Loading…

Particle Dynamics in the Nearshore of Lake Michigan Revealed by an Observation‐Modeling System

Given that few drifter experiments combined with a wave‐current coupled model system had been conducted in the complex nearshore area, this work was motivated to reveal the nearshore dynamics by applying an observation‐modeling system to Lake Michigan. Analysis of 11 surface drifters, wind, and curr...

Full description

Saved in:
Bibliographic Details
Published in:Journal of geophysical research. Oceans 2020-08, Vol.125 (8), p.n/a
Main Authors: Mao, Miaohua, Xia, Meng
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13
cites cdi_FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13
container_end_page n/a
container_issue 8
container_start_page
container_title Journal of geophysical research. Oceans
container_volume 125
creator Mao, Miaohua
Xia, Meng
description Given that few drifter experiments combined with a wave‐current coupled model system had been conducted in the complex nearshore area, this work was motivated to reveal the nearshore dynamics by applying an observation‐modeling system to Lake Michigan. Analysis of 11 surface drifters, wind, and current observations along the lake's eastern coast indicates that their trajectories are synergistically controlled by winds and initial releasing sites. Additionally, strong winds significantly impact nearshore dynamics, and the highly sensitive nearshore and offshore drifters are stranded in distinct regions. Simulations indicate that the model reproduces drifter trajectories and endpoints reasonably and that particle fates are mainly dominated by winds, while effects from heat flux and waves are also important. Further analysis of wave effects on particle dynamics indicates that both the wave‐induced sea surface roughness and Stokes drift advection are crucial to the simulated particle trajectories during wind events. Finally, virtual experiments confirm that particle dynamics are evidently susceptible to winds and initial locations. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The successful application of this nearshore observation‐modeling system to Lake Michigan can be beneficial to the understanding of nearshore‐offshore transports and larval and fisheries recruitment success in similar freshwater and estuarine environments. Plain Language Summary We combine surface drifter observations and computer simulations to understand movements of particles in the nearshore of Lake Michigan. Analysis of drifters' moving paths, wind, and current measurements in the summers of 2014 and 2015 indicates that drifter movements are strongly related to winds and initial releasing sites. Multiple computer programs were run to simulate the designed scenarios by artificially removing one of the influencing factors at each simulation from the model. We find that particle movements are collectively affected by winds, heat flux transfer between the air and lake water, and surface gravity waves. Further investigations demonstrate that both wave‐induced sea surface roughness and Stokes drift advection are
doi_str_mv 10.1029/2019JC015765
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2437393998</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2437393998</sourcerecordid><originalsourceid>FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13</originalsourceid><addsrcrecordid>eNp90M1Kw0AQB_AgCpbamw-w4NXofmazR4laLa2Vque42UzarWlSd9NKbj6Cz-iTGKmIJ-cyM_BjBv5BcEzwGcFUnVNM1CjBRMhI7AU9SiIVKqrI_u8sxWEw8H6Ju4pJzLnqBc_32jXWlIAu20qvrPHIVqhZALoD7fyidoDqAo31C6CJNQs71xWawRZ0CTnKWtSt08yD2-rG1tXn-8ekzqG01Rw9tL6B1VFwUOjSw-Cn94On66vH5CYcT4e3ycU41JxxHKo8k4JrGcUUcy0ijLngIAST3OQyzjMjdEa0pLpTBc81AMuVFCbLTFEAYf3gZHd37erXDfgmXdYbV3UvU8qZZIopFXfqdKeMq713UKRrZ1fatSnB6XeM6d8YO852_M2W0P5r09FwllBOCGZfLqJ0WQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2437393998</pqid></control><display><type>article</type><title>Particle Dynamics in the Nearshore of Lake Michigan Revealed by an Observation‐Modeling System</title><source>Wiley-Blackwell Read &amp; Publish Collection</source><source>Alma/SFX Local Collection</source><creator>Mao, Miaohua ; Xia, Meng</creator><creatorcontrib>Mao, Miaohua ; Xia, Meng</creatorcontrib><description>Given that few drifter experiments combined with a wave‐current coupled model system had been conducted in the complex nearshore area, this work was motivated to reveal the nearshore dynamics by applying an observation‐modeling system to Lake Michigan. Analysis of 11 surface drifters, wind, and current observations along the lake's eastern coast indicates that their trajectories are synergistically controlled by winds and initial releasing sites. Additionally, strong winds significantly impact nearshore dynamics, and the highly sensitive nearshore and offshore drifters are stranded in distinct regions. Simulations indicate that the model reproduces drifter trajectories and endpoints reasonably and that particle fates are mainly dominated by winds, while effects from heat flux and waves are also important. Further analysis of wave effects on particle dynamics indicates that both the wave‐induced sea surface roughness and Stokes drift advection are crucial to the simulated particle trajectories during wind events. Finally, virtual experiments confirm that particle dynamics are evidently susceptible to winds and initial locations. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The successful application of this nearshore observation‐modeling system to Lake Michigan can be beneficial to the understanding of nearshore‐offshore transports and larval and fisheries recruitment success in similar freshwater and estuarine environments. Plain Language Summary We combine surface drifter observations and computer simulations to understand movements of particles in the nearshore of Lake Michigan. Analysis of drifters' moving paths, wind, and current measurements in the summers of 2014 and 2015 indicates that drifter movements are strongly related to winds and initial releasing sites. Multiple computer programs were run to simulate the designed scenarios by artificially removing one of the influencing factors at each simulation from the model. We find that particle movements are collectively affected by winds, heat flux transfer between the air and lake water, and surface gravity waves. Further investigations demonstrate that both wave‐induced sea surface roughness and Stokes drift advection are important to the simulated particle trajectories during wind events. After doing “what‐if” scenarios in the computer model, distinct particle routes driven by wind‐induced surface flows were simulated for virtual particles hypothetically released at various locations near the lake's southeastern coast. For example, nearshore group primarily shows longshore movements, while offshore one drifts into the deep basin. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The outcome from this study will enhance the understanding of larval transport from nearshore to offshore areas in Lake Michigan and similar freshwater and estuarine environments. Key Points A wave‐current coupled particle model combined with surface drifter observations were applied to reveal nearshore particle dynamics Winds dominate nearshore particle dynamics while effects of heat flux and waves are important as well Including physical effects and diminishing uncertainties are important to the improved model performance</description><identifier>ISSN: 2169-9275</identifier><identifier>EISSN: 2169-9291</identifier><identifier>DOI: 10.1029/2019JC015765</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Advection ; Aerodynamics ; Brackishwater environment ; Computational fluid dynamics ; Computer programs ; Computer simulation ; Computer software ; Computers ; Current observations ; Data sources ; Drag ; Drag coefficient ; Drag coefficients ; Drift ; drifter observation ; Drifters ; Estuaries ; Estuarine environments ; Fisheries ; Formulations ; Freshwater ; Freshwater fish ; Freshwater lakes ; Geophysics ; Gravity waves ; Heat ; Heat flux ; Heat transfer ; Inland water environment ; Lakes ; Larvae ; Mathematical models ; Methods ; Modelling ; Nearshore dynamics ; numerical modeling ; Offshore ; Particle dynamics ; Particle trajectories ; Physics ; Sea surface ; Sea surface roughness ; Simulation ; Software ; Stokes drift ; Strong winds ; Surface drifters ; Surface gravity waves ; Surface roughness ; Trajectory control ; Turbulent mixing ; Uncertainty ; Wave analysis ; Wave effects ; waves ; Wind ; Wind effects ; Wind measurement ; Winds</subject><ispartof>Journal of geophysical research. Oceans, 2020-08, Vol.125 (8), p.n/a</ispartof><rights>2020. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13</citedby><cites>FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13</cites><orcidid>0000-0002-3013-4849 ; 0000-0002-4295-385X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Mao, Miaohua</creatorcontrib><creatorcontrib>Xia, Meng</creatorcontrib><title>Particle Dynamics in the Nearshore of Lake Michigan Revealed by an Observation‐Modeling System</title><title>Journal of geophysical research. Oceans</title><description>Given that few drifter experiments combined with a wave‐current coupled model system had been conducted in the complex nearshore area, this work was motivated to reveal the nearshore dynamics by applying an observation‐modeling system to Lake Michigan. Analysis of 11 surface drifters, wind, and current observations along the lake's eastern coast indicates that their trajectories are synergistically controlled by winds and initial releasing sites. Additionally, strong winds significantly impact nearshore dynamics, and the highly sensitive nearshore and offshore drifters are stranded in distinct regions. Simulations indicate that the model reproduces drifter trajectories and endpoints reasonably and that particle fates are mainly dominated by winds, while effects from heat flux and waves are also important. Further analysis of wave effects on particle dynamics indicates that both the wave‐induced sea surface roughness and Stokes drift advection are crucial to the simulated particle trajectories during wind events. Finally, virtual experiments confirm that particle dynamics are evidently susceptible to winds and initial locations. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The successful application of this nearshore observation‐modeling system to Lake Michigan can be beneficial to the understanding of nearshore‐offshore transports and larval and fisheries recruitment success in similar freshwater and estuarine environments. Plain Language Summary We combine surface drifter observations and computer simulations to understand movements of particles in the nearshore of Lake Michigan. Analysis of drifters' moving paths, wind, and current measurements in the summers of 2014 and 2015 indicates that drifter movements are strongly related to winds and initial releasing sites. Multiple computer programs were run to simulate the designed scenarios by artificially removing one of the influencing factors at each simulation from the model. We find that particle movements are collectively affected by winds, heat flux transfer between the air and lake water, and surface gravity waves. Further investigations demonstrate that both wave‐induced sea surface roughness and Stokes drift advection are important to the simulated particle trajectories during wind events. After doing “what‐if” scenarios in the computer model, distinct particle routes driven by wind‐induced surface flows were simulated for virtual particles hypothetically released at various locations near the lake's southeastern coast. For example, nearshore group primarily shows longshore movements, while offshore one drifts into the deep basin. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The outcome from this study will enhance the understanding of larval transport from nearshore to offshore areas in Lake Michigan and similar freshwater and estuarine environments. Key Points A wave‐current coupled particle model combined with surface drifter observations were applied to reveal nearshore particle dynamics Winds dominate nearshore particle dynamics while effects of heat flux and waves are important as well Including physical effects and diminishing uncertainties are important to the improved model performance</description><subject>Advection</subject><subject>Aerodynamics</subject><subject>Brackishwater environment</subject><subject>Computational fluid dynamics</subject><subject>Computer programs</subject><subject>Computer simulation</subject><subject>Computer software</subject><subject>Computers</subject><subject>Current observations</subject><subject>Data sources</subject><subject>Drag</subject><subject>Drag coefficient</subject><subject>Drag coefficients</subject><subject>Drift</subject><subject>drifter observation</subject><subject>Drifters</subject><subject>Estuaries</subject><subject>Estuarine environments</subject><subject>Fisheries</subject><subject>Formulations</subject><subject>Freshwater</subject><subject>Freshwater fish</subject><subject>Freshwater lakes</subject><subject>Geophysics</subject><subject>Gravity waves</subject><subject>Heat</subject><subject>Heat flux</subject><subject>Heat transfer</subject><subject>Inland water environment</subject><subject>Lakes</subject><subject>Larvae</subject><subject>Mathematical models</subject><subject>Methods</subject><subject>Modelling</subject><subject>Nearshore dynamics</subject><subject>numerical modeling</subject><subject>Offshore</subject><subject>Particle dynamics</subject><subject>Particle trajectories</subject><subject>Physics</subject><subject>Sea surface</subject><subject>Sea surface roughness</subject><subject>Simulation</subject><subject>Software</subject><subject>Stokes drift</subject><subject>Strong winds</subject><subject>Surface drifters</subject><subject>Surface gravity waves</subject><subject>Surface roughness</subject><subject>Trajectory control</subject><subject>Turbulent mixing</subject><subject>Uncertainty</subject><subject>Wave analysis</subject><subject>Wave effects</subject><subject>waves</subject><subject>Wind</subject><subject>Wind effects</subject><subject>Wind measurement</subject><subject>Winds</subject><issn>2169-9275</issn><issn>2169-9291</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp90M1Kw0AQB_AgCpbamw-w4NXofmazR4laLa2Vque42UzarWlSd9NKbj6Cz-iTGKmIJ-cyM_BjBv5BcEzwGcFUnVNM1CjBRMhI7AU9SiIVKqrI_u8sxWEw8H6Ju4pJzLnqBc_32jXWlIAu20qvrPHIVqhZALoD7fyidoDqAo31C6CJNQs71xWawRZ0CTnKWtSt08yD2-rG1tXn-8ekzqG01Rw9tL6B1VFwUOjSw-Cn94On66vH5CYcT4e3ycU41JxxHKo8k4JrGcUUcy0ijLngIAST3OQyzjMjdEa0pLpTBc81AMuVFCbLTFEAYf3gZHd37erXDfgmXdYbV3UvU8qZZIopFXfqdKeMq713UKRrZ1fatSnB6XeM6d8YO852_M2W0P5r09FwllBOCGZfLqJ0WQ</recordid><startdate>202008</startdate><enddate>202008</enddate><creator>Mao, Miaohua</creator><creator>Xia, Meng</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-3013-4849</orcidid><orcidid>https://orcid.org/0000-0002-4295-385X</orcidid></search><sort><creationdate>202008</creationdate><title>Particle Dynamics in the Nearshore of Lake Michigan Revealed by an Observation‐Modeling System</title><author>Mao, Miaohua ; Xia, Meng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Advection</topic><topic>Aerodynamics</topic><topic>Brackishwater environment</topic><topic>Computational fluid dynamics</topic><topic>Computer programs</topic><topic>Computer simulation</topic><topic>Computer software</topic><topic>Computers</topic><topic>Current observations</topic><topic>Data sources</topic><topic>Drag</topic><topic>Drag coefficient</topic><topic>Drag coefficients</topic><topic>Drift</topic><topic>drifter observation</topic><topic>Drifters</topic><topic>Estuaries</topic><topic>Estuarine environments</topic><topic>Fisheries</topic><topic>Formulations</topic><topic>Freshwater</topic><topic>Freshwater fish</topic><topic>Freshwater lakes</topic><topic>Geophysics</topic><topic>Gravity waves</topic><topic>Heat</topic><topic>Heat flux</topic><topic>Heat transfer</topic><topic>Inland water environment</topic><topic>Lakes</topic><topic>Larvae</topic><topic>Mathematical models</topic><topic>Methods</topic><topic>Modelling</topic><topic>Nearshore dynamics</topic><topic>numerical modeling</topic><topic>Offshore</topic><topic>Particle dynamics</topic><topic>Particle trajectories</topic><topic>Physics</topic><topic>Sea surface</topic><topic>Sea surface roughness</topic><topic>Simulation</topic><topic>Software</topic><topic>Stokes drift</topic><topic>Strong winds</topic><topic>Surface drifters</topic><topic>Surface gravity waves</topic><topic>Surface roughness</topic><topic>Trajectory control</topic><topic>Turbulent mixing</topic><topic>Uncertainty</topic><topic>Wave analysis</topic><topic>Wave effects</topic><topic>waves</topic><topic>Wind</topic><topic>Wind effects</topic><topic>Wind measurement</topic><topic>Winds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mao, Miaohua</creatorcontrib><creatorcontrib>Xia, Meng</creatorcontrib><collection>CrossRef</collection><collection>Meteorological &amp; Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy &amp; Non-Living Resources</collection><collection>Meteorological &amp; Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of geophysical research. Oceans</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mao, Miaohua</au><au>Xia, Meng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Particle Dynamics in the Nearshore of Lake Michigan Revealed by an Observation‐Modeling System</atitle><jtitle>Journal of geophysical research. Oceans</jtitle><date>2020-08</date><risdate>2020</risdate><volume>125</volume><issue>8</issue><epage>n/a</epage><issn>2169-9275</issn><eissn>2169-9291</eissn><abstract>Given that few drifter experiments combined with a wave‐current coupled model system had been conducted in the complex nearshore area, this work was motivated to reveal the nearshore dynamics by applying an observation‐modeling system to Lake Michigan. Analysis of 11 surface drifters, wind, and current observations along the lake's eastern coast indicates that their trajectories are synergistically controlled by winds and initial releasing sites. Additionally, strong winds significantly impact nearshore dynamics, and the highly sensitive nearshore and offshore drifters are stranded in distinct regions. Simulations indicate that the model reproduces drifter trajectories and endpoints reasonably and that particle fates are mainly dominated by winds, while effects from heat flux and waves are also important. Further analysis of wave effects on particle dynamics indicates that both the wave‐induced sea surface roughness and Stokes drift advection are crucial to the simulated particle trajectories during wind events. Finally, virtual experiments confirm that particle dynamics are evidently susceptible to winds and initial locations. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The successful application of this nearshore observation‐modeling system to Lake Michigan can be beneficial to the understanding of nearshore‐offshore transports and larval and fisheries recruitment success in similar freshwater and estuarine environments. Plain Language Summary We combine surface drifter observations and computer simulations to understand movements of particles in the nearshore of Lake Michigan. Analysis of drifters' moving paths, wind, and current measurements in the summers of 2014 and 2015 indicates that drifter movements are strongly related to winds and initial releasing sites. Multiple computer programs were run to simulate the designed scenarios by artificially removing one of the influencing factors at each simulation from the model. We find that particle movements are collectively affected by winds, heat flux transfer between the air and lake water, and surface gravity waves. Further investigations demonstrate that both wave‐induced sea surface roughness and Stokes drift advection are important to the simulated particle trajectories during wind events. After doing “what‐if” scenarios in the computer model, distinct particle routes driven by wind‐induced surface flows were simulated for virtual particles hypothetically released at various locations near the lake's southeastern coast. For example, nearshore group primarily shows longshore movements, while offshore one drifts into the deep basin. Overall, both the inclusion of physics effects (e.g., adding winds, heat fluxes, and waves) and diminishing the model uncertainties (e.g., from various wind data sources, wind drag coefficient formulations, model grids, and vertical turbulent mixing parameterizations) are important methods to improve the particle simulations. The outcome from this study will enhance the understanding of larval transport from nearshore to offshore areas in Lake Michigan and similar freshwater and estuarine environments. Key Points A wave‐current coupled particle model combined with surface drifter observations were applied to reveal nearshore particle dynamics Winds dominate nearshore particle dynamics while effects of heat flux and waves are important as well Including physical effects and diminishing uncertainties are important to the improved model performance</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2019JC015765</doi><tpages>26</tpages><orcidid>https://orcid.org/0000-0002-3013-4849</orcidid><orcidid>https://orcid.org/0000-0002-4295-385X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2169-9275
ispartof Journal of geophysical research. Oceans, 2020-08, Vol.125 (8), p.n/a
issn 2169-9275
2169-9291
language eng
recordid cdi_proquest_journals_2437393998
source Wiley-Blackwell Read & Publish Collection; Alma/SFX Local Collection
subjects Advection
Aerodynamics
Brackishwater environment
Computational fluid dynamics
Computer programs
Computer simulation
Computer software
Computers
Current observations
Data sources
Drag
Drag coefficient
Drag coefficients
Drift
drifter observation
Drifters
Estuaries
Estuarine environments
Fisheries
Formulations
Freshwater
Freshwater fish
Freshwater lakes
Geophysics
Gravity waves
Heat
Heat flux
Heat transfer
Inland water environment
Lakes
Larvae
Mathematical models
Methods
Modelling
Nearshore dynamics
numerical modeling
Offshore
Particle dynamics
Particle trajectories
Physics
Sea surface
Sea surface roughness
Simulation
Software
Stokes drift
Strong winds
Surface drifters
Surface gravity waves
Surface roughness
Trajectory control
Turbulent mixing
Uncertainty
Wave analysis
Wave effects
waves
Wind
Wind effects
Wind measurement
Winds
title Particle Dynamics in the Nearshore of Lake Michigan Revealed by an Observation‐Modeling System
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T07%3A40%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Particle%20Dynamics%20in%20the%20Nearshore%20of%20Lake%20Michigan%20Revealed%20by%20an%20Observation%E2%80%90Modeling%20System&rft.jtitle=Journal%20of%20geophysical%20research.%20Oceans&rft.au=Mao,%20Miaohua&rft.date=2020-08&rft.volume=125&rft.issue=8&rft.epage=n/a&rft.issn=2169-9275&rft.eissn=2169-9291&rft_id=info:doi/10.1029/2019JC015765&rft_dat=%3Cproquest_cross%3E2437393998%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a4340-9db754a768204a5600454e55374cd78dbc5ab1a72a54af4daee3d975cbbcffe13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2437393998&rft_id=info:pmid/&rfr_iscdi=true