Michael J. Pavolonis

3.5k total citations
73 papers, 2.3k citations indexed

About

Michael J. Pavolonis is a scholar working on Global and Planetary Change, Atmospheric Science and Artificial Intelligence. According to data from OpenAlex, Michael J. Pavolonis has authored 73 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Global and Planetary Change, 56 papers in Atmospheric Science and 10 papers in Artificial Intelligence. Recurrent topics in Michael J. Pavolonis's work include Atmospheric aerosols and clouds (43 papers), Meteorological Phenomena and Simulations (31 papers) and Atmospheric chemistry and aerosols (26 papers). Michael J. Pavolonis is often cited by papers focused on Atmospheric aerosols and clouds (43 papers), Meteorological Phenomena and Simulations (31 papers) and Atmospheric chemistry and aerosols (26 papers). Michael J. Pavolonis collaborates with scholars based in United States, Canada and Sweden. Michael J. Pavolonis's co-authors include Andrew K. Heidinger, Justin Sieglaff, John L. Cintineo, Wayne F. Feltz, Taneil Uttal, Jeffrey R. Key, Bryan A. Baum, P. W. Webley, Lee M. Cronce and Daniel T. Lindsey and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and Journal of Climate.

In The Last Decade

Michael J. Pavolonis

69 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael J. Pavolonis United States 31 1.9k 1.8k 220 209 188 73 2.3k
Jochen Kerkmann Germany 11 1.2k 0.7× 1.2k 0.7× 220 1.0× 163 0.8× 125 0.7× 15 1.6k
D. Vane United States 14 3.1k 1.6× 3.2k 1.7× 99 0.5× 121 0.6× 143 0.8× 26 3.5k
P. W. Webley United States 22 901 0.5× 1.2k 0.7× 300 1.4× 147 0.7× 387 2.1× 73 2.1k
Stefano Corradini Italy 24 975 0.5× 1.1k 0.6× 119 0.5× 90 0.4× 172 0.9× 77 1.5k
Stephen Tjemkes Germany 19 1.6k 0.8× 1.5k 0.8× 265 1.2× 186 0.9× 214 1.1× 49 2.0k
Wayne F. Feltz United States 30 2.6k 1.4× 2.7k 1.5× 338 1.5× 72 0.3× 303 1.6× 62 3.1k
Daniel T. Lindsey United States 28 1.7k 0.9× 1.5k 0.8× 214 1.0× 79 0.4× 218 1.2× 62 2.2k
Simona Scollo Italy 29 868 0.5× 1.3k 0.7× 262 1.2× 155 0.7× 85 0.5× 97 2.2k
Lazaros Oreopoulos United States 31 2.2k 1.2× 2.1k 1.1× 158 0.7× 220 1.1× 94 0.5× 105 2.5k
Kerry Meyer United States 26 2.3k 1.2× 2.1k 1.2× 123 0.6× 173 0.8× 180 1.0× 83 2.5k

Countries citing papers authored by Michael J. Pavolonis

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Pavolonis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael J. Pavolonis

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Pavolonis. A scholar is included among the top collaborators of Michael J. Pavolonis 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 Michael J. Pavolonis. Michael J. Pavolonis 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.
Crawford, Alice, Tianfeng Chai, Mark Cohen, et al.. (2025). Improving Volcanic SO 2 Cloud Modeling Through Data Fusion and Trajectory Analysis: A Case Study of the 2022 Hunga Tonga Eruption. Journal of Geophysical Research Atmospheres. 130(4).
2.
3.
Eaton, Alexa R. Van, Jeff Lapierre, Sonja A. Behnke, et al.. (2023). Lightning Rings and Gravity Waves: Insights Into the Giant Eruption Plume From Tonga's Hunga Volcano on 15 January 2022. Geophysical Research Letters. 50(12). 20 indexed citations
4.
Pavolonis, Michael J., et al.. (2023). The Development and Initial Capabilities of ThunderCast, a Deep Learning Model for Thunderstorm Nowcasting in the United States. NOAA Institutional Repository. 2(4). 1 indexed citations
5.
Crawford, Alice, Tianfeng Chai, Barbara J. B. Stunder, et al.. (2022). Evaluation and bias correction of probabilistic volcanic ash forecasts. Atmospheric chemistry and physics. 22(21). 13967–13996. 8 indexed citations
6.
Pavolonis, Michael J., et al.. (2020). Probabilistic retrieval of volcanic SO 2 layer height and partial column density using the Cross-track Infrared Sounder (CrIS). Atmospheric measurement techniques. 13(11). 5891–5921. 14 indexed citations
7.
Cintineo, John L., et al.. (2020). A Deep-Learning Model for Automated Detection of Intense Midlatitude Convection Using Geostationary Satellite Images. Weather and Forecasting. 35(6). 2567–2588. 27 indexed citations
8.
Cintineo, John L., Michael J. Pavolonis, Justin Sieglaff, Lee M. Cronce, & Jason Brunner. (2020). NOAA ProbSevere v2.0—ProbHail, ProbWind, and ProbTor. Weather and Forecasting. 35(4). 1523–1543. 44 indexed citations
9.
Gültepe, Ismail, Eric R. Pardyjak, Qing Wang, et al.. (2019). C-FOG Field Campaign for Coastal Fog: Emphases on Microphysics versus Dynamics. EGU General Assembly Conference Abstracts. 3795. 2 indexed citations
10.
Pavolonis, Michael J., Justin Sieglaff, & John L. Cintineo. (2018). Automated Detection of Explosive Volcanic Eruptions Using Satellite‐Derived Cloud Vertical Growth Rates. Earth and Space Science. 5(12). 903–928. 30 indexed citations
11.
Reath, K., M. E. Pritchard, M. P. Poland, et al.. (2017). The Powell Volcano Remote Sensing Working Group Overview. AGU Fall Meeting Abstracts. 2017. 1 indexed citations
12.
Chai, Tianfeng, Alice Crawford, Barbara J. B. Stunder, et al.. (2017). Improving volcanic ash predictions with the HYSPLIT dispersion model by assimilating MODIS satellite retrievals. Atmospheric chemistry and physics. 17(4). 2865–2879. 42 indexed citations
13.
Patra, Abani, Marcus Bursik, J. Dehn, et al.. (2013). Challenges in Developing DDDAS based Methodology for Volcanic Ash Hazard Analysis – Effect of Numerical Weather Prediction Variability and Parameter Estimation. Procedia Computer Science. 18. 1871–1880. 8 indexed citations
14.
Bursik, Marcus, R. S. J. Sparks, Andrew J. Hogg, et al.. (2013). Gravity current model of the volumetric growth of volcanic clouds: remote assessment with satellite imagery and estimation of mass eruption rate. AGU Fall Meeting Abstracts. 2013. 1 indexed citations
15.
Schneider, D. J., Christopher F. Waythomas, Kristi L. Wallace, et al.. (2013). The 2013 Eruptions of Pavlof and Mount Veniaminof Volcanoes, Alaska. AGUFM. 2013. 1 indexed citations
16.
Pavolonis, Michael J., Andrew K. Heidinger, & Justin Sieglaff. (2013). Automated retrievals of volcanic ash and dust cloud properties from upwelling infrared measurements. Journal of Geophysical Research Atmospheres. 118(3). 1436–1458. 101 indexed citations
17.
Pavolonis, Michael J.. (2010). Advances in Extracting Cloud Composition Information from Spaceborne Infrared Radiances—A Robust Alternative to Brightness Temperatures. Part I: Theory. Journal of Applied Meteorology and Climatology. 49(9). 1992–2012. 101 indexed citations
18.
Heidinger, Andrew K., Michael J. Pavolonis, Robert E. Holz, Bryan A. Baum, & S. Berthier. (2010). Using CALIPSO to explore the sensitivity to cirrus height in the infrared observations from NPOESS/VIIRS and GOES‐R/ABI. Journal of Geophysical Research Atmospheres. 115(D4). 55 indexed citations
19.
Pavolonis, Michael J. & Andrew K. Heidinger. (2005). Advancements in identifying cirrus and multilayered cloud systems from operational satellite imagers at night. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5658. 225–225. 2 indexed citations
20.
Pavolonis, Michael J., Jeffrey R. Key, & John J. Cassano. (2004). A Study of the Antarctic Surface Energy Budget Using a Polar Regional Atmospheric Model Forced with Satellite-Derived Cloud Properties. Monthly Weather Review. 132(2). 654–661. 8 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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