EarthArXiv (California Digital Library), Jul 27, 2021
Rapid and accurate prediction of peak storm surges across an extensive coastal region is necessar... more Rapid and accurate prediction of peak storm surges across an extensive coastal region is necessary to inform assessments used to design the systems that protect coastal communities' life and property. Significant advances in high-fidelity, physics-based numerical models have been made in recent years, but use of these models for probabilistic forecasting and probabilistic hazard assessment is computationally intensive. Several surrogate modeling approaches based on existing databases of high-fidelity synthetic storm surge simulations have been recently suggested to reduce computational burden without substantial loss of accuracy. In these previous studies, however, the surrogate modeling approaches relied on a tropical cyclone condition at one moment (usually at or near landfall), which is not always most correlated with the peak storm surge. In this study, a new one-dimensional convolutional neural network model combined with principal component analysis and a k-means clustering (C1PKNet) is presented that can rapidly predict peak storm surge across an extensive coastal region from time-series of tropical cyclone conditions, namely the storm track. The C1PKNet model was trained and cross-validated for the Chesapeake Bay area of the United States using existing database of 1031 high-fidelity storm surge simulations, including both landfalling and bypassing storms. Moreover, the performance of the C1PKNet model was evaluated based on observations from three historical hurricanes (Hurricane Isabel in 2003, Hurricane Irene in 2011, and Hurricane Sandy in 2012). The results indicate that the C1PKNet model is computationally e cient and can predict peak storm surges from realistic tropical cyclone track time-series. We believe that this new surrogate model can enhance coastal resilience by providing rapid storm surge predictions.
A topobathy digital elevation model (DEM) is a single surface combining the land elevation with t... more A topobathy digital elevation model (DEM) is a single surface combining the land elevation with the seafloor surface—and which can be used to examine processes that occur across the coastal and nearshore areas. A Roadmap to a Seamless Topobathy Surface (Roadmap) is a series of documents and maps that seek to improve and streamline the process of creating a topobathy DEM. The series aims to make topographic and bathymetric data and reference information accessible and make connections between data set quality and DEM application (such as coastal inundation modeling). Understanding the links between input data quality and application can help users create a DEM surface designed for a particular purpose, can help data collectors provide data sets that meet needs, and can assist technical users in defining their data requirements more explicitly. The Roadmap examines resources and processes associated with DEM creation, including the following: (1) available data resources, (2) processe...
Rapid and accurate prediction of peak storm surges across an extensive coastal region is necessar... more Rapid and accurate prediction of peak storm surges across an extensive coastal region is necessary to inform assessments used to design the systems that protect coastal communities' life and property. Significant advances in high-fidelity, physics-based numerical models have been made in recent years, but use of these models for probabilistic forecasting and probabilistic hazard assessment is computationally intensive. Several surrogate modeling approaches based on existing databases of high-fidelity synthetic storm surge simulations have been recently suggested to reduce computational burden without substantial loss of accuracy. In these previous studies, however, the surrogate modeling approaches relied on a tropical cyclone condition at one moment (usually at or near landfall), which is not always most correlated with the peak storm surge. In this study, a new one-dimensional convolutional neural network model combined with principal component analysis and a k-means clustering (C1PKNet) is presented that can rapidly predict peak storm surge across an extensive coastal region from time-series of tropical cyclone conditions, namely the storm track. The C1PKNet model was trained and cross-validated for the Chesapeake Bay area of the United States using existing database of 1031 high-fidelity storm surge simulations, including both landfalling and bypassing storms. Moreover, the performance of the C1PKNet model was evaluated based on observations from three historical hurricanes (Hurricane Isabel in 2003, Hurricane Irene in 2011, and Hurricane Sandy in 2012). The results indicate that the C1PKNet model is computationally e cient and can predict peak storm surges from realistic tropical cyclone track time-series. We believe that this new surrogate model can enhance coastal resilience by providing rapid storm surge predictions.
Interagency report: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines
<strong>Code and data for Section 2 of the Interagency report: Global and Regional Sea Leve... more <strong>Code and data for Section 2 of the Interagency report: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines</strong> <strong>Versions:</strong> Version 1.1 This one: updated region names Version 1.0 https://doi.org/10.5281/zenodo.5951626 This repository contains the code and data needed to produce the trajectories, projections, and observations for the Interagency report: Global and Regional Sea Level Rise Scenarios for the United States: Updated Mean Projections and Extreme Water Level Probabilities Along U.S. Coastlines. The report can be found on https://oceanservice.noaa.gov/hazards/sealevelrise/sealevelrise-tech-report-sections.html An interactive tool to study the observations, trajectories, and scenarios can be accessed from https://sealevel.nasa.gov/task-force-scenario-tool Frequently-asked questions: https://sealevel.sit.earthdata.nasa.gov/faq/16/ <strong>Authors</strong> William V. Sweet, NOAA National Ocean Service Benjamin D. Hamlington, NASA Jet Propulsion Laboratory Robert E. Kopp, Rutgers University Christopher P. Weaver, U.S. Environmental Protection Agency Patrick L. Barnard, U.S. Geological Survey Michael Craghan, U.S. Environmental Protection Agency Gregory Dusek, NOAA National Ocean Service Thomas Frederikse, NASA Jet Propulsion Laboratory Gregory Garner, Rutgers University Ayesha S. Genz, University of Hawai'i at Mānoa, Cooperative Institute for Marine and Atmospheric Research John P. Krasting, NOAA Geophysical Fluid Dynamics Laboratory Eric Larour, NASA Jet Propulsion Laboratory Doug Marcy, NOAA National Ocean Service John J. Marra, NOAA National Centers for Environmental Information Jayantha Obeysekera, Florida International University Mark Osler, NOAA National Ocean Service Matthew Pendleton, Lynker Daniel Roman, NOAA National Ocean Service Lauren Schmied, FEMA Risk Management Directorate William C. Veatch, U.S. Army Corps of Engineers Kathleen D. White, U.S. Department of Defense Ca [...]
Technical Considerations for Use of Geospatial Data in Sea Level Change Mapping and Assessment
This document is intended to provide technical guidance to agencies, practitioners, and coastal d... more This document is intended to provide technical guidance to agencies, practitioners, and coastal decision - makers seeking to use and/or collect geospatial data to assist with sea level change assessments and mapping products. There is a lot of information available today regarding sea level change and navigating this information can be challenging. This document seeks to clarify existing data and information and provide guidance on how to understand and apply this information to analysis and planning applications by directing readers to specific resources for various applications. There is no single approach to sea level change mapping and assessment. The specific data and information requirements of any user are unique depending on their application, location, and need. It is important to understand what to look for and what questions to ask when applying existing information or collecting new data. The discussion in this document is structured around four key questions to address ...
The National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-O... more The National Ocean Service (NOS) Center for Operational Oceanographic Products and Services (CO-OPS) provides the National infrastructure, science, and technical expertise to collect and distribute observations and predictions of water levels and currents to ensure safe, efficient and environmentally sound maritime commerce. The Center provides the set of water level and tidal current products required to support NOS' Strategic Plan mission requirements, and to assist in providing operational oceanographic data/products required by NOAA's other Strategic Plan themes. For example, COOPS provides data and products required by the National Weather Service to meet its flood and tsunami warning responsibilities. The Center manages the National Water Level Observation Network (NWLON), a national network of Physical Oceanographic Real-Time Systems (PORTS ®) in major U. S. harbors, and the National Current Observation Program consisting of current surveys in near shore and coastal areas utilizing bottom mounted platforms, subsurface buoys, horizontal sensors and quick response real time buoys. The Center: establishes standards for the collection and processing of water level and current data; collects and documents user requirements, which serve as the foundation for all resulting program activities; designs new and/or improved oceanographic observing systems; designs software to improve CO-OPS' data processing capabilities; maintains and operates oceanographic observing systems; performs operational data analysis/quality control; and produces/disseminates oceanographic products.
Advanced Inundation Modeling and Decision-Support Tools for Gulf Coast Communities
Solutions to Coastal Disasters 2008, 2008
The National Ocean Service's Storm Surge Partnership Project is a demonstration effort aimed... more The National Ocean Service's Storm Surge Partnership Project is a demonstration effort aimed at improving coastal resiliency to inundation through use of emerging technologies. The project's objectives include determining the needs of the management community, assembling ...
It is one thing to have a discussion or write about a one-or two-foot rise in the ocean surface a... more It is one thing to have a discussion or write about a one-or two-foot rise in the ocean surface and potential impacts to a local community; it is another to show someone a map highlighting the areas that would potentially be impacted. The ability to visualize the potential depth and inland extent of water gives us a better understanding of the corresponding impacts and consequences. Mapping sea level changes in a geographic information system (GIS) gives the user the ability to overlay the potentially impacted areas with other data such as critical infrastructure, roads, ecologically sensitive areas, demographics, and economics. Providing maps on the Web via Internet mapping technologies enables the user to have an interactive experience that truly brings out the "visual" part of the map definition. Over the past several years, the lessons learned from investigating pilot sea level change mapping applications have led to the development of a next-generation sea level rise and coastal flooding viewer. In addition, new mapping techniques have been developed to use high-resolution data sources to show flooding impacts on local public infrastructure, mapping confidence, flooding frequency, marsh impacts, and social and economic impacts from potential inundation. This paper will provide a brief history of previous sea level change visualization pilot projects, detailed discussion of new methods, current status of new tool development and outputs, and future plans for expanding to the rest of the U.S.
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Papers by Doug Marcy