Abstract. OceanMesh2D is a set of MATLAB functions with preprocessing and post-processing utilities to generate two-dimensional (2-D) unstructured meshes for coastal ocean circulation models. Mesh resolution is controlled according to a variety of feature-driven geometric and topo-bathymetric functions. Mesh generation is achieved through a force balance algorithm to locate vertices and a number of topological improvement strategies aimed at improving the worst-case triangle quality. The placement of vertices along the mesh boundary is adapted automatically according to the mesh size function, eliminating the need for contour simplification algorithms. The software expresses the mesh design and generation process via an objected-oriented framework that facilitates efficient workflows that are flexible and automatic. This paper illustrates the various capabilities of the software and demonstrates its utility in realistic applications by producing high-quality, multiscale, unstructured meshes.
The total surface area of the Great Lakes is over 94,250 miles 2 . Consisting of five large lakes, they contain over one fifth of the world's total surface fresh water, with depths of up to 400 m (EPA, 2020). The Great Lakes substantially influence the regional weather and climate via their effects on the atmospheric energy and water budget; open water typically has greater thermal conductance, lower albedo, and lower roughness compared to soil or vegetated surfaces (Notaro et al.,2013;Scott & Huff, 1996). The large thermal inertia of the lakes leads to a reduction in annual and diurnal temperature ranges across the Great Lakes Basin (Harris & Kotamarthi, 2005;Notaro et al., 2013). Mean minimum temperatures in the region are warmer during all seasons and over all five lakes, while maximum temperatures are cooler during spring and summer (Scott & Huff, 1996). Lake thermal impacts and associated evaporation have a strong influence on regional precipitation patterns. While many studies have investigated the impact of lake surface temperature (LST) on the cold-season precipitationwhich is primarily a direct product of warmth and moisture from the Great Lakes (e.g., lake-effect snow; Notaro et al., 2021; Shi & Xue, 2019)-the impact of LST on summer precipitation has only rarely been studied. During early summer, the lake surface is still relatively cool compared to the atmosphere, resulting in condensation on the lake surface and a stable boundary layer that deters over-lake convective processes (Miner & Fritsch, 1997;Workoff et al., 2012). Due to the temperature differences over lake and inland, lake breeze can cause air to rise inland and increases the likelihood of over-land precipitation (Schulkowski, 2020). During late summer, while the land cools and the lakes remain warm, the temperature differential between land and lake surface coupled with baroclinic waves (e.g., cold front and trough) and/or the Great Plains low-level jets can generate enhanced precipitation (Feng et al., 2016;Miner & Fritsch, 1997). Therefore, changes in summer LST could potentially affect its feedback to atmospheric stability and change the water and energy budget over the entire Great Lakes Region (GLR). The summer is an ideal time to evaluate the influence of LST on the lake surface-atmosphere
Abstract. This paper details and tests numerical improvements to the ADvanced CIRCulation (ADCIRC) model, a widely used finite-element method shallow-water equation solver, to more accurately and efficiently model global storm tides with seamless local mesh refinement in storm landfall locations. The sensitivity to global unstructured mesh design was investigated using automatically generated triangular meshes with a global minimum element size (MinEle) that ranged from 1.5 to 6 km. We demonstrate that refining resolution based on topographic seabed gradients and employing a MinEle less than 3 km are important for the global accuracy of the simulated astronomical tide. Our recommended global mesh design (MinEle = 1.5 km) based on these results was locally refined down to two separate MinEle values (500 and 150 m) at the coastal landfall locations of two intense storms (Hurricane Katrina and Super Typhoon Haiyan) to demonstrate the model's capability for coastal storm tide simulations and to test the sensitivity to local mesh refinement. Simulated maximum storm tide elevations closely follow the lower envelope of observed high-water marks (HWMs) measured near the coast. In general, peak storm tide elevations along the open coast are decreased, and the timing of the peak occurs later with local coastal mesh refinement. However, this mesh refinement only has a significant positive impact on HWM errors in straits and inlets narrower than the MinEle and in bays and lakes separated from the ocean by these passages. Lastly, we demonstrate that the computational performance of the new numerical treatment is 1 to 2 orders of magnitude faster than studies using previous ADCIRC versions because gravity-wave-based stability constraints are removed, allowing for larger computational time steps.
As part of a U.S. Integrated Ocean Observing System (IOOS) funded Coastal and Ocean Modeling Testbed (COMT), hindcasts of waves and storm surge for 2017 Hurricanes Irma and Maria are examined and compared to wave and water level gauge data in the vicinity of Puerto Rico and the U.S. Virgin Islands. The region is characterized by adjacent deep ocean water, narrow shelves, and coral reef systems providing coastal protection. The storm physics are analyzed using an unstructured grid third‐generation wave circulation coupled modeling system (ADCIRC+SWAN) with respect to tides, winds, atmospheric pressure, waves, and wave radiation stress‐induced setup. The water level response is generally dominated by the pressure deficit of the hurricanes. Wind‐driven surge is important over the shallow shelf to the east of Puerto Rico and wave‐induced setup becomes significant at locations in close proximity to the coastline. Contrary to conditions along the Gulf of Mexico shelf, geostrophically induced setup is negligible. Characteristics from a range of meteorological forcing models are assessed, and the associated errors in the hydrodynamic response are quantified. A data‐assimilated tropical planetary boundary model leads to the smallest atmospheric pressure, water level and wave property errors across both storms. Through comparisons between ADCIRC+SWAN and SLOSH‐FW (a structured grid first‐generation wave circulation coupled model), it is shown that the response to atmospheric forcing is similar; however, nearshore wave setup is smaller in SLOSH‐FW due to its coarser resolution here. Further, in addition to erroneous wind‐driven surge through depth limiting over the open ocean, numerical oscillations in the water level time series develop in SLOSH‐FW likely due to its small domain size.
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