Search results for "Conte"

showing 10 items of 10369 documents

Measuring the electron temperatures of coronal mass ejections with future space-based multi-channel coronagraphs: a numerical test

2018

Context. The determination from coronagraphic observations of physical parameters of the plasma embedded in coronal mass ejections (CMEs) is of crucial importance for our understanding of the origin and evolution of these phenomena. Aims. The aim of this work is to perform the first ever numerical simulations of a CME as it will be observed by future two-channel (visible light VL and UV Ly-α) coronagraphs, such as the Metis instrument on-board ESA-Solar Orbiter mission, or any other future coronagraphs with the same spectral band-passes. These simulations are then used to test and optimize the plasma diagnostic techniques to be applied to future observations of CMEs. Methods. The CME diagno…

010504 meteorology & atmospheric sciencesSun: coronal mass ejections (CMEs)Plasma parametersT-NDASContext (language use)Astrophysics01 natural sciencessymbols.namesakeMethods: data analysis0103 physical sciencesRadiative transferCoronal mass ejectionAstrophysics::Solar and Stellar AstrophysicsQB Astronomydata analysis [Methods]010303 astronomy & astrophysicsQCQB0105 earth and related environmental sciencesPhysicsUV radiation [Sun]numerical [Methods]Methods: numericalAstronomy and AstrophysicsPlasmaSun: UV radiationPolarization (waves)coronal mass ejections (CMEs) [Sun]Computational physicsQC PhysicsPlasmasSpace and Planetary SciencePhysics::Space PhysicssymbolsMagnetohydrodynamicsDoppler effectAstronomy & Astrophysics
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Long-term annual burning of grassland increases CO2 emissions from soils.

2016

7 pages; International audience; Grasslands have potential to mitigate against climate change because of their large capacity to store soil organic carbon (SOC). However, the long-term impact of grassland management such as burning, which is still common in many areas of the world, on SOC is still a matter of debate. The objective of this study was to quantify the long-term effects of annual burning on CO2 output from soils and SOC stocks. The study was performed on a 62 years old field trial comparing annual burning (AB) to no burning associated with tree encroachment (NB), and to annual mowing (AM) with all treatments laid out in randomized block design with three replicates per treatment…

010504 meteorology & atmospheric sciences[ SDV.SA.SDS ] Life Sciences [q-bio]/Agricultural sciences/Soil study[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomySoil Science[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study01 natural sciencesCarbon cycleSoil respiration[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/AgronomyGrassland managementWater content0105 earth and related environmental sciences2. Zero hungerBurningSoil organic matterSoil chemistry04 agricultural and veterinary sciencesSoil carbonSoil respirationCarbon cycle15. Life on landBulk densitySoil carbonAgronomy13. Climate actionSoil water040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental science
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Soil moisture modelling of a SMOS pixel: interest of using the PERSIANN database over the Valencia Anchor Station

2010

In the framework of Soil Moisture and Ocean Salinity (SMOS) Calibration/Validation (Cal/Val) activities, this study addresses the use of the PERSIANN-CCS<sup>1</sup>database in hydrological applications to accurately simulate a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over a wide area (50×50 km<sup>2</sup>). The study focuses on the Valencia Anchor Station (VAS) experimental site, in Spain, which is one of the main SMOS Cal/Val sites in Europe. <br><br> A faithful representation of the soil moisture distribution at SMOS pixel scale (50×50 km<sup>2</sup>) requires an accurate estimation…

010504 meteorology & atmospheric sciences[SDE.MCG]Environmental Sciences/Global Changessatellite0207 environmental engineeringContext (language use)02 engineering and technologysystemcomputer.software_genrerainfall estimation01 natural scienceslcsh:Technologylcsh:TD1-1066Precipitation[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrologylcsh:Environmental technology. Sanitary engineering020701 environmental engineeringWater contentprecipitation estimationretrievallcsh:Environmental sciences0105 earth and related environmental sciencesRemote sensinglcsh:GE1-350DatabaseRain gaugeMoisturelcsh:Tlcsh:Geography. Anthropology. RecreationLife Sciencesneural-network15. Life on landparameterizationokavango riverproductsafricalcsh:G13. Climate actionSoil waterPERSIANNEnvironmental scienceSpatial variabilitycomputerHydrology and Earth System Sciences
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Hydrostratigraphic characterization of glaciofluvial deposits underlying an infiltration basin using ground penetrating radar.

2008

14 pages; International audience; An understanding of the heterogeneity of quaternary gravelly deposits is required to predict flow and contaminant transfer through these formations. In such deposits, preferential flow paths can lead to contamination at depths greater than predicted under the assumption of a homogeneous medium. The difficulties in characterizing their complex structure with conventional methods represent an obstacle for this prediction. In this study, we developed an approach relying on the use of ground penetrating radar (GPR) for the detection of sedimentary depositional units. A genetic interpretation of the radar stratigraphy allowed us to construct a distribution model…

010504 meteorology & atmospheric sciences[SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph][SDE.MCG]Environmental Sciences/Global Changes0207 environmental engineeringInfiltration basinSoil Science[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]02 engineering and technology[ SDU.STU.ST ] Sciences of the Universe [physics]/Earth Sciences/Stratigraphy01 natural scienceslaw.inventionSedimentary depositional environment[ SDU.STU.GP ] Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph][ PHYS.PHYS.PHYS-GEO-PH ] Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]lawRadar020701 environmental engineeringPetrologyGeomorphologyWater content0105 earth and related environmental sciences6. Clean waterInfiltration (hydrology)[ SDE.MCG ] Environmental Sciences/Global Changes[SDU.STU.ST]Sciences of the Universe [physics]/Earth Sciences/StratigraphyGround-penetrating radarSedimentary rockSaturation (chemistry)Geology
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Models and data analysis tools for the Solar Orbiter mission

2020

All authors: Rouillard, A. P.; Pinto, R. F.; Vourlidas, A.; De Groof, A.; Thompson, W. T.; Bemporad, A.; Dolei, S.; Indurain, M.; Buchlin, E.; Sasso, C.; Spadaro, D.; Dalmasse, K.; Hirzberger, J.; Zouganelis, I.; Strugarek, A.; Brun, A. S.; Alexandre, M.; Berghmans, D.; Raouafi, N. E.; Wiegelmann, T.; Pagano, P.; Arge, C. N.; Nieves-Chinchilla, T.; Lavarra, M.; Poirier, N.; Amari, T.; Aran, A.; Andretta, V.; Antonucci, E.; Anastasiadis, A.; Auchère, F.; Bellot Rubio, L.; Nicula, B.; Bonnin, X.; Bouchemit, M.; Budnik, E.; Caminade, S.; Cecconi, B.; Carlyle, J.; Cernuda, I.; Davila, J. M.; Etesi, L.; Espinosa Lara, F.; Fedorov, A.; Fineschi, S.; Fludra, A.; Génot, V.; Georgoulis, M. K.; Gilbe…

010504 meteorology & atmospheric sciencescorona [Sun]Solar windAstrophysics[SDU.ASTR] Sciences of the Universe [physics]/Astrophysics [astro-ph]7. Clean energy01 natural scienceslaw.inventionData acquisitionlawCoronal mass ejectiongeneral [Sun]QB AstronomyAstrophysics::Solar and Stellar Astrophysics010303 astronomy & astrophysicsSun: magnetic fieldsQCComputingMilieux_MISCELLANEOUSQBPhysics[SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph]3rd-DASenergetic particlesSolar windCORONAL MASS EJECTIONSnumerical modelingmagnetic fields [Sun]solar windPhysics::Space PhysicsSystems engineeringAstrophysics::Earth and Planetary Astrophysicsatmosphere [Sun]fundamental parameters [Sun]Sun: generalFORCE-FREE FIELDSun: fundamental parametersSolar radiusContext (language use)STREAMER STRUCTUREOrbiter0103 physical sciencesOPTIMIZATION APPROACH[SDU.ASTR.SR] Sciences of the Universe [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR]POLARIZATION MEASUREMENTSSun: Solar wind3-DIMENSIONAL STRUCTURE0105 earth and related environmental sciencesSpacecraftbusiness.industrySun: corona[SDU.ASTR.SR]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR]solar coronaMAGNETIC-FLUX ROPESAstronomy and AstrophysicsSHOCKS DRIVEN115 Astronomy Space scienceSPECTRAL-LINESQC Physics13. Climate actionSpace and Planetary SciencebusinessHeliosphereSun: atmosphereELECTRON-DENSITY
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Estimating Gravimetric Moisture of Vegetation Using an Attenuation-Based Multi-Sensor Approach

2018

Estimating parameters for global climate models via combined active and passive microwave remote sensing data has been a subject of intensive research in recent years. A variety of retrieval algorithms has been proposed for the estimation of soil moisture, vegetation optical depth and other parameters. A novel attenuation-based retrieval approach is proposed here to globally estimate the gravimetric moisture of vegetation (m g ) and retrieve information about the amount of water [kg] per amount of wet vegetation [kg]. The parameter m g is particularly interesting for agro-ecosystems, to assess the status of growing vegetation. The key feature of the proposed approach is that it relies on mu…

010504 meteorology & atmospheric sciencesgravimetric moisture0211 other engineering and technologies02 engineering and technology01 natural scienceslaw.inventionlawVegetation optical depthRadarWater contentattenuation021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingLidarRadarVegetationMoistureAttenuationMicrowave radiometerVegetationSMAPMulti-sensorLidarGravimetric analysisRadiometer
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Driving through floodwater: Exploring driver decisions through the lived experience

2019

Abstract More than half of unintentional flood-related drowning deaths in Australia are due to driving through floodwater, despite on-going public campaigns. Currently, there is a knowledge gap in understanding why individuals choose to drive through floodwater and the decisions that may lead to such actions. We propose that a more complete understanding of individuals’ decisions to drive through floodwater needs to be considered in the context of the lived experience. Australian drivers (N = 20) who had intentionally driven through floodwater participated in semi-structured interviews. Data were analysed using a thematic analysis based in an interpretivist approach. Past experience, indivi…

010504 meteorology & atmospheric sciencesmedia_common.quotation_subjectflooded waterways0211 other engineering and technologiesPsychological interventionContext (language use)02 engineering and technologydriving skills01 natural sciencesuskomuksetkäyttäytymismallithukkuminenPerceptiondrivingHuman geographyta5150105 earth and related environmental sciencesmedia_common021110 strategic defence & security studiesdrowningbusiness.industryLived experienceGeologytulvatajotaitofloodPublic relationsGeotechnical Engineering and Engineering GeologybeliefsThematic analysisConstruct (philosophy)businessPsychologySafety ResearchInternational Journal of Disaster Risk Reduction
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Analysis of the radar vegetation index and assessment of potential for improvement

2018

The Radar Vegetation Index (RVI) is widely applied to indicate vegetation cover. The index includes the backscattering intensities of co- and cross-polarization that do not only contain information coming from vegetation scattering at longer wavelength (L-band), but also from the soil underneath. A forward modelling approach using active and passive microwave-derived parameters to obtain the scattering contribution of the soil is pursued. The idea of this research study is a subtraction of the attenuated soil scattering contribution from the measured backscattering intensities, to provide a clean vegetation-based solution, called improved RVI (RVII). For latter analysis, the vegetation volu…

010504 meteorology & atmospheric sciencesmicrowave[SDV]Life Sciences [q-bio]0211 other engineering and technologiesSoil science02 engineering and technology01 natural scienceslaw.inventionVegetation coverlawmedicineRange (statistics)RadarComputingMilieux_MISCELLANEOUS021101 geological & geomatics engineering0105 earth and related environmental sciencesRadarVegetationScatteringSMAP15. Life on landWavelength[SDE]Environmental SciencesVegetation water contentEnvironmental scienceactive-passive sensingmedicine.symptomVegetation IndexVegetation (pathology)Cartography
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Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

2010

16 páginas, 9 figuras, 5 tablas.

010504 meteorology & atmospheric sciencestélédétectionMISSION SMOS0211 other engineering and technologiesSpaceespagne02 engineering and technologylcsh:Technology01 natural sciencesValidationTraitement du signal et de l'imagelcsh:Environmental technology. Sanitary engineering020701 environmental engineeringWater contentlcsh:Environmental sciencesComputingMilieux_MISCELLANEOUSlcsh:GE1-350InclusionRetrievalMoistureModelling soil moistureSignal and Image processinglcsh:Geography. Anthropology. RecreationRemote sensingDISPOSITIF EXPERIMENTAL; MISSION SMOSProductseurope[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSMOS[SDE.MCG]Environmental Sciences/Global Changessatellite0207 environmental engineeringGrowing seasonParameterizationSpatial distributionlcsh:TD1-1066SchemeHapexspectroradiomètre14. Life underwater[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometerlcsh:TAMSR-Epays méditerranéenSalinityERS scatterometerlcsh:G13. Climate actionDISPOSITIF EXPERIMENTALSoil waterEnvironmental scienceRadiometry
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Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations

2015

Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval…

010504 meteorology & atmospheric sciencestélédétectionScience0211 other engineering and technologiesWeather forecasting[SDU.STU]Sciences of the Universe [physics]/Earth SciencesElectromagnétismesoil surface roughness02 engineering and technologySurface finishcomputer.software_genredonnée satellite01 natural sciencesSciences de la TerreNormalized Difference Vegetation Indexsoil moisture;soil surface roughness;AMSR-EElectromagnetismEmissivitySurface roughnessTraitement du signal et de l'image14. Life underwaterWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometercapteur smosQSignal and Image processingradiométrie microondesVegetationAMSR-E15. Life on land[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismEarth SciencesGeneral Earth and Planetary SciencesEnvironmental sciencesoil moisturecomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingRemote Sensing
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