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Simulating Mantle Convection and Seismic Anisotropy with Data Assimilation Project PI: Lijun Liu, UIUC Presenter: Jiashun Hu Collaborator: Manuele Faccenda, University of Padua, Italy Group members: Quan Zhou, Ching Chang NCSA team: Ryan Mokos, Bill Gropp, Darren Adams, Yifeng Cui Geologist’s view on plate subduction CourtesytoandinmemoryofProf.PaulHeller Whyitmatters– tomodelmantleconvection • Howtheearthworks • Naturalhazards Fromthefilm SanAndreas (Braun2010) TherealEarthismuch morecomplex. fromUSGS Keychallenges • Cleanupboundaryconditions • Earth’shistoryisverycomplex.Wehavelimitedconstraints onthemotionsandtheagesoftheplates. • Largeviscositycontrast • Significantlyslowdowntheconvergenceofthesolver • Requireshigherresolutiontoresolve • Unknownpropertiesandprocesses • Suchasthegenerationandbehaviorofmagmainthe mantlewedge,andthepropertiesofthesuperplumesin deepmantle Potentialproblemswithexisting models • Mostearliermodelsarein2D A • Recent3Dmodelsusedidealized boundaryconditions [vanHunen etal.,2002] B [vanHunen etal.,2000] C [Manea et al.,2012] (Taramon et al., G-cubed, 2015) 5 Potentialproblemswithexisting models • Recent3Dmodelsusedfixedslabgeometry (Flament et al., EPSL, 2015) 6 ModelingS.Americansubduction history Wetrytodevelopamodelthatisconsistentwithallavailable geophysicalandtectonicconstraints: • Theknownsubductionhistory(platemotion&seafloorage) • Dynamicallyevolvinginsteadofprescribedslabs • GoverningEquations • Assumethemantleis an incompressible fluid, which satisfies theBoussinesq approximation 7 WhyBlueWaters • CitcomS hasaverygoodscalability,up to~10,000CPUsonBlueWaters. Machine time (second) 1000 • BlueWatersiscompatiblewiththe softwares weuse,includingCitcomS, DrexS andFSTRACK 100 10 129×257×257 Blue Waters 513×1025×1025 Stampede 1 0 10 1 10 2 10 CPU number 3 10 4 10 • Largercapacityleadstolarger allocationandshorterwaitingtime. Data Assimilation Seafloor age, plate motion, plate geometry,cratons 9 ViscositystructureofS.Americanmodel 4ordersof magnitude incontrast (Huetal.,EPSL, 2016) 10 PredictedSouthAmericansubduction since 100 Ma Modelsize:8.6mgrids Maximumresolution: 27kmx20kmx8km 1024CPUs ~150hours (Huetal.,EPSL, 2016) 11 Accomplishments Thepowerofdataassimilation: Fittinguppermantleslab geometry 12 Fittinglowermantletomography Themodelfitstothetomographyimages wellto1000kmdepth,especiallyinthe northernpartofSouthAmericathathas abetterseismiccoveragethanthe southernpart. 13 Slabtearvs.intra-slabseismicity (Hu&Liu,EPSL,2016) Newinterpretationofflatslabsubduction (Hu&Liu,EPSL,2016) Late Cenozoic Andean Flare-up ThecentralAndesareunusualfortheabundanceoffelsicignimbritesand theirdistributionisshownseparatelyfromtheintermediatetomafic volcaniccenters. Volcaniczoneissignificantlybroadenedsince~30Ma. Thrumbull etal.,2006 Haschke etal.,2002 16 Geologicimplication:Slabdynamics&Andeanevolution N The30-Maslabtear correlateswiththe Andeanignimbriteflareupbothinspaceandin time. Newimplicationson Andeanshortening& upliftaswell? 33Ma N 5Ma 40Ma 15Ma 30Ma N 17 Predictingseismicanisotropy • Calculateseismicanisotropy(LPO)byintegratingthe mantle flowfield • Integrating the anisotropy in the upper mantle to generate synthetic SWS Conclusions • Supercomputers,suchasBlueWaters,makeitfeasibletorun mantle-convectionmodelsin3Dwithatimescaleofhundredsof millionyears. • Theimplementationofdataassimilationmethodisnecessaryin ordertodirectlycompareobservationwithprediction. • Challengesremaininfastsolvingfluiddynamicswithcomplex rheology,suchasnon-Newtonianrheologyandextremelyvarying rheology. 19 Publications • Hu,J.,Liu,L.,Hermosillo,A.andZhou,Q.,2016.SimulationoflateCenozoic SouthAmericanflat-slabsubductionusinggeodynamicmodelswithdata assimilation. EarthandPlanetaryScienceLetters, 438,pp.1-13. • Hu,J.andLiu,L.,2016.Abnormalseismologicalandmagmaticprocesses controlledbythetearingSouthAmericanflatslabs. EarthandPlanetary ScienceLetters, 450,pp.40-51. • Hu,J.,Faccenda,M.andLiu,L.,2017.Subduction-controlledmantleflow andseismicanisotropyinSouthAmerica. EarthandPlanetaryScience Letters, 470,pp.13-24. Modelsize:51.5mgrids On-goingResearch Maximumresolution: 27kmx27kmx8km ~10,000CPUs ~200hours Featuredresearchinourgroup Zhouetal., submitted Featuredresearchinourgroup Observation 125˚W 60˚N 20˚N 70Ma ModelI(Dyn.Topo.only) 65˚W subsidence Topography(m) (Liuetal.2008;Smithetal.1994) -2000 0 2000 Changetal.,inprep.
