Brian Blanton

The role of hydrodynamics in explaining variability in fish populations

A review of the physical processes present in coastal regions and their effect on pelagic stages of flatfish populations is presented. While quantitative understanding of processes affecting cross-shelf transport and exchange continues to be a fundamental problem shared by physical oceanographers and fisheries scientists studying the early life history of flatfish, advances in hydrodynamic and coupled physical-biological models have made it possible to begin to examine population-level implications of environmental processes. There is now a need to rank these processes in terms of their impact on recruit strength. Existing paradigms provide testable frameworks for explaining the role of physical variability in the observed population patterns, abundance and variability. Identifying explicit links between physical variability and recruitment could result in new approaches to fisheries management strategies.

Monitoring and Understanding Changes in Extremes: Extratropical Storms, Winds, and Waves

This scientific assessment examines changes in three climate extremes—extratropical storms, winds, and waves—with an emphasis on U.S. coastal regions during the cold season. There is moderate evidence of an increase in both extratropical storm frequency and intensity during the cold season in the Northern Hemisphere since 1950, with suggestive evidence of geographic shifts resulting in slight upward trends in offshore/coastal regions. There is also suggestive evidence of an increase in extreme winds (at least annually) over parts of the ocean since the early to mid-1980s, but the evidence over the U.S. land surface is inconclusive. Finally, there is moderate evidence of an increase in extreme waves in winter along the Pacific coast since the 1950s, but along other U.S. shorelines any tendencies are of modest magnitude compared with historical variability. The data for extratropical cyclones are considered to be of relatively high quality for trend detection, whereas the data for extreme winds and waves ar...

Lateral dynamic analysis and classification of barotropic tidal inlets

The dynamical balances at shallow tidal inlets are highly nonlinear, and can vary substantially over sub-kilometer scales. In this study, barotropic dynamics are examined with numerical experiments on a series of idealized inlets with differing inlet widths and lengths. Circulation and elevation fields obtained from fully nonlinear depth-integrated circulation models are used to reconstruct the contribution of each term in the momentum equations. Momentum terms are rotated into a streamline coordinate system to simplify interpretation of the dynamics. Spatial patterns in momentum reveal that the lateral balances at inlets can vary from nearly geostrophic to strongly cyclostrophic. Marked dynamical differences are seen between inlets with different lengths and widths. Inlet regions of geostrophic or cyclostrophic balances can be predicted using two dimensionless parameters, the dynamic length L* and dynamic width W*. A classification scheme is proposed using L* and W* to compare the idealized inlets analyzed here with inlets from 20 previous studies. Four distinct inlet types are identified and discussed.

Urgent Computing of Storm Surge for North Carolina's Coast

Forecasting and prediction of natural events, such as tropical and extra-tropical cyclones, inland flooding, and severe winter weather, provide critical guidance to emergency managers and decision-makers from the local to the national level, with the goal of minimizing both human and economic losses. This guidance is used to facilitate evacuation route planning, post-disaster response and resource deployment, and critical infrastructure protection and securing, and it must be available within a time window in which decision makers can take appropriate action. This latter element is that which induces the need for urgency in this area. In this paper, we outline the North Carolina Forecasting System (NCFS) for storm surge and waves for coastal North Carolina, which is threatened by tropical cyclones about once every three years. We initially used advanced cyberinfrastructure techniques (e.g., opportunistic grid computing) in an effort to provide timely guidance for storm surge and wave impacts. However, our experience has been that a distributed computing approach is not robust enough to consistently produce the real-time results that end users expect. As a result, our technical approach has shifted so that the reliable and timely delivery of forecast products has been guaranteed by provisioning dedicated computational resources as opposed to relying on opportunistic availability of external resources. Our experiences with this forecasting effort is discussed in this paper, with a focus on Hurricane Irene (2011) that impacted a substantial portion of the US east coast from North Carolina, up along the eastern seaboard, and into New England.

Comparison of Observed and Modeled Drifter Trajectories in Coastal Regions: An Improvement through Adjustments for Observed Drifter Slip and Errors in Wind Fields

Abstract Lagrangian particle tracking using three-dimensional (3D) numerical modeling approaches has become an important tool in coastal oceanography. In this note, an approach is described that can reduce the difference between observed and numerical drifter trajectories in the coastal ocean by including corrections to the water velocity due to differences between observed winds and the wind field used to drive the 3D circulation model and some specific characteristics of the observed drifters in the algorithm that estimate the numerical trajectory. Quantitative improvements are obtained whereby the separation distance between the numerical and observed drifters is almost halved (in this particular field case from 2.6 to 1.4 km day−1).

Forecasting the Coastal Ocean: Resolution, Tide, and Operational Data in the South Atlantic Bight

Abstract This paper addresses shelf-scale simulation with dominant open-water boundary conditions obtained by inversion of interior data. Important, established operational data streams are located along the shore of the study area, in areas influenced strongly by the local geometry. Failure to properly resolve the modeled near field surrounding these data results in their incorrect interpretation, causing invalid inversions and erroneous field estimates far across the shelf. Specifically, improving the model fit to the unresolved data leads to skill degeneration farther offshore and generally unacceptable field estimates remarkably far from shore. Proper near-field resolution leads to valid interpretation and inversion of the same data, with high inverse skill apparent across the shelf. The resolution required is within reach of todays technology.

The CI-Flow Project: A System for Total Water Level Prediction from the Summit to the Sea

The objective of the Coastal and Inland Flooding Observation and Warning (CI-FLOW) project is to prototype new hydrometeorologic techniques to address a critical NOAA service gap: routine total water level predictions for tidally influenced watersheds. Since February 2000, the project has focused on developing a coupled modeling system to accurately account for water at all locations in a coastal watershed by exchanging data between atmospheric, hydrologic, and hydrodynamic models. These simulations account for the quantity of water associated with waves, tides, storm surge, rivers, and rainfall, including interactions at the tidal/surge interface. Within this project, CI-FLOW addresses the following goals: i) apply advanced weather and oceanographic monitoring and prediction techniques to the coastal environment; ii) prototype an automated hydrometeorologic data collection and prediction system; iii) facilitate interdisciplinary and multiorganizational collaborations; and iv) enhance techniques and techn...

Real-Time Forecasting and Visualization of Hurricane Waves and Storm Surge Using SWAN+ADCIRC and FigureGen

Storm surge due to hurricanes and tropical storms can result in significant loss of life, property damage, and long-term damage to coastal ecosystems and landscapes. Computer modeling of storm surge is useful for two primary purposes: forecasting of storm impacts for response planning, particularly the evacuation of vulnerable coastal populations; and hindcasting of storms for determining risk, development of mitigation strategies, coastal restoration, and sustainability. Model results must be communicated quickly and effectively, to provide context about the magnitudes and locations of the maximum waves and surges in time for meaningful actions to be taken in the impact region before a storm strikes.In this paper, we present an overview of the SWAN + ADCIRC modeling system for coastal waves and circulation. We also describe FigureGen, a graphics program adapted to visualize hurricane waves and storm surge as computed by these models. The system was applied recently to forecast Hurricane Isaac (2012) as it made landfall in southern Louisiana. Model results are shown to be an accurate warning of the impacts of waves and circulation along the northern Gulf coastline, especially when communicated to emergency managers as geo-referenced images.

Scenario-Based Hazard Trees for Depicting Resolution of Hurricane Uncertainty over Time

AbstractGreat uncertainty surrounds the future track, intensity, and resulting flooding and wind hazards associated with an offshore hurricane. As time progresses, that uncertainty is reduced, but ...

An Integrated Scenario Ensemble-Based Framework for Hurricane Evacuation Modeling: Part 1-Decision Support System: Hurricane Evacuation Decision Support

This article introduces a new integrated scenario-based evacuation (ISE) framework to support hurricane evacuation decision making. It explicitly captures the dynamics, uncertainty, and human-natural system interactions that are fundamental to the challenge of hurricane evacuation, but have not been fully captured in previous formal evacuation models. The hazard is represented with an ensemble of probabilistic scenarios, population behavior with a dynamic decision model, and traffic with a dynamic user equilibrium model. The components are integrated in a multistage stochastic programming model that minimizes risk and travel times to provide a tree of evacuation order recommendations and an evaluation of the risk and travel time performance for that solution. The ISE framework recommendations offer an advance in the state of the art because they: (1) are based on an integrated hazard assessment (designed to ultimately include inland flooding), (2) explicitly balance the sometimes competing objectives of minimizing risk and minimizing travel time, (3) offer a well-hedged solution that is robust under the range of ways the hurricane might evolve, and (4) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. A case study for Hurricane Isabel (2003) in eastern North Carolina is presented to demonstrate how the framework is applied, the type of results it can provide, and how it compares to available methods of a single scenario deterministic analysis and a two-stage stochastic program.