A5016509981- Atmospheric and Environmental Gas Dynamics
- Plant Water Relations and Carbon Dynamics
- Climate variability and models
- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Soil Geostatistics and Mapping
- Spectroscopy and Laser Applications
- Air Quality Monitoring and Forecasting
- Horticultural and Viticultural Research
- Atmospheric chemistry and aerosols
- Youth Substance Use and School Attendance
- Ionosphere and magnetosphere dynamics
- Plant responses to elevated CO2
- Child and Adolescent Psychosocial and Emotional Development
- Gaussian Processes and Bayesian Inference
- Land Use and Ecosystem Services
- Hydrology and Drought Analysis
- Hydrology and Watershed Management Studies
- Meteorological Phenomena and Simulations
- Marine and coastal ecosystems
- Stuttering Research and Treatment
- Fluid Dynamics and Turbulent Flows
- Voice and Speech Disorders
- Drilling and Well Engineering
- Language Development and Disorders
Terra
2024
Parc Científic de la Universitat de València
2019-2022
Azienda Sanitaria Locale Viterbo
2022
Università degli Studi della Tuscia
2009-2020
Universitat de València
2020
Pennsylvania State University
2011-2012
Abstract. Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number strategies for empirical with eddy-covariance flux data have been applied, systematic intercomparison these methods has missing so far. In this study, we performed cross-validation experiment predicting carbon dioxide, latent heat, sensible heat and net radiation across different ecosystem types 11 machine learning (ML)...
Abstract Although a key driver of Earth’s climate system, global land-atmosphere energy fluxes are poorly constrained. Here we use machine learning to merge flux measurements from FLUXNET eddy covariance towers with remote sensing and meteorological data estimate gridded net radiation, latent sensible heat their uncertainties. The resulting FLUXCOM database comprises 147 products in two setups: (1) 0.0833° resolution using MODIS (RS) (2) 0.5° (RS + METEO). Within each setup full factorial...
Abstract. FLUXNET comprises globally distributed eddy-covariance-based estimates of carbon fluxes between the biosphere and atmosphere. Since eddy covariance flux towers have a relatively small footprint are unevenly across world, upscaling observations is necessary to obtain global-scale biosphere–atmosphere exchange. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) dynamic global vegetation models (DGVMs), here we provide systematic assessment...
Self-reported self-esteem, life orientation, satisfaction with life, and bullying were examined in relation to victimization experiences among 54 students who stuttered did not stutter. Those reported greater, i.e., clinically significant, (44.4%) than stutter (9.2%). Significant differences found between means for self-esteem reporting lower less optimistic orientation those In both groups of students, high scores had statistically significant negative correlations scores. Given the...
Abstract Groundwater is an integral component of the water cycle, and it also influences carbon cycle by supplying moisture to ecosystems. However, extent determinants groundwater‐vegetation interactions are poorly understood at global scale. Using several high‐resolution data products, we show that spatial patterns ecosystem gross primary productivity groundwater table depth correlated during least one season in more than two thirds vegetated area. Positive relationships, i.e., larger under...
Abstract Empirical modeling approaches are frequently used to upscale local eddy covariance observations of carbon, water, and energy fluxes regional global scales. The predictive capacity such models largely depends on the data for parameterization identification input‐output relationships, while prediction conditions outside training domain is generally uncertain. In this work, artificial neural networks (ANNs) were gross primary production (GPP) latent heat flux (LE) European scales with...
Abstract The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO 2 between ecosystems and atmosphere, offering a unique opportunity study responses climate change. NEE difference total release due all respiration processes (RECO), gross carbon uptake by photosynthesis (GPP). These two fluxes are derived from EC measurements applying partitioning methods that rely on physiologically based functional relationships with limited number environmental drivers....
Abstract. Mapping in-situ eddy covariance measurements of terrestrial land-atmosphere fluxes to the globe is a key method for diagnosing Earth system from data-driven perspective. We describe first global products (called X-BASE) newly implemented up-scaling framework, FLUXCOM-X. The X-BASE comprise estimates CO2 net ecosystem exchange (NEE), gross primary productivity (GPP) as well evapotranspiration (ET) and, time, novel fully transpiration product (ETT), at high spatial (0.05°) and...
Abstract. Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative environmental change. A full characterization C cycling requires detailed information on spatiotemporal patterns surface–atmosphere fluxes. However, relevant observations are highly variable in their coverage reporting standards. Especially problematic lack integration dioxide (CO2) exchange ocean, inland freshwaters land surface with atmosphere. Here we adopt a...
Abstract. Spatial-temporal fields of land-atmosphere fluxes derived from data-driven models can complement simulations by process-based Land Surface Models. While a number strategies for empirical with eddy covariance flux data have been applied, systematic intercomparison these methods has missing so far. In this study, we perform cross-validation experiment predicting carbon dioxide (CO2), latent heat, sensible heat and net radiation fluxes, in different ecosystem types eleven machine...
Abstract. Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing Earth system from data-driven perspective. We describe first global products (called X-BASE) newly implemented upscaling framework, FLUXCOM-X, representing an advancement previous generation FLUXCOM terms flexibility and technical capabilities. The X-BASE are comprised estimates CO2 net ecosystem exchange (NEE), gross primary productivity (GPP),...
The relationship between vegetation optical depth (VOD) retrieved by L-band SMOS radiometer and forest above ground biomass (AGB) was investigated in tropical areas of Africa South America. VOD from the latest version level 2 algorithm, while reference AGB obtained a pantropical database, encompassing large number plot data derived field surveys conducted on both continents. In South-America, increased with AGB, reaching saturation at about 350 Mg ha−1. strength relation improved selecting...
Abstract. FLUXNET assembles globally-distributed eddy covariance-based estimates of carbon fluxes between the biosphere and atmosphere. Since covariance flux towers have a relatively small footprint are distributed unevenly across world, upscaling observations is necessary in order to obtain global-scale biosphere-atmosphere exchange from tower network. Based on cross-consistency checks with atmospheric inversions, sun-induced fluorescence (SIF) dynamic global vegetation models (DGVM), we...
Abstract. Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions terrestrial cycle. However, there are several uncertainties unknowns related current photosynthesis estimates. In this study, we evaluate four different methods for estimating at a boreal forest ecosystem scale, which two based on dioxide (CO2) flux measurements carbonyl sulfide (COS) measurements. The CO2-based use traditional partitioning artificial...
Monitoring ecosystem functions in forests is a priority climate change scenario, as climate-induced events may initially alter the more than slow-changing attributes, such biomass. The functional properties (EFPs) are quantities that characterize key processes. They can be derived by point observations of gas and energy exchanges between ecosystems atmosphere collected globally at FLUXNET flux tower sites upscaled level. here considered describe ability to optimize use resources for carbon...
The accurate estimation of carbon and heat fluxes at global scale is paramount for future policy decisions in the context climate change. This paper analyzes relative relevance potential remote sensing meteorological drivers energy over land. study done an indirect way via upscaling both Gross Primary Production (GPP) latent (LE) using Gaussian Process regression (GPR). In summary, GPR successfully compared to multivariate linear (RMSE gain +4.17% GPP +7.63% LE) kernel ridge (+2.91% +3.07%...
The purpose of this paper is to describe coping in the context adolescence and stuttering. Adolescents who stutter are a unique group individuals dealing with an episodic, variable, chronic disorder during critical developmental stage their lives. We provide brief review adolescence, constructs, programs. highlight role speech-language pathologist as advocate/guide assisting adolescents develop appropriate, adaptive strategies for everyday stressors added potential stress associated
Abstract. Understanding the global carbon (C) cycle is of crucial importance to map current and future climate dynamics relative environmental change. A full characterization C cycling requires detailed information on spatiotemporal patterns surface-atmosphere fluxes. However, relevant observations are highly variable in their coverage reporting standards. Especially problematic lack integration vertical oceanic, inland freshwaters terrestrial dioxide (CO2) exchange. Here we adopt a...
Although a key driver of Earth's climate system, global land-atmosphere energy fluxes are poorly constrained. Here we use machine learning to merge flux measurements from FLUXNET eddy covariance towers with remote sensing and meteorological data estimate net radiation, latent sensible heat their uncertainties. The resulting FLUXCOM database comprises 147 gridded products in two setups: (1) 0.0833${\deg}$ resolution using MODIS (RS) (2) 0.5${\deg}$ (RS+METEO). Within each setup full factorial...