0000000000148717

AUTHOR

Sujan Koirala

showing 3 related works from this author

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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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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Global Groundwater-Vegetation Relations

2017

Groundwater is an integral component of the water cycle, and it also influences the carbon cycle by supplying moisture to ecosystems. However, the extent and determinants of groundwater-vegetation interactions are poorly understood at the global scale. Using several high-resolution data products, we show that the spatial patterns of ecosystem gross primary productivity and groundwater table depth are correlated during at least one season in more than two-thirds of the global vegetated area. Positive relationships, i.e., larger productivity under shallower groundwater table, predominate in moisture-limited dry to mesic conditions with herbaceous and shrub vegetation. Negative relationships, …

010504 meteorology & atmospheric sciencesWater table0208 environmental biotechnology02 engineering and technologyecohydrological patterns01 natural sciencesgroundwaterEcosystemWater cycleplant productivity0105 earth and related environmental sciencesHydrologyecosystemVegetation15. Life on land6. Clean water020801 environmental engineeringGeophysicsProductivity (ecology)13. Climate actionSpatial ecologyGeneral Earth and Planetary SciencesEnvironmental scienceGroundwaterWater usespatial covariation
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