Jeffrey L. Hanson

A Multigrid Wave Forecasting Model: A New Paradigm in Operational Wave Forecasting

AbstractA new operational wave forecasting system has been implemented at the National Centers for Environmental Prediction (NCEP) using the third public release of WAVEWATCH III. The new system uses a mosaic of grids with two-way nesting in a single model. This global system replaces a previous operational wave modeling suite (based on the second release of WAVEWATCH III). The new forecast system consists of nine grids at different resolutions to provide the National Weather Service (NWS) and NCEP centers with model guidance of suitable resolution for all areas where they have the responsibility of providing gridded forecast products. New features introduced in WAVEWATCH III, such as two-way nesting between grids and carving out selected areas of the computational domain, have allowed the operational model to increase spatial resolution and extend the global domain closer to the North Pole, while at the same time optimizing the computational cost. A spectral partitioning algorithm has been implemented to...

Extraction of coastal wavefield properties from X-band radar

The dynamic wave field in a high-energy coastal environment is investigated using frequency direction wave spectra obtained by nautical X-band radar imagery. Nautical radars are generally used for navigation and ship traffic control. Under various conditions (wind speed > 3m/s, significant wave height > 0.5m1), signatures of the sea surface (sea clutter) become visible in the near range (less than 3 nautical miles) of nautical radar images. Swell and wind sea waves become visible in nautical radar images as they modulate the sea clutter signal. Since standard X-band nautical radar systems scan the sea surface with high temporal and spatial resolution, they are able to monitor the sea surface in both time and space. The combination of the temporal and spatial wave information allows the determination of unambiguous directional wave spectra.

The US IOOS Coastal and Ocean Modeling Testbed for advancing research to applications

Coastal waters and lowlands of the U.S. are threatened by climate change, sea-level rise, flooding, oxygen depleted “dead zones”, oil spills and unforeseen disasters. With funding from U.S. Integrated Ocean Observing System (IOOS®), the Southeast University Research Association (SURA) facilitated strong and strategic collaborations among experts from academia, federal operational centers and industry and guided the U.S. IOOS Coastal and Ocean Modeling Testbed (COMT) through its successful pilot phase. The focus of this paper is the development of the cyberinfrastructure, including successes and challenges during this pilot phase of the COMT. This is the first testbed intended to serve multiple federal agencies and be focused on the coastal ocean and Great Lakes. National Oceanic and Atmospheric Administrations (NOAA) National Center for Environmental Prediction (NCEP) has offered an operational base for the COMT, which addresses NCEP modeling challenges in coastal predictions by enabling the transition of research improvements into NCEPs operational forecast capability. Additional Federal participants include Navy, U.S. Geological Survey (USGS), Environmental Protection Agency and the U.S. Army Corps of Engineers (USACE). The mission of the Coastal and Ocean Modeling Testbed (COMT) is to use targeted research and development to accelerate the transition of scientific and technical advances from the coastal and ocean modeling research community to improve identified operational ocean products and services (i.e. via research to applications and also applications to research). The vision of the program is to enhance the accuracy, reliability, and scope of the federal suite of operational ocean modeling products, while ensuring its user community is better equipped to solve challenging coastal problems and recognize the COMT to be where the best coastal science is operationalized. Since its initiation in June, 2010, the COMT has developed to include a flexible and extensible community research framework to test and evaluate predictive models to address key coastal environmental issues. Initially, the COMT addressed three general research challenges of socioeconomic relevance: estuarine hypoxia, shelf hypoxia, and coastal inundation. A cyberinfrastructure was developed to facilitate model assessment based on community standards, including a distributed data repository, automated cataloging mechanism, quick browse facility, and tools for flexible and detailed scientific investigation of both model output and data. Models, tools and techniques from the Testbed are starting to be incorporated into the NOAA research and operational frameworks, reducing the transition time from research to federal operations. Ultimately, the COMT has had many successes as a pilot project and provides an effective and efficient environment for coordinating and improving coastal ocean and Great Lakes modeling efforts needed by the federal operational forecasting community.

North Atlantic wind and wave climate: Observed extremes, hindcast performance, and extratropical recurrence intervals

An investigation of the extreme offshore wind and wave climate in the mid-Atlantic region has been conducted for the U.S. Bureau of Safety and Environmental Enforcement (BSEE). The overall objective of the project is to assist with the development of Metocean standards for offshore wind farm design, and establish a 100-yr extratropical wind speed and wave height climatology for the specific regions of interest. Specific accomplishments include evaluating and selecting a climatological data base to use for the study, establish a technique for performing the extremal analysis, and generating maps of 100-yr return period wind speeds and wave heights. Measured data from National Data Buoy Center (NDBC) and Scripps Coastal Data Information Program (CDIP) offshore stations were used to characterize the storm climate and to assess the strengths and weaknesses of two North Atlantic Ocean hindcasts. Hindcasts under consideration included the 20-yr USACE Wave Information Studies (WIS) with kinematically adjusted storm winds, and a new 30-yr WAVEWATCH III® hindcast using National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis Reforecast (CFSRR) winds. Using the latest available techniques for wave spectral partitioning, a sea and swell climatology for the region is presented. Robust error metrics quantify hindcast performance in replicating both the observed wave systems and event peak conditions. Each hindcast product was found to have specific strengths and weaknesses. Although the WIS hindcast is shown to have superior winds, the WIS and NCEP wave hindcast results are mixed. As the NCEP product is presently only available for research purposes, the WIS hindcast was selected for use in computation of the final map products. A total of four extremal analysis techniques were evaluated for assessment of extratropical wind and wave storm data. The Empirical Simulation Technique (EST) provided in [14] employs a life-cycle approach to extreme value analysis. In contrast, the Generalized Pareto Distribution (GPD) [2], Weibull [11], and Generalized Extreme Value (GEV) [22] methods are parametric extrapolations to the data. To evaluate these approaches in our area of interest, extratropical Storm populations were identified at five test stations by applying both Peak over Threshold (POT) and Annual Maximum Series (AMS) techniques (for use with the GEV) to the NCEP 30-yr hindcast which is the longest hindcast currently available. Tropical storms were removed by an automated process linked to the North Atlantic Hurricane Database (HURDAT). The four extremal techniques were applied to the storm populations and comparisons made at the 50- and 100-yr recurrence interval. The selection of a final methodology will be described and resulting maps of the 50- and 100-yr recurrence interval extratropical wind speeds and wave heights will be presented.

Spatial Tracking of Numerical Wave Model Output Using a Spiral Search Algorithm

Numerical ocean wave models output a frequency-direction energy spectrum at each grid point in space and time over a defined domain (e.g. the Pacific Ocean). After identifying each wave component (wind-sea, young swell and mature swell) using a spectral partitioning technique, a spiral search algorithm is used to identify the different wave systems, which are a cluster of wave-components propagating from a common origin on the ocean. This spiral search algorithm is being tested on output from two different wave models: the NOAA National Center for Environmental Prediction (NCEP) WaveWatch III and the Delft near-shore wave model SWAN (Simulating WAve Near shore). The tracking algorithm, prototyped in Matlab, spirals once through the entire domain to identify existing wave systems. A second loop then combines neighboring wave systems initially separated by land.

Alongshore momentum transfer to the nearshore zone from energetic ocean waves generated by passing hurricanes

Wave and current measurements from a cross-shore array of nearshore sensors in Duck, NC, are used to elucidate the balance of alongshore momentum under energetic wave conditions with wide surf zones, generated by passing hurricanes that are close to and far from to the coast. The observations indicate that a distant storm (Hurricane Bill, 2009) with large waves has low variability in directional wave characteristics resulting in alongshore currents that are driven mainly by the changes in wave energy. A storm close to the coast (Hurricane Earl, 2010), with strong local wind stress and combined sea and swell components in wave energy spectra, has high variability in wave direction and wave period that influence wave breaking and nearshore circulation as the storm passes. During both large wave events, the horizontal current shear is strong and radiation stress gradients, bottom stress, wind stress, horizontal mixing, and cross-shore advection contribute to alongshore momentum at different spatial locations across the nearshore region. Horizontal mixing during Hurricane Earl, estimated from rotational velocities, was particularly strong suggesting that intense eddies were generated by the high horizontal shear from opposing wind-driven and wave-driven currents. The results provide insight into the cross-shore distribution of the alongshore current and the connection between flows inside and outside the surf zone during major storms, indicating that the current shear and mixing at the interface between the surf zone and shallow inner shelf is strongly dependent on the distance from the storm center to the coast.

Oceanographic Observations dataset : data management plan

This Data Management Plan details the Oceanographic Observations dataset, which is maintained at the U.S. Army Corps of Engineers (USACE) Engineer Research and Development Center Coastal and Hydraulics Laboratory (ERDC-CHL) Field Research Facility (FRF), Duck, NC. The plan was developed to support the FRF Data Integration Framework (FDIF) project. Information is organized in the following categories: general description, points of contact, data stewardship, data documentation, data sharing, initial data storage and protection, longterm archiving and preservation, hardware and software requirements, products/programs, tools, references, data catalog, and abbreviations and acronyms. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR.

Air-sea forcing of coastal ocean sea surface temperature

Nearshore sea surface temperatures show both strong seasonal trends and rapid changes associated with local weather events. As a result, commercial fishing operations search and rescue services, and recreational users have a very limited capability to predict expected sea surface temperatures for any given day. We use empirical and neural net modeling techniques to describe the seasonal relationships between wind velocity, offshore sea surface temperature, air temperature, wave energy and nearshore sea surface temperature along the Outer Banks of North Carolina. In the winter months, nearshore sea surface temperature is influenced by both offshore sea surface temperatures and air temperature, both of which reflect solar input. During the summer months, the ocean is stratified. Consequently, winds influence nearshore sea surface temperatures by inducing upwelling and downwelling phenomena, resulting in decreases and increases in nearshore SSTs respectively. The spring and fall seasons exhibit trends from both the summer and the winter, but these trends are weaker. We also look at how the greater prevalence of winds and waves during various seasons also influences nearshore sea surface temperatures. The resulting neural net model can predict nearshore sea surface temperature with a reasonable amount of accuracy.