A Numerical Simulation of Residual Circulation in Tampa Bay. Part II: Lagrangian Residence Time
Lagrangian retention and flushing are examined by advecting neutrally buoyant point particles within a circulation field generated by a numerical ocean model of Tampa Bay. Large temporal variations in Lagrangian residence time are found under realistic changes in boundary conditions. Two 90-day time...
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description | Lagrangian retention and flushing are examined by advecting neutrally buoyant point particles within a circulation field generated by a numerical ocean model of Tampa Bay. Large temporal variations in Lagrangian residence time are found under realistic changes in boundary conditions. Two 90-day time periods are examined. The first (PI) is characterized by low freshwater inflow and weak baroclinic circulation. The second (P2) has high freshwater inflow and strong baroclinic circulation. At the beginning of both time periods, 686,400 particles are released uniformly throughout the bay. Issues relating to particle distribution and flushing are examined at three different spatial scales: (1) at the scale of the entire bay, (2) the four major regions within the bay, and (3) at the scale of individual model grid cells. Two simple theoretical models for the particle number over time, N(t), are fit to the particle counts from the ocean model. The theoretical models are shown to represent N(t) reasonably well when considering the entire bay, allowing for straightforward calculation of baywide residence times: 156 days for PI and 36 days for P2. However, the accuracy of these simple models decreases with decreasing spatial scale. This is likely due to the fact that particles may exit, reenter, or redistribute from one region to another in any sequence. The smaller the domain under consideration, the more this exchange process dominates. Therefore, definitions of residence time need to be modified for "non-local" situations. After choosing a reasonable definition, and removal of the tidal and synoptic signals, the residence times at each grid cell in PI is found to vary spatially from a few days to 90 days, the limit of the calculation, with an average residence time of 53 days. For P2, the overall spatial pattern is more homogeneous, and the residence times have an average value of 26 days. |
doi_str_mv | 10.1007/s12237-008-9085-0 |
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Part II: Lagrangian Residence Time</title><source>Jstor Complete Legacy</source><source>SpringerLink Journals</source><creator>Meyers, Steven D. ; Luther, Mark E.</creator><creatorcontrib>Meyers, Steven D. ; Luther, Mark E.</creatorcontrib><description>Lagrangian retention and flushing are examined by advecting neutrally buoyant point particles within a circulation field generated by a numerical ocean model of Tampa Bay. Large temporal variations in Lagrangian residence time are found under realistic changes in boundary conditions. Two 90-day time periods are examined. The first (PI) is characterized by low freshwater inflow and weak baroclinic circulation. The second (P2) has high freshwater inflow and strong baroclinic circulation. At the beginning of both time periods, 686,400 particles are released uniformly throughout the bay. Issues relating to particle distribution and flushing are examined at three different spatial scales: (1) at the scale of the entire bay, (2) the four major regions within the bay, and (3) at the scale of individual model grid cells. Two simple theoretical models for the particle number over time, N(t), are fit to the particle counts from the ocean model. The theoretical models are shown to represent N(t) reasonably well when considering the entire bay, allowing for straightforward calculation of baywide residence times: 156 days for PI and 36 days for P2. However, the accuracy of these simple models decreases with decreasing spatial scale. This is likely due to the fact that particles may exit, reenter, or redistribute from one region to another in any sequence. The smaller the domain under consideration, the more this exchange process dominates. Therefore, definitions of residence time need to be modified for "non-local" situations. After choosing a reasonable definition, and removal of the tidal and synoptic signals, the residence times at each grid cell in PI is found to vary spatially from a few days to 90 days, the limit of the calculation, with an average residence time of 53 days. For P2, the overall spatial pattern is more homogeneous, and the residence times have an average value of 26 days.</description><identifier>ISSN: 1559-2723</identifier><identifier>EISSN: 1559-2731</identifier><identifier>DOI: 10.1007/s12237-008-9085-0</identifier><language>eng</language><publisher>New York: Spring Science + Business Media</publisher><subject>Animal and plant ecology ; Animal, plant and microbial ecology ; Biological and medical sciences ; Boundary conditions ; Brackish water ecosystems ; Coastal Sciences ; Earth and Environmental Science ; Ecology ; Environment ; Environmental Management ; Estuaries ; Flushing ; Fresh water ; Freshwater & Marine Ecology ; Freshwater ecology ; Fundamental and applied biological sciences. 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Part II: Lagrangian Residence Time</title><title>Estuaries and coasts</title><addtitle>Estuaries and Coasts</addtitle><description>Lagrangian retention and flushing are examined by advecting neutrally buoyant point particles within a circulation field generated by a numerical ocean model of Tampa Bay. Large temporal variations in Lagrangian residence time are found under realistic changes in boundary conditions. Two 90-day time periods are examined. The first (PI) is characterized by low freshwater inflow and weak baroclinic circulation. The second (P2) has high freshwater inflow and strong baroclinic circulation. At the beginning of both time periods, 686,400 particles are released uniformly throughout the bay. Issues relating to particle distribution and flushing are examined at three different spatial scales: (1) at the scale of the entire bay, (2) the four major regions within the bay, and (3) at the scale of individual model grid cells. Two simple theoretical models for the particle number over time, N(t), are fit to the particle counts from the ocean model. The theoretical models are shown to represent N(t) reasonably well when considering the entire bay, allowing for straightforward calculation of baywide residence times: 156 days for PI and 36 days for P2. However, the accuracy of these simple models decreases with decreasing spatial scale. This is likely due to the fact that particles may exit, reenter, or redistribute from one region to another in any sequence. The smaller the domain under consideration, the more this exchange process dominates. Therefore, definitions of residence time need to be modified for "non-local" situations. After choosing a reasonable definition, and removal of the tidal and synoptic signals, the residence times at each grid cell in PI is found to vary spatially from a few days to 90 days, the limit of the calculation, with an average residence time of 53 days. For P2, the overall spatial pattern is more homogeneous, and the residence times have an average value of 26 days.</description><subject>Animal and plant ecology</subject><subject>Animal, plant and microbial ecology</subject><subject>Biological and medical sciences</subject><subject>Boundary conditions</subject><subject>Brackish water ecosystems</subject><subject>Coastal Sciences</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Environment</subject><subject>Environmental Management</subject><subject>Estuaries</subject><subject>Flushing</subject><subject>Fresh water</subject><subject>Freshwater & Marine Ecology</subject><subject>Freshwater ecology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Lagrangian function</subject><subject>Marine</subject><subject>Ocean circulation</subject><subject>Ocean circulation models</subject><subject>Particle tracks</subject><subject>Quantum statistics</subject><subject>Salinity</subject><subject>Sea water ecosystems</subject><subject>Shipping</subject><subject>Simulation</subject><subject>Spatial models</subject><subject>Synecology</subject><subject>Three dimensional modeling</subject><subject>Water and Health</subject><subject>Water inflow</subject><issn>1559-2723</issn><issn>1559-2731</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kU1LAzEQhoMoqNUf4EEIgt5WJ8l-etPiR6GoaD2HJDtbUvajJrsH_70pqxU8eJph8r4vk2cIOWFwyQCyK884F1kEkEcF5EkEO-SAJUkR8Uyw3W3PxT459H4FECcJxAdE3tCnoUFnjarpm22GWvW2a2lX0Vf0thzCeGqd-Znbli5Us1b0Vn1e0hflejqbXdO5WjrVLq1qRxu2BunCNnhE9ipVezz-rhPyfn-3mD5G8-eH2fRmHhlR5H3E41wbow0InZiYay1yUwiVClGmAhUarDAzBddVpjWEiro0ZaoZ4yXPNYoJuRhz1677GND3srHeYF2rFrvBSw4py5Pw_wk5-yNcdYNrw26SCwCWFSINIjaKjOu8d1jJtbONcp-SgdzwliNvGXjLDW8JwXP-Hax8gFkFHsb6rZFDFk4AGx0fdT48tUt0vwv8F346mla-79w2NIY0FXEO4guFD5lD</recordid><startdate>20081101</startdate><enddate>20081101</enddate><creator>Meyers, Steven D.</creator><creator>Luther, Mark E.</creator><general>Spring Science + Business Media</general><general>Springer-Verlag</general><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QG</scope><scope>7SN</scope><scope>7TN</scope><scope>7U7</scope><scope>7UA</scope><scope>7XB</scope><scope>8AO</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H95</scope><scope>H96</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>7QH</scope><scope>7TG</scope><scope>KL.</scope></search><sort><creationdate>20081101</creationdate><title>A Numerical Simulation of Residual Circulation in Tampa Bay. Part II: Lagrangian Residence Time</title><author>Meyers, Steven D. ; Luther, Mark E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c398t-248bccbc03b5c42bb38c93a633d63eaecefe7c92bf7bb092bebdcd6b112d28be3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Animal and plant ecology</topic><topic>Animal, plant and microbial ecology</topic><topic>Biological and medical sciences</topic><topic>Boundary conditions</topic><topic>Brackish water ecosystems</topic><topic>Coastal Sciences</topic><topic>Earth and Environmental Science</topic><topic>Ecology</topic><topic>Environment</topic><topic>Environmental Management</topic><topic>Estuaries</topic><topic>Flushing</topic><topic>Fresh water</topic><topic>Freshwater & Marine Ecology</topic><topic>Freshwater ecology</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Lagrangian function</topic><topic>Marine</topic><topic>Ocean circulation</topic><topic>Ocean circulation models</topic><topic>Particle tracks</topic><topic>Quantum statistics</topic><topic>Salinity</topic><topic>Sea water ecosystems</topic><topic>Shipping</topic><topic>Simulation</topic><topic>Spatial models</topic><topic>Synecology</topic><topic>Three dimensional modeling</topic><topic>Water and Health</topic><topic>Water inflow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Meyers, Steven D.</creatorcontrib><creatorcontrib>Luther, Mark E.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Ecology Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><jtitle>Estuaries and coasts</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Meyers, Steven D.</au><au>Luther, Mark E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Numerical Simulation of Residual Circulation in Tampa Bay. Part II: Lagrangian Residence Time</atitle><jtitle>Estuaries and coasts</jtitle><stitle>Estuaries and Coasts</stitle><date>2008-11-01</date><risdate>2008</risdate><volume>31</volume><issue>5</issue><spage>815</spage><epage>827</epage><pages>815-827</pages><issn>1559-2723</issn><eissn>1559-2731</eissn><abstract>Lagrangian retention and flushing are examined by advecting neutrally buoyant point particles within a circulation field generated by a numerical ocean model of Tampa Bay. Large temporal variations in Lagrangian residence time are found under realistic changes in boundary conditions. Two 90-day time periods are examined. The first (PI) is characterized by low freshwater inflow and weak baroclinic circulation. The second (P2) has high freshwater inflow and strong baroclinic circulation. At the beginning of both time periods, 686,400 particles are released uniformly throughout the bay. Issues relating to particle distribution and flushing are examined at three different spatial scales: (1) at the scale of the entire bay, (2) the four major regions within the bay, and (3) at the scale of individual model grid cells. Two simple theoretical models for the particle number over time, N(t), are fit to the particle counts from the ocean model. The theoretical models are shown to represent N(t) reasonably well when considering the entire bay, allowing for straightforward calculation of baywide residence times: 156 days for PI and 36 days for P2. However, the accuracy of these simple models decreases with decreasing spatial scale. This is likely due to the fact that particles may exit, reenter, or redistribute from one region to another in any sequence. The smaller the domain under consideration, the more this exchange process dominates. Therefore, definitions of residence time need to be modified for "non-local" situations. After choosing a reasonable definition, and removal of the tidal and synoptic signals, the residence times at each grid cell in PI is found to vary spatially from a few days to 90 days, the limit of the calculation, with an average residence time of 53 days. For P2, the overall spatial pattern is more homogeneous, and the residence times have an average value of 26 days.</abstract><cop>New York</cop><pub>Spring Science + Business Media</pub><doi>10.1007/s12237-008-9085-0</doi><tpages>13</tpages></addata></record> |
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subjects | Animal and plant ecology Animal, plant and microbial ecology Biological and medical sciences Boundary conditions Brackish water ecosystems Coastal Sciences Earth and Environmental Science Ecology Environment Environmental Management Estuaries Flushing Fresh water Freshwater & Marine Ecology Freshwater ecology Fundamental and applied biological sciences. Psychology Lagrangian function Marine Ocean circulation Ocean circulation models Particle tracks Quantum statistics Salinity Sea water ecosystems Shipping Simulation Spatial models Synecology Three dimensional modeling Water and Health Water inflow |
title | A Numerical Simulation of Residual Circulation in Tampa Bay. Part II: Lagrangian Residence Time |
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