Interactive computer graphics method for the combined interpretation of gravity and magnetic data

A program for computation of the gravity and magnetic anomalies associated with two-dimensional structures has been adapted for use in an interactive mode using a storage-screen CRT linked to a remote computer via standard telephone lines. This new program aids the user in developing a structural model that satisfies both magnetic and gravity observations. Examples are included to demonstrate the increased efficiency of interpretation using this low-cost graphics approach and to illustrate the detail of the model resulting from the compromise necessary to satisfy both potential-field data sets.     

Cambridge deep Ocean geophone

We describe recent mechanical andeelectronic modifications to the Cambridge Ocean Bottom Hydrophone system, enabling it to record in addition three geophone channels from a deployed, disposable geophone package. Examples of data from seismic refraction experiments show good correspondence between records of ground motion detected by the hydrophone and the vertical geophone. Seismic signals are undistorted by noise from instrument related sources. Clear examples of P to S conversions just below the receiver are observed. Improved recording conditions are achieved by deploying the geophones in a small pressure vessel as far away as possible from the main instrument package.     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.     

The Elusive AD 1826 Tsunami, South Westland, New Zealand

In AD 1826 sealers reported earthquake and tsunami activity in Fiordland, although, contemporary or near‐contemporary accounts of tsunami inundation at the time are elusive. A detailed analysis of recent sediments from Okarito Lagoon builds on contextual evidence provided by earlier research concerning past tsunami inundation. Sedimentological, geochemical, micropalaeontological and geochronological data are used to determine palaeoenvironments before, during and after what was most probably tsunami inundation in AD 1826. The most compelling chronological control is provided fry a young cohort of trees growing on a raised shoreline bench stranded fry a drop in the lagoon water level following tsunami inundation.     

The role of moisture cycling in the weathering of a quartz chlorite schist in a tropical environment: findings of a laboratory simulation

Long‐term weathering of a quartz chlorite schist via wetting and drying was studied under a simulated tropical climate. Cubic rock samples (15 mm × 15 mm × 15 mm) were cut from larger rocks and subjected to time‐compressed climatic conditions simulating the tropical wet season climate at the Ranger Uranium Mine in the Northern Territory, Australia. Fragmentation, moisture content and moisture uptake rate were monitored over 5000 cycles of wetting and drying. To determine the impact of climatic variables, five climatic regimes were simulated, varying water application, temperature and drying. One of the climatic regimes reproduced observed temperature and moisture variability at the Ranger Uranium Mine, but over a compressed time scale. It is shown that wetting and drying is capable of weathering quartz chlorite schist with changes expected over a real time period of decades. While wetting and drying alone does produce changes to rock morphology, the incorporation of temperature variation further enhances weathering rates. Although little fragmentation occurred in experiments, significant changes to internal pore structure were observed, which could potentially enhance other weathering mechanisms. Moisture variability is shown to lead to higher weathering rates than are observed when samples are subjected only to leaching. Finally, experiments were conducted on two rock samples from the same source having only subtle differences in mineralogy. The samples exhibited quite different weathering rates leading to the conclusion that our knowledge of the role of rock type and composition in weathering is insufficient for the accurate determination of weathering rates. Copyright © 2005 John Wiley & Sons, Ltd.     

Diagnosing snow accumulation errors in a rain‐snow transitional environment with snow board observations

Diagnosing the source of errors in snow models requires intensive observations, a flexible model framework to test competing hypotheses, and a methodology to systematically test the dominant snow processes. We present a novel process‐based approach to diagnose model errors through an example that focuses on snow accumulation processes (precipitation partitioning, new snow density, and snow compaction). Twelve years of meteorological and snow board measurements were used to identify the main source of model error on each snow accumulation day. Results show that modeled values of new snow density were outside observational uncertainties in 52% of days available for evaluation, while precipitation partitioning and compaction were in error 45% and 16% of the time, respectively. Precipitation partitioning errors mattered more for total winter accumulation during the anomalously warm winter of 2014–2015, when a higher fraction of precipitation fell within the temperature range where partition methods had the largest error. These results demonstrate how isolating individual model processes can identify the primary source(s) of model error, which helps prioritize future research.