Simulating Mantle Convection and Seismic Anisotropy with ... · Simulating Mantle Convection and...
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Simulating Mantle Convection and Seismic Anisotropy with Data Assimilation
Project PI: Lijun Liu, UIUCPresenter: Jiashun HuCollaborator: Manuele Faccenda, University of Padua, ItalyGroup members: Quan Zhou, Ching ChangNCSA team: Ryan Mokos, Bill Gropp, Darren Adams, Yifeng Cui
CourtesytoandinmemoryofProf.PaulHeller
Geologist’s view on plate subduction
Whyitmatters– tomodelmantleconvection
• Howtheearthworks
(Braun2010)
TherealEarthismuchmorecomplex.
• Naturalhazards
FromthefilmSanAndreas
fromUSGS
Keychallenges• Cleanupboundaryconditions
• Earth’shistoryisverycomplex.Wehavelimitedconstraintsonthemotionsandtheagesoftheplates.
• Largeviscositycontrast• Significantlyslowdowntheconvergenceofthesolver• Requireshigherresolutiontoresolve
• Unknownpropertiesandprocesses• Suchasthegenerationandbehaviorofmagmainthemantlewedge,andthepropertiesofthesuperplumesindeepmantle
Potentialproblemswithexistingmodels
• Mostearliermodelsarein2D
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A
B
C
[vanHunenetal.,2002]
[vanHunenetal.,2000]
[Manea etal.,2012]
• Recent3Dmodelsusedidealizedboundaryconditions
(Taramon et al., G-cubed, 2015)
Potentialproblemswithexistingmodels
• Recent3Dmodelsusedfixedslabgeometry
6(Flament et al., EPSL, 2015)
ModelingS.Americansubductionhistory
Wetrytodevelopamodelthatisconsistentwithallavailablegeophysicalandtectonicconstraints:• Theknownsubductionhistory(platemotion&seafloorage)• Dynamicallyevolvinginsteadofprescribedslabs
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• GoverningEquations
• Assumethemantleis an incompressible fluid, which satisfiestheBoussinesq approximation
WhyBlueWaters• CitcomS hasaverygoodscalability,upto~10,000CPUsonBlueWaters.
• BlueWatersiscompatiblewiththesoftwares weuse,includingCitcomS,DrexS andFSTRACK
• Largercapacityleadstolargerallocationandshorterwaitingtime.
100 101 102 103 104
Mac
hine
tim
e (s
econ
d)
CPU number
1
10
100
1000
129×257×257
513×1025×1025
Blue Waters
Stampede
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Data Assimilation Seafloor age, plate motion, plate geometry,cratons
ViscositystructureofS.Americanmodel
10(Huetal.,EPSL, 2016)
4ordersof
magnitude
incontrast
11(Huetal.,EPSL, 2016)
PredictedSouthAmericansubduction since 100Ma
1024CPUs~150hours
Modelsize:8.6mgrids
Maximumresolution:27kmx20kmx8km
Thepowerofdataassimilation:
Fittinguppermantleslab
geometry
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Accomplishments
Fittinglowermantletomography
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Themodelfitstothetomographyimages
wellto1000kmdepth,especiallyinthe
northernpartofSouthAmericathathas
abetterseismiccoveragethanthe
southernpart.
Slabtearvs.intra-slabseismicity
(Hu&Liu,EPSL,2016)
Newinterpretationofflatslabsubduction
(Hu&Liu,EPSL,2016)
Late Cenozoic Andean Flare-up
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ThecentralAndesareunusualfortheabundanceoffelsicignimbritesandtheirdistributionisshownseparatelyfromtheintermediatetomaficvolcaniccenters.
Volcaniczoneissignificantlybroadenedsince~30Ma.
Thrumbull etal.,2006 Haschke etal.,2002
Geologicimplication:Slabdynamics&Andeanevolution
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The30-MaslabtearcorrelateswiththeAndeanignimbriteflare-upbothinspaceandintime.
N N
NewimplicationsonAndeanshortening&upliftaswell?
40Ma30Ma15Ma5Ma
N
33Ma
Predictingseismicanisotropy
• Calculateseismicanisotropy(LPO)byintegratingthemantle flowfield
• Integrating the anisotropy in the upper mantle togenerate synthetic SWS
Conclusions
• Supercomputers,suchasBlueWaters,makeitfeasibletorunmantle-convectionmodelsin3Dwithatimescaleofhundredsofmillionyears.
• Theimplementationofdataassimilationmethodisnecessaryinordertodirectlycompareobservationwithprediction.
• Challengesremaininfastsolvingfluiddynamicswithcomplexrheology,suchasnon-Newtonianrheologyandextremelyvaryingrheology.
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Publications
• Hu,J.,Liu,L.,Hermosillo,A.andZhou,Q.,2016.SimulationoflateCenozoicSouthAmericanflat-slabsubductionusinggeodynamicmodelswithdataassimilation. EarthandPlanetaryScienceLetters, 438,pp.1-13.
• Hu,J.andLiu,L.,2016.AbnormalseismologicalandmagmaticprocessescontrolledbythetearingSouthAmericanflatslabs. EarthandPlanetaryScienceLetters, 450,pp.40-51.
• Hu,J.,Faccenda,M.andLiu,L.,2017.Subduction-controlledmantleflowandseismicanisotropyinSouthAmerica. EarthandPlanetaryScienceLetters, 470,pp.13-24.
On-goingResearch~10,000CPUs~200hours
Modelsize:51.5mgrids
Maximumresolution:27kmx27kmx8km
Featuredresearchinourgroup
Zhouetal.,submitted
Featuredresearchinourgroup
70Masubsidence
60˚N
20˚N
125˚W 65˚W
ModelI(Dyn.Topo.only)Observation
(Liuetal.2008;Smithetal.1994)
Topography(m)
0 2000-2000
Changetal.,inprep.