Is the ocean floor a fractal?

The topographic structure of the ocean bottom is investigated at different scales of resolution to answer the question: Can the seafloor be described as a fractal process? Methods from geostatistics, the theory of regionalized variables, are used to analyze the spatial structure of the ocean floor at different scales of resolution. The key to the analysis is the variogram criterion: Self-similarity of a stochastic process implies self-similarity of its variogram. The criterion is derived and proved here: it also is valid for special cases of self-affinity (in a sense adequate for topography). It has been proposed that seafloor topography can be simulated as a fractal (an object of Hausdorff dimension strictly larger than its topological dimension), having scaling properties (self-similarity or self-affinity). The objective of this study is to compare the implications of these concepts with observations of the seafloor. The analyses are based on SEABEAM bathymetric data from the East Pacific Rise at 13°N/104°W and at 9°N/104°W and use tracks that run both across the ridge crest and along the ridge flank. In the geostatistical evaluation, the data are considered as a stochastic process. The spatial continuity of this process is described by variograms that are calculated for different scales and directions. Applications of the variogram criterion to scale-dependent variogram models yields the following results: Although the seafloor may be a fractal in the sense of the definition involving the Hausdorff dimension, it is not self-similar, nor self-affine (in the given sense). Mathematical models of scale-dependent spatial structures are presented, and their relationship to geologic processes such as ridge evolution, crust formation, and sedimentation is discussed.     

Validation and error analysis of a strata modelling technique

Summary Sources of error are investigated for a two-dimensional finite difference computer program designed to model strata deformation. The program calculates the displacements of a mesh of mass points, by the iterative solution of equations of equilibrium for the stresses acting on each mass point. The effect of errors on both displacement estimates and stress estimates is considered.Round-off errors are discussed analytically, while the effect of choosing too coarse a mesh density is demonstrated by comparison of two runs of the program with identical material properties, but different mesh densities. The influence of boundary conditions and the result of incomplete relaxation of the finite difference equations is estimated by comparison with Kirsch's analytical solution for a thin plate of finite width with a circular hole under unidimensional load.As a result of the analysis, estimators for stresses and displacements are derived, which make allowance for some of the sources of error; suitable boundary conditions for first and subsequent runs of the program are proposed; and a convergence criterion for the iterative process is suggested. These results are then applied to simulations of mining situations, together with various refinements of the basic model, such as separation and slip between adjacent strata, and an allowance for failure of material.     

Insights into oil cracking based on laboratory experiments

The objectives of this pyrolysis investigation were to determine changes in (1) oil composition, (2) gas composition and (3) gas carbon isotope ratios and to compare these results with hydrocarbons in reservoirs. Laboratory cracking of a saturate-rich Devonian oil by confined, dry pyrolysis was performed at T=350–450 °C, P=650 bars and times ranging from 24 h to 33 days. Increasing thermal stress results in the C₁₅₊ hydrocarbon fraction cracking to form C_6–14 and C_1–5 hydrocarbons and pyrobitumen. The C_6–14 fraction continues to crack to C_1–5 gases plus pyrobitumen at higher temperatures and prolonged heating time and the δ ¹³C_ethane–δ¹³C_propane difference becomes greater as oil cracking progresses. There is considerable overlap in product generation and product cracking. Oil cracking products accumulate either because the rate of generation of any product is greater than the rate of removal by cracking of that product or because the product is a stable end member under the experimental conditions. Oil cracking products decrease when the amount of product generated from a reactant is less than the amount of product cracked. If pyrolysis gas compositions are representative of gases generated from oil cracking in nature, then understanding the processes that alter natural gas composition is critical.     

Surface current patterns in front of the Venice Lagoon

Surface patterns of the low-frequency current in a 20 × 30 km region in front of the Venice Lagoon were analysed from a 13-month-long HF radar data set. Surface circulation was related to prevalent wind regimes in the area and to the tidal flow through the lagoon inlet. Three different categories of wind-forcing were defined: bora (NE wind), sirocco (SE wind), and finally the category containing all other wind directions and calms (winds lower than 3 m/sec). Mean flow and vorticity spatial distributions were discussed for different wind conditions. The coastal area about 5 km wide is characterized by a flow field with maximum vorticity. Outside the coastal boundary layer the interior flow is part of the Adriatic basin-wide cyclonic circulation. Two counter-rotating vortices of the dimension of about 4–5 km were evidenced in the average flow field in front of the lagoon inlet (Malamocco inlet) in all situations except for the bora. The vortex-pair is probably associated with the tidal flow through the inlet. The bora wind induces a strong southward coastal jet detached from the coast by about 5 km homogenizing the flow and eliminating the dipole. The average coastal flow pattern in calm wind conditions was also analysed as a function of the strong inflow/outflow (currents in the inlet > 0.7 m s⁻¹) from the lagoon inlet. In both cases the vorticity pattern is similar, with the negative vorticity to the left of the inlet and positive to the right looking seaward.     

Effects of beach slope breaks on nearshore groundwater dynamics

Interactions between fresh groundwater and seawater affect significantly the nearshore pore water flow, which in turn influences the fate of nutrients and contaminants in coastal aquifers prior to discharge to the marine environment. Field investigations and numerical simulations were carried out to examine the groundwater dynamics in the intertidal zone of a carbonate sandy aquifer on the tropical island of Rarotonga, Cook Islands. The study site was featured by distinct cross‐shore slope breaks on the beach surface. Measured pore water salinities revealed different distributions under the influences of different beach profiles, inland heads, and tidal oscillations. Fresh groundwater was found to discharge around a beach slope break located in the middle area of the intertidal zone. The results indicate a strong interplay between the slope break beach morphology and tidal force in controlling the nearshore groundwater flow and solute transport. The fresh groundwater discharge location was largely determined by the beach morphology in combination with the tidal force. The nearshore groundwater flow can be very sensitive to beach slope breaks, which induce local circulation and flow instabilities. As slope breaks are a common feature of beaches around the world, these results have important, general implications for future studies of nutrients transport and transformations in nearshore aquifers and associated fluxes via submarine groundwater discharge.     

Deblending by modified dictionary learning using Sparse Parameter Training

Considerable attempts have been made on removing the crosstalk noise in a simultaneous source data using the popular K-means Singular Value Decomposition algorithm ( KSVD ). Several hybrids of this method have been designed and successfully deployed, but the complex nature of blending noise makes it difficult to manipulate easily. One of the challenges of the K-means Singular Value Decomposition approach is the chal-lenge to obtain an exact KSVD for each data patch which is believed to result in a better output. In this work, we propose a learnable architecture capable of data training while retaining the K-means Singular Value Decom-position essence to deblend simultaneous source data.     

RCP2.6: exploring the possibility to keep global mean temperature increase below 2��C

The RCP2.6 emission and concentration pathway is representative of the literature on mitigation scenarios aiming to limit the increase of global mean temperature to 2°C. These scenarios form the low end of the scenario literature in terms of emissions and radiative forcing. They often show negative emissions from energy use in the second half of the 21st century. The RCP2.6 scenario is shown to be technically feasible in the IMAGE integrated assessment modeling framework from a medium emission baseline scenario, assuming full participation of all countries. Cumulative emissions of greenhouse gases from 2010 to 2100 need to be reduced by 70% compared to a baseline scenario, requiring substantial changes in energy use and emissions of non-CO₂ gases. These measures (specifically the use of bio-energy and reforestation measures) also have clear consequences for global land use. Based on the RCP2.6 scenario, recommendations for further research on low emission scenarios have been formulated. These include the response of the climate system to a radiative forcing peak, the ability of society to achieve the required emission reduction rates given political and social inertia and the possibilities to further reduce emissions of non-CO₂ gases.     

A simulation of probabilistic wildfire risk components for the continental United States

This simulation research was conducted in order to develop a large-fire risk assessment system for the contiguous land area of the United States. The modeling system was applied to each of 134 Fire Planning Units (FPUs) to estimate burn probabilities and fire size distributions. To obtain stable estimates of these quantities, fire ignition and growth was simulated for 10,000 to 50,000 “years” of artificial weather. The fire growth simulations, when run repeatedly with different weather and ignition locations, produce burn probabilities and fire behavior distributions at each landscape location (e.g., number of times a “cell” burns at a given intensity divided by the total years). The artificial weather was generated for each land unit using (1) a fire danger rating index known as the Energy Release Component (ERC) which is a proxy for fuel moisture contents, (2) a time-series analysis of ERC to represent daily and seasonal variability, and (3) distributions of wind speed and direction from weather records. Large fire occurrence was stochastically modeled based on historical relationships to ERC. The simulations also required spatial data on fuel structure and topography which were acquired from the LANDFIRE project (). Fire suppression effects were represented by a statistical model that yields a probability of fire containment based on independent predictors of fire growth rates and fuel type. The simulated burn probabilities were comparable to observed patterns across the U.S. over the range of four orders of magnitude, generally falling within a factor of 3 or 4 of historical estimates. Close agreement between simulated and historical fire size distributions suggest that fire sizes are determined by the joint distributions of spatial opportunities for fire growth (dependent on fuels and ignition location) and the temporal opportunities produced by conducive weather sequences. The research demonstrates a practical approach to using fire simulations at very broad scales for purposes of operational planning and perhaps ecological research.