Scott Collis

2.4k total citations · 1 hit paper
52 papers, 1.3k citations indexed

About

Scott Collis is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Scott Collis has authored 52 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Atmospheric Science, 24 papers in Global and Planetary Change and 12 papers in Environmental Engineering. Recurrent topics in Scott Collis's work include Meteorological Phenomena and Simulations (29 papers), Precipitation Measurement and Analysis (18 papers) and Climate variability and models (14 papers). Scott Collis is often cited by papers focused on Meteorological Phenomena and Simulations (29 papers), Precipitation Measurement and Analysis (18 papers) and Climate variability and models (14 papers). Scott Collis collaborates with scholars based in United States, Australia and Germany. Scott Collis's co-authors include Jonathan Helmus, Alain Protat, Scott Giangrande, Christopher R. Williams, Pavlos Kollias, Ann M. Fridlind, Jiwen Fan, Andrew S. Ackerman, Joe Khachan and Robert Jackson and has published in prestigious journals such as Monthly Weather Review, Atmospheric chemistry and physics and Bulletin of the American Meteorological Society.

In The Last Decade

Scott Collis

50 papers receiving 1.3k citations

Hit Papers

The Python ARM Radar Toolkit (Py-ART), a Library for Work... 2016 2026 2019 2022 2016 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Scott Collis United States 20 1.0k 845 199 87 76 52 1.3k
Michael Baldauf Germany 12 1.5k 1.4× 1.3k 1.5× 225 1.1× 86 1.0× 42 0.6× 41 1.8k
Mario Montopoli Italy 25 1.3k 1.2× 667 0.8× 447 2.2× 121 1.4× 27 0.4× 111 1.6k
Jussi Leinonen United States 22 1.2k 1.1× 821 1.0× 177 0.9× 24 0.3× 33 0.4× 41 1.4k
Ricardo Todling United States 22 1.7k 1.6× 1.5k 1.8× 258 1.3× 80 0.9× 59 0.8× 57 1.9k
M. Corazza Italy 12 996 1.0× 903 1.1× 210 1.1× 25 0.3× 94 1.2× 21 1.2k
Andreas Macke Germany 23 1.7k 1.6× 1.8k 2.2× 117 0.6× 76 0.9× 223 2.9× 31 2.3k
Alan Geer United Kingdom 27 2.5k 2.4× 2.1k 2.5× 243 1.2× 93 1.1× 89 1.2× 72 2.7k
Jon Reisner United States 20 1.5k 1.4× 1.6k 1.9× 219 1.1× 91 1.0× 14 0.2× 64 2.2k
D. J. Patil United States 13 1.4k 1.3× 1.2k 1.5× 282 1.4× 45 0.5× 117 1.5× 20 1.6k
K. Franklin Evans United States 27 2.0k 1.9× 2.0k 2.4× 196 1.0× 112 1.3× 160 2.1× 59 2.5k

Countries citing papers authored by Scott Collis

Since Specialization
Citations

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

Fields of papers citing papers by Scott Collis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Scott Collis

This figure shows the co-authorship network connecting the top 25 collaborators of Scott Collis. A scholar is included among the top collaborators of Scott Collis 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 Scott Collis. Scott Collis 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.
Muradyan, Paytsar, Maxwell Grover, Joseph J. O’Brien, et al.. (2025). The Chicago Urban Flux Network with Perspectives from an Eddy Covariance Workshop. Bulletin of the American Meteorological Society. 106(8). E1724–E1730. 1 indexed citations
2.
Sankaran, Rajesh, et al.. (2024). Acoustic fingerprints in nature: A self-supervised learning approach for ecosystem activity monitoring. Ecological Informatics. 83. 102823–102823. 3 indexed citations
3.
Jones, William K., Julia Kukulies, Fabian Senf, et al.. (2024). tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena. Geoscientific model development. 17(13). 5309–5330. 12 indexed citations
4.
Muradyan, Paytsar, Rajesh Sankaran, Robert Jackson, et al.. (2023). Optimizing cloud motion estimation on the edge with phase correlation and optical flow. Atmospheric measurement techniques. 16(5). 1195–1209. 5 indexed citations
6.
Silber, Israel, Robert Jackson, Ann M. Fridlind, et al.. (2022). The Earth Model Column Collaboratory (EMC 2 ) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models. Geoscientific model development. 15(2). 901–927. 11 indexed citations
7.
Jackson, Robert, Scott Collis, Valentin Louf, et al.. (2021). The development of rainfall retrievals from radar at Darwin. Atmospheric measurement techniques. 14(1). 53–69. 4 indexed citations
9.
Kollias, Pavlos, Nitin Bharadwaj, E. E. Clothiaux, et al.. (2020). Leading Edge Radar: The Upgraded ARM Network. Bulletin of the American Meteorological Society. 101(8). 703–708. 2 indexed citations
10.
Kollias, Pavlos, Nitin Bharadwaj, Eugene E. Clothiaux, et al.. (2019). The ARM Radar Network: At the Leading Edge of Cloud and Precipitation Observations. Bulletin of the American Meteorological Society. 101(5). E588–E607. 52 indexed citations
11.
Fridlind, Ann M., Marcus van Lier‐Walqui, Scott Collis, et al.. (2019). Use of polarimetric radar measurements to constrain simulated convective cell evolution: a pilot study with Lagrangian tracking. Atmospheric measurement techniques. 12(6). 2979–3000. 25 indexed citations
12.
Jackson, Robert, Scott Collis, Timothy J. Lang, Corey K. Potvin, & Todd Munson. (2019). PyDDA: A new Pythonic Wind Retrieval Package. Proceedings of the Python in Science Conferences. 111–117. 3 indexed citations
13.
Jackson, Robert, et al.. (2018). A 17 year climatology of convective cloud top heights in Darwin. 1 indexed citations
14.
Jackson, Robert, et al.. (2018). A 17 year climatology of the macrophysical properties of convection in Darwin. Atmospheric chemistry and physics. 18(23). 17687–17704. 10 indexed citations
15.
North, Kirk, Mariko Oue, Pavlos Kollias, et al.. (2017). Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E. Atmospheric measurement techniques. 10(8). 2785–2806. 34 indexed citations
16.
Collis, Scott & Jonathan Helmus. (2015). Using the Scientific Python ecosystem to advance open radar science. AGU Fall Meeting Abstracts. 2015. 1 indexed citations
17.
Heistermann, Maik, et al.. (2015). An Open Virtual Machine for Cross-Platform Weather Radar Science. Bulletin of the American Meteorological Society. 96(10). 1641–1645. 5 indexed citations
18.
Collis, Scott, et al.. (2013). Quantitative rainfall metrics for comparing volumetric rainfall retrievals to fine scale models. EGUGA. 1 indexed citations
19.
Collis, Scott, Alain Protat, Peter T. May, & Christopher R. Williams. (2013). Statistics of Storm Updraft Velocities from TWP-ICE Including Verification with Profiling Measurements. Journal of Applied Meteorology and Climatology. 52(8). 1909–1922. 52 indexed citations
20.
Giangrande, Scott, Scott Collis, Jerry M. Straka, et al.. (2013). A Summary of Convective-Core Vertical Velocity Properties Using ARM UHF Wind Profilers in Oklahoma. Journal of Applied Meteorology and Climatology. 52(10). 2278–2295. 74 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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