Quantifying the Uncertainty in the Weather Research and Forecasting Model under Sea Breeze and Low-Level Jet Conditions in the New York Bight: Importance to Offshore Wind Energy

Elizabeth J. McCabe Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York

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Jeffrey M. Freedman Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York

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Abstract

As the development of offshore wind energy continues in the New York Bight (NYB; defined as the region of ocean waters south of Long Island and east of New Jersey), understanding mesoscale circulations such as the sea breeze and accompanying low-level jet (LLJ) is increasingly important. With offshore wind turbines continuing to increase in size and hub heights extending up to 150 m or more above the ocean surface, there is a need for long-term atmospheric measurements within the rotor plane. Limited access to publicly available and long-term wind profiles in the NYB makes it necessary to rely on numerical weather prediction models to fully understand the dynamics of the offshore wind field. While models can provide a four-dimensional picture of the sea-breeze circulation and extent of the LLJ (defined here as a wind speed maximum of 150–300 m above the ocean surface), they exhibit poor performance in reproducing these features. Using the Weather Research and Forecasting (WRF) Model, this study performs sensitivity analyses to determine the best configuration for reproducing the temporal and spatial dynamics of the NYB sea breeze and LLJ. We test seven planetary boundary layer (PBL) schemes, two land surface schemes, sea surface temperature fields, and an urban surface physical parameterization to examine model performance and accuracy. Sensitivity analysis testing 18 different WRF configurations determines that the Mellor–Yamada–Janjić (MYJ) PBL scheme, combined with the Noah land surface model and the urban parameterization turned off, is best suited to model these mesoscale summertime phenomena.

© 2025 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Elizabeth McCabe, emccabe@albany.edu

Abstract

As the development of offshore wind energy continues in the New York Bight (NYB; defined as the region of ocean waters south of Long Island and east of New Jersey), understanding mesoscale circulations such as the sea breeze and accompanying low-level jet (LLJ) is increasingly important. With offshore wind turbines continuing to increase in size and hub heights extending up to 150 m or more above the ocean surface, there is a need for long-term atmospheric measurements within the rotor plane. Limited access to publicly available and long-term wind profiles in the NYB makes it necessary to rely on numerical weather prediction models to fully understand the dynamics of the offshore wind field. While models can provide a four-dimensional picture of the sea-breeze circulation and extent of the LLJ (defined here as a wind speed maximum of 150–300 m above the ocean surface), they exhibit poor performance in reproducing these features. Using the Weather Research and Forecasting (WRF) Model, this study performs sensitivity analyses to determine the best configuration for reproducing the temporal and spatial dynamics of the NYB sea breeze and LLJ. We test seven planetary boundary layer (PBL) schemes, two land surface schemes, sea surface temperature fields, and an urban surface physical parameterization to examine model performance and accuracy. Sensitivity analysis testing 18 different WRF configurations determines that the Mellor–Yamada–Janjić (MYJ) PBL scheme, combined with the Noah land surface model and the urban parameterization turned off, is best suited to model these mesoscale summertime phenomena.

© 2025 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Elizabeth McCabe, emccabe@albany.edu
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