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The mean land-surface temperature represents an important boundary condition for many geothermal studies. This boundary is particularly important to help constrain the models made to analyse resource systems, many of which are shallow in nature and observe relatively small thermal gradients. Consequently, a mean land-surface temperature map of the Australian continent has been produced from 13 years of MODIS satellite imagery, for the period 2003–2015. The map shows good agreement with independent methods of estimating mean land-surface temperature, including borehole surface-temperature extrapolation and long-term, near-surface ground measurements. In comparison to previously used methods of estimating mean land-surface temperature, our new estimates are up to 12 °C warmer. The MODIS-based method presented in this study provides spatially continuous estimates of land-surface temperature that can be incorporated as the surface thermal boundary condition in geothermal studies. The method is also able to provide a quantification of the uncertainties expected in the application of these estimates for the purposes of thermal modelling. [ABSTRACT FROM AUTHOR]

Abstract: India–Somalia and North America–Eurasia relative motions since Early Miocene ( ) have been recently reconstructed at unprecedented temporal resolution ( ) from magnetic surveys of the Carlsberg and northern Mid-Atlantic Ridges. These new datasets revamped interest in the convergence of India relative to Eurasia, which is obtained from the India–Somalia–Nubia–North America–Eurasia plate circuit. Unless finite rotations are arbitrarily smoothed through time, however, the reconstructed kinematics (i.e. stage Euler vectors) appear to be surprisingly unusual over the past . In fact, the Euler pole for the India–Eurasia rigid motion scattered erratically over a broad region, while the associated angular velocity underwent sudden increases and decreases. Consequently, convergence across the Himalayan front featured significant speed-ups as well as slow-downs with almost no consistent trend. Arguably, this pattern arises from the presence of data-noise, which biases kinematic reconstructions—particularly at high temporal resolution. The rapid and important India–Eurasia plate-motion changes reconstructed since Early Miocene are likely to be of apparent nature, because they cannot result even from the most optimistic estimates of torques associated, for instance, with the descent of the Indian slab into Earth's mantle. Our previous work aimed at reducing noise in finite-rotation datasets via an expanded Bayesian formulation, which offers several advantages over arbitrary smoothing methods. Here we build on this advance and revise the India–Eurasia kinematics since , accounting also for three alternative histories of rifting in Africa. We find that India–Eurasia kinematics are simpler and, most importantly, geodynamically plausible upon noise reduction. Convergence across the Himalayan front overall decreased until , but then systematically increased, albeit moderately, towards the present-day. We test with global dynamic models of the coupled mantle/lithosphere system how a previously proposed uplift of the Tibetan plateau by 1–2km, as well as the break-up of the Indo-Australian plate into the India and Australia units, impact the kinematic record from to . Our modelling results indicate that the convergence slow-down until resulted chiefly from the Indo-Australian break-up. However, the tectonic scenario yielding the best fit to kinematic reconstructions is indeed one where the Tibetan mean elevation increased by 1–2km before the Indo-Australian break-up was accomplished. [Copyright &y& Elsevier]

Abstract: We present a method to quantify abrupt changes (or changepoints) in data series, represented as a function of depth or time. These changes are often the result of climatic or environmental variations and can be manifested in multiple datasets as different responses, but all datasets can have the same changepoint locations/timings. The method we present uses transdimensional Markov chain Monte Carlo to infer probability distributions on the number and locations (in depth or time) of changepoints, the mean values between changepoints and, if required, the noise variance associated with each dataset being considered. This latter point is important as we generally will have limited information on the noise, such as estimates only of measurement uncertainty, and in most cases it is not practical to make repeat sampling/measurement to assess other contributions to the variation in the data. We describe the main features of the approach (and describe the mathematical formulation in supplementary material), and demonstrate its validity using synthetic datasets, with known changepoint structure (number and locations of changepoints) and distribution of noise variance for each dataset. We show that when using multiple data, we expect to achieve better resolution of the changepoint structure than when we use each dataset individually. This is conditional on the validity of the assumption of common changepoints between different datasets. We then apply the method to two sets of real geochemical data, both from peat cores, taken from NE Australia and eastern Tibet. Under the assumption that changes occur at the same time for all datasets, we recover solutions consistent with those previously inferred qualitatively from independent data and interpretations. However, our approach provides a quantitative estimate of the relative probability of the inferred changepoints, allowing an objective assessment of the significance of each change. [Copyright &y& Elsevier]

Over the past decade, we have applied laser ablation ICP mass spectrometry U-series analysis to a large number of bones and teeth. The method is fast and provides high-resolution data of U-series isotopes, which give insights into the complexity of uranium migration into, within and out of bones. In this paper, we present our laser ablation approach in detail, from the experimental set up, to data reduction and uranium diffusion modelling. Laser ablation analysis can now be applied with minimum damage. Complete diffusion data sets can be obtained by laser drilling which leaves a hole of around 200 μm in diameter and 1–2 mm depth. If the natural U-diffusion follows a simple single-stage process, valuable age information can be obtained. In other cases, highly complex U-migrations have been observed, which make any age assessment impossible. Two examples from Wadjak and Callao illustrate the potential of nearly non-destructive laser ablation U-series analysis of human skeletal tissues. The results demonstrate the physical presence of modern humans in south-east Asia at a time when our species just started to migrate into Europe. [ABSTRACT FROM AUTHOR]

Abstract: The silicon (Si) isotope (δ 30Si) composition of deep-sea sponges from near Antarctica, subantarctic waters (Tasmania Seamounts) and subtropical waters north of New Zealand vary widely between +0.87‰ and −3.40‰ (vs. NBS28). Depth profiles show that sponge δ 30Si compositions trend to lower values with increasing depth. This is exemplified by sponges from the Tasmania Seamounts where δ 30Si varies from +0.87‰ to −3.13‰ over a depth range from 100m to 1200m. These changes in δ 30Si of sponges are inconsistent with a Rayleigh type isotope fractionation model requiring constant δ 30Si fractionation between sponge and seawater. We conclude that overall Si isotope fractionation Δ 30Si (δ 30Si sponge – δ 30Si seawater) is influenced by seawater Si concentration, with more fractionated (lower) isotope values being associated with sponges collected from waters high in Si. We invoke and fit a model whereby the Δ 30Si fractionation varies as a function Si influx and efflux. Using this model it appears that Δ 30Si fractionation during transport into the sponge is constant at −1.34‰. The model also shows asymptotic behaviour with Δ 30Si trending towards a maximum of −6.02‰ at very high Si concentrations. These results suggest that the δ 30Si composition of fossil spicules may be useful for reconstruction paleo-Si concentrations during the past. [Copyright &y& Elsevier]

Abstract: We present an overview of Markov chain Monte Carlo, a sampling method for model inference and uncertainty quantification. We focus on the Bayesian approach to MCMC, which allows us to estimate the posterior distribution of model parameters, without needing to know the normalising constant in Bayes'' theorem. Given an estimate of the posterior, we can then determine representative models (such as the expected model, and the maximum posterior probability model), the probability distributions for individual parameters, and the uncertainty about the predictions from these models. We also consider variable dimensional problems in which the number of model parameters is unknown and needs to be inferred. Such problems can be addressed with reversible jump (RJ) MCMC. This leads us to model choice, where we may want to discriminate between models or theories of differing complexity. For problems where the models are hierarchical (e.g. similar structure but with a different number of parameters), the Bayesian approach naturally selects the simpler models. More complex problems require an estimate of the normalising constant in Bayes'' theorem (also known as the evidence) and this is difficult to do reliably for high dimensional problems. We illustrate the applications of RJMCMC with 3 examples from our earlier working involving modelling distributions of geochronological age data, inference of sea-level and sediment supply histories from 2D stratigraphic cross-sections, and identification of spatially discontinuous thermal histories from a suite of apatite fission track samples distributed in 3D. [Copyright &y& Elsevier]

• A quantitative method resolves the fine structure of the D″ layer. • Small-scale heterogeneities exist at CMB beneath eastern Alaska & northern Pacific. • There is a lack of correlation between D″ topography and shear velocity variation. • The D″ layer may be a mixed boundary layer comprised of thermo-chemical anomalies. • Inferred accumulated slab material suggests different mantle convection styles. The D″ layer, regarded as a thermal boundary layer and a chemically distinct region above the core-mantle boundary (CMB), has been associated with the phase transition from bridgmanite (Bm) to post-perovskite (pPv) in the lowermost mantle. However, the composition of the lowermost mantle and thermal conditions where Bm-pPv phase-transition occurs is still debatable. The methods typically used to study the fine-scale seismic features in the D″ layer has provided important information. However, trial-and-error seismic waveform modelling cannot uniquely quantify D″-layer properties because of subjective model-parameterization choices and inherent non-uniqueness of solutions and the waveform inversion method has a limited resolution of the velocity gradient and depth of the D″ discontinuity. We develop a grid-search scheme to constrain the detailed 1-D shear-wave velocity structure in the lowermost mantle beneath Alaska and the northern Pacific, accompanied with quantitative assessment of the uncertainty of 1D models. Our results show strong lateral variations of the D″ discontinuity from west to east beneath Alaska, along with the existence of smaller-scale heterogeneities in the east. We find a broad velocity increase, as thick as 240 km, at the top of D″ that indicates this region may involve a composite of downwelling thermo-chemical anomalies at the CMB. There are even smaller scale heterogeneities of approximately 120 km × 120 km in size with larger lateral variations in the lowermost mantle beneath northern Pacific. Both the magnitude and gradient of the velocity at the top of the D″ layer vastly change in adjacent regions, with an increase from 2.8% to 4.5% in magnitude and from 0.08% to 1.2% in gradient, but with a relatively consistent depth of the D″ discontinuity at ∼340 km above the CMB. The weak correlation between D″ topography and velocity variations indicate chemical heterogeneities must be present beneath the northern Pacific, which might come from north-westward subducted Pacific oceanic lithosphere. Our characterisation of the spatial pattern of small-scale heterogeneities in the lowermost mantle supports a hybrid thermo-chemical boundary layer (TCBL) model beneath Alaska and northern Pacific. [ABSTRACT FROM AUTHOR]