Machine-learning-based evidence and attribution mapping of 100,000 climate 
impact studies

Callaghan, Max W.; Schleussner, Carl-Friedrich; Nath, Shruti; Lejeune, Quentin; Knutson, Thomas R.; Reichstein, Markus; Hansen, Gerrit; Theokritoff, Emily; Andrijevic, Marina; Brecha, Robert J.; Hegarty, Michael; Jones, Chelsea; Lee, Kaylin; Lucas, Agathe; van Maanen, Nicole; Menke, Inga; Pfleiderer, Peter; Yesil, Burcu; Minx, Jan C.

doi:10.1038/s41558-021-01168-6

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Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies

Authors

Callaghan, Max W.
External Organizations;

Schleussner, Carl-Friedrich

Nath, Shruti

Lejeune, Quentin

Knutson, Thomas R.

Reichstein, Markus

Hansen, Gerrit

Theokritoff, Emily

Andrijevic, Marina

Brecha, Robert J.

Hegarty, Michael

Jones, Chelsea

Lee, Kaylin

Lucas, Agathe

van Maanen, Nicole

Menke, Inga

Pfleiderer, Peter

Yesil, Burcu

Minx, Jan C.

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Citation

Callaghan, M. W., Schleussner, C.-F., Nath, S., Lejeune, Q., Knutson, T. R., Reichstein, M., Hansen, G., Theokritoff, E., Andrijevic, M., Brecha, R. J., Hegarty, M., Jones, C., Lee, K., Lucas, A., van Maanen, N., Menke, I., Pfleiderer, P., Yesil, B., Minx, J. C. (2021): Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies. - Nature Climate Change, 11, 11, 966-972.
https://doi.org/10.1038/s41558-021-01168-6

Cite as: https://publications.pik-potsdam.de/pubman/item/item_31034

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