Laura Palamara

Analysis of the wind resource off New Jersey for offshore wind energy development

The state of New Jersey has the goal of producing 23% of its energy from renewable sources by 2021. Offshore wind is envisioned as being part of that renewable portfolio. To meet this goal New Jersey passed the nations first offshore wind renewable energy standard which requires that at least 1,100 megawatts (MW) by 2021. Currently NJ has 0 MW of offshore wind energy. In order to reduce the risk associated with installing these turbines, the Rutgers University Coastal Ocean Observation Laboratory has undertaken a two year study of the ocean winds and currents to provide insight to the wind farm developers to the best locations for siting the wind turbines. A 13 MHz HF radar network was installed to measure the surface currents every 2 km out to a range of 60 km from the coast. These surface current measurements were validated against surface wind measurements from available meteorological stations. The surface currents will then be used to validate the surface winds from a weather model that has been created for this program.

Cooperative development of dynamic habitat models informed by the Integrated Ocean Observing System (IOOS) informs fisheries management decision making in the coastal ocean.

Defining pelagic habitat indicators for migratory fish is particularly interesting and challenging due to the complex interaction between the marine food web and the physical variability. Through a multidisciplinary study, a group of experts in marine ecology, physical oceanography and stock assessment from the fishing industry, government and academia developed a method to explicitly account for shifting habitat distributions in fish population assessments. The study group initially developed a thermal niche model for an important shortlived pelagic forage fish, Atlantic Butterfish (Peprilus traicanthus) in the Northwest Atlantic Ocean. This niche model was coupled to a hindcast of daily bottom water temperature derived from a de-biased regional numerical ocean model (ROMS) in order to project thermal habitat suitability in the Northwest Atlantic on a daily basis over the last 40 years. The hindcast of thermal habitat suitability was used to estimate the proportion of thermal habitat suitability available on the Northeast US continental shelf that was sampled on fishery-independent surveys conducted during the spring and fall. We were able to create 40 years of daily maps of predicted butterfish thermal habitat suitability. This time series of Habitat Suitability was then used to determine a time dependent availability, or stock range, based on butterfish thermal niche space. The time dependent availability was then provided to the stock assessment scientists for inclusion in the model.

Toward dynamic marine spatial planning tools: Can we inform fisheries stock assessments by using dynamic habitat models informed by the integrated ocean observing system (IOOS)?

Since marine organisms are tightly coupled to the properties of the turbulent ocean fluid, the locations of critical habitat can change rapidly in time and space. Historically it has been difficult to measure these dynamic properties, but advances in ocean observing technologies allow us to measure many aspects of habitat (e.g. surface temperature, currents) and model others (e.g. bottom temperature, phytoplankton, zooplankton) over large spatial scales with fine temporal resolution. We observed a strong relationship between bottom temperature and butterfish (Peprilus triacanthus) distribution on the Mid Atlantic Bight continental shelf and used modeled temperature from 1958-2007 to observe changes in the spread of predicted habitat. Predicted habitat maps showed high seasonal and high interannual variability. This model was incorporated into the 2013 Butterfish stock assessment. In addition, observing platforms like gliders have become resources to expanding tracking studies that can now target pelagic habitats of the target species. We see these approaches as a step toward ecosystem based solutions that actually account for the measured dynamics of the system.

Using ocean observing systems and local ecological knowledge to nowcast butterfish bycatch events in the Mid-Atlantic Bight longfin squid fishery

Through an interdisciplinary workgroup of habitat scientists, oceanographers, fishery managers, social scientists, and commercial fishermen we developed ecologically informed models for the specific purpose of reducing butterfish (Peprilus triacanthus) bycatch in the longfin squid (Doryteuthis pealeii) fishery in the Mid-Atlantic Bight (MAB). We used generalized additive modeling (GAM) to associate butterfish biomass collected during National Marine Fisheries Service (NMFS) bottom trawl surveys with benthic and pelagic habitat characteristics. Pelagic variables were obtained from the trawl survey CTD, satellite and high-frequency radar. The sea surface measures of temperature and color from the satellites and the surface current fields from the HF radar were provided through the Mid-Atlantic Regional Association Coastal Ocean Observing System (MARACOOS), a regional component of the U.S. Integrated Ocean Observing System (IOOS).

Rutgers university coastal ocean observation laboratory (RU-COOL) advanced modeling system developed to cost-effectively support offshore wind energy development and operational applications

Studies are underway that are evaluating the offshore wind resource along the coast of New Jersey in an effort to determine the variability of the wind resource. One major source of variability is the sea-land breeze circulation that occurs during periods of peak energy demand. The sea breeze front, driven by the thermal difference between the warm land and relatively cooler ocean during hot summer afternoons, propagates inland and under weak atmospheric boundary layer wind conditions can affect much of the state. However, little is known about the offshore component of the sea breeze circulation. A large zone of subsidence over the coastal ocean, and subsequent divergence near the surface, is known to occur in unison with the inland-propagating sea breeze front. RU-COOLs unique monitoring and modeling endeavors are focused on exploring the details of these offshore dynamics of the sea breeze circulation and its development during both coastal upwelling and non-upwelling events. A case study from the August 13, 2012 is analyzed in this paper; coastal upwelling resulted from persistent south to southeasterly winds for days. In addition, a sea breeze front formed in the afternoon, propagating inland and producing a zone of weak winds offshore that coincides with the targeted area of offshore wind development. Model results, using unique declouded satellite sea surface temperature data, are validated inshore against weather radar and offshore against coastal ocean radar (CODAR). Small-scale offshore wind variability is resolved and verified in the model, which will be critical for producing accurate and reliable offshore wind resource assessments and precise operational forecasts for the future.

Impact of ocean observations on hurricane forecasts in the Mid-Atlantic: Forecasting lessons learned from Hurricane Irene

Hurricane Irene followed a track that curved northward over the Bahamas and ran directly over the U.S. east coast from Cape Hatteras to New England in August of 2011, causing severe storm surges, intense inland flooding, loss of life and over

Ocean observatory data are useful for regional ­habitat modeling of species with different vertical habitat preferences

8 billon in storm damage. While the ensemble of atmospheric forecast models accurately predicted the hurricane timing and track, the hurricane intensity was consistently over-predicted. Data from the U.S. Integrated Ocean Observing System (IOOS) were used to better understand the potential impact of the Mid-Atlantic Bights coastal ocean on the Hurricane Irene intensity forecast.