Nuno Carvalhais, Dr.

Gruppenleiter

Aufgabengebiet

   TERRESTRIAL ECOSYSTEM DYNAMICS               MODEL-DATA FUSION APPROACHES
      BIOGEOCHEMICAL C-H2O CYCLES                  MODEL EVALUATION & DEVELOPMENT
         VEGETATION REMOTE SENSING                              HYBRID MODELING
                                                MODEL DATA INTEGRATION GROUP


Papers submitted / pre-prints:

Fan*, N., Reichstein, M., Koirala, S., Mahecha, M.D., Ahrens, B., and N. Carvalhais (2022), Hydrometeorology influences the apparent temperature sensitivity of terrestrial carbon turnover times, accepted in Nature Geoscience, doi:10.21203/rs.3.rs-1415250/v1.

Wang*, S., Yang, H., Koirala, S., Forkel, M., Reichstein, M., and N. Carvalhais (2022), Understanding disturbance regimes from patterns in biomass and primary productivity, doi:10.1002/essoar.10512199.2.

Bao*, S., Alonso, L., Wang, S., Gensheimer, J., De, R., and N. Carvalhais (2022), A Robust Light Use Efficiency Model Parameterization Method Based on Ecosystem Properties, doi:10.1002/essoar.10512186.1.

Koirala*, S., Jones, C., Ahrens, B., Fan, N., Brovkin, V., Delire, C., Fan, Y., Gayler, V., Joetzjer, V., Lee, H., Materia, S., Nabel, J., Peano, D., Peylin, P., Warlind, D., Wiltshire, A., Zaehle, S., Reichstein, M,. and N. Carvalhais (2022), Underrepresented controls of aridity in climate sensitivity of carbon cycle models, doi:10.21203/rs.3.rs-2013805/v1.

Peer reviewed publications


Projects:

Current : SeasFire | Project Office BIOMASS | DeepCube | ESM2025 | SINDBAD

Past : CRESCENDO | BIOMASCAT | ESDL2 | MEDSPEC | GlobBiomass | CARBO-Extreme | GeoCarbon | EMBRACE | COREGAL


Vita

2012 - ...

Scientist, group leader, Model Data Integration group

2021 - ...

Member of ELLIS JenaEuropean Laboratory for Learning and Intelligent Systems

2010 - ...

Invited Researcher, CENSE @ FCT NOVA, New University of Lisbon, Portugal

2010 - 2012

Postdoc at the Max-Planck-Institute for Biogeochemistry (CarboExtremes)

2010

PhD in Environmental Sciences and Engineering from the Faculty of Sciences and Technology, New University of Lisbon, Portugal, on integrating multiple observational data streams and diagnostic modeling of ecosystem carbon fluxes.

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