Variability of Millennial-Scale Trends in the Geomagnetic Axial Dipole

The historical trend in the axial dipole is sufficient to reverse the field in less than 2 kyr. Assessing the prospect of an imminent polarity reversal depends on the probability of sustaining the historical trend for long enough to produce a reversal. We use a stochastic model to predict the variability of trends for arbitrary time windows. Our predictions agree well with the trends computed from paleomagnetic models. Applying these predictions to the historical record shows that the current trend is likely due to natural variability. Furthermore, an extrapolation of the current trend for the next 1 to 2 kyr is highly unlikely. Instead, we compute the trend and time window needed to reverse the field with a specified probability. We find that the dipole could reverse in the next 20 kyr with a probability of 2%

Stochastic Heterogeneity Mapping as a tool to quantify turbulence in reflectivity layers of thermohaline staircases in the Tyrrhenian Sea

European Geosciences Union General Assembly 2013, 7-12 April 2013, Vienna, AustriaProcessed multi-channel seismic data acquired in the Tyrrhenian Sea in April-May 2010 with the B/O Sarmiento de Gamboa provide images of oceanic thermohaline staircases. Thermohaline staircases are regular, well-defined step-like variations in vertical profiles of temperature and salinity. In the ocean they are thought to be the result of double diffusion driven by the two order of magnitude difference in the diffusivities of heat and salt. Staircases are believed to have an anomalously weak internal wave-induced turbulence, making them suitable for the estimation of a lower limit of turbulent disturbances detectable by multi-channel seismics. We apply stochastic heterogeneity mapping based on the band-limited von Kármán function to post-stack time-migrated seismic data to extract stochastic parameters such as the Hurst number (a measure of reflection interface roughness) and correlation length (scale length). For scale sizes smaller than the correlation length, the von Kármán model describes a power law (fractal) process where the Hurst number is its exponent. We present the results of our analysis corroborated by benchmark tests performed on synthetic seismic data generated from random fractal surfaces. The synthetic tests are found to verify the robustness of the technique. Lower Hurst numbers represent a richer range of high wavenumbers and therefore correspond to a broader range of heterogeneity in reflection events. We interpret a broader range of heterogeneity as indicative of a greater degree of turbulence. Some areas of the seismic data show a spatial variation in Hurst number across several frequency bands that may indicate some preferential coupling of energy at different depthsPeer Reviewe

Thermal and electrical conductivity of iron at Earth's core conditions

The Earth acts as a gigantic heat engine driven by decay of radiogenic isotopes and slow cooling, which gives rise to plate tectonics, volcanoes, and mountain building. Another key product is the geomagnetic field, generated in the liquid iron core by a dynamo running on heat released by cooling and freezing to grow the solid inner core, and on chemical convection due to light elements expelled from the liquid on freezing. The power supplied to the geodynamo, measured by the heat-flux across the core-mantle boundary (CMB), places constraints on Earth's evolution. Estimates of CMB heat-flux depend on properties of iron mixtures under the extreme pressure and temperature conditions in the core, most critically on the thermal and electrical conductivities. These quantities remain poorly known because of inherent difficulties in experimentation and theory. Here we use density functional theory to compute these conductivities in liquid iron mixtures at core conditions from first principles- the first directly computed values that do not rely on estimates based on extrapolations. The mixtures of Fe, O, S, and Si are taken from earlier work and fit the seismologically-determined core density and inner-core boundary density jump. We find both conductivities to be 2-3 times higher than estimates in current use. The changes are so large that core thermal histories and power requirements must be reassessed. New estimates of adiabatic heat-flux give 15-16 TW at the CMB, higher than present estimates of CMB heat-flux based on mantle convection; the top of the core must be thermally stratified and any convection in the upper core driven by chemical convection against the adverse thermal buoyancy or lateral variations in CMB heat flow. Power for the geodynamo is greatly restricted and future models of mantle evolution must incorporate a high CMB heat-flux and explain recent formation of the inner core.Comment: 11 pages including supplementary information, two figures. Scheduled to appear in Nature, April 201

Performance benchmarks for a next generation numerical dynamo model

Numerical simulations of the geodynamo have successfully represented many observable characteristics of the geomagnetic field, yielding insight into the fundamental processes that generate magnetic fields in the Earth's core. Because of limited spatial resolution, however, the diffusivities in numerical dynamo models are much larger than those in the Earth's core, and consequently, questions remain about how realistic these models are. The typical strategy used to address this issue has been to continue to increase the resolution of these quasi-laminar models with increasing computational resources, thus pushing them toward more realistic parameter regimes. We assess which methods are most promising for the next generation of supercomputers, which will offer access to O(106) processor cores for large problems. Here we report performance and accuracy benchmarks from 15 dynamo codes that employ a range of numerical and parallelization methods. Computational performance is assessed on the basis of weak and strong scaling behavior up to 16,384 processor cores. Extrapolations of our weak-scaling results indicate that dynamo codes that employ two-dimensional or three-dimensional domain decompositions can perform efficiently on up to ∼106 processor cores, paving the way for more realistic simulations in the next model generation