Millennial-scale sea-level control on avulsion events on the Amazon Fan

The Late Quaternary Amazon deep-sea fan provides a modern analogue to ancient fan systems containing coarse-grained hydrocarbon reservoirs. Sand lenses deposited within the Amazon Fan, due to abrupt shifts in channel pathways called avulsion events, were drilled as part of ODP Leg 155. The hemipelagic sediment directly on top of the avulsion sands was dated using primarily AMS radio carbon dating. This dating shows that these large sand lobes (1 km³) are triggered by relatively small, millennial scale changes in marine transgression and regression (±5–10 m). Relative sea level also controls the architecture of the Channel–levee distributive systems within the Amazon Fan. For example prior to 22 k calendar years BP there is a tripartite channel system. After 22 ka there is only one active Channel–levee system. Transitions between the multi-channel and single channel configurations are related to variations in the volume of sediment supply resulting in aggradation or erosion of channel floor and levee growth in the canyon-channel transition area. The sensitivity of the Amazon deep-sea Fan sedimentation to relatively small changes in sea level supports one of the central assumptions of the theory of Sequence Stratigraphy. In addition this study demonstrates how traps for hydrocarbons may have been formed in ancient fan systems.     

A comparison of permafrost prediction models along a section of Trail Ridge Road, Rocky Mountain National Park, Colorado, USA

The distribution of mountain permafrost along Trail Ridge Road (TRR) in Rocky Mountain National Park, Colorado, was modeled using ‘frost numbers’ and a ‘temperature of permafrost model’ (TTOP) in order to assess the accuracy of prediction models. The TTOP model is based on regional observations of air temperature and heat transfer functions involving vegetation, soil, and snow; whereas the frost number model is based on site-specific ratios of ground temperature measurements of frozen and thawed degree-days. Thirty HOBO© temperature data loggers were installed near the surface as well as at depth (30 to 85 cm). From mid-July 2008 to 2010, the mean annual soil temperature (MAST) for all surface sites was − 1.5 °C. Frost numbers averaged 0.56; TTOP averaged − 1.8 °C. The MAST was colder on western-facing slopes at high elevations. Surface and deeper probes had similar MASTs; however, deeper probes had less daily and seasonal variation. Another model developed at the regional scale based on proxy indicators of permafrost (rock glaciers and land cover) classified 5.1 km² of permafrost within the study area, whereas co-kriging interpolations of frost numbers and TTOP data indicated 2.0 km² and 4.6 km² of permafrost, respectively. Only 0.8 km² were common among all three models. Three boreholes drilled within 2 m of TRR indicate that permafrost does not exist at these locations despite each borehole being classified as containing permafrost by at least one model. Addressing model uncertainty is important because nutrients stored within frozen or frost-affected soils can be released and impact alpine water bodies. The uncertainty also exposes two fundamental problems: empirical models designed for high latitudes are not necessarily applicable to mountain permafrost, and the presence of mountain permafrost in the alpine tundra of the Colorado Front Range has not been validated.     

A Severance Tax Revenue Forecast Model for Louisiana

Most states levy severance taxes on the value of natural resources when they are severed or extracted from the ground or subsurface. In Louisiana, severance tax on oil and gas production contributes to the majority of mineral revenue in the state, and over the last decade, has ranged between $400 million and $1.1 billion, or between 5 and 9% of annual state revenue. The purpose of this article is to develop a forecast model for severance tax revenue to better understand the severance tax regime and to assist in state budgeting and planning purposes. We couple an oil and gas production model with empirical relationships describing historical severance tax receipts to perform the forecast. We demonstrate that oil production correlations are robust, but that in recent years, unconventional gas production from the Haynesville shale has led to a significant departure from historic trends. We estimate that cumulative oil and gas severance tax revenues during 2011–2015 will range from $1.0 to $2.1 billion for oil and $1.3–$1.9 billion for gas. Louisiana is transforming into a gas-producing state, and more attention needs to be paid to tax design and the impact of exemptions on future severance revenue receipts.     

Power spectrum for the small-scale Universe

The first objects to arise in a cold dark matter (CDM) universe present a daunting challenge for models of structure formation. In the ultra small-scale limit, CDM structures form nearly simultaneously across a wide range of scales. Hierarchical clustering no longer provides a guiding principle for theoretical analyses and the computation time required to carry out credible simulations becomes prohibitively high. To gain insight into this problem, we perform high-resolution  ( N = 720³–1584³)  simulations of an Einstein–de Sitter cosmology where the initial power spectrum is   P ( k ) ∝ k ⁿ ,  with  −2.5 ≤ n ≤− 1  . Self-similar scaling is established for   n =−1  and −2 more convincingly than in previous, lower resolution simulations and for the first time, self-similar scaling is established for an   n =−2.25  simulation. However, finite box-size effects induce departures from self-similar scaling in our   n =−2.5  simulation. We compare our results with the predictions for the power spectrum from (one-loop) perturbation theory and demonstrate that the renormalization group approach suggested by McDonald improves perturbation theory's ability to predict the power spectrum in the quasi-linear regime. In the non-linear regime, our power spectra differ significantly from the widely used fitting formulae of Peacock & Dodds and Smith et al. and a new fitting formula is presented. Implications of our results for the stable clustering hypothesis versus halo model debate are discussed. Our power spectra are inconsistent with predictions of the stable clustering hypothesis in the high- k limit and lend credence to the halo model. Nevertheless, the fitting formula advocated in this paper is purely empirical and not derived from a specific formulation of the halo model.     

Mechanisms for the land/sea warming contrast exhibited by simulations of climate change

The land/sea warming contrast is a phenomenon of both equilibrium and transient simulations of climate change: large areas of the land surface at most latitudes undergo temperature changes whose amplitude is more than those of the surrounding oceans. Using idealised GCM experiments with perturbed SSTs, we show that the land/sea contrast in equilibrium simulations is associated with local feedbacks and the hydrological cycle over land, rather than with externally imposed radiative forcing. This mechanism also explains a large component of the land/sea contrast in transient simulations as well. We propose a conceptual model with three elements: (1) there is a spatially variable level in the lower troposphere at which temperature change is the same over land and sea; (2) the dependence of lapse rate on moisture and temperature causes different changes in lapse rate upon warming over land and sea, and hence a surface land/sea temperature contrast; (3) moisture convergence over land predominantly takes place at levels significantly colder than the surface; wherever moisture supply over land is limited, the increase of evaporation over land upon warming is limited, reducing the relative humidity in the boundary layer over land, and hence also enhancing the land/sea contrast. The non-linearity of the Clausius–Clapeyron relationship of saturation specific humidity to temperature is critical in (2) and (3). We examine the sensitivity of the land/sea contrast to model representations of different physical processes using a large ensemble of climate model integrations with perturbed parameters, and find that it is most sensitive to representation of large-scale cloud and stomatal closure. We discuss our results in the context of high-resolution and Earth-system modelling of climate change.     

Mesoscale Structure of Trade Wind Convection over Puerto Rico: Composite Observations and Numerical Simulation

We examine the mesoscale structure of the atmospheric boundary layer (ABL), low-level circulation, and trade wind convection over the sub-tropical island of Puerto Rico in mid-summer. Shallow afternoon thunderstorms are frequently seen over the western plains of the island. Observational data include automatic weather station measurements, radiosonde profiles, infrared satellite images, and mesoscale reanalysis data with a focus on the summer of 2006. Satellite microwave radar data (TRMM and CloudSat) indicate that island clouds typically extend just above the −20°C level during afternoon hours with reflectivity values reaching 50 dBz. A singular value decomposition of 3-hourly high resolution satellite rainfall maps reveals an island mode. From this a composite is constructed for a group of ten cases. With a Froude number ≈1 the trade winds pass over the mountains and standing vortices and gravity waves are trapped in the meandering wake. The Weather and Research Forecasting (WRF) model at 1-km resolution with 51 vertical layers is used to simulate the short-lived thunderstorms for two cases: 27 June and 20 July 2006. The model correctly locates the convective cells that develop between 1400 and 1700 LST. The shallow afternoon thunderstorms are triggered by surface heat fluxes, confluent sea breezes and a mountain wake. Recommendations for enhanced observations are given.     

Bias Correction for View-limited Lidar Scanning of Rock Outcrops for Structural Characterization

Lidar is a remote sensing technology that uses time-of-flight and line-of-sight to calculate the accurate locations of physical objects in a known space (the known space is in relation to the scanner). The resultant point-cloud data can be used to virtually identify and measure geomechanical data such as joint set orientations, spacing and roughness. The line-of-sight property of static Lidar scanners results in occluded (hidden) zones in the point-cloud and significant quantifiable bias when analyzing the data generated from a single scanning location. While the use of multiple scanning locations and orientations, with merging of aligned (registered) scans, is recommended, practical limitations often limit setup to a single location or a consistent orientation with respect to the slope and rock structure. Such setups require correction for measurement bias. Recent advancements in Lidar scanning and processing technology have facilitated the routine use of Lidar data for geotechnical investigation. Current developments in static scanning have lead to large datasets and generated the need for automated bias correction methods. In addition to the traditional bias correction due to outcrop or scanline orientation, this paper presents a methodology for correction of measurement bias due to the orientation of a discrete discontinuity surface with respect to the line-of-sight of the Lidar scanner and for occlusion. Bias can be mathematically minimized from the analyzed discontinuity orientation data.