A Feature Model for Arctic Upper Ocean Thermal Structure

The radiation balance at high latitudes is dominated by presence or absence of snow and ice which affects the albedo in a great deal. Any oceanic processes that affect the snow and ice cover in polar regions will cause the change of deposition of sun's energy over the earth's surface, and...

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Bibliographic Details
Main Author: Chu, Peter C.
Other Authors: NAVAL POSTGRADUATE SCHOOL MONTEREY CA DEPT OF OCEANOGRAPHY
Format: Text
Language:English
Published: 1995
Subjects:
Meteorology
Physical and Dynamic Oceanography
Thermodynamics
*SURFACE TEMPERATURE
*ICE
*OCEAN SURFACE
*ARCTIC OCEAN
SNOW
EARTH SURFACE
MIXED LAYER(MARINE)
SALINITY
HIGH LATITUDES
WATER MASSES
ATMOSPHERIC CHEMISTRY
ALBEDO
ICE FORMATION
ENVIRONMENTS
RADIATION
DATA BASES
POLAR REGIONS
Arctic
Arctic Ocean
albedo
Online Access:http://www.dtic.mil/docs/citations/ADA530525
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA530525
Description
Summary:The radiation balance at high latitudes is dominated by presence or absence of snow and ice which affects the albedo in a great deal. Any oceanic processes that affect the snow and ice cover in polar regions will cause the change of deposition of sun's energy over the earth's surface, and hence the environmental change. Besides, the ice cover, ocean, and atmosphere exchange water mass and energy in a very complicated way. Three major feedback loops (both positive and negative), in which the upper ocean is a key component, possibly exist in a theoretical air-ice-ocean coupled system (Chu, 1990). Thus, investigation of the polar upper ocean thermal structure from observation becomes urgent. Up until now, the effort is limited to study some individual data set, e.g., AIDJEX, MIZEX, CEAREX, etc., separately. No investigation is pursued for the Arctic upper ocean thermal structure from the all available data sets. This study deals with the most complete temperature and salinity data sets in the Arctic Ocean, which is the U.S. Navy's Master Oceanographic Data sets (MOODS). To get physical insights from the data, we use a feature model (Haeger, 1994) to transfer each MOODS Arctic temperature (or salinity) profile into a set of several characteristics: sea surface temperature (SST), mixed layer depth, thermocline depth, temperature difference across the thermocline. These characteristics reveal strong term poral and spatial variabilities. Presented at the Conference on Polar Meteorology and Oceanography, American Meteorological Society (4th), 224-227, 1995.

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