Search results for "FluxNet"

showing 10 items of 12 documents

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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Environment-sensitivity functions for gross primary productivity in light use efficiency models

2022

International audience; The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full fact…

0106 biological sciencesAtmospheric Science010504 meteorology & atmospheric sciencesVapour Pressure DeficitBiomeRandomly sampled sitesPlant Ecology and Nature ConservationForcing (mathematics)04 Earth Sciences 06 Biological Sciences 07 Agricultural and Veterinary SciencesAtmospheric sciences01 natural sciences[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/EcosystemsFluxNetLaboratory of Geo-information Science and Remote SensingEvapotranspirationMeteorology & Atmospheric SciencesEcosystemLaboratorium voor Geo-informatiekunde en Remote SensingRadiation use efficiencySensitivity formulations0105 earth and related environmental sciencesGlobal and Planetary ChangeDiffuse fractionGlobal warmingModel equifinalityForestryModel comparison15. Life on landPE&RCLight intensity13. Climate actionEnvironmental sciencePlantenecologie en NatuurbeheerCarbon assimilationTemporal scalesAgronomy and Crop Science010606 plant biology & botany
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Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

2020

Abstract The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO2 between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO2 release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO2 fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co‐acting…

0106 biological sciencesecosystem respiration010504 meteorology & atmospheric sciencesnet ecosystem exchangeneural networkEddy covarianceClimate changeAtmospheric sciencesPhotosynthesis01 natural sciences7. Clean energyCarbon CycleAtmosphereFlux (metallurgy)FluxNetRespirationeddy covarianceEnvironmental ChemistryEcosystemPrimary Research ArticlePhotosynthesisEcosystem0105 earth and related environmental sciencesGeneral Environmental ScienceGlobal and Planetary ChangeEcologycarbon dioxide fluxes partitioningRespirationgross primary production (GPP)Carbon DioxideBiological Sciences15. Life on landgross primary productionmachine learning13. Climate action[SDE]Environmental SciencesEnvironmental scienceNeural Networks ComputerSeasonsecosystem respiration (RECO)Environmental Sciences010606 plant biology & botanyGlobal Change Biology
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Improved meteorology and surface fluxes in mesoscale modelling using adjusted initial vertical soil moisture profiles

2018

The Regional Atmospheric Modeling System (RAMS) is being used for different and diverse purposes, ranging from atmospheric and dispersion of pollutants forecasting to agricultural meteorology and ecological modelling as well as for hydrological purposes, among others. The current paper presents a comprehensive assessment of the RAMS forecasts, comparing the results not only with observed standard surface meteorological variables, measured at FLUXNET stations and other portable and permanent weather stations located over the region of study, but also with non-standard observed variables, such as the surface energy fluxes, with the aim of evaluating the surface energy budget and its relation …

Atmospheric ScienceGround truth010504 meteorology & atmospheric sciencesMoistureMeteorologySurface fluxes0208 environmental biotechnologyRAMSFísica de la TierraMesoscale meteorology02 engineering and technology01 natural sciences020801 environmental engineeringMesoscale modellingData assimilationFluxNetRegional Atmospheric Modeling SystemSoil horizonEnvironmental scienceMeteorologiaSoil moistureModel initializationWater content0105 earth and related environmental sciences
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A carbon sink-driven approach to estimate gross primary production from microwave satellite observations

2019

Abstract Global estimation of Gross Primary Production (GPP) - the uptake of atmospheric carbon dioxide by plants through photosynthesis - is commonly based on optical satellite remote sensing data. This presents a source-driven approach since it uses the amount of absorbed light, the main driver of photosynthesis, as a proxy for GPP. Vegetation Optical Depth (VOD) estimates obtained from microwave sensors provide an alternative and independent data source to estimate GPP on a global scale, which may complement existing GPP products. Recent studies have shown that VOD is related to aboveground biomass, and that both VOD and temporal changes in VOD relate to GPP. In this study, we build upon…

Earth observationTeledetecció010504 meteorology & atmospheric sciences0208 environmental biotechnologySoil ScienceComputerApplications_COMPUTERSINOTHERSYSTEMS02 engineering and technologyData_CODINGANDINFORMATIONTHEORY01 natural sciencesCross-validationFluxNetVegetacióComputers in Earth Sciences0105 earth and related environmental sciencesRemote sensingRadiometerComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSPrimary productionGeology15. Life on landScatterometer020801 environmental engineeringSpectroradiometer13. Climate actionEnvironmental scienceSpatial variability
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The FLUXCOM ensemble of global land-atmosphere energy fluxes

2019

Although a key driver of Earth’s climate system, global land-atmosphere energy fluxes are poorly constrained. Here we use machine learning to merge energy flux measurements from FLUXNET eddy covariance towers with remote sensing and meteorological data to estimate global gridded net radiation, latent and sensible heat and their uncertainties. The resulting FLUXCOM database comprises 147 products in two setups: (1) 0.0833° resolution using MODIS remote sensing data (RS) and (2) 0.5° resolution using remote sensing and meteorological data (RS + METEO). Within each setup we use a full factorial design across machine learning methods, forcing datasets and energy balance closure corrections. For…

FOS: Computer and information sciencesStatistics and ProbabilityComputer Science - Machine LearningData Descriptor010504 meteorology & atmospheric sciencesMeteorology0208 environmental biotechnologyEnergy balanceEddy covarianceFOS: Physical sciencesEnergy fluxMachine Learning (stat.ML)02 engineering and technologySensible heatLibrary and Information Sciences01 natural sciences7. Clean energyMachine Learning (cs.LG)EducationFluxNetStatistics - Machine LearningEvapotranspirationLatent heatlcsh:Science0105 earth and related environmental sciences020801 environmental engineeringComputer Science ApplicationsMetadataEnvironmental sciencesPhysics - Atmospheric and Oceanic Physics13. Climate actionAtmospheric and Oceanic Physics (physics.ao-ph)Environmental sciencelcsh:QStatistics Probability and UncertaintyHydrologyClimate sciencesInformation SystemsScientific Data
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Simulation of surface energy fluxes and meteorological variables using the Regional Atmospheric Modeling System (RAMS): Evaluating the impact of land…

2018

Atmospheric mesoscale numerical models are commonly used not only for research and air quality studies, but also for other related applications, such as short-term weather forecasting for atmospheric, hydrological, agricultural and ecological modelling. A key element to produce faithful simulations is the proper representation of the soil parameters used in the initialization of the corresponding mesoscale numerical model. The Regional Atmospheric Modeling System (RAMS) is used in the current study. The model code has been updated in order to permit the model to be initialized using a heterogeneous soil moisture and temperature distribution derived from land surface models. Particularly, RA…

Land coverAtmospheric ScienceNumerical weather prediction/forecasting010504 meteorology & atmospheric sciencesMeteorology0208 environmental biotechnologyWeather forecastingMesoscale meteorologyInitialization02 engineering and technologyLand covercomputer.software_genre01 natural sciencesMesoscale modellingWeather stationData assimilationFluxNetMeteorologiaLand surface modelsSurface energy fluxes0105 earth and related environmental sciencesGlobal and Planetary ChangeSoil initializationFísica de la TierraForestry020801 environmental engineeringRegional Atmospheric Modeling SystemEnvironmental scienceAgronomy and Crop Sciencecomputer
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Time-domain based feature space at FLUXNET sites for vegetation patterns identification

2019

Monitoring the flux transfer of mass and energy occurring within the soil-plant-atmosphere continuum is a pivotal key for understanding hydrological and vegetation relationships. Average daily values of the Priestley - Taylor (PT) parameter were calculated for 4 eddy covariance (EC) flux tower sites from FLUXNET network, characterized by different vegetation features, over the 2010-12 reference period. Site-by-site feature spaces (built by difference in diurnal and night-time land surface temperature versus enhanced vegetation index, ΔLST-EVI) were obtained by combining satellite data (MODIS) and observed PT parameter (ϕ) retrieved by FLUXNET surface energy balance (SEB) fluxes. The results…

Land surface temperatureFeature vectorEddy covarianceEnhanced vegetation indexEddy covarianceEVIAtmospheric sciencessurface energy balance fluxesEddy covariance; EVI; Land Surface Temperature; surface energy balance fluxesFlux (metallurgy)FluxNetEnvironmental monitoringEnvironmental scienceTime domainLand Surface Temperature
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Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach

2020

FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and the atmosphere. Since eddy covariance flux towers have a relatively small footprint and are distributed unevenly across the world, upscaling the observations is necessary to obtain global-scale estimates of biosphere–atmosphere exchange. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) and dynamic global vegetation models (DGVMs), here we provide a systematic assessment of the latest upscaling efforts for gross primary production (GPP) and net ecosystem exchange (NEE) of the FLUXCOM initiative, where different machine learning methods…

Meteorologie en Luchtkwaliteit010504 meteorology & atmospheric sciencesMeteorology and Air Qualitylcsh:LifeEddy covarianceFlux010501 environmental sciencesAtmospheric sciences01 natural sciencesCarbon cycle03 medical and health sciencesFluxNetLaboratory of Geo-information Science and Remote Sensinglcsh:QH540-549.5ddc:550Life ScienceLaboratorium voor Geo-informatiekunde en Remote SensingBiogeosciences[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmentScalingEcology Evolution Behavior and Systematics030304 developmental biology0105 earth and related environmental sciencesCarbon fluxEarth-Surface ProcessesSDG 15 - Life on Land[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere0303 health sciencesWIMEKlcsh:QE1-996.5Carbon sinkBiospherePrimary production15. Life on landlcsh:GeologyEarth scienceslcsh:QH501-53113. Climate actionGreenhouse gasEnvironmental sciencelcsh:Ecology
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A satellite stand-alone procedure for deriving net radiation by using SEVIRI and MODIS products

2018

Abstract In this study, a new stand-alone satellite approach for the estimation of net surface radiation (Rn) has been implemented and validated for the Italian territory. The method uses the MODIS and MSG-SEVIRI time series products and it is independent of the use of ancillary data (i.e. ground measurements). A database of daily measurements of Rn, provided by 9 stations of the FLUXNET network, was used to validate the method in different ecological scenarios in the period 2010-12. The Rn modelled by the proposed approach and the corresponding FLUXNET measurements were in good agreement, with RMSE and R2 of 19.8 Wm−2 and 0.87, respectively, at 8-days scale, and 23.3 Wm−2 and 0.92, respect…

Monitoring010504 meteorology & atmospheric sciencesMean squared errorFLUXNET0211 other engineering and technologiesClimate change02 engineering and technologyManagement Monitoring Policy and Law01 natural sciencesVegetation characteristicsFluxNetSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliComputers in Earth Sciences021101 geological & geomatics engineering0105 earth and related environmental sciencesEarth-Surface ProcessesRemote sensingGlobal and Planetary ChangePolicy and LawFLUXNET; MODIS; MSG-SEVIRI; Net radiation; Vegetation characteristics; Global and Planetary Change; Earth-Surface Processes; Computers in Earth Sciences; Management Monitoring Policy and LawManagementNet radiation MODIS MSG-SEVIRI FLUXNET Vegetation characteristicsSettore AGR/02 - Agronomia E Coltivazioni ErbaceeAncillary dataWater resourcesNet radiationVariable (computer science)MODISMSG-SEVIRIEnvironmental scienceSatelliteScale (map)International Journal of Applied Earth Observation and Geoinformation
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