021)
Article
Meteorology & Atmospheric Sciences
Helga Kristin Olafsdottir, Holger Rootzen, David Bolin
Summary: The study found that as the average temperature increases, the frequency of extreme rainfall events in the northeastern United States increases, but there is little evidence of trends in the distribution of the intensities of individual extreme rainfall events. The frequency trends show that extreme rainfall may become 83% more frequent for each 1 degrees C of temperature increase.
JOURNAL OF CLIMATE
(2021)
Article
Engineering, Mechanical
Anders Hildeman, David Bolin, Igor Rychlik
Summary: Sea state, which describes the distribution of ocean waves in a specific region of space and time, plays a crucial role in assessing risks and wear associated with ship journeys. This study proposes a joint spatial model for significant wave height and mean wave period in the north Atlantic ocean, using a bivariate Gaussian random field. The model, estimated from data using a stepwise maximum likelihood method, accurately predicts accumulated fatigue damage and capsizing risk for a transatlantic route.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Geosciences, Multidisciplinary
Finn Lindgren, David Bolin, Havard Rue
Summary: This article provides an overview of Gaussian processes and random fields, their history, and various approaches to representing spatial and spatiotemporal dependence structures. The connection between stochastic partial differential equation approach and Matern covariance models is explained, along with important extensions, theory, applications, and recent developments.
SPATIAL STATISTICS
(2022)
Article
Statistics & Probability
Kristin Kirchner, David Bolin
Summary: The study focuses on optimal linear prediction based on known mean value and covariance functions, revealing the requirements for the performance of linear predictors and applying them to different types of random fields.
ANNALS OF STATISTICS
(2022)
Article
Neurosciences
Daniel Spencer, Yu Ryan Yue, David Bolin, Sarah Ryan, Amanda F. Mejia
Summary: The general linear model (GLM) is a popular tool for estimating brain response and identifying activation areas, but it has limitations. The surface-based spatial Bayesian GLM leverages activation patterns and produces more accurate estimates. It is reliable for individual subjects and can detect functional topologies even in small samples.
Article
Physics, Multidisciplinary
G. Lindgren, K. Podgorski, I Rychlik
Summary: This study tackles the problem of finding the probability that a stochastic system stays in a certain region of its state space over a specified time. The extended and multivariate Rice formula is used to provide an exact integral representation, yielding accurate results. The method is more accurate and efficient than previous methods, particularly for Gaussian processes.
JOURNAL OF PHYSICS COMMUNICATIONS
(2022)
Article
Statistics & Probability
Amanda F. Mejia, David Bolin, Yu Ryan Yue, Jiongran Wang, Brian S. Caffo, Mary Beth Nebel
Summary: Independent Component Analysis (ICA) is commonly used in extracting functional brain networks from fMRI data. However, single-subject ICA often produces noisy results. This study proposes a spatial template ICA (stICA) method that incorporates spatial priors into the template ICA framework for greater estimation efficiency. The results show that stICA produces more accurate and reliable estimates compared to benchmark approaches, and identifies larger and more reliable areas of engagement.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2023)
Article
Management
Victor Medina-Olivares, Raffaella Calabrese, Jonathan Crook, Finn Lindgren
Summary: The inclusion of time-varying covariates into survival analysis has improved predictions in behavioural credit scoring models. However, problems arise when these covariates are endogenous, including estimation bias and lack of a prediction framework. This paper explores the application of discrete-time joint models to credit scoring and proposes a novel extension by including autoregressive terms. Empirical analysis shows that discrete joint models can improve discrimination performance, especially when autoregressive terms are included.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Statistics & Probability
Joaquin Martinez-Minaya, Finn Lindgren, Antonio Lopez-Quilez, Daniel Simpson, David Conesa
Summary: This article introduces a Laplace approximation method for Bayesian inference in Dirichlet regression models, which allows analyzing skewed and heteroscedastic variables on a simplex without data transformation. The article provides theoretical foundations, implementation details, and introduces the dirinla package in R-language for Dirichlet regression. Simulation studies validate the proposed method, and a real data case-study demonstrates its application.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2023)
Article
Construction & Building Technology
David Bolin, Jonas Wallin
Summary: Averages of proper scoring rules are commonly used to rank probabilistic forecasts. However, some popular scoring rules give more importance to observations with large uncertainty, resulting in unintuitive rankings. To address this issue, we propose a new proper scoring rule called scaled CRPS (SCRPS), which is locally scale invariant and works in varying uncertainty situations.
ENERGY AND BUILDINGS
(2023)
Article
Management
Victor Medina-Olivares, Finn Lindgren, Raffaella Calabrese, Jonathan Crook
Summary: Survival models with time-varying covariates (TVCs) are commonly used in credit risk prediction, but the handling of endogeneity in these models is limited. This study proposes a joint model for bivariate endogenous TVCs and discrete survival data using integrated nested Laplace approximation (INLA). The implementation is illustrated through simulations and a model for full-prepayment consumer loans, and a methodology for individual survival prediction is also proposed. The superiority of joint models over traditional survival approaches is demonstrated in an out-of-sample and out-of-time analysis.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Statistics & Probability
David Bolin, Alexandre B. Simas, Zhen Xiong
Summary: The stochastic partial differential equation (SPDE) approach is widely used for modeling large spatial datasets. A new method is proposed for Bayesian inference using a stable Gaussian Markov random fields (GMRF) approximation, which approximates the covariance operator of the Gaussian field by a finite element method combined with a rational approximation of the fractional power. The method is rigorously analyzed for convergence and the accuracy is investigated with simulated data.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
(2023)
Article
Mathematics, Interdisciplinary Applications
Per Siden, Finn Lindgren, David Bolin, Anders Eklund, Mattias Villani
Summary: Bayesian whole-brain fMRI analysis based on Mate'rn covariance functions offers a more flexible and interpretable spatial prior, maintaining the sparsity required for fast inference in high-dimensional settings. An accelerated stochastic gradient descent optimization algorithm is used for empirical Bayes inference of spatial hyperparameters, followed by a fully Bayesian treatment of brain activity. The Mate'rn prior is shown to be a more reasonable choice compared to previous priors through comparisons of activity maps, prior simulation, and cross-validation.
