Jakob Runge

5.5k total citations · 1 hit paper
63 papers, 2.4k citations indexed

About

Jakob Runge is a scholar working on Global and Planetary Change, Atmospheric Science and Artificial Intelligence. According to data from OpenAlex, Jakob Runge has authored 63 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Global and Planetary Change, 17 papers in Atmospheric Science and 14 papers in Artificial Intelligence. Recurrent topics in Jakob Runge's work include Climate variability and models (23 papers), Meteorological Phenomena and Simulations (9 papers) and Atmospheric and Environmental Gas Dynamics (8 papers). Jakob Runge is often cited by papers focused on Climate variability and models (23 papers), Meteorological Phenomena and Simulations (9 papers) and Atmospheric and Environmental Gas Dynamics (8 papers). Jakob Runge collaborates with scholars based in Germany, United Kingdom and United States. Jakob Runge's co-authors include Jürgen Kurths, Vladimir Petoukhov, Dim Coumou, Marlene Kretschmer, Jonathan F. Donges, Jobst Heitzig, Norbert Marwan, Veronika Eyring, Reik V. Donner and Bernd Pompe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.

In The Last Decade

Jakob Runge

59 papers receiving 2.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Causal inference for time series

2023 107 citations Jakob Runge, Andreas Gerhardus et al. profile →

Peers

Jakob Runge

GPC

AS

SNP

EE

CN

Ethan R. Deyle United States

Nicola Scafetta Italy

Wen‐wen Tung United States

Niklas Boers Germany

Valerie Livina United Kingdom

Martin Vejmelka Czechia

Valerio Lucarini United Kingdom

N. W. Watkins United Kingdom

Reik V. Donner Germany

Anastasios A. Tsonis United States

Ethan R. Deyle United States

Jakob Runge

1.2k ×1.0

GPC

376 ×0.5

AS

312 ×0.8

SNP

406 ×1.1

EE

347 ×1.0

CN

Citations per year, relative to Jakob Runge Jakob Runge (= 1×) peers Ethan R. Deyle

Countries citing papers authored by Jakob Runge

Since Specialization

Citations

This map shows the geographic impact of Jakob Runge's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jakob Runge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jakob Runge more than expected).

Fields of papers citing papers by Jakob Runge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jakob Runge. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jakob Runge. The network helps show where Jakob Runge may publish in the future.

Co-authorship network of co-authors of Jakob Runge

This figure shows the co-authorship network connecting the top 25 collaborators of Jakob Runge. A scholar is included among the top collaborators of Jakob Runge based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jakob Runge. Jakob Runge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Ballinger, Andrew, et al.. (2025). Decreasing aerosols increase the European summer diurnal temperature range. npj Climate and Atmospheric Science. 8(1). 47–47.

2.

Meehl, Gerald A., et al.. (2024). Changing effects of external forcing on Atlantic–Pacific interactions. Earth System Dynamics. 15(3). 689–715. 2 indexed citations

3.

Luijten, Maartje, Wilson F. Abdo, Jana Vyrastekova, et al.. (2024). Triangulation for causal loop diagrams: constructing biopsychosocial models using group model building, literature review, and causal discovery. elib (German Aerospace Center). 1(1). 1 indexed citations

4.

Iglesias‐Suarez, Fernando, Pierre Gentine, Tom Beucler, et al.. (2024). Causally‐Informed Deep Learning to Improve Climate Models and Projections. Journal of Geophysical Research Atmospheres. 129(4). 19 indexed citations

5.

Runge, Jakob. (2023). Modern causal inference approaches to investigate biodiversity-ecosystem functioning relationships. Nature Communications. 14(1). 1917–1917. 15 indexed citations

6.

Beucler, Tom, et al.. (2023). Selecting robust features for machine-learning applications using multidata causal discovery. SHILAP Revista de lepidopterología. 2. 4 indexed citations

7.

Runge, Jakob, et al.. (2023). Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6. Earth System Dynamics. 14(2). 309–344. 12 indexed citations

8.

Mahecha, Miguel D., Mirco Migliavacca, Martin G. De Kauwe, et al.. (2022). Decoupling between ecosystem photosynthesis and transpiration: a last resort against overheating. Environmental Research Letters. 17(4). 44013–44013. 36 indexed citations

9.

Gerhardus, Andreas, et al.. (2021). Mapped-PCMCI: an algorithm for causal discovery at the grid level.

10.

Migliavacca, Mirco, Diego G. Miralles, Guido Kraemer, et al.. (2021). Functional convergence of biosphere–atmosphere interactions in response to meteorological conditions. Biogeosciences. 18(7). 2379–2404. 6 indexed citations

11.

Gerhardus, Andreas & Jakob Runge. (2021). LPCMCI: Causal Discovery in Time Series with Latent Confounders. elib (German Aerospace Center). 12 indexed citations

12.

Runge, Jakob, Diego G. Miralles, Mirco Migliavacca, et al.. (2020). Estimating causal networks in biosphere–atmosphere interaction with the PCMCI approach. Biogeosciences. 17(4). 1033–1061. 57 indexed citations

13.

Capua, Giorgia Di, Jakob Runge, Reik V. Donner, et al.. (2020). Dominant patterns of interaction between the tropics and mid-latitudes in boreal summer: causal relationships and the role of timescales. Weather and Climate Dynamics. 1(2). 519–539. 29 indexed citations

14.

Runge, Jakob, Diego G. Miralles, Mirco Migliavacca, et al.. (2019). Causal networks of biosphere–atmosphere interactions. elib (German Aerospace Center). 3 indexed citations

15.

Nowack, Peer & Jakob Runge. (2018). Large-scale causal network discovery in CMIP5 models: robustness and intercomparison. AGU Fall Meeting Abstracts. 2018. 2 indexed citations

16.

Runge, Jakob. (2018). Causal network reconstruction from time series: From theoretical assumptions to practical estimation. Chaos An Interdisciplinary Journal of Nonlinear Science. 28(7). 75310–75310. 247 indexed citations

17.

Runge, Jakob. (2016). Reconstructing causal pathways and optimal prediction from multivariate time series using the Tigramite package. EGU General Assembly Conference Abstracts. 1 indexed citations

18.

Kretschmer, Marlene, Dim Coumou, Jonathan F. Donges, & Jakob Runge. (2016). Using Causal Effect Networks to analyze different Arctic drivers of mid-latitude winter circulation. Publication Database PIK (Potsdam Institute for Climate Impact Research (PIK)). 3 indexed citations

19.

Schleussner, Carl‐Friedrich, Jakob Runge, Jascha Lehmann, & Anders Levermann. (2014). The role of the North Atlantic overturning and deep ocean for multi-decadal global-mean-temperature variability. Earth System Dynamics. 5(1). 103–115. 20 indexed citations

20.

Donges, Jonathan F., Jobst Heitzig, Jakob Runge, et al.. (2013). Advanced functional network analysis in the geosciences: The pyunicorn package. EGUGA. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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