Darren Engwirda
YOU?
Author Swipe
View article: Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model
Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model Open
Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes acros…
View article: Attention‐Based Reconstruction of Full‐Field Tsunami Waves From Sparse Tsunameter Networks
Attention‐Based Reconstruction of Full‐Field Tsunami Waves From Sparse Tsunameter Networks Open
We investigate the potential of an attention‐based neural network architecture, the Senseiver, for sparse sensing in tsunami forecasting. Specifically, we focus on the Tsunami Data Assimilation Method, which generates forecasts from tsunam…
View article: Discrete global grid system-based flow routing datasets in the Amazon and Yukon basins
Discrete global grid system-based flow routing datasets in the Amazon and Yukon basins Open
Discrete global grid systems (DGGS) are emerging spatial data structures widely used to organize geospatial datasets across scales. While DGGS have found applications in various scientific disciplines, including atmospheric science and eco…
View article: Evaluation of Flow Routing on the Unstructured Voronoi Meshes in Earth System Modeling
Evaluation of Flow Routing on the Unstructured Voronoi Meshes in Earth System Modeling Open
Flow routing is a fundamental process of Earth System Models' (ESMs) river component. Traditional flow routing models rely on Cartesian rectangular meshes, which exhibit limitations, particularly when coupled with unstructured mesh‐based o…
View article: Dynamic ice sheet-ocean interactions in the Energy Exascale Earth System Model
Dynamic ice sheet-ocean interactions in the Energy Exascale Earth System Model Open
Representing ice-shelf and ocean interactions in Earth system models (ESMs) has been challenging due to their coarse resolution and static ice shelf cavity geometries. Additionally, coupling techniques often struggle to conserve mass and e…
View article: Uncertainties in Simulating Flooding During Hurricane Harvey Using 2D Shallow Water Equations
Uncertainties in Simulating Flooding During Hurricane Harvey Using 2D Shallow Water Equations Open
Flooding is one of the most impactful weather‐related natural hazards. Numerical models that solve the two dimensional (2D) shallow water equations (SWE) represent the first‐principles approach to simulate all types of spatial flooding, su…
View article: Attention-Based Reconstruction of Full-Field Tsunami Waves from Sparse Tsunameter Networks
Attention-Based Reconstruction of Full-Field Tsunami Waves from Sparse Tsunameter Networks Open
We investigate the potential of an attention-based neural network architecture, the Senseiver, for sparse sensing in tsunami forecasting. Specifically, we focus on the Tsunami Data Assimilation Method, which generates forecasts from tsunam…
View article: Local time-stepping for the shallow water equations using CFL optimized forward-backward Runge-Kutta schemes
Local time-stepping for the shallow water equations using CFL optimized forward-backward Runge-Kutta schemes Open
The Courant–Friedrichs–Lewy (CFL) condition is a well known, necessary condition for the stability of explicit time-stepping schemes that effectively places a limit on the size of the largest admittable time-step for a given problem. We fo…
View article: Disentangling Atmospheric, Hydrological, and Coupling Uncertainties in Compound Flood Modeling within a Coupled Earth System Model
Disentangling Atmospheric, Hydrological, and Coupling Uncertainties in Compound Flood Modeling within a Coupled Earth System Model Open
Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts of modeling this phenomenon often rely on models that do not integrate hydro…
View article: Comment on essd-2023-398
Comment on essd-2023-398 Open
Abstract. Discrete Global Grid systems (DGGs) are emerging spatial data structures widely used to organize geospatial datasets across scales. While DGGs have found applications in various scientific disciplines, including atmospheric scien…
View article: Comment on essd-2023-398
Comment on essd-2023-398 Open
Abstract. Discrete Global Grid systems (DGGs) are emerging spatial data structures widely used to organize geospatial datasets across scales. While DGGs have found applications in various scientific disciplines, including atmospheric scien…
View article: Simulation of Compound Flooding Using River‐Ocean Two‐Way Coupled E3SM Ensemble on Variable‐Resolution Meshes
Simulation of Compound Flooding Using River‐Ocean Two‐Way Coupled E3SM Ensemble on Variable‐Resolution Meshes Open
Coastal zone compound flooding (CF) can be caused by the interactive fluvial and oceanic processes, particularly when coastal backwater propagates upstream and interacts with high river discharge. The modeling of CF is limited in existing …
View article: Discrete Global Grid System-based Flow Routing Datasets in the Amazon and Yukon Basins
Discrete Global Grid System-based Flow Routing Datasets in the Amazon and Yukon Basins Open
Discrete Global Grid systems (DGGs) are emerging spatial data structures widely used to organize geospatial datasets across scales. While DGGs have found applications in various scientific disciplines, including atmospheric science and eco…
View article: A new Dataset for Belowground Urban Stormwater Networks over the U.S.
A new Dataset for Belowground Urban Stormwater Networks over the U.S. Open
Belowground urban stormwater network (BUSN) data are usually not available to the public at the regional or national scales, hindering predictive understanding of BUSN’s impacts on urban flooding under extreme climates. We derived a …
View article: A nonhydrostatic formulation for MPAS-Ocean
A nonhydrostatic formulation for MPAS-Ocean Open
The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. In this work,…
View article: Topological Relationship‐Based Flow Direction Modeling: Stream Burning and Depression Filling
Topological Relationship‐Based Flow Direction Modeling: Stream Burning and Depression Filling Open
Flow direction modeling consists of (a) an accurate representation of the river network and (b) digital elevation model (DEM) processing to preserve characteristics with hydrological significance. In part 1 of our study, we presented a mes…
View article: CFL Optimized Forward–Backward Runge–Kutta Schemes for the Shallow-Water Equations
CFL Optimized Forward–Backward Runge–Kutta Schemes for the Shallow-Water Equations Open
We present the formulation and optimization of a Runge–Kutta-type time-stepping scheme for solving the shallow-water equations, aimed at substantially increasing the effective allowable time step over that of comparable methods. This schem…
View article: CFL Optimized Forward-Backward Runge-Kutta Schemes for the Shallow Water Equations
CFL Optimized Forward-Backward Runge-Kutta Schemes for the Shallow Water Equations Open
We present the formulation and optimization of a Runge-Kutta-type time-stepping scheme for solving the shallow water equations, aimed at substantially increasing the effective allowable time-step over that of comparable methods. This schem…
View article: Improving Tidal Modeling with Self-Attraction and Loading
Improving Tidal Modeling with Self-Attraction and Loading Open
The objective is to improve the accuracy of tides in the Model for Prediction Across ScalesOcean (MPAS-Ocean) by using a computationally-efficient method of calculating the self-attraction and loading (SAL)
View article: Faster Storm Surge Modeling with Local Time-Stepping
Faster Storm Surge Modeling with Local Time-Stepping Open
The objective is to evaluate the efficiency and efficacy of local time-stepping (LTS) methods in the Model for Prediction Across Scales-Ocean (MPAS-Ocean).
View article: LANL Institutional Computing Close-out Report for Project t22_ocean_time_step
LANL Institutional Computing Close-out Report for Project t22_ocean_time_step Open
This year, my team made a very productive use of LANL IC time. Four papers were published that used IC resources, and two more are under review. These publications fall into three categories: 1.) Improving tide modeling in the global ocean…