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Surface current observations using h...

Stevens Institute of Technology.

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Surface current observations using high frequency radar and its assimilation into the New York Harbor Observing and Prediction System.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Surface current observations using high frequency radar and its assimilation into the New York Harbor Observing and Prediction System./
作者:	Gopalakrishnan, Ganesh.
面頁冊數:	206 p.
附註:	Advisers: Alan F. Blumberg; Richard I. Hires.
Contained By:	Dissertation Abstracts International70-03B.
標題:	Engineering, Marine and Ocean. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3351556
ISBN:	9781109078619

Surface current observations using high frequency radar and its assimilation into the New York Harbor Observing and Prediction System.
Gopalakrishnan, Ganesh.

Surface current observations using high frequency radar and its assimilation into the New York Harbor Observing and Prediction System. - 206 p.

Advisers: Alan F. Blumberg; Richard I. Hires.

Thesis (Ph.D.)--Stevens Institute of Technology, 2009.

A surface current observation system based on high-frequency (HF) radar (CODAR) has been constructed for Raritan Bay, NJ; and the New York Bight (NYB) Apex. The availability of surface current data measured using HF radar in real-time over a synoptic scale makes it appropriate for data assimilation (DA). The present work is an attempt to validate HF radar data in the NYB Apex and to develop a practical, but still nearly optimal, method to assimilate HF radar data into an estuarine and coastal ocean circulation model in a tidally-dominated region of NY/NJ Harbor Estuary and the NYB Apex. This model, forced by an extensive real-time observational network, is called the New York Harbor Observing and Prediction System (NYHOPS). A nudging or Newtonian damping scheme is developed to assimilate HF radar data. A nudging parameter is introduced into the equations of motion which affects the model dynamics. The data is imparted to neighboring (three-dimensional) grid points via model dynamics. The effectiveness of HF radar DA is studied by computing the DA skill based on mean square error. A positive DA skill (0 -- 100%) represents an improvement in the model performance by HF radar DA.

ISBN: 9781109078619Subjects--Topical Terms:

1019064
Engineering, Marine and Ocean.

Surface current observations using high frequency radar and its assimilation into the New York Harbor Observing and Prediction System.
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520 $a A surface current observation system based on high-frequency (HF) radar (CODAR) has been constructed for Raritan Bay, NJ; and the New York Bight (NYB) Apex. The availability of surface current data measured using HF radar in real-time over a synoptic scale makes it appropriate for data assimilation (DA). The present work is an attempt to validate HF radar data in the NYB Apex and to develop a practical, but still nearly optimal, method to assimilate HF radar data into an estuarine and coastal ocean circulation model in a tidally-dominated region of NY/NJ Harbor Estuary and the NYB Apex. This model, forced by an extensive real-time observational network, is called the New York Harbor Observing and Prediction System (NYHOPS). A nudging or Newtonian damping scheme is developed to assimilate HF radar data. A nudging parameter is introduced into the equations of motion which affects the model dynamics. The data is imparted to neighboring (three-dimensional) grid points via model dynamics. The effectiveness of HF radar DA is studied by computing the DA skill based on mean square error. A positive DA skill (0 -- 100%) represents an improvement in the model performance by HF radar DA.
520 $a The HF radar data validation study showed a reasonable comparison between HF radar surface currents and near-surface in-situ currents obtained from one out of the two moorings. HF radar DA experiments focused on both the hindcasting as well as forecast capabilities of the NYHOPS model with respect to three regions; inner-shelf region (0 -- 30 m), mid-shelf (30 -- 90m), and outer-shelf (90 -- 120 m). For the inner-NJ shelf region, based on NYHOPS model hindcasts, a 40 day long DA study using HF radar data in Raritan Bay and the NYB Apex region yielded a DA skill of +22% for near-surface currents (with respect to mooring data), and +53% and +38% for near-surface temperature and salinity (with respect to Glider/fixed sensor data). Based on NYHOPS model forecasts, for the inner-NJ shelf region, another 120 days long DA study using HF radar data in the NYB region yielded a DA skill of +11% for near-surface currents (with respect to mooring data), and +10% and +16% for near-surface temperature and salinity (with respect to Glider/fixed sensor data). The DA skill for temperature and salinity is higher in the inner-NJ shelf (0 -- 30m) region and decreases steadily towards mid-NJ shelf (30 -- 90m) and outer-NJ shelf (90 -- 120m) regions. The nudging scheme is found to be robust and efficient for the NYHOPS model with minimum computational burden.
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