David Neubauer

4.7k total citations
76 papers, 1.7k citations indexed

About

David Neubauer is a scholar working on Atmospheric Science, Global and Planetary Change and Astronomy and Astrophysics. According to data from OpenAlex, David Neubauer has authored 76 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Atmospheric Science, 55 papers in Global and Planetary Change and 7 papers in Astronomy and Astrophysics. Recurrent topics in David Neubauer's work include Atmospheric chemistry and aerosols (53 papers), Atmospheric aerosols and clouds (53 papers) and Atmospheric Ozone and Climate (24 papers). David Neubauer is often cited by papers focused on Atmospheric chemistry and aerosols (53 papers), Atmospheric aerosols and clouds (53 papers) and Atmospheric Ozone and Climate (24 papers). David Neubauer collaborates with scholars based in Switzerland, Germany and United States. David Neubauer's co-authors include Ulrike Lohmann, Philip Stier, Sylvaine Ferrachat, Kai Zhang, Martin Dressel, S. J. Ghan, Daniel G. Partridge, Minghuai Wang, A. V. Pronin and Anja Löhle 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

David Neubauer

70 papers receiving 1.7k citations

Peers

David Neubauer

GPC

EOMM

AMPO

Duncan Watson‐Parris United Kingdom

Takashi Shibata Japan

Hisashi Yashiro Japan

Gwenaël Berthet France

D. Kim United States

Kyo‐Sun Sunny Lim South Korea

E. M. Patterson United States

Jisk Attema Netherlands

Stefan Körner Germany

M. Kroon Netherlands

Duncan Watson‐Parris United Kingdom

David Neubauer

769 ×0.6

796 ×0.6

GPC

126 ×0.8

100 ×0.7

EOMM

183 ×1.3

AMPO

Citations per year, relative to David Neubauer David Neubauer (= 1×) peers Duncan Watson‐Parris

Countries citing papers authored by David Neubauer

Since Specialization

Citations

This map shows the geographic impact of David Neubauer'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 David Neubauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Neubauer more than expected).

Fields of papers citing papers by David Neubauer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Neubauer. 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 David Neubauer. The network helps show where David Neubauer may publish in the future.

Co-authorship network of co-authors of David Neubauer

This figure shows the co-authorship network connecting the top 25 collaborators of David Neubauer. A scholar is included among the top collaborators of David Neubauer 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 David Neubauer. David Neubauer 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

Wang, Yu, David Neubauer, Ying Chen, et al.. (2025). Challenges in global climate models to represent cloud response to aerosols: insights from volcanic eruptions. Nature Communications. 17(1). 627–627.

Malavelle, Florent, Ying Chen, Daniel G. Partridge, et al.. (2024). How well are aerosol–cloud interactions represented in climate models? – Part 1: Understanding the sulfate aerosol production from the 2014–15 Holuhraun eruption. Atmospheric chemistry and physics. 24(3). 1939–1960. 3 indexed citations

Proske, Ulrike, et al.. (2024). Simulating the seeder–feeder impacts on cloud ice and precipitation over the Alps. Atmospheric chemistry and physics. 24(9). 5389–5404. 3 indexed citations

Georgoulias, Aristeidis K., Dimitris Akritidis, Robert J. Allen, et al.. (2024). Decomposing the effective radiative forcing of anthropogenic aerosols based on CMIP6 Earth system models. Atmospheric chemistry and physics. 24(13). 7837–7872. 5 indexed citations

Neubauer, David, et al.. (2023). Understanding cirrus clouds using explainable machine learning. SHILAP Revista de lepidopterología. 2. 2 indexed citations

Neubauer, David, et al.. (2023). Does prognostic seeding along flight tracks produce the desired effects of cirrus cloud thinning?. Atmospheric chemistry and physics. 23(13). 7673–7698. 5 indexed citations

Zhong, Qirui, Nick Schutgens, Guido R. van der Werf, et al.. (2022). Using modelled relationships and satellite observations to attribute modelled aerosol biases over biomass burning regions. Nature Communications. 13(1). 5914–5914. 12 indexed citations

Salzmann, Marc, Sylvaine Ferrachat, Steffen Münch, et al.. (2022). The Global Atmosphere‐aerosol Model ICON‐A‐HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness. Journal of Advances in Modeling Earth Systems. 14(4). e2021MS002699–e2021MS002699. 11 indexed citations

Su, Wenying, Lusheng Liang, Gunnar Myhre, et al.. (2021). Understanding Top‐of‐Atmosphere Flux Bias in the AeroCom Phase III Models: A Clear‐Sky Perspective. Journal of Advances in Modeling Earth Systems. 13(9). 4 indexed citations

10.

Gryspeerdt, Edward, Johannes Mülmenstädt, Andrew Gettelman, et al.. (2020). Surprising similarities in model and observational aerosol radiative forcing estimates. Atmospheric chemistry and physics. 20(1). 613–623. 42 indexed citations

11.

Lohmann, Ulrike, et al.. (2020). Scripts for the publication "Future warming exacerbated by aged soot effect on cloud formation". Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

12.

Mülmenstädt, Johannes, Christine Nam, Marc Salzmann, et al.. (2020). Reducing the aerosol forcing uncertainty using observational constraints on warm rain processes. Science Advances. 6(22). eaaz6433–eaaz6433. 36 indexed citations

13.

Proske, Ulrike, et al.. (2020). How frequent is natural cloud seeding over Switzerland?. 1 indexed citations

14.

Tegen, Ina, David Neubauer, Sylvaine Ferrachat, et al.. (2019). The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 1: Aerosol evaluation. Geoscientific model development. 12(4). 1643–1677. 113 indexed citations

15.

Lobo, Prem, et al.. (2019). Impact of isolated atmospheric aging processes on the cloud condensation nuclei activation of soot particles. Atmospheric chemistry and physics. 19(24). 15545–15567. 12 indexed citations

16.

Kokkola, Harri, Thomas Kühn, Anton Laakso, et al.. (2018). SALSA2.0: The sectional aerosol module of the aerosol–chemistry–climate model ECHAM6.3.0-HAM2.3-MOZ1.0. Geoscientific model development. 11(9). 3833–3863. 49 indexed citations

17.

Tegen, Ina, David Neubauer, Sylvaine Ferrachat, et al.. (2018). The aerosol-climate model ECHAM6.3-HAM2.3: Aerosol evaluation. Biogeosciences (European Geosciences Union). 6 indexed citations

18.

Zhang, Shipeng, Minghuai Wang, S. J. Ghan, et al.. (2016). On the characteristics of aerosol indirect effect based on dynamic regimes in global climate models. Atmospheric chemistry and physics. 16(5). 2765–2783. 62 indexed citations

19.

Leitner, Johannes, et al.. (2010). Generalizing Habitable Zones in Exoplanetary Systems — The Concept of the Life Supporting Zone. LPICo. 1538. 5255. 3 indexed citations

20.

Leitner, Johannes, et al.. (2010). The Life Supporting Zone I - From Classic to Exotic Life. 677. 1 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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