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Wind energy resource assessment typically requires numerical modeling at fine resolutions, which is computationally expensive for multi‐year timescales. Increasingly, unsupervised machine learning techniques are used to identify representative weather patterns that can help simulate long‐term behavior. Here we develop a novel wind energy workflow that combines the weather patterns from unsupervised clustering with a numerical weather prediction model (WRF) to obtain efficient long‐term predictions of wind farm power and downstream wakes, which provide a good approximation to full WRF simulations at vastly reduced computational cost. We use ERA5 reanalysis data and compare clustering on low altitude pressure and wind velocity, a more relevant variable for wind resource assessment. We also compare varying domain sizes for the clustering. A WRF simulation is run at each cluster center and the results aggregated into a long‐term prediction using a novel post‐processing technique. We consider two case study regions and show that our long‐term predictions achieve good agreement with a year of WRF simulations in 2% of the computational time. Moreover, clustering over a Europe‐wide domain produces good agreement for predicting wind farm power output, but clustering over smaller domains is required for downstream wake predictions which agree with the year of WRF simulations. Our approach facilitates multi‐year predictions of power output and downstream farm wakes, by providing a fast, reliable, and flexible methodology applicable to any global region. Moreover, this constitutes the first tool to help mitigate effects of wind energy loss downstream of wind farms. Plain Language Summary: With the need to transition to renewable energy, wind energy is becoming increasingly important. However, the build‐out of wind farms must be carefully planned, not least because entire wind farms extracting energy from the atmosphere cause large scale wind velocity deficits downstream. Wind energy resource assessment typically relies on numerical models, but these are computationally expensive to run for the multi‐year predictions required for sustainable development. It is therefore common to use a smaller set of weather conditions that are representative of a longer period. Here, we develop such a workflow based on identifying characteristic weather patterns using a clustering technique from the machine learning literature. Based on the characteristic patterns identified, we perform a small number of short numerical model experiments, one for each weather pattern. By applying a novel post‐processing technique to combine the outputs from these experiments, we obtain predictions of wind farm power and downstream wakes over the original multi‐year period, using just 2% of the computation time required by a purely numerical modeling approach. Our workflow thus constitutes a fast, reliable, and flexible methodology that is applicable to any global region, which can be used for the sustainable development of wind energy. Key Points: Fast, reliable and flexible method for long‐term wind energy resource assessment using only six short‐term simulationsEvaluation of suitable variables and domain sizes for deriving weather patternsWeather prediction model is combined with clustering method for energy prediction [ABSTRACT FROM AUTHOR]

A new two‐layer model for impulsive wave generation by deformable granular landslides is developed based upon a discontinuous Galerkin finite element discretization. Landslide motion is modeled using a depth‐averaged formulation for a shallow subaerial debris flow, which considers the bed curvature represented by the local slope angle variable and accounts for inter‐granular stresses using Coulomb friction. Wave generation and propagation are simulated with the three‐dimensional non‐hydrostatic coastal ocean model Thetis to accurately capture key features such as wave dispersion. Two different techniques are used in treating wetting and drying (WD) processes during the landslide displacement and wave generation, respectively. For the lower‐layer landslide motion across the dry bed a classical thin‐layer explicit WD method is implemented, while for the resulting free‐surface waves interacted with the moving landslide an implicit WD scheme is utilized to naturally circumvent the artificial pressure gradient problem which may appear in the dynamic interaction between the landslide and water if using the thin‐layer method. The two‐layer model is validated using a suite of test cases, with the resulting good agreement demonstrating its capability in describing both the complex behaviors of granular landslides from initiation to deposition, and the consequent wave generation and propagation. [ABSTRACT FROM AUTHOR]

The Maldives faces a unique range of environmental challenges. While the country is almost entirely dependent upon oceanic resources with more than 99% of the area covered by ocean, the absence of a suitable bathymetric map of the seafloor of the Maldives severely limits the adoption and application of modern scientific methods for the prediction of both physical and biological oceanic processes across the country. Here, we present a new bathymetric data set for the country based upon accumulating data from various sources and demonstrate that the synthesis of these provides a far more accurate representation of the shallow water areas of the region than currently available products. We also show that the new bathymetric data set is of sufficiently high resolution to model tidal flows across the archipelago for the first time. The new bathymetric data set provides numerous opportunities to better understand oceanic flow, associated physical and biogeochemical processes, and their correlation to one another across the Maldives archipelago. Plain Language Summary: The seafloor of the Maldives archipelago has been mapped in high resolution for the first time combining all available data sources. To demonstrate the capability of the data set, simulation of tides in the Greater Male' area is carried out with good comparison to observational data. This new seafloor map opens up a multitude of exciting opportunities to scientifically study different phenomenon in the Indian Ocean island nation, ranging from coastal erosion due to land reclamation to modelling the movement of plankton. Key Points: A new improved gridded bathymetric data set of the Maldives archipelago has been constructed from multiple data sourcesThe data set maps the shallow water regions in high‐resolution for the first time using satellite‐derived bathymetryTidal flow in the Maldives is simulated at high‐resolution for the first time with comparisons to tide gauge data [ABSTRACT FROM AUTHOR]

Summary: Submarine landslides can exhibit complex rheologies, including a finite yield stress and shear thinning, yet are often simulated numerically using a Newtonian fluid rheology and simplistic boundary conditions. Here we present improvements made to a Smoothed Particle Hydrodynamics simulator to allow the accurate simulation of submarine landslide generated waves. The improvements include the addition of Bingham and Herschel‐Bulkley rheologies, which better simulate the behavior of submarine mudflows. The interaction between the base of the slide and the slope is represented more accurately through the use of a viscous stress boundary condition. This condition treats the interface between the seafloor and the slide as a fluid boundary layer with a user‐defined viscosity and length scale. Modifications to the pressure and density calculations are described that improve their stability for landslide generated wave scenarios. An option for pressure decomposition is introduced to prevent particle locking under high pressure. This facilitates the application of this simulator to landslide scenarios beneath significant water depths. Additional modifications to the reaveraging and renormalization routines improve the stability of the free surface and fluid density. We present the mathematical formulations of these improvements alongside commentary on their performance and applicability to landslide generated wave modeling. The modifications are verified against analytical fluid flow solutions and a wave generation experiment. [ABSTRACT FROM AUTHOR]

Numerical models of the flow and wakes due to turbines operating within a real‐scale offshore wind farm can lead to a prohibitively large computational cost, particularly when considering blade‐resolved simulations. With the introduction of turbine parametrizations such as the actuator disk (AD) or the actuator line (AL) models, this problem has been partially addressed, yet the computational cost associated with these simulations remains high. In this work, we present an implementation and validation of an AL model within the mesh‐adaptive three‐dimensional fluid dynamics solver, Fluidity, under a unsteady Reynolds‐averaged Navier‐Stokes–based turbulence modelling approach. A key feature of this implementation is the use of mesh optimization techniques, which allow for the automatic refinement or coarsening of the mesh locally according to the resolution needed by the fluid flow solver. The model is first validated against experimental data from wind tunnel tests. Finally, we demonstrate the benefits of mesh‐adaptivity by considering flow past the Lillgrund offshore wind farm. [ABSTRACT FROM AUTHOR]

Numerical tidal modelling, when integrated with other geological datasets, can significantly inform the analysis of physical sedimentation processes and the depositional and preservational record of ancient tide‐influenced shoreline–shelf systems. This is illustrated in the Oligo–Miocene of the South China Sea, which experienced significant changes in basin physiography and where tide‐influenced, shoreline–shelf deposition is preserved in ca 10 sub‐basins. Palaeogeographic reconstructions, palaeotidal modelling and regional sedimentary facies analysis have been integrated in order to evaluate the spatial–temporal evolution and physiographic controls on tidal sedimentation and preservation during the ca 25 Myr Oligo–Miocene record in the South China Sea. Palaeotidal modelling, using an astronomically‐forced and global tidal model (Fluidity) at a maximum 10 km resolution, indicates that spring tides along Late Oligocene to Middle Miocene coastlines were predominantly mesotidal–macrotidal and capable of transporting sand, which reflects two main conditions: (i) increased tidal inflow through wider ocean connections to the Pacific Ocean; and (ii) tidal amplification resulting from constriction of the tidal wave in a 'blind gulf' type of basin morphology. Since the Middle to Late Miocene, a reduction in the amplitude and strength of tides in the South China Sea was mainly due to diminishing tidal inflow from the Pacific Ocean caused by the northward movement of the Philippines and Izu–Bonin–Mariana arc. Sensitivity tests to palaeogeographic and palaeobathymetric uncertainty indicate that regional‐scale (hundreds to thousands of kilometres) palaeogeographic changes influencing tidal inflow versus outflow can override local‐scale (one to hundreds of kilometres) changes to tidal resonance and convergence effects (funnelling and shoaling), such as shelf width and shoreline geometry. Palaeotidal model results compare favourably to the distribution and sedimentary fabric of Oligo–Miocene, tide‐influenced, shoreline–shelf successions in peripheral South China Sea basins. However, the preservation potential of tidal deposits is lower in open coastline environments, probably due to enhanced reworking during storms and river floods. [ABSTRACT FROM AUTHOR]

Lower to Middle Turonian deposits within the Bohemian Cretaceous Basin (Central Europe) consist of coarse-grained deltaic sandstones passing distally into fine-grained offshore sediments. Dune-scale cross-beds superimposed on delta-front clinoforms indicate a vigorous basinal palaeocirculation capable of transporting coarse-grained sand across the entire depth range of the clinoforms ( ca 35 m). Bi-directional, alongshore-oriented, trough cross-set axes, silt drapes and reactivation surfaces indicate tidal activity. However, the Bohemian Cretaceous Basin at this time was over a thousand kilometres from the shelf break and separated from the open ocean by a series of small islands. The presence of tidally-influenced deposits in a setting where co-oscillating tides are likely to have been damped down by seabed friction and blocked by emergent land masses is problematic. The Imperial College Ocean Model, a fully hydrodynamic, unstructured mesh finite element model, is used to test the hypothesis that tidal circulation in this isolated region was capable of generating the observed grain-size distributions, bedform types and palaeocurrent orientations. The model is first validated for the prediction of bed shear stress magnitudes and sediment transport pathways against the present-day North European shelf seas that surround the British Isles. The model predicts a microtidal to mesotidal regime for the Bohemian Cretaceous Basin across a range of sensitivity tests with elevated tidal ranges in local embayments. Funnelling associated with straits increases tidal current velocities, generating bed shear stresses that were capable of forming the sedimentary structures observed in the field. The model also predicts instantaneous bi-directional currents with orientations comparable with those measured in the field. Overall, the Imperial College Ocean Model predicts a vigorous tide-driven palaeocirculation within the Bohemian Cretaceous Basin that would indisputably have influenced sediment dispersal and facies distributions. Palaeocurrent vectors and sediment transport pathways however vary markedly in the different sensitivity tests. Accurate modelling of these parameters, in this instance, requires greater palaeogeographic certainty than can be extracted from the available rock record. [ABSTRACT FROM AUTHOR]

Due to a lack of modern analogues, debate surrounds the importance of tides in ancient epi-continental seas. However, numerical modelling can provide a quantitative means of investigating palaeo-tidality without recourse to analogues. Finite element modelling of the European Upper Carboniferous epi-continental seaway predicts an exceedingly low Lunar tidal range ( ca 5 cm in the open water regions of the UK and Southern North Sea). The Imperial College Ocean Model (ICOM) uses finite element methods and an unstructured tetrahedral mesh that is computationally very efficient. The accuracy and sensitivity of ICOM tidal range predictions were tested using bathymetric data from the present-day Mediterranean Sea. The Mediterranean Sea is micro-tidal and varies in depth up to 5·4 km with an average depth of 1–2 km. ICOM accurately predicts the tidal range given both a realistic, but smoothed, bathymetry and a straight sided basin with a uniform depth of 1 km. Variation in uniform depth from 100 to 3000 m with and without islands consistently predicts micro-tidality, demonstrating that the model is robust and the effect of bathymetric uncertainty on model output is relatively small. The extremely low tidal range predicted for the European Upper Carboniferous is thus deemed robust. Putative Upper Carboniferous tidal deposits have been described in the UK and southern North Sea, but are represented by cyclic rhythmites and are limited to palaeo-estuaries. Calculations based on an embayed coast model show that the tidal range could have been amplified to ca 1 m in estuaries and that this is sufficient to form cyclic rhythmites. Without tidal mixing, the tropical equatorial heat and salinity enhancement would promote stratification in the open water body. The introduction of organic matter probably caused anoxia, biotic mortality and carbon accumulation, as evidenced by numerous black ‘marine-band’ shales. [ABSTRACT FROM AUTHOR]