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Crustal Thickness and Geodynamics of the Western U.S. (NEW!!! Brought to You By EarthScope) Anthony R. Lowry Department of Geology, Utah State University.

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Presentation on theme: "Crustal Thickness and Geodynamics of the Western U.S. (NEW!!! Brought to You By EarthScope) Anthony R. Lowry Department of Geology, Utah State University."— Presentation transcript:

1 Crustal Thickness and Geodynamics of the Western U.S. (NEW!!! Brought to You By EarthScope) Anthony R. Lowry Department of Geology, Utah State University tony.lowry@usu.edu Thanks Also To: Philip Crotwell, University of South Carolina Jon Kirby, Curtin University, Perth, Australia Marta Pérez-Gussinyé, CSIC Barcelona, Spain Christine Puskas, University of Utah Joel Rackham, Utah State University Bob Smith, University of Utah Chris Swain, Curtin University, Perth, Australia Topography Gravity Seismic (Moho) Heat Flow 3D Viscosity

2 Just a bit on Isostatic Analysis Where Geodynamics (& Rheology) come into play… Crustal Thickness estimation from EarthScope Transportable Array (TA) seismometers Some likely geodynamical implications of western U.S. crustal thickness…

3 Isostasy Local Isostasy    Flexural Isostasy Balance of vertical stress in a fluid “asthenosphere” Equilibrium of horizontal and vertical stress for an elastic plate (or “lithosphere”) over a fluid “asthenosphere”   

4 Isostatic Analysis:  Uses easily available data (gravity, topography)  Parameterized by flexural rigidity (  rheology)  Provides information about loads (  mass flux processes) Topography &/or Bathymetry Gravity or Geoid Effective Elastic Thickness (T e )

5 Loads  Mass Flux Processes: Gravity & Topography reflect a complicated mix of all mass flux processes… But if we can separate the loads from their isostatic response, it narrows the field of candidate processes. Surface Loads  Erosion  Deposition  Fault Displacements  Volcanic Construction Subsurface Loads  Thermal Variations  Lithologic Variations  Crustal Thickness (Lower Crustal Flow)

6 METHOD: Using equations for observed topography h and geoid N including:  the definition of surface load  finite amplitude geoid calculation  flexure of a thin elastic shell over a self-gravitating, viscous sphere Then search for T e (& perhaps other parameters) that minimize the difference between observed & predicted coherence Or equivalently, that minimize coherence of the load fields

7 EXAMPLE   The Tharsis Rise, Mars: Martian Topography: Hemispheric “crustal dichotomy” Tharsis rise ~ 5000 m elevation 20% of surface area Martian Geoid: 2000 m Tharsis anomaly (largest in solar system!)

8 Controversial Nature of Tharsis Rise: Volcanic Construction? (  Surface Load!) Thermal/chemical buoyancy of a single mantle plume? [e.g., Willemann & Turcotte, 1982; Solomon & Head, 1982] [e.g., Sleep & Phillips, 1979; Harder & Christensen, 1996; Harder, 2000] Probably some combination of both!

9 “BEST ESTIMATE” (i.e., minimum load correlation)  ~ 17 km volcanic extrusives ~ 12 km flexural deflection Small (~ 5%) internal load

10 Flexural Rigidity reflects rheology, and hence distributions of intraplate seismicity

11 Reflects both the geotherm and composition… T e and Flow Rheology

12 A Geodynamical Application: Flat Slab Subduction Many studies emphasize buoyancy of the down-going slab and/or velocity of the over-riding upper plate as controls on subduction geometry But these are poorly correlated with slab dip in South America

13 Correlation of South American flat slab subduction with high T e near the trench suggests thickness of viscous upper plate may control subduction geometry! Isostasy illuminates geodynamics…

14 The Problem: Recovery from synthetic data, from Pérez-Gussinyé et al. [2007]: Kirby & Swain [G 3, 2008] found poor recovery where sub-sampled wavelet load fields exhibit chance correlation

15 E.g., EARS receiver function estimates of crustal thickness [Crotwell & Owens, SRL, 2005] http://www.seis.sc.edu/ears/index.html Possible Solution: Use seismic data to independently constrain internal mass fields

16 EarthScope sampling is promising, but Receiver function compilations such as EARS are prone to outliers & errors

17 Receiver Function Estimates of Crustal Thickness: PPsPs Delay Time Deconvolve source-time function to get impulse response of phases converted at impedance boundaries Delay time between phase arrivals depends on crustal thickness and P- & S-velocity EARS uses iterative time-domain deconvolution [Ligorria & Ammon, BSSA, 1999]: well-suited to automation PPsPs Crust Mantle

18 PPsPsPpPs PpSs PsPs Contribution of crustal thickness H versus V p /V s ratio K to delay time is ambiguous… Resolve using reverberations, which have differing sensitivity to H and K PPsPsPpPsPpSsPsPsPsPs

19 Ps PsPs PpSs & PpPs H - K parameters that predict the observed phase delay times intersect at a point in parameter space PPsPpPs PpSs PsPs H–K Stacking: [Zhu & Kanamori, JGR, 2000]

20 Ps PsPs PpSs & PpPs Method stacks observed amplitudes at delay times predicted for each phase, for all earthquakes. Max stack amplitude should reveal true crustal thickness & V p /V s ratio. H–K Stacking: [Zhu & Kanamori, JGR, 2000] PPsPpPs PpSs PsPs (EARS H–K stack for station COR)

21 The Moho is not the only lithospheric impedance contrast… And crustal thickness is not constant EARS can yield extreme crustal thickness or unlikely changes over short distances. The Problem: (EARS H–K stack for station Y35)

22 Despite outliers, H & K have properties consistent with a fractal surface… Crustal Thickness H V p /V s Ratio K

23 Station TA.P10A (Central Nevada) The semivariance properties can be used to estimate a “most likely” crustal thickness and V p /V s ratio by optimal interpolation from nearby sites. 11 22

24 Station TA.P10A (Central Nevada) Can also model gravity predicted by estimates… And find a “most likely” model with uncertainties. 11 22 11 22

25 Station TA.S16A (Central Utah) Gravity Model Likelihood Filter Optimal Interp. Likelihood Filter Combined

26  Unlikely stack amplitude maxima are downweighted using likelihood statistics Station TA.P10A (Central Nevada)

27 Method removes outliers, provides a map that makes sense (with some exceptions)

28 The reliable (i.e. western) parts of the map confirm some already- known aspects of western U.S. geodynamics & also suggest a few new interpretations…

29 EARS-derived Old refraction data

30 The reliable (i.e. western) parts of the map confirm some already- known aspects of western U.S. geodynamics & also suggest a few new interpretations…

31 And interesting patterns show up in V p /V s Raw EARS estimatesWeighted stack estimates

32 Perhaps the most intriguing implications arise from the gravity modeling however…


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