CoSMoS-COAST Active
Coastal Resilience Project with USGS and Partners Receives Nearly $1 Million in Funds From NOAA
CoSMoS-COAST is a USGS-developed, large-scale coastal change prediction model. It seeks to model coastal change due to a variety of oceanographic and terrestrial processes across a multitude of spatiotemporal scales (e.g., local to national-scale).
Beaches, the first line of defense against extreme coastal storms, are thinning due to chronic erosion caused by rising sea levels, declining sediment supply, and entrenched coastal infrastructure. Reliable, quantitative predictions of coastal change are increasingly sought to support coastal management. Yet, few well-validated models exist.
CoSMoS-COAST is a USGS-developed, large-scale coastal change prediction model. It seeks to model coastal change due to a variety of oceanographic and terrestrial processes across a multitude of spatiotemporal scales (e.g., local to national-scale). The model was initially developed and applied as part of the larger USGS Coastal Storm Modeling System (CoSMoS) in Southern California. The CoSMoS-COAST model is unique in the scientific community because it applies data assimilation to calibrate site-specific behavior and characteristics into large-scale modeling applications. Recently, the model has been improved to integrate weekly satellite-derived shoreline observations of individual beaches over large regions (e.g., the entire California coastline), which provide a thousandfold increase in the amount of observational data to assimilate.
Through this and other research efforts, we continue to enhance the model towards the goal of providing national-scale predictions of coastal change. Additionally, we have sought to improve model workflows to incorporate output from other coastal change models in order to provide multi-model ensemble predictions.
Objectives
- Integrate satellite-derived observations of shoreline position into CoSMoS-COAST;
- Evaluate the accuracy of satellite-derived shoreline observations compared to traditional (e.g., LIDAR, GPS) surveys;
- Evaluate the accuracy of coastal change modeling predictions over large scales;
- Improve modeling capabilities of beach nourishments and fluvial (i.e. river) sediment inputs to the coastal zone;
- Integrate CoSMoS-COAST with dynamical models of beach and cliff position; and
- Integrate modern coastal change prediction methodology, based on CoSMoS-COAST, into the USGS Total Water Level (TWL) viewer based on the same wave and hydrodynamic forcing conditions.
Climate change-driven cliff and beach evolution at decadal to centennial time scales
Doubling of coastal flooding frequency within decades due to sea-level rise
A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change
A nonlinear, implicit one-line model to predict long-term shoreline change
- Overview
CoSMoS-COAST is a USGS-developed, large-scale coastal change prediction model. It seeks to model coastal change due to a variety of oceanographic and terrestrial processes across a multitude of spatiotemporal scales (e.g., local to national-scale).
Beaches, the first line of defense against extreme coastal storms, are thinning due to chronic erosion caused by rising sea levels, declining sediment supply, and entrenched coastal infrastructure. Reliable, quantitative predictions of coastal change are increasingly sought to support coastal management. Yet, few well-validated models exist.
CoSMoS-COAST is a USGS-developed, large-scale coastal change prediction model. It seeks to model coastal change due to a variety of oceanographic and terrestrial processes across a multitude of spatiotemporal scales (e.g., local to national-scale). The model was initially developed and applied as part of the larger USGS Coastal Storm Modeling System (CoSMoS) in Southern California. The CoSMoS-COAST model is unique in the scientific community because it applies data assimilation to calibrate site-specific behavior and characteristics into large-scale modeling applications. Recently, the model has been improved to integrate weekly satellite-derived shoreline observations of individual beaches over large regions (e.g., the entire California coastline), which provide a thousandfold increase in the amount of observational data to assimilate.
Through this and other research efforts, we continue to enhance the model towards the goal of providing national-scale predictions of coastal change. Additionally, we have sought to improve model workflows to incorporate output from other coastal change models in order to provide multi-model ensemble predictions.
Objectives
- Integrate satellite-derived observations of shoreline position into CoSMoS-COAST;
- Evaluate the accuracy of satellite-derived shoreline observations compared to traditional (e.g., LIDAR, GPS) surveys;
- Evaluate the accuracy of coastal change modeling predictions over large scales;
- Improve modeling capabilities of beach nourishments and fluvial (i.e. river) sediment inputs to the coastal zone;
- Integrate CoSMoS-COAST with dynamical models of beach and cliff position; and
- Integrate modern coastal change prediction methodology, based on CoSMoS-COAST, into the USGS Total Water Level (TWL) viewer based on the same wave and hydrodynamic forcing conditions.
- Science
- Data
- Publications
Filter Total Items: 16
Climate change-driven cliff and beach evolution at decadal to centennial time scales
Here we develop a computationally efficient method that evolves cross-shore profiles of sand beaches with or without cliffs along natural and urban coastal environments and across expansive geographic areas at decadal to centennial time-scales driven by 21st century climate change projections. The model requires projected sea level rise rates, extrema of nearshore wave conditions, bluff recessionAuthorsLi H. Erikson, Andrea C. O'Neill, Patrick L. Barnard, Sean Vitousek, Patrick W. LimberDoubling of coastal flooding frequency within decades due to sea-level rise
Global climate change drives sea-level rise, increasing the frequency of coastal flooding. In most coastal regions, the amount of sea-level rise occurring over years to decades is significantly smaller than normal ocean-level fluctuations caused by tides, waves, and storm surge. However, even gradual sea-level rise can rapidly increase the frequency and severity of coastal flooding. So far, globalAuthorsSean Vitousek, Patrick L. Barnard, Charles H. Fletcher, Neil Frazer, Li H. Erikson, Curt D. StorlazziA model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change
We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolutionAuthorsSean Vitousek, Patrick L. Barnard, Patrick W. Limber, Li H. Erikson, Blake ColeA nonlinear, implicit one-line model to predict long-term shoreline change
We present the formulation, validation, and application of a nonlinear, implicit one-line model to simulate long-term (decadal and longer) shoreline change. The purpose of the implicit numerical method presented here is to allow large time steps without sacrificing model stability compared to explicit approaches, and thereby improve computational efficiency. The model uses a Jacobian-free Newton-KAuthorsSean Vitousek, Patrick L. Barnard - News