• Archer, C. L., and Coauthors, 2014: Meteorology for coastal/offshore wind energy in the United States: Recommendations and research needs for the next 10 years. Bull. Amer. Meteor. Soc., 95, 515519, doi:10.1175/BAMS-D-13-00108.1.

    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., and Coauthors, 2009: Technical review of Rapid Refresh/RUC project. NOAA/ESRL/GSD Internal Review, 168 pp.

  • Bonner, W. D., 1968: Climatology of the low level jet. Mon. Wea. Rev., 96, 833850, doi:10.1175/1520-0493(1968)096<0833:COTLLJ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Carvalho, D., A. Rocha, M. Gomez-Gesteira, and C. Santos, 2014a: Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula. Appl. Energy, 135, 234246, doi:10.1016/j.apenergy.2014.08.082.

    • Search Google Scholar
    • Export Citation
  • Carvalho, D., A. Rocha, M. Gomez-Gesteira, and C. Santos, 2014b: Comparison of reanalyzed, analyzed, satellite-retrieved and NWP modelled winds with buoy data along the Iberian Peninsula coast. Remote Sens. Environ., 152, 480492, doi:10.1016/j.rse.2014.07.017.

    • Search Google Scholar
    • Export Citation
  • Colby, F. P., Jr., 2004: Simulation of the New England sea breeze: The effect of grid spacing. Wea. Forecasting, 19, 277285, doi:10.1175/1520-0434(2004)019<0277:SOTNES>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., and D. R. Novak, 2010: The New York Bight jet: Climatology and dynamical evolution. Mon. Wea. Rev., 138, 23852404, doi:10.1175/2009MWR3231.1.

    • Search Google Scholar
    • Export Citation
  • Doyle, J., and T. Warner, 1991: A Carolina coastal low-level jet during GALE IOP 2. Mon. Wea. Rev., 119, 24142428, doi:10.1175/1520-0493(1991)119<2414:ACCLLJ>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, doi:10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Dvorak, M. J., B. Corcoran, J. Ten Hoeve, N. McIntyre, and M. Jacobson, 2012a: US East Coast offshore wind energy resources and their relationship to peak-time electricity demand. Wind Energy, 16, 977997, doi:10.1002/we.1524.

    • Search Google Scholar
    • Export Citation
  • Dvorak, M. J., E. D. Stoutenburg, C. L. Archer, W. Kempton, and M. Z. Jacobson, 2012b: Where is the ideal location for a US East Coast offshore grid? Geophys. Res. Lett., 39, L06804, doi:10.1029/2011GL050659.

    • Search Google Scholar
    • Export Citation
  • Edson, J. B., and Coauthors, 2007: The Coupled Boundary Layers and Air–Sea Transfer Experiment in Low Winds (CBLAST-LOW). Bull. Amer. Meteor. Soc., 88, 341356, doi:10.1175/BAMS-88-3-341.

    • Search Google Scholar
    • Export Citation
  • Evensen, G., 2003: The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn., 53, 343367, doi:10.1007/s10236-003-0036-9.

    • Search Google Scholar
    • Export Citation
  • Hahmann, A. N., C. L. Vincent, A. Peña, J. Lange, and C. B. Hasager, 2015: Wind climate estimation using WRF model output: Method and model sensitivities over the sea. Int. J. Climatol., 35, 34223439, doi:10.1002/joc.4217.

    • Search Google Scholar
    • Export Citation
  • Helmis, C. G., Q. Wang, G. Sgouros, S. Wang, and C. Halios, 2013: Investigating the summertime low-level jet over the East Coast of the USA: A case study. Bound.-Layer Meteor., 149, 259276, doi:10.1007/s10546-013-9841-y.

    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, doi:10.1175/MWR3199.1.

    • Search Google Scholar
    • Export Citation
  • Hughes, C. P., and D. E. Veron, 2015: Characterization of low-level winds of southern and coastal Delaware. J. Appl. Meteor. Climatol., 54, 7793, doi:10.1175/JAMC-D-14-0011.1.

    • Search Google Scholar
    • Export Citation
  • Iacono, M. J., E. J. Mlawer, S. A. Clough, and J.-J. Morcrette, 2000: Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR Community Climate Model, CCM3. J. Geophys. Res., 105, 14 87314 890, doi:10.1029/2000JD900091.

    • Search Google Scholar
    • Export Citation
  • Kempton, W., C. L. Archer, A. Dhanju, R. W. Garvine, and M. Z. Jacobson, 2007: Large CO2 reductions via offshore wind power matched to inherent storage in energy end-uses. Geophys. Res. Lett., 34, L02817, doi:10.1029/2006GL028016.

    • Search Google Scholar
    • Export Citation
  • Manwell, J., A. Rogers, J. McGowan, and B. Bailey, 2002: An offshore wind resource assessment study for New England. Renew. Energy, 27, 175187, doi:10.1016/S0960-1481(01)00183-5.

    • Search Google Scholar
    • Export Citation
  • Monaldo, F. M., X. Lui, W. Pichel, and C. Jackson, 2014: Ocean wind speed climatology from spaceborne SAR imagery. Bull. Amer. Meteor. Soc., 95, 565569, doi:10.1175/BAMS-D-12-00165.1.

    • Search Google Scholar
    • Export Citation
  • Musial, W., and B. Ram, 2010: Large-scale offshore wind power in the United States: Assessment of opportunities and barriers. National Renewable Energy Laboratory Rep. NREL/TP-500–40745, 240 pp.

  • Novak, D., and B. A. Colle, 2006: Observations of multiple sea breeze boundaries during an unseasonably warm day in metropolitan New York City. Bull. Amer. Meteor. Soc., 87, 169174, doi:10.1175/BAMS-87-2-169.

    • Search Google Scholar
    • Export Citation
  • Nunalee, C., and S. Basu, 2014: Mesoscale modeling of coastal low-level jets: Implications for offshore wind resource estimation. Wind Energy, 17, 11991216, doi:10.1002/we.1628.

    • Search Google Scholar
    • Export Citation
  • Ryan, W. F., 2004: The low level jet in Maryland: Profiler observations and preliminary climatology. Maryland Department of the Environment, Air and Radiation Administration Tech. Rep., 43 pp.

  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., doi:10.5065/D68S4MVH.

  • Tewari, M., and Coauthors, 2004: Implementation and verification of the unified Noah land surface model in the WRF Model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 14.2A. [Available online at https://ams.confex.com/ams/84Annual/techprogram/paper_69061.htm.]

  • Thompson, G., R. M. Rasmussen, and K. Manning, 2004: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev., 132, 519542, doi:10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 50955115, doi:10.1175/2008MWR2387.1.

    • Search Google Scholar
    • Export Citation
  • Woods, B. K., T. Nehrkorn, and J. M. Henderson, 2013: A downscaled wind climatology on the outer continental shelf. J. Appl. Meteor. Climatol., 52, 18781890, doi:10.1175/JAMC-D-12-0216.1.

    • Search Google Scholar
    • Export Citation
  • Zhang, D., S. Zhang, and S. Weaver, 2006: Low-level jets over the mid-Atlantic states: A warm season climatology and a case study. J. Appl. Meteor. Climatol., 45, 194209, doi:10.1175/JAM2313.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 397 168 12
PDF Downloads 253 114 3

Improving the Mapping and Prediction of Offshore Wind Resources (IMPOWR): Experimental Overview and First Results

Brian A. ColleSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York

Search for other papers by Brian A. Colle in
Current site
Google Scholar
PubMed
Close
,
Matthew J. SienkiewiczSchool of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York

Search for other papers by Matthew J. Sienkiewicz in
Current site
Google Scholar
PubMed
Close
,
Cristina ArcherCollege of Earth, Ocean, and Environment, University of Delaware, Newark, Delaware

Search for other papers by Cristina Archer in
Current site
Google Scholar
PubMed
Close
,
Dana VeronCollege of Earth, Ocean, and Environment, University of Delaware, Newark, Delaware

Search for other papers by Dana Veron in
Current site
Google Scholar
PubMed
Close
,
Fabrice VeronCollege of Earth, Ocean, and Environment, University of Delaware, Newark, Delaware

Search for other papers by Fabrice Veron in
Current site
Google Scholar
PubMed
Close
,
Willett KemptonCollege of Earth, Ocean, and Environment, University of Delaware, Newark, Delaware

Search for other papers by Willett Kempton in
Current site
Google Scholar
PubMed
Close
, and
John E. MakUltraPure Air LLC, Setauket, New York

Search for other papers by John E. Mak in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The wind resource offshore of the East Coast of the United States is well known for its potential to provide abundant, clean, renewable, and domestic electricity. However, limited observations from this region are recorded at heights above the water that penetrate significantly into the planetary boundary layer (PBL). As a result, mesoscale models have been used to characterize the offshore wind resource in this region but have not been evaluated fully within the PBL due to the scarcity of observations. This paper describes the setup and some early results from the Improving the Mapping and Prediction of Offshore Wind Resources (IMPOWR) field study conducted in the Nantucket Sound area in 2013/14. The IMPOWR campaign provides a rich dataset of observations within the PBL from a variety of sources: high-frequency Long-EZ aircraft, a multilevel atmospheric and oceanic tower in Nantucket Sound, and lidars on the south shore of eastern Long Island and Block Island. In addition to new data for model validation and wind resource assessment, the IMPOWR field campaign provides new insights on meteorological features important for wind power development, such as the New York Bight jet and shallow marine layer.

CORRESPONDING AUTHOR: Dr. Brian A. Colle, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000, E-mail: brian.colle@stonybrook.edu

Abstract

The wind resource offshore of the East Coast of the United States is well known for its potential to provide abundant, clean, renewable, and domestic electricity. However, limited observations from this region are recorded at heights above the water that penetrate significantly into the planetary boundary layer (PBL). As a result, mesoscale models have been used to characterize the offshore wind resource in this region but have not been evaluated fully within the PBL due to the scarcity of observations. This paper describes the setup and some early results from the Improving the Mapping and Prediction of Offshore Wind Resources (IMPOWR) field study conducted in the Nantucket Sound area in 2013/14. The IMPOWR campaign provides a rich dataset of observations within the PBL from a variety of sources: high-frequency Long-EZ aircraft, a multilevel atmospheric and oceanic tower in Nantucket Sound, and lidars on the south shore of eastern Long Island and Block Island. In addition to new data for model validation and wind resource assessment, the IMPOWR field campaign provides new insights on meteorological features important for wind power development, such as the New York Bight jet and shallow marine layer.

CORRESPONDING AUTHOR: Dr. Brian A. Colle, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000, E-mail: brian.colle@stonybrook.edu
Save