Search results for "Intercomparison"

showing 5 items of 15 documents

Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contributi…

2013

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedente…

M60/5SalinityChlorophyll aDiazotrophs total biomass as carbonUniform resource locator link to source data fileNitrateCTD/RosetteLatitude of eventNiskinM55 1Temperature waterCalothrix abundance expressed in number of nifH gene copiesratio expressed in mass of carbon per amount of nifH gene copiesCalculatedtop minUnicellular cyanobacteria-B biological trait ratio expressed in mass of carbon per amount of nifH gene copiesCD132biomass as carbonTrichodesmium biomass as carbonM55/1bottom maxCTD SeabirdTemperatureDepth top/minCTD RosetteSeabirdRichelia biological trait ratio expressed in mass of carbon per amount of nifH gene copiesCalothrixSO187 2Unicellular cyanobacteria-B abundance expressed in number of nifH gene copiesTrichodesmiumEarth System ResearchMARine Ecosystem Model Intercomparison Project MAREMIPDiazotrophsLongitude of eventRichelia associated speciesSample methodCalothrix biological trait ratio expressed in mass of carbon per amount of nifH gene copiesIronBottle NiskinwaterIn situ pumpMARine Ecosystem Model Intercomparison Project (MAREMIP)Unicellular cyanobacteria-C abundance expressed in number of nifH gene copiesPhosphateWater sampleSample commentUnicellular cyanobacteria biomassUniform resource locator/link to source data filetotal biomass as carbonHeterocyst biomassUnicellular cyanobacteriaProteobacteriaDate/Time of eventMeteor 1986Richelia abundance expressed in number of nifH gene copiesUnicellular cyanobacteria CUnicellular cyanobacteria Bbiological traitSO187/2RicheliaUnicellular cyanobacteria ADEPTH waterbiomassTrichodesmium abundance expressed in number of nifH gene copiesMeteor (1986)BottleDepthEvent labelDate Time of eventTrichodesmium biological trait ratio expressed in mass of carbon per amount of nifH gene copiesUnicellular cyanobacteria-C biological trait ratio expressed in mass of carbon per amount of nifH gene copiesMeasured at sea surfaceCTDCalothrix associated speciesCharles DarwinSonneabundance expressed in number of nifH gene copiesM60 5Depth bottom/maxUnicellular cyanobacteria-A abundance expressed in number of nifH gene copiesassociated speciesProteobacteria abundance expressed in number of nifH gene copiesHeterocyst
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Comparison of the strain field of abdominal aortic aneurysm measured by magnetic resonance imaging and stereovision: a feasibility study for predicti…

2015

International audience; The prediction of the risk of rupture of abdominal aortic aneurysm (AAA) is a complex problem. Currently the criteria to predict rupture of abdominal aortic aneurysms are aneurysm diameter and growth rates. It is generally believed that study of the wall strain distribution could be helpful to find a better decision criterion for surgery of aortic aneurysms before their rupture. The wall strain distribution depends on many biological and biomechanical factors such as elastic properties of the aorta, turbulent blood flow, anatomy of the aorta, presence of thrombus or not and so on. Recently, numerical simulations to estimate rupture-potential have received many attent…

Risk[ SPI.MECA.GEME ] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]medicine.medical_specialtyAortic RuptureBiomedical EngineeringBiophysicsBlood PressureStereovisionModels BiologicalRisk AssessmentAneurysmRisk Factorsmedicine.arterymedicineMedical imagingHumansOrthopedics and Sports Medicinecardiovascular diseasesThrombusAbdominal Aortic AneurismAortaCardiac cyclemedicine.diagnostic_testPhantoms Imagingbusiness.industryRehabilitationMagnetic resonance imagingmedicine.diseaseMagnetic Resonance ImagingAbdominal aortic aneurysmBiomechanical Phenomena[SPI.MECA.GEME]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Mechanical engineering [physics.class-ph]medicine.anatomical_structurecardiovascular systemFeasibility StudiesIntercomparison studyRadiologybusinessAortic Aneurysm AbdominalArteryMRI
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Intercomparison of SO2 camera systems for imaging volcanic gas plumes

2015

Abstract SO 2 camera systems are increasingly being used to image volcanic gas plumes. The ability to derive SO 2 emission rates directly from the acquired imagery at high time resolution allows volcanic process studies that incorporate other high time-resolution datasets. Though the general principles behind the SO 2 camera have remained the same for a number of years, recent advances in CCD technology and an improved understanding of the physics behind the measurements have driven a continuous evolution of the camera systems. Here we present an intercomparison of seven different SO 2 cameras. In the first part of the experiment, the various technical designs are compared and the advantage…

geographygeography.geographical_feature_categoryMeteorologyProcess (computing)Volcanic gas emissionsTime resolutionRemote sensingSpatial integrationPlumeSettore GEO/08 - Geochimica E VulcanologiaGeophysicsSO2 CameraVolcanoInstrument intercomparisonSulfur dioxideGeochemistry and PetrologyUltraviolet spectroscopyContinuous evolutionGeologyRemote sensing
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Radar-rain gauges intercomparison for the estimation of high resolution rainfall.

2015

An accurate rainfall estimation is essential for many applications like precision viticulture. Rainfall is most of the time estimated by two methods:radar and rain gauges. High resolution rain gauges network Hydravitis was installed in 2014. Data coming from radar,composite product and the network was extracted for the 2014 3 to 4 November event. Data from the network were kriged tocompare with the other products. Results show that PANTHERE radar image well reproduces the spatial variability ofrainfall but underestimates rainfall amounts over a 4 mm/h intensité. Composite product ANTILOPE gives a goodvisualization of spatial variability and intensity of rainfall. Expectations of viticulture…

high density network[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatologyrainfallréseau haute densitéprécipitations[ SDU.STU.CL ] Sciences of the Universe [physics]/Earth Sciences/Climatologycomparaison radar/pluviomètrespatialisationradar/rain gauge intercomparison
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On Line Validation Exercise (OLIVE): A Web Based Service for the Validation of Medium Resolution Land Products. Application to FAPAR Products

2014

International audience; The OLIVE (On Line Interactive Validation Exercise) platform is dedicated to the validation of global biophysical products such as LAI (Leaf Area Index) and FAPAR (Fraction of Absorbed Photosynthetically Active Radiation). It was developed under the framework of the CEOS (Committee on Earth Observation Satellites) Land Product Validation (LPV) sub-group. OLIVE has three main objectives: (i) to provide a consistent and centralized information on the definition of the biophysical variables, as well as a description of the main available products and their performances (ii) to provide transparency and traceability by an online validation procedure compliant with the CEO…

validation;LAI;FAPAR;intercomparison;product;CEOSService (systems architecture)Earth observationTraceabilityComputer scienceScienceintercomparison10127 Institute of Evolutionary Biology and Environmental StudiesDocumentationBenchmark (surveying)Web applicationproductFAPARComputingMilieux_MISCELLANEOUSRemote sensingvalidationbusiness.industryQ1900 General Earth and Planetary SciencesLAI13. Climate action[SDE]Environmental Sciences570 Life sciences; biology590 Animals (Zoology)General Earth and Planetary SciencesbusinessHost (network)Quality assuranceCEOSRemote Sensing
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