A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean.
Bathythermograph data acquired from the research vessel USNS SILAS BENT along a meridional track in the Northeast Pacific during September 1977 were statistically analyzed to determine possible associations between the subsurface thermal structures and sea surface temperature. Strongly correlated va...
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Monterey, California. Naval Postgraduate School
2012
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Online Access: | http://hdl.handle.net/10945/19997 |
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ndltd-nps.edu-oai-calhoun.nps.edu-10945-199972014-11-27T16:13:35Z A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. Howell, Terry A. Bathythermograph data acquired from the research vessel USNS SILAS BENT along a meridional track in the Northeast Pacific during September 1977 were statistically analyzed to determine possible associations between the subsurface thermal structures and sea surface temperature. Strongly correlated variables (thermocline gradients, mixed layer depth, and locations of the seasonal and main thermoclines) within the vertical temperature profile were used in linear regression methods to form empirical relationships. The generated equations then are utilized to define the subsurface thermal structure from only an input of sea surface temperature. Comparison tests with temporally and spatially removed BT data were conducted with results indicating successful application within a water mass domain with uniformly changing characteristics 2012-11-20T00:00:06Z 2012-11-20T00:00:06Z 1983 Thesis http://hdl.handle.net/10945/19997 ocm640300798 en_US Monterey, California. Naval Postgraduate School |
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en_US |
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description |
Bathythermograph data acquired from the research vessel USNS SILAS BENT along a meridional track in the Northeast Pacific during September 1977 were statistically analyzed to determine possible associations between the subsurface thermal structures and sea surface temperature. Strongly correlated variables (thermocline gradients, mixed layer depth, and locations of the seasonal and main thermoclines) within the vertical temperature profile were used in linear regression methods to form empirical relationships. The generated equations then are utilized to define the subsurface thermal structure from only an input of sea surface temperature. Comparison tests with temporally and spatially removed BT data were conducted with results indicating successful application within a water mass domain with uniformly changing characteristics |
author |
Howell, Terry A. |
spellingShingle |
Howell, Terry A. A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. |
author_facet |
Howell, Terry A. |
author_sort |
Howell, Terry A. |
title |
A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. |
title_short |
A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. |
title_full |
A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. |
title_fullStr |
A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. |
title_full_unstemmed |
A statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast Pacific Ocean. |
title_sort |
statistical approach for determining subsurface thermal structure from sea surface temperature in the northeast pacific ocean. |
publisher |
Monterey, California. Naval Postgraduate School |
publishDate |
2012 |
url |
http://hdl.handle.net/10945/19997 |
work_keys_str_mv |
AT howellterrya astatisticalapproachfordeterminingsubsurfacethermalstructurefromseasurfacetemperatureinthenortheastpacificocean AT howellterrya statisticalapproachfordeterminingsubsurfacethermalstructurefromseasurfacetemperatureinthenortheastpacificocean |
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1716723429981290496 |