Phase One: 14 April 2011-13 April 2013

Phase Two: 24 June 2013-23 June 2014alt

Phase Three: 24 June 2014-23 June 2015


The Rutgers University Center for Ocean Observing Leadership (RU-COOL) is one of the world’s leaders in the study of physical and biological environmental conditions for the coastal ocean and it is the foremost expert in the study of the offshore waters along coastal NJ and the New York Bight (Schofield et al., 2008). RU-COOL has over a decade of experience applying advanced ocean observing technology (e.g. Schofield et al, 2007) along with atmospheric and ocean models to support a network of State, Local, and Federal government agencies (Glenn and Schofield, 2003).  Additionally, the Rutgers Department of Marine and Coastal Sciences (DMCS) has established several academic-government-industry partnerships to accomplish a wide array of innovative research and applied goals for public, scientific, and military applications (Glenn and Schofield, 2009). RU-COOL is a member of the Rutgers Energy Institute (REI) which integrates Rutgers’ expertise in science, engineering, economics, and policy, putting it at the forefront of alternative energy research. (  The technologies developed and employed by RU-COOL have been tried, tested, and accepted by the world’s foremost experts in the scientific community. Additionally, we have extensive experience running the state-of-the-art Weather Research and Forecasting (WRF) model, which has been optimized for research quality simulations (NSF Ocean Observing Initiative) and operational applications (NOAA Integrated Ocean Observing System) for the coastal ocean from Cape Cod to Cape Hatteras. This model has been well tested through a cooperative education operational forecasting project with PSEG that provided highly accurate and reliable information for severe storm management and power restoration activities.  The innovative Rutgers WRF (RU-WRF) model is also configured for offshore wind resource evaluations.

The variability in the wind resource at atmospheric heights representative of offshore wind turbine dimensions in conjunction with varying energy demand must be taken into account to ensure economical and reliable electrical grid management.  Therefore, the “risks” and associated costs resulting from the variability of wind power production and uncertain demand requirements can be significantly reduced with a representative analytical/predictive program designed specifically for each offshore wind energy site, transmission/distribution hubs, and affected adjacent coastal/inland areas.  RU-COOL has developed an innovative monitoring/modeling program that is designed for realistic coastal/offshore wind resource assessments that are relevant to the offshore area that is adjacent to NJ’s coast.  The advanced and adaptive monitoring/modeling programs developed by RU-COOL have been extensively applied to determine the climatology and associated variability of both the mesoscale and microscale wind resource encompassed by NJ’s offshore area that is designated for wind energy development (Glenn and Dunk, 2013).  The final reports for Phase I II and III of the associated project, “An Advanced Atmospheric/Ocean Assessment Program Designed to Reduce the Risks Associated with Offshore Wind Energy Development Defined by the NJ Energy Master Plan and the NJ Offshore Wind Energy Economic Development Act”, can be reviewed using the links provided below.

The technologies developed by RU-COOL include high-resolution sea surface current monitoring along with representative surface wind field estimations determined by coastal radar (CODAR), which is used to detect sea breeze development and spatially evaluate model performance.  Also, RU-COOL has developed a unique product for determining realistic sea surface temperatures (SSTs) detected by infrared (IR) satellite remote sensing.  This product enables high-resolution SST detection during both clear and cloudy atmospheric conditions.  The spatial and temporal resolution of SSTs derived enables identification of coastal upwelling centers that affect the extent of sea breeze propagation and vertical development.  Furthermore, it has been demonstrated that SST is one of the most significant model inputs for determining the dynamics of the offshore wind resource.  Therefore, advanced and adaptive monitoring/modeling programs developed by RU-COOL should prove to be the most accurate and representative techniques for analyzing and predicting the wind characteristics along with other atmospheric/oceanic parameters that are specific for NJ’s coastal and adjacent offshore areas. 










 Virtual Met Station Data Directory



Final Report Phase One (For Ideal Viewing of PDFs right click and select "save as")

Final Report Phase Two (For Ideal Viewing of PDFs right click and select "save as")

Final Report Phase Three

HF Radar Diagnostics

HF Radar Totals


  80 m 90 m 100 m 110 m 120 m
ANNUAL  annual-80 annual-90 annual-100 annual-110 annual-120



  annual-d-80 annual-d-90    annual-d-100 annual-d-110  annual-d-120 
 SPRING   spring-80   spring-90   spring-100 spring-110    spring-120



  spring-d-80   spring-d-90   spring-d-100   spring-d-110 spring-d-120 
 SUMMER   summer-80   summer-90   summer-100   summer-110 summer-120 



  summer-d-80   summer-d-90   summer-d-100   summer-d-110   summer-d-120
 FALL   fall-80   fall-90   fall-100 fall-110    fall-120



fall-d-80    fall-d-90 fall-d-100  fall-d-110    fall-d-120
 WINTER   winter-80   winter-90   winter-100   winter-110   winter-120



winter-d-80    winter-d-90   winter-d-100   winter-d-110   winter-d-120

Next Page > > Monthly Wind Resource Maps 

Last Page > > Wind Resource Maps Extended Field



Related Publications:

Growing a Distributed Ocean Observatory: Our View from the COOL Room

Performance Evaluation of SeaSonde High-Frequency Radar for Vessel Detection

Operation and Application of a Regional High-Frequency Radar Newtork in the Mid-Atlantic Bight

The Trans-Atlantic Slocum Glider Expeditions: A Catalyst for Undergraduate Participation in Ocean Science Technology

A Regional Slocum Glider Network in the Mid-Atlantic Bight Leverages Broad Community Engagement

Implementing a Southern Ocean Observing System

Autonomous Gliders Reveal Features of the Water Column Associated with Foraging by Adelie Penguins

Recent Changes in Phytoplankton Communities Associated with Rapid Regional Climate Change Along the Western Antarctic Peninsula

Automated Sensor Networks to Advance Ocean Sciences

How do Polar Marine Ecosystems Respond to Rapid Climate Change?

Analysis of the Wind Resource off New Jersey for Offshore Wind Energy Development

Process-Driven Improvements to Hurricane Intensity and Storm Surge Forecasts in the Mid-Atlantic Bight: Lessons Learned from Hurricanes Irene and Sandy

Analysis of the Wind Resource off New Jersey for Offshore Wind Energy Development

Rutgers University Coastal Ocean Observation Laboratory (RU-COOL) Advanced Modeling System Developed to Cost-Effectively Support Offshore Wind Energy Development and Operational Applications



Related Presentations:

Webinar: Evaluation of New Jersey Offshore Wind Resource

An Advanced Atmosphere/Ocean Assessment Program: Reducing the Risks Associated with Offshore Wind Energy Development BPU Kickoff

An Advanced Atmosphere/Ocean Assessment Program: Reducing the Risks Associated with Offshore Wind Energy Development BPU Interim Report

Exploring Offshore Wind Energy: Why is it important and what is being done at Rutgers?

RU-COOL Advanced Modeling System in Support of Offshore Wind Energy Development and Operational Applications: Investigating the NJ Sea/Land Breeze

Impact of Ocean Observations on Hurricane Irene and Hurricane Sandy Forecasts (poster)

Impact of Ocean Observations on Hurricane Irene and Hurricane Sandy (presentation)

Funding provided by alt This study benefits from and contributes to the  alt through alt