Search results for "lcsh:Geology"

showing 10 items of 216 documents

Quantifying geological uncertainty in metamorphic phase equilibria modelling; a Monte Carlo assessment and implications for tectonic interpretations

2016

AbstractPseudosection modelling is rapidly becoming an essential part of a petrologist's toolkit and often forms the basis of interpreting the tectonothermal evolution of a rock sample, outcrop, or geological region. Of the several factors that can affect the accuracy and precision of such calculated phase diagrams, “geological” uncertainty related to natural petrographic variation at the hand sample- and/or thin section-scale is rarely considered. Such uncertainty influences the sample's bulk composition, which is the primary control on its equilibrium phase relationships and thus the interpreted pressure–temperature (P–T) conditions of formation. Two case study examples—a garnet–cordierit…

010504 meteorology & atmospheric sciencesMetamorphic rockMonte Carlo methodMineralogyPseudosectionEarth and Planetary Sciences(all)3705 Geologysub-05010502 geochemistry & geophysics01 natural sciencesKyaniteGeological uncertaintyMatrix (geology)ErrorPetrographyMonte Carlo0105 earth and related environmental sciencesMnNCKFMASHTOlcsh:QE1-996.5Schist37 Earth Scienceslcsh:GeologyTectonicsvisual_artStaurolitevisual_art.visual_art_mediumGeneral Earth and Planetary Sciences3706 GeophysicsGeologyGeoscience Frontiers
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The UKC3 regional coupled environmental prediction system

2019

Abstract. This paper describes an updated configuration of the regional coupled research system, termed UKC3, developed and evaluated under the UK Environmental Prediction collaboration. This represents a further step towards a vision of simulating the numerous interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land using more integrated regional coupled prediction systems at km-scale resolution. The UKC3 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean surface waves (WAVEWATCH III), coupled together using OASIS3-MC…

010504 meteorology & atmospheric sciencesMeteorology010505 oceanographylcsh:QE1-996.5Forecast skillContext (language use)Unified Model01 natural sciencesWind speedAtmospherelcsh:GeologyCoupling (physics)Meteorology and ClimatologySurface waveRange (statistics)Environmental sciencePhysics::Atmospheric and Oceanic Physics0105 earth and related environmental sciences
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The Making of the New European Wind Atlas - Part 2: production and evaluation

2020

This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). In Part 1, we described the sensitivity experiments and accompanying evaluation done to arrive at the final mesoscale model setup used to produce the mesoscale wind atlas. In this paper, Part 2, we document how we made the final wind atlas product, covering both the production of the mesoscale climatology generated with the Weather Research and Forecasting (WRF) model and the microscale climatology generated with the Wind Atlas Analysis and Applications Program (WAsP). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulati…

010504 meteorology & atmospheric sciencesMeteorology020209 energyMesoscale meteorologyTerrainParameterization02 engineering and technology01 natural sciencesWind speedWind speed0202 electrical engineering electronic engineering information engineeringWind atlasData flow modelSurface wind0105 earth and related environmental sciences:Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia [Àrees temàtiques de la UPC]lcsh:QE1-996.5Física atmosféricalcsh:GeologyWeather Research and Forecasting ModelEnvironmental scienceNew European Wind AtlasSimulacio per ordinadorComputational methods in engineeringDownscalingModel
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A space-time rainfall generator for highly convective Mediterranean rainstorms

2003

Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rai…

010504 meteorology & atmospheric sciencesMeteorology0207 environmental engineering[SDU.STU]Sciences of the Universe [physics]/Earth Sciences02 engineering and technologyMethod of moments (statistics)01 natural sciencesPoint processlcsh:TD1-1066lcsh:Environmental technology. Sanitary engineering020701 environmental engineering[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentlcsh:Environmental sciences0105 earth and related environmental scienceslcsh:GE1-350[SDU.OCEAN]Sciences of the Universe [physics]/Ocean AtmosphereComputer simulationRain gauge[SDU.OCEAN] Sciences of the Universe [physics]/Ocean AtmosphereSpace timelcsh:QE1-996.5lcsh:Geography. Anthropology. Recreation[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces environment6. Clean waterRunoff modellcsh:Geologylcsh:G13. Climate actionClimatology[SDU.STU] Sciences of the Universe [physics]/Earth SciencesGeneral Earth and Planetary SciencesEnvironmental scienceIntensity (heat transfer)Generator (mathematics)
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2016

Gianluca Tramontana was supported by the GEOCARBON EU FP7 project (GA 283080). Dario Papale, Martin Jung and Markus Reichstein acknowledge funding from the EU FP7 project GEOCARBON (grant agreement no. 283080) and the EU H2020 BACI project (grant agreement no. 640176). Gustau Camps-Valls wants to acknowledge the support by an ERC Consolidator Grant with grant agreement 647423 (SEDAL). Kazuhito Ichii was supported by Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan and the JAXA Global Change Observation Mission (GCOM) project (no. 115). Christopher R. Schwalm was supported by National Aeronautics and Space Administration (NASA) gran…

010504 meteorology & atmospheric sciencesMeteorologyFLUXNET0208 environmental biotechnology0207 environmental engineeringlcsh:Life02 engineering and technologySensible heatAtmospheric sciences7. Clean energy01 natural sciencesFlux (metallurgy)FluxNetMachine learning; Carbon fluxes; Energy fluxes; FLUXNET; Remote sensing; FLUXCOMlcsh:QH540-549.5Latent heatMachine learningCarbon fluxes020701 environmental engineeringEcology Evolution Behavior and Systematics0105 earth and related environmental sciencesEarth-Surface ProcessesFLUXCOMMultivariate adaptive regression splineslcsh:QE1-996.5Empirical modellingPrimary production15. Life on landRemote sensingEnergy fluxes020801 environmental engineeringlcsh:Geologylcsh:QH501-531Kernel method13. Climate actionEnvironmental sciencelcsh:EcologyBiogeosciences
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The making of the New European Wind Atlas - Part 1: Model sensitivity

2020

This is the first of two papers that document the creation of the New European Wind Atlas (NEWA). It describes the sensitivity analysis and evaluation procedures that formed the basis for choosing the final setup of the mesoscale model simulations of the wind atlas. The suitable combination of model setup and parameterizations, bound by practical constraints, was found for simulating the climatology of the wind field at turbine-relevant heights with the Weather Research and Forecasting (WRF) model. Initial WRF model sensitivity experiments compared the wind climate generated by using two commonly used planetary boundary layer schemes and were carried out over several regions in Europe. They…

010504 meteorology & atmospheric sciencesMeteorologyPlanetary boundary layer010505 oceanography020209 energylcsh:QE1-996.5Mesoscale meteorologyFísica atmosférica02 engineering and technology01 natural sciences7. Clean energyWind speedlcsh:GeologyBoundary layerRoughness length/dk/atira/pure/sustainabledevelopmentgoals/climate_action13. Climate actionWeather Research and Forecasting ModelWind resource assessmentWind atlasSDG 13 - Climate Action0202 electrical engineering electronic engineering information engineeringEnvironmental science0105 earth and related environmental sciences
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Influence of basement heterogeneity on the architecture of low subsidence rate Paleozoic intracratonic basins (Reggane, Ahnet, Mouydir and Illizi bas…

2018

The Paleozoic intracratonic North African Platform is characterized by an association of arches (ridges, domes, swells, or paleo-highs) and low subsidence rate syncline basins of different wavelengths (75–620 km). The Reggane, Ahnet, Mouydir and Illizi basins are successively delimited from east to west by the Amguid El Biod, Arak-Foum Belrem, and Azzel Matti arches. Through the analysis of new unpublished geological data (i.e., satellite images, well logs, seismic lines), the deposits associated with these arches and syncline basins exhibit thickness variations and facies changes ranging from continental to marine environments. The arches are characterized by thin amalgamated deposi…

010504 meteorology & atmospheric sciencesPaleozoicStratigraphyInversion (geology)Soil Science[SDU.STU]Sciences of the Universe [physics]/Earth Sciences010502 geochemistry & geophysics01 natural sciencesDevonianHorst and grabenPaleontologylcsh:StratigraphyGeochemistry and PetrologyCarboniferous[SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geologylcsh:QE640-6990105 earth and related environmental sciencesEarth-Surface Processes[SDU.STU.TE]Sciences of the Universe [physics]/Earth Sciences/TectonicsProterozoiclcsh:QE1-996.5PaleontologyGeologyOrogeny15. Life on landlcsh:GeologyGeophysicsSyncline[SDU.STU.PG]Sciences of the Universe [physics]/Earth Sciences/PaleontologyGeology
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Active tectonics along the south east offshore margin of Mt. Etna: New insights from high-resolution seismic profiles

2018

The offshore margin of Mt. Etna has been shaped by Middle Pleistocene to Holocene shortening and extension and, more recently, by gravity-related sliding of the volcanic edifice. These processes have acted contemporaneously although the gravitational component largely prevails over the tectonic one. In order to investigate this issue, we focused on the main role of active tectonics along the south-eastern offshore of Mt. Etna by means of marine high-resolution seismic data. Seismic profiles revealed post-220 ka sedimentary deposits unconformably overlaying the Lower-Middle Pleistocene Etnean clayey substratum and volcanics of the Basal Tholeiitic phase and the Timpe phase. Offshore Aci Trez…

010504 meteorology & atmospheric sciencesPleistoceneSettore GEO/02 - Geologia Stratigrafica E SedimentologicaSettore GEO/03 - Geologia Strutturaleactive tectonics010502 geochemistry & geophysics01 natural sciencesSicilian thrust-beltPaleontologyActive tectonicActive tectonics; Ionian Sea; Mt. Etna; Seismic investigation; Sicilian thrust-belt; Earth and Planetary Sciences (all)Seismic investigationHolocene0105 earth and related environmental sciencesgeographygeography.geographical_feature_categoryContinental shelfMt. Etnalcsh:QE1-996.5Fold (geology)Ionian SeaMt. Etna; seismic investigation; active tectonics; Sicilian thrust-belt; Ionian SeaSeafloor spreadingVolcanic rocklcsh:GeologyTectonicsGeneral Earth and Planetary SciencesSedimentary rockEarth and Planetary Sciences (all)Geology
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Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

2021

The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then d…

010504 meteorology & atmospheric sciencesReceiver operating characteristicbusiness.industryDeep learningSpatial databaselcsh:QE1-996.5Deep learningLandslideIranLandslide susceptibility010502 geochemistry & geophysicsRNN01 natural sciencesConvolutional neural networklcsh:GeologyLandslideRecurrent neural networkGeneral Earth and Planetary SciencesArtificial intelligenceScale (map)businessAlgorithmCNNGeology0105 earth and related environmental sciencesGeoscience Frontiers
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Historical analysis of rainfall-triggered rockfalls: the case study of the disaster of the ancient hydrothermal Sclafani Spa (Madonie Mts, northern-c…

2017

Abstract. In 1851, the region of Sicily experienced many rainstorm-induced landslides. On 13 March 1851, a rainstorm brought about a severe rockfall disaster near the small town of Sclafani (Madonie Mountains, northern-central Sicily, Italy). Rocks detached from the carbonate crest of Mt Sclafani (813 m above sea level) and fell downslope, causing the collapse of the ancient hydrothermal spa (about 430 m above sea level) and burying it. Fortunately, there were no injuries or victims. Given its geological, geomorphological and tectonic features, the calcareous–dolomitic and carbonate–siliciclastic relief of Mt Sclafani is extremely prone to landsliding. This study combines the findings of de…

010504 meteorology & atmospheric sciencesSettore GEO/04 - Geografia Fisica E GeomorfologiaClimate change010502 geochemistry & geophysics01 natural scienceslcsh:TD1-1066Extreme weatherRockfalllcsh:Environmental technology. Sanitary engineeringNatural disasterlcsh:Environmental sciencesSea level0105 earth and related environmental scienceslcsh:GE1-350geographygeography.geographical_feature_categorylcsh:QE1-996.5Global warminglcsh:Geography. Anthropology. RecreationLandslideLandslide rainfall rockfall thermal spring Sicilylcsh:GeologyTectonicslcsh:GGeneral Earth and Planetary SciencesPhysical geographyGeologyNatural Hazards and Earth System Sciences
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