Using MM5 to hindcast the ocean surface forcing fields over the Gulf of Maine and Georges Bank Region

• Published in: Journal of Atmospheric and Oceanic Technology
• Main Authors: Chen, Changsheng, Beardsley, Robert C., Hu, Song, Xu, Qichun, Lin, Huichan
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Meteorological Society 2005
• Subjects: Eta; Northwest Atlantic
• Online Access: https://hdl.handle.net/1912/4187

Author Posting. © American Meteorological Society 2005. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Atmospheric and Oceanic Technology 22 (2005): 131–145, doi:10.1175/JTECH-1682.1. The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) is applied to the Gulf of Maine/Georges Bank (GoM/GB) region. This model is configured with two numerical domains with horizontal resolutions of 30 and 10 km, respectively, and driven by the NCAR-Eta weather model through a nested grid approach. Comparison of model-computed winds, wind stress, and heat flux with in situ data collected on moored meteorological buoys in the western GoM and over GB in 1995 shows that during the passage of atmospheric fronts over this region, MM5 provides a reasonable prediction of wind speed but not wind direction, and provides a relatively accurate estimation of longwave radiation but overestimates sensible and latent fluxes. The nudging data assimilation approach with inclusion of in situ wind data significantly improves the accuracy of the predicted wind speed and direction. Incorporation of the Fairall et al. air–sea flux algorithms with inclusion of Advanced Very High Resolution Radiometer (AVHRR)-derived SST improves the accuracy of the predicted latent and sensible heat fluxes in the GoM/GB region for both stable and unstable weather conditions. This research was supported by the U.S. GLOBEC Northwest Atlantic/Georges Bank program through NSF Grants OCE 02-34545 and OCE 02-27679, NOAA Grant NA 16092323, and NSF CoOP Grant OCE 01-96543 to C. Chen, and NSF Grant OCE 02-27679 to R. C. Beardsley. Song Hu was supported by a SMAST graduate scholarship from NASA Grant NAG 13-02042, and Qichun Xu was supported by Chen’s NSF and NOAA grants mentioned above. Huichan Lin was supported by the Georgia DNR Grants 024409-01 and 026450-01.