Report from the
CIDER Dynamic Topography Working Group Meeting
Boulder, CO, April 67, 2015
Shijie Zhong, CU Boulder
Becky Flowers, CU Boulder
Thorsten W. Becker, USC
April 8, 2015
Sponsored by CIDER, the Dynamic Topography Working Group that formed during the 2013
CIDER Summer Program met in April of 2015 on the CU Boulder campus to discuss a range of issues involving the evolution of Earth's surface topography from a deep mantle dynamics, surface process, and geological perspective.
The meeting brought together 22 participants, five of which were international (see list below), for two days of keynote presentations, shorter format lectures, and extensive discussions. The organizing committee consisted of Becky Flowers, Shijie Zhong, and
Thorsten Becker.
The scientific program was roughly split into of a day of discussions of the role of deep mantle flow and geodynamics in predicting nonisostatic surface topography, and a day of discussions as to how such deflections of the surface are expressed geomorphologically, what controls surface evolution over 10s of millions of years, and longer geological times, and how we can combine efforts from the geologic, geomorphologic, and geodynamic communities across a range of spatiotemporal scales.
While the definition of dynamic topography , or the actual need for a definition, remains vigorously debated, it has been clear since the seventies that the power spectrum of gravity anomalies can be explained by Airy isostasy with the addition of flexural effects for wavelengths shorter than ~1000 km. Signals with wavelengths longer than ~2000 km, however, require an additional explanation, and are hence commonly associated with the effects of mantle flow, and can so be described as dynamic topography . It is therefore typically the longest wavelengths of topography that are explored by mantle dynamic models, although the intermediate range, perhaps ~100 ... 1000 km, is increasingly being probed in terms of dynamic modeling predictions, and attribution remains problematic.
We discussed key geographic sites where one might point to the specific effects of the mantle in affecting topography, and candidates explored were plume regions (Hawaii), anomalously deflected ridge segments (Iceland, Red Sea), and the degree two signal of geoid highs that correlates with deep mantle tomographic velocity anomalies.
One approach of inferring nonisostatically compensated topography that also heralds from the seventies is to use rheologically and geometrically simplified mantle flow models to
derive scaling parameters to directly link the amplitude of gravity anomaly to dynamic deflections of topography. Such admittance values have remained in widespread use since they require no direct modeling of mantle flow. Recently, questions were raised if gravity anomalies then permit dynamic topography anomalies of amplitudes larger than ~300 m, which appears a factor of ten or so smaller than many published mantle flow models would suggest.
There was a lot of discussion at the meeting about the origin of this potential discrepancy, with a number of participants recalling the work of Hager, Richards, and Ricard that showed in the 80ies that a spherical annulus, 3D mantle with a radial viscosity increase exhibits behavior that cannot be approximated by a simple admittance scaling factor. In particular, the geoid, the integral of freeair gravity anomalies, can depend negatively on density anomalies at certain mantle depths and wavelengths, whereas topography shows monotonously positive dependence on density anomalies in the upper ~500 km of the mantle.
This complexity implies that a single admittance value represents a very poor approximation of mantle dynamics, at best. Instead, actual, global mantle flow computations have to be performed, and the resulting model predictions then need to match the geoid and dynamic topography, along a range of other observables such as plate motions. The group spent a lot of time discussing the remaining uncertainties in the associated modeling and inverse approaches.
In some sense, the physics of mantle convection and how it is expressed as dynamic topography are quite well understood, but there is still considerable uncertainty as to the properties of the mantle and lithosphere, both in terms of their density anomalies and viscosity structure, and this leads to limited agreement between the predictions of different geodynamic modelers.
Dynamic topography scales with density anomalies, to first order, and for this, the role of compositional anomalies compared to temperature, e.g. when inferred from seismic tomography, particularly in the thermochemical boundary layers of the mantle, remain to be fully understood. Uplift rates scale with the density anomaly squared divided by viscosity, making rheological uncertainties important for comparisons with the rate of change from topography. Further constraining these parameters and their uncertainties, particularly for the scales and amplitudes of dynamic topography was identified as a key challenge for the near future. While not a new demand, recent advances in numerical modeling now allow performance of more realistic and comprehensive inversions, including exploration of the role of lateral viscosity variations. In this context, renewed efforts in glacial isostatic adjustment studies were called for that include a selfconsistent treatment of the ice loading model to arrive at better constraints on viscosity structure. Since freeair gravity anomalies are sensitive to intermediate and short wavelength structures, geodynamic models should also pay more attention to explain freeair anomalies in addition to the geoid,
Another discussion ensued about the proper reference for a “typical” oceanic lithosphere, for
example from halfspace cooling or plate models, and what such definitions imply for the range of amplitudes of anomalous topography that can be inferred. Using best possible constraints for crustal structure and propagating errors as well as being clear about model assumptions, inherent in any correction of actual topography for residuals, were identified as two key requirements for improved models of nonisostatic topography.
The geomorphologic sessions focused more on comparisons of geological observables, such as exhumation rates from thermochronometry and successive deposition of sedimentary strata throughout continental plate history, with potential deep mantle, tectonic, and erosion signals, and how to best model the process of landscape evolution. For the latter, different methods of inferring river network stability and functionallytransformed steepnessdrainage area curves were explored, along with different numerical approaches to approximate surface processes.
Using landscape evolution models to infer spatiotemporally varying uplift rates from river profiles and general topography metrics is a promising avenue. Such efforts are, however, partially hampered by our understanding of variations in total erodability, the product of actual rock erodability and “precipitation”, i.e. lithological and climate effects. While suggestions of variations of rock erodability of several orders of magnitude can be found in the literature, variations within a factor of ~ten or so appeared more probable to the workshop audience. The degree of fracturing of rock, i.e. density and connectivity of flaws, appears to be a stronger control than actual rock type.
Another argument ensued about the meaning of the stream transport “law”, an empirical relationship with robust observational support that, however, suffers from an incomplete understanding of the underlying physics. Like the GutenbergRichter relationship, it may be one of those powerlaw relationships in nature with several possible, and hence nonunique explanations. This implies that stream transport may be generally described well by a “law” but this relationship may arise from a range of physical processes, with implications for investigations such as the degree to which erosion of high topography might be in the transport limited regime or the extent to which weak lithologies may be shielded from erosion in rivers owing to mantling by gravels (which is in turn affected by climate).
Further characterization of variations in rock erodability, for example by near surface seismic studies trying to link fracture density with empirical variations in erodability, were indentified as a high priority future effort. Moreover, it remains to be seen how climatic and lithological effects might quantitatively explain observed variations in total erodability in a predictive sense.
One of the major challenges overall remains in trying to match the scales of the deep mantle estimates of uplift rates to those seen geologically, where it appears that geological uplift rates might be larger than what geodynamic models would predict, with the uncertainties in rheology being one of the key problems in achieving a parsimonious description. Such efforts are, of course, complicated by the difficulty of removing erosional and tectonic (i.e.
shortening and extension) contributions to topography. This is perhaps the biggest challenge in our joint efforts in trying to establish the first order observable topography, including in tectonically active regions, as a true constraint for our understanding of deep mantle dynamics.
It is likely that such efforts of topographic fingerprinting will require an interdisciplinary approach and comprehensive, joint modeling work, establishing multiple links between the deep mantle and surface processes for increased robustness. Eventually, such efforts will contribute by opening up the study of topography variations as a realization of just one component of one of the grand challenges in the Earth sciences, understanding, predicting, and constraining intraplate deformation, plate boundary evolution, and continental dynamics over geological time.
Workshop participants
Bob Anderson (University of Colorado at Boulder)
Thorsten Becker (University of Southern California)
Magali Billen (University of California at Davis)
Clint Conrad (University of Hawaii)
Lang Farmer (University of Colorado at Boulder)
Becky Flowers (University of Colorado at Boulder)
Alessandro Forte (University of Montreal)
Mike Gurnis (Caltech)
Paul Heller (University of Wyoming)
Gene Humphreys (University of Oregon)
Lijun Liu (University of Illinois at Urbana-Champaign)
Peter Molnar (University of Colorado at Boulder)
Louis Moresi (University of Melbourne)
David Rowley (University of Chicago)
Mousumi Roy (University of New Mexico)
Greg Tucker (University of Colorado at Boulder)
Tony Watts (Oxford University)
Jolante van Wijk (New Mexico Tech)
Kelin Whipple (Arizona State University)
Nicky White (Cambridge University)
Sean Willett (ETH)
Shijie Zhong (University of Colorado at Boulder)