What is he best known for?
The fields of study he is best known for:
- Ecology
- Ecosystem
- Climate change
The scientist’s investigation covers issues in Climate change, Carbon cycle, Ecology, Atmospheric sciences and Carbon dioxide.
The various areas that Nuno Carvalhais examines in his Climate change study include Soil carbon, Carbon sequestration, Land cover, Meteorology and Land management.
His Carbon cycle study combines topics from a wide range of disciplines, such as Boreal, Temperate rainforest, Temperate forest, Northern Hemisphere and Biome.
His study in Ecosystem, FluxNet, Taiga and Temperate climate is carried out as part of his studies in Ecology.
His Ecosystem research incorporates elements of Vegetation and Precipitation.
FluxNet is a subfield of Eddy covariance that he studies.
His most cited work include:
- Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate (1439 citations)
- Deep learning and process understanding for data-driven Earth system science (556 citations)
- Deep learning and process understanding for data-driven Earth system science (556 citations)
What are the main themes of his work throughout his whole career to date?
Nuno Carvalhais spends much of his time researching Atmospheric sciences, Ecosystem, Carbon cycle, Eddy covariance and Vegetation.
His Atmospheric sciences research is multidisciplinary, relying on both Primary production, Climate change, Meteorology, Evapotranspiration and FluxNet.
Ecosystem is a subfield of Ecology that Nuno Carvalhais tackles.
His Carbon cycle research includes elements of Climatology, Biomass, Carbon sink, Physical geography and Data assimilation.
His studies in Eddy covariance integrate themes in fields like Latent heat, Leaf area index, Water-use efficiency and Spatial variability.
His research in Vegetation intersects with topics in Biosphere and Groundwater.
He most often published in these fields:
- Atmospheric sciences (64.52%)
- Ecosystem (34.95%)
- Carbon cycle (36.02%)
What were the highlights of his more recent work (between 2017-2021)?
- Atmospheric sciences (64.52%)
- Vegetation (35.48%)
- Ecosystem (34.95%)
In recent papers he was focusing on the following fields of study:
Nuno Carvalhais mostly deals with Atmospheric sciences, Vegetation, Ecosystem, Physical geography and Eddy covariance.
His work deals with themes such as Primary production, FluxNet and Transpiration, which intersect with Atmospheric sciences.
Nuno Carvalhais interconnects Remote sensing and Photosynthetically active radiation in the investigation of issues within Vegetation.
His Ecosystem research incorporates themes from Groundwater, Climatology, Biosphere and Vegetation cover.
His Biosphere research includes themes of Atmosphere, Climate change and Carbon cycle.
Nuno Carvalhais has researched Eddy covariance in several fields, including Leaf area index, Carbon flux and Spatial variability.
Between 2017 and 2021, his most popular works were:
- Deep learning and process understanding for data-driven Earth system science (556 citations)
- Deep learning and process understanding for data-driven Earth system science (556 citations)
- Unexpectedly large impact of forest management and grazing on global vegetation biomass (172 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Ecosystem
- Statistics
His main research concerns Eddy covariance, Atmospheric sciences, Physical geography, Biosphere and Climate change.
His Eddy covariance research is multidisciplinary, incorporating elements of Transpiration, Ecohydrology, Carbon flux and Spatial variability.
As a part of the same scientific family, Nuno Carvalhais mostly works in the field of Atmospheric sciences, focusing on Vegetation and, on occasion, Atmosphere.
His Biosphere research is multidisciplinary, incorporating perspectives in Forest management and Ecosystem, Carbon cycle.
His Carbon cycle study integrates concerns from other disciplines, such as Primary production, FluxNet, Carbon sink and Greenhouse gas.
His work on Climate model, Coupled model intercomparison project and Earth system model as part of general Climate change research is frequently linked to Python, thereby connecting diverse disciplines of science.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
