D
Dieter Gerten
Researcher at Potsdam Institute for Climate Impact Research
Publications - 166
Citations - 28212
Dieter Gerten is an academic researcher from Potsdam Institute for Climate Impact Research. The author has contributed to research in topics: Climate change & Global warming. The author has an hindex of 65, co-authored 157 publications receiving 22677 citations. Previous affiliations of Dieter Gerten include Humboldt University of Berlin & Leibniz Association.
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Journal ArticleDOI
Planetary boundaries: Guiding human development on a changing planet
Will Steffen,Will Steffen,Katherine Richardson,Johan Rockström,Sarah Cornell,Ingo Fetzer,Elena M. Bennett,Reinette Biggs,Reinette Biggs,Stephen R. Carpenter,Wim de Vries,Cynthia A. de Wit,Carl Folke,Carl Folke,Dieter Gerten,Jens Heinke,Jens Heinke,Jens Heinke,Georgina M. Mace,Linn Persson,Veerabhadran Ramanathan,Veerabhadran Ramanathan,Belinda Reyers,Belinda Reyers,Sverker Sörlin +24 more
TL;DR: An updated and extended analysis of the planetary boundary (PB) framework and identifies levels of anthropogenic perturbations below which the risk of destabilization of the Earth system (ES) is likely to remain low—a “safe operating space” for global societal development.
Journal ArticleDOI
Recent decline in the global land evapotranspiration trend due to limited moisture supply
Martin Jung,Markus Reichstein,Philippe Ciais,Sonia I. Seneviratne,Justin Sheffield,Michael L. Goulden,Gordon B. Bonan,Alessandro Cescatti,Jiquan Chen,Richard de Jeu,A. Johannes Dolman,Werner Eugster,Dieter Gerten,Damiano Gianelle,Nadine Gobron,Jens Heinke,John S. Kimball,Beverly E. Law,Leonardo Montagnani,Qiaozhen Mu,Brigitte Mueller,Keith W. Oleson,Dario Papale,Andrew D. Richardson,Olivier Roupsard,S. W. Running,Enrico Tomelleri,Nicolas Viovy,Ulrich Weber,Christopher B. Williams,Eric F. Wood,Sönke Zaehle,Ke Zhang +32 more
TL;DR: An estimate of global land evapotranspiration from 1982 to 2008 is provided using a global monitoring network, meteorological and remote-sensing observations, and a machine-learning algorithm, which suggests that increasing soil-moisture limitations on evapOTranspiration largely explain the recent decline of the global land-evapotranpiration trend.
Journal ArticleDOI
Multimodel assessment of water scarcity under climate change
Jacob Schewe,Jens Heinke,Jens Heinke,Dieter Gerten,Ingjerd Haddeland,Nigel W. Arnell,Douglas B. Clark,Rutger Dankers,Stephanie Eisner,Balázs M. Fekete,Felipe J. Colón-González,Simon N. Gosling,Hyungjun Kim,Xingcai Liu,Yoshimitsu Masaki,Felix T. Portmann,Felix T. Portmann,Yusuke Satoh,Tobias Stacke,Qiuhong Tang,Yoshihide Wada,Dominik Wisser,Torsten Albrecht,Katja Frieler,Franziska Piontek,Lila Warszawski,Pavel Kabat +26 more
TL;DR: It is shown that climate change is likely to exacerbate regional and global water scarcity considerably and GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.
Journal ArticleDOI
Modelling the role of agriculture for the 20th century global terrestrial carbon balance
Alberte Bondeau,P. C. Smith,Sönke Zaehle,Sibyll Schaphoff,Wolfgang Lucht,Wolfgang Cramer,Dieter Gerten,Hermann Lotze-Campen,Christoph Müller,Markus Reichstein,Benjamin Smith +10 more
TL;DR: In this paper, the authors present a model of the managed planetary land surface, LPJmL, which simulates biophysical and biogeochemical processes as well as productivity and yield of the most important crops worldwide, using a concept of crop functional types (CFTs).
Journal ArticleDOI
Terrestrial vegetation and water balance-hydrological evaluation of a dynamic global vegetation model
TL;DR: In this paper, the hydrological performance of the Lund-Potsdam-Jena model (LPJ), a prominent dynamic global vegetation model, is evaluated, and it is shown that runoff and evapotranspiration computed by LPJ agree well with respective results from state-of-the-art global hydrologogical models, while in some regions, runoff is significantly over- or underestimated compared to observations.