Forecasting eruptions from long-quiescent volcanoes

Forecasts of eruption are uncertain. The uncertainty is amplified when volcanoes reawaken after several generations in repose, because direct evidence of previous behaviour is rarely available. It fosters scepticism about warnings of volcanic activity and may compromise the success of emergency procedures. The quality of forecasts has improved over the past 50 years, owing mainly to a growing sophistication in statistical analyses of unrest. Physics-based analyses have yet to achieve the same level of maturity. Their application has been delayed by a view that volcanoes are too complex to share patterns of behaviour that can be described in a deterministic manner. This view is being increasingly challenged and an emerging line of inquiry is to understand how forecasts can be further improved by integrating statistical approaches with new constraints on possible outcomes from physics-based criteria. The introduction of deterministic reasoning yields rational explanations of why forecasts are not perfect and, as a result, offers new opportunities for increasing public confidence in warnings of eruption

Bounds on Quantum Correlations in Bell Inequality Experiments

Bell inequality violation is one of the most widely known manifestations of entanglement in quantum mechanics; indicating that experiments on physically separated quantum mechanical systems cannot be given a local realistic description. However, despite the importance of Bell inequalities, it is not known in general how to determine whether a given entangled state will violate a Bell inequality. This is because one can choose to make many different measurements on a quantum system to test any given Bell inequality and the optimization over measurements is a high-dimensional variational problem. In order to better understand this problem we present algorithms that provide, for a given quantum state, both a lower bound and an upper bound on the maximal expectation value of a Bell operator. Both bounds apply techniques from convex optimization and the methodology for creating upper bounds allows them to be systematically improved. In many cases these bounds determine measurements that would demonstrate violation of the Bell inequality or provide a bound that rules out the possibility of a violation. Examples are given to illustrate how these algorithms can be used to conclude definitively if some quantum states violate a given Bell inequality.Comment: 13 pages, 1 table, 2 figures. Updated version as published in PR

Intonational Phrases for Speech Summarization

Extractive speech summarization approaches select relevant segments of spoken documents and concatenate them to generate a summary. The extraction unit chosen, whether a sentence, syntactic constituent, or other segment, has a significant impact on the overall quality and fluency of the summary. Even though sentences tend to be the choice of most the extractive speech summarizers, in this paper, we present the results of an empirical study indicating that intonational phrases are better units of extraction for summarization. Our study compared four types of input segmentation: sentences, two pause-based segmentation, and intonational phrases (IP). We found that IPs are the best candidates for extractive summarization, improving over the second highest-performing approach, sentence-based summarization, by 8.2% F-measure

Control of polymorphism in coronene by the application of magnetic fields

Coronene, a polyaromatic hydrocarbon, has been crystallized for the first time in a different polymorph using a crystal growth method that utilizes magnetic fields to access a unit cell configuration that was hitherto unknown. Crystals grown in magnetic field of 1 T are larger, have a different appearance to those grown in zero field and retain their structure in ambient conditions. We identify the new form, beta-coronene, as the most stable at low temperatures. As a result of the new supramolecular configuration we report significantly altered electronic, optical and mechanical properties.Comment: 32 pages, 17 figure

Structural and Stratigraphic Evolution of the Mid North Sea High Region of the UK Continental Shelf

This research was undertaken as part of a 2-year Post-Doctoral Research Associate (PDRA) project undertaken at the Applied Geoscience Unit in the Centre of Exploration Geoscience at Heriot Watt University. The project was funded by the UK Oil and Gas Authority (OGA) as part of their Frontier Basins Research program. We extend our gratitude Jo Bagguley, Malcolm Gall and Nick Richardson for their support of the work and technical discussions. All research outputs are available for download on the Oil and Gas Authority’s National Data Repository (NDR) website, and we thank the OGA’s data management and Arc GIS team for their work to make this publicly available. The work has benefitted from technical discussion with Matthew Booth, Ross Grant and Richard McKeen, who have undertaken complementary studies in neighbouring parts of the basin.Peer reviewedPostprin

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true for areas with lower GVF in the SPoRT model runs. These differences in the heating and evaporation rates produced subtle yet quantifiable differences in the simulated convective precipitation systems for the selected severe weather case examined

Advantages and Applications of Synthetic Aperture Radar as a Decision Support Tool

No abstract availabl

Using Satellite Imagery to Identify Tornado Damage Tracks and Recovery from the April 27, 2011 Severe Weather Outbreak

Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process

Flood Mapping of Recent Major Hurricane Events with Synthetic Aperture Radar, Commercial Imaging, and Aerial Observations

Floodwater mapping is an important remote sensing process that is used for disaster response, recovery, and damage assessment practices. Developing a system to read in Synthetic Aperture Radar (SAR) data and perform land cover classification will allow for the production of near real-time inundation mapping, enabling government and emergency response entities to get a preliminary idea of the situation. SAR is a unique remote sensing tool. Data in this project was obtained by NASA Jet Propulsion Laboratorys Uninhabited Aerial Vehicle SAR (UAVSAR), an L-band radar mounted to a Gulfstream III jet. Data collected by UAVSAR is similar to what will be available from the NASA-Indian Space Research Organization (NISAR) mission starting in early 2022. Using Python and ArcGIS applications, a model was developed using training samples taken from NOAA post-event aerial photography and UAVSAR data gathered in the aftermath of Hurricane Florence in September 2018