Georg J. Mayr

2.7k total citations
88 papers, 1.7k citations indexed

About

Georg J. Mayr is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Georg J. Mayr has authored 88 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Atmospheric Science, 56 papers in Global and Planetary Change and 18 papers in Environmental Engineering. Recurrent topics in Georg J. Mayr's work include Meteorological Phenomena and Simulations (58 papers), Climate variability and models (39 papers) and Wind and Air Flow Studies (16 papers). Georg J. Mayr is often cited by papers focused on Meteorological Phenomena and Simulations (58 papers), Climate variability and models (39 papers) and Wind and Air Flow Studies (16 papers). Georg J. Mayr collaborates with scholars based in Austria, United States and Germany. Georg J. Mayr's co-authors include Achim Zeileis, Jakob W. Messner, Alexander Gohm, Laurence Armi, Reto Stauffer, Daniel S. Wilks, Martin Weißmann, Günther Zängl, Andreas Giez and Nikolaus Umlauf and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the Atmospheric Sciences and Monthly Weather Review.

In The Last Decade

Georg J. Mayr

85 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Georg J. Mayr Austria 27 1.3k 1.1k 451 122 105 88 1.7k
Curtis R. Alexander United States 22 2.1k 1.6× 1.6k 1.5× 628 1.4× 139 1.1× 95 0.9× 56 2.4k
David Gill United States 10 2.0k 1.6× 1.7k 1.5× 534 1.2× 117 1.0× 314 3.0× 12 2.7k
Stephen S. Weygandt United States 17 2.3k 1.8× 2.1k 1.9× 514 1.1× 168 1.4× 131 1.2× 30 2.7k
Geoffrey S. Manikin United States 10 1.7k 1.4× 1.6k 1.5× 383 0.8× 147 1.2× 101 1.0× 18 2.1k
Kimberly L. Elmore United States 22 1.8k 1.4× 1.5k 1.4× 478 1.1× 97 0.8× 77 0.7× 57 2.4k
Tatiana G. Smirnova United States 18 2.6k 2.0× 2.4k 2.2× 546 1.2× 172 1.4× 144 1.4× 33 3.0k
Keith Brewster United States 23 2.4k 1.9× 2.1k 1.9× 557 1.2× 100 0.8× 128 1.2× 71 2.7k
Michael Dixon United States 14 1.4k 1.1× 1.1k 1.0× 322 0.7× 180 1.5× 95 0.9× 46 1.9k
W. R. Moninger United States 15 1.2k 0.9× 977 0.9× 271 0.6× 171 1.4× 91 0.9× 36 1.5k
Joshua P. Hacker United States 20 1.3k 1.1× 1.2k 1.1× 339 0.8× 52 0.4× 64 0.6× 50 1.6k

Countries citing papers authored by Georg J. Mayr

Since Specialization
Citations

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

Fields of papers citing papers by Georg J. Mayr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Georg J. Mayr. 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 Georg J. Mayr. The network helps show where Georg J. Mayr may publish in the future.

Co-authorship network of co-authors of Georg J. Mayr

This figure shows the co-authorship network connecting the top 25 collaborators of Georg J. Mayr. A scholar is included among the top collaborators of Georg J. Mayr 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 Georg J. Mayr. Georg J. Mayr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Zeileis, Achim, Georg J. Mayr, Thorsten Simon, et al.. (2024). Diagnosing upward lightning from tall objects from meteorological thunderstorm environments. Electric Power Systems Research. 229. 110199–110199. 1 indexed citations
3.
Mayr, Georg J., et al.. (2024). Detection and consequences of atmospheric deserts: insights from a case study. Weather and Climate Dynamics. 5(4). 1545–1560. 3 indexed citations
4.
Mayr, Georg J., et al.. (2023). Thunderstorm environments in Europe. Weather and Climate Dynamics. 4(2). 489–509. 8 indexed citations
5.
Diendorfer, Gerhard, Georg J. Mayr, Hannes Pichler, et al.. (2023). Upward Lightning at the Gaisberg Tower: The Larger‐Scale Meteorological Influence on the Triggering Mode and Flash Type. Journal of Geophysical Research Atmospheres. 128(10). e2022JD037776–e2022JD037776. 4 indexed citations
6.
Diendorfer, Gerhard, Georg J. Mayr, Hannes Pichler, et al.. (2023). Upward Lightning at Wind Turbines: Risk Assessment From Larger‐Scale Meteorology. Journal of Geophysical Research Atmospheres. 129(1). e2023JD039505–e2023JD039505. 2 indexed citations
7.
Mayr, Georg J., et al.. (2022). Predicting power ramps from joint distributions of future wind speeds. Wind energy science. 7(6). 2393–2405. 2 indexed citations
8.
Simon, Thorsten, et al.. (2022). Differentiating lightning in winter and summer with characteristics of the wind field and mass field. Weather and Climate Dynamics. 3(1). 361–375. 12 indexed citations
9.
Lerch, Sebastian, et al.. (2020). Remember the past: a comparison of time-adaptive training schemes for non-homogeneous regression. Nonlinear processes in geophysics. 27(1). 23–34. 26 indexed citations
10.
Mallaun, Christian, Andreas Giez, Georg J. Mayr, & Mathias W. Rotach. (2019). Subsiding shells and the distribution of up- and downdraughts in warm cumulus clouds over land. Atmospheric chemistry and physics. 19(15). 9769–9786. 5 indexed citations
11.
Vüllers, Jutta, Georg J. Mayr, U. Corsmeier, & Christoph Kottmeier. (2018). Characteristics and evolution of diurnal foehn events in the Dead Sea valley. Atmospheric chemistry and physics. 18(24). 18169–18186. 12 indexed citations
12.
Mallaun, Christian, Andreas Giez, Georg J. Mayr, & Mathias W. Rotach. (2018). Subsiding shells and vertical mass flux in warm cumulus clouds over land. Biogeosciences (European Geosciences Union). 2 indexed citations
13.
Simon, Thorsten, Nikolaus Umlauf, Achim Zeileis, et al.. (2017). Spatio-temporal modelling of lightning climatologies for complex terrain. Natural hazards and earth system sciences. 17(3). 305–314. 10 indexed citations
14.
Ostermann, Simon, et al.. (2015). Experiences with distributed computing for meteorological applications: grid computing and cloud computing. Geoscientific model development. 8(7). 2067–2078. 9 indexed citations
15.
Messner, Jakob W., Georg J. Mayr, Daniel S. Wilks, & Achim Zeileis. (2014). Heteroscedastic Extended Logistic Regression for Post-Processing of Ensemble Guidance. EGU General Assembly Conference Abstracts. 6639. 48 indexed citations
16.
Ostermann, Simon, et al.. (2013). The RainCloud project: Harnessing Cloud Computing for a meteorological application at the Tyrolean Avalanche Service. EGUGA. 2 indexed citations
17.
Raab, Thomas & Georg J. Mayr. (2008). Hydraulic Interpretation of the Footprints of Sierra Nevada Windstorms Tracked with an Automobile Measurement System. Journal of Applied Meteorology and Climatology. 47(10). 2581–2599. 7 indexed citations
18.
Mayr, Georg J. & Thomas B. McKee. (2007). Evolution of orogenic blocking. Digital Collections of Colorado (Colorado State University).
19.
Mayr, Georg J.. (2005). GAP FLOWS – OUR STATE OF KNOWLEDGE AT THE END OF MAP. University of Zagreb University Computing Centre (SRCE). 40(40). 6–10. 1 indexed citations
20.
Mayr, Georg J., et al.. (2002). An Automobile Platform for the Measurement of Foehn and Gap Flows. Journal of Atmospheric and Oceanic Technology. 19(10). 1545–1556. 13 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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