Oxygen fugacity control in piston-cylinder experiments: a re-evaluation

Jakobsson (Contrib Miner Petrol 164(3):397–407, 2012) investigated a double capsule assembly for use in piston-cylinder experiments that would allow hydrous, high-temperature, and high-pressure experiments to be conducted under controlled oxygen fugacity conditions. Using a platinum outer capsule containing a metal oxide oxygen buffer (Ni–NiO or Co–CoO) and H₂O, with an inner gold–palladium capsule containing hydrous melt, this study was able to compare the oxygen fugacity imposed by the outer capsule oxygen buffer with an oxygen fugacity estimated by the AuPdFe ternary system calibrated by Barr and Grove (Contrib Miner Petrol 160(5):631–643, 2010). H₂O loss or gain, as well as iron loss to the capsule walls and carbon contamination, is often observed in piston-cylinder experiments and often go unexplained. Only a few have attempted to actually quantify various aspects of these changes (Brooker et al. in Am Miner 83(9–10):985–994, 1998; Truckenbrodt and Johannes in Am Miner 84:1333–1335, 1999). It was one of the goals of Jakobsson (Contrib Miner Petrol 164(3):397–407, 2012) to address these issues by using and testing the AuPdFe solution model of Barr and Grove (Contrib Miner Petrol 160(5):631–643, 2010), as well as to constrain the oxygen fugacity of the inner capsule. The oxygen fugacities of the analyzed melts were assumed to be equal to those of the solid Ni–NiO and Co–CoO buffers, which is incorrect since the melts are all undersaturated in H₂O and the oxygen fugacities should therefore be lower than that of the buffer by 2 log $a_{{{\text{H}}_{ 2} {\text{O}}}}$ .     

Internal deformation of a muddy gravity flow and its interaction with the seafloor (site C0018 of IODP Expedition 333, Nankai Trough,SE Japan)

The processes of flow deformation of marine mass-transport sediments, including their ability to affect the underlying substrate and add mass during sediment flow events, are addressed based on sedimentological analyses of strata from the distal part of a ～61-m-thick mass-transport deposit (MTD 6) drilled during Integrated Ocean Drilling Program (IODP) Expedition 333. Our analyses, supported by 3D seismic data, show a cohesive density flow deformed by folding, faulting and shear, except for its lowermost part (～7 m), where no deformation and sediment entrainment was identified. While the lowermost part moved as rigid sediment, the underlying sand layer acted as the basal shear zone for this part of the distal MTD 6. This shear zone was restricted to the sand, not involving the overlying sediments. From this, the studied part of MTD 6 was found to represent a case where the flow behaviour at least partly depended on the location and properties of the underlying sand layer, a situation that so far has received little attention in studies of marine flows. Our results also show that shear-induced mixing, located by the initial layering, is an important process in the flow transformation from cohesive slumps to mud flows and that this may occur over short distances (<4 km) without involving disintegration into blocks, probably due to only moderate prefailure consolidation of the sediments involved. In conclusion, we find that the bulk part of the flow was self-contained from a mass balance point of view and that that the overall amount of entrainment was limited.     

Near real-time ocean circulation assimilation and prediction in the Intra-Americas Sea with ROMS

We present the feasibility of a prototype, near real-time assimilation and ensemble prediction system for the Intra-Americas Sea run autonomously aboard a ship of opportunity based on the Regional Ocean Modeling System (ROMS). Predicting an ocean state depends upon numerical models that contain uncertainties in their modeled physics, initial conditions, and model state. An advanced model, four-dimensional variational assimilation, and ensemble forecasting techniques are used to account for each of these uncertainties. Every 3 days, data from the previous 7 days period were assimilated to generate an estimate of the circulation and to create an ensemble of 2 weeks forecasts of the ocean state. This paper presents the methods and results for a multi-resolution assimilation system and ensemble forecasts of surface fields and dominant surface circulation features. When compared to post-processed science quality observations, the state estimates suffer from our reliance on real-time, quick-look satellite observations of the ocean surface. Despite a number of issues, the ensemble forecast estimate is often superior to observational persistence. This proof-of-concept prototype performed well enough to reveal deficiencies, provide useful insights, valuable lessons, and guidance for future improvements in real-time ocean forecasting.     

High pressure crystallization of the Ewarara,Kalka and Gosse Pile intrusions,Giles Complex,central Australia

Evidence is presented for the primary high pressure crystallization of the Ewarara, Kalka and Gosse Pile layered intrusions which form part of the Giles Complex in central Australia. These pressures are estimated at 10 to 12 kb. The high pressure characteristics include subsolidus reactions between olivine and plagioclase, orthopyroxene and plagioclase, and orthopyroxene and spinel; spinel and rutile exsolution in both ortho- and clino-pyroxene; spinel exsolution in plagioclase; high Al₂O₃ and Cr₂O₃ contents of both ortho- and clinopyroxene; high Al^VI in clinopyroxene; dominance of orthopyroxene as an early crystallizing phase; high distribution coefficients for co-existing pyroxene pairs; and thin chilled margins. Such phenomena are rare in documented layered basic intrusions.     

Modelling snowpack bulk density using snow depth,cumulative degree-days,and climatological predictor variables

Snowpack water equivalent (SWE) is a key variable for water resource management in snow-dominated catchments. While it is not feasible to quantify SWE at the catchment scale using either field surveys or remotely sensed data, technologies such as airborne LiDAR (light detection and ranging) support the mapping of snow depth at scales relevant to operational water management. To convert snow depth to water equivalent, models have been developed to predict SWE or snowpack density based on snow depth and additional predictor variables. This study builds upon previous models that relate snowpack density to snow depth by including additional predictor variables to account for (1) long-term climatologies that describe the prevailing conditions influencing regional snowpack properties, and (2) the effect of intra- and inter-year variability in meteorological conditions on densification through a cumulative degree-day index derived from North American Regional Reanalysis products. A non-linear model was fit to 114 506 snow survey measurements spanning 41 years from 1166 snow courses across western North America. Under spatial cross-validation, the predicted densities had a root-mean-square error of 47.1 kg m⁻³, a mean bias of −0.039 kg m⁻³, and a Nash-Sutcliffe Efficiency of 0.70. The model developed in this study had similar overall performance compared to a similar regression-based model reported in the literature, but had reduced seasonal biases. When applied to predict SWE from simulated depths with random errors consistent with those obtained from LiDAR or Structure-from-Motion, 50% of the SWE estimates for April and May fell within −45 to 49 mm of the observed SWE, representing prediction errors of −15% to 20%.