Christian Folberth

Senior Research Scholar

Agriculture, Forestry, and Ecosystem Services Research Group

Biodiversity and Natural Resources Program

Biography

Chris Folberth is a senior researcher in the Agriculture, Forestry, and Ecosystem Services Research Group of the IIASA Biodiversity and Natural Resources Program. The main focus of his research is process-based agro-ecosystem modeling to improve the understanding of the interactions between crop and soil management, climate impacts, and adaptation potentials. He also serves as the group’s liaison to community networks such as the Intersectoral Impact Model Intercomparison Project (ISIMIP) and the Global Gridded Crop Model Intercomparison (GGCMI) initiative.

Besides process-based modeling, he leads initiatives on data-driven and hybrid modeling to harness the combined advantages of both process-based and machine-learning methods. He also engages in transdisciplinary research that aligns methods and tools with stakeholder needs.

Prior to joining IIASA in 2013, he was a research assistant at the Swiss Federal Institute of Aquatic Science and Technology (EAWAG) and the Federal Institute of Technology Zurich (ETH Zurich), where he also acquired a doctoral degree. In the years 2015-2016, he completed a research fellowship at Ludwig Maximilian University Munich, focusing on geographies of substance flows in the agro-food system.

Last update: 21 MAY 2024

Publications

Laso Bayas, J.C. , Gardeazabal, A., Kerner, M., Vargas, L., Folberth, C. , Skalský, R. , Balkovič, J. , Declerce, S., Crespo Cuaresma, J., Hlouskova, J., Verhulst, N., See, L. , Fritz, S. , Obersteiner, M. , & Govaerts, B. (2019). AgroTutor: Promoting agricultural sustainable intensification and crowdsourcing plot information. In: ESA Living Planet Symposium, May 2019, Milan, Italy.

Müller, C., Elliott, J., Ruane, A., Jägermeyr, J., Balkovic, J. , Ciais, P., Dury, M., Falloon, P., Folberth, C. , Francois, L., Hank, T., Hoffmann, M., Izaurralde, C., Jacquemin, I., Jones, C., Khabarov, N. , Koch, M., Liu, W., Olin, S., Pugh, T., Reddy, A., Wang, X., Williams, K., & Zabel, F. (2019). Understanding crop model response types in a global gridded crop model ensemble. In: Agriculture and Climate Change, 24-26 March 2019, Budapest, Hungary.

Folberth, C. , Baklanov, A. , Balkovic, J. , Skalsky, R. , Khabarov, N. , & Obersteiner, M. (2019). Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning. Agricultural and Forest Meteorology 264 1-15. 10.1016/j.agrformet.2018.09.021.

Schewe, J., Gosling, S., Reyer, C., Zhao, F., Ciais, P., Elliott, J., Francois, L., Huber, V., Lotze, H., Seneviratne, S., van Vliet, M., Vautard, R., Wada, Y. , Breuer, L., Buchner, M., Carozza, D., Chang, J., Coll, M., Deryng, D., de Wit, A., Eddy, T., Folberth, C. , Frieler, K., Friend, A., Gerten, D., Gudmundsson, L., Hanasaki, N., Ito, A., Khabarov, N. , Kim, H., Lawrence, P., Morfopoulos, C., Mueller, C., Schmied, H., Orth, R., Ostberg, S., Pokhrel, Y., Pugh, T., Sakuri, G., Satoh, Y., Schmid, E., Stacke, T., Steenbeek, J., Steinkamp, J., Tang, Q., Tian, H., Tittensor, D., Volkholz, J., Wang, X., & Warszawski, L. (2019). State-of-the-art global models underestimate impacts from climate extremes. Nature Communications 10.1038/s41467-019-08745-6.

Liu, W., Yang, H., Folberth, C. , Müller, C., Ciais, P., Abbaspour, K.C., & Schulin, R. (2018). Achieving High Crop Yields with Low Nitrogen Emissions in Global Agricultural Input Intensification. Environmental Science & Technology 52 (23) 13782-13791. 10.1021/acs.est.8b03610.