Curtis J. Seaman

771 total citations
25 papers, 531 citations indexed

About

Curtis J. Seaman is a scholar working on Global and Planetary Change, Atmospheric Science and Aerospace Engineering. According to data from OpenAlex, Curtis J. Seaman has authored 25 papers receiving a total of 531 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Global and Planetary Change, 18 papers in Atmospheric Science and 6 papers in Aerospace Engineering. Recurrent topics in Curtis J. Seaman's work include Atmospheric Ozone and Climate (10 papers), Atmospheric and Environmental Gas Dynamics (9 papers) and Atmospheric aerosols and clouds (8 papers). Curtis J. Seaman is often cited by papers focused on Atmospheric Ozone and Climate (10 papers), Atmospheric and Environmental Gas Dynamics (9 papers) and Atmospheric aerosols and clouds (8 papers). Curtis J. Seaman collaborates with scholars based in United States, South Korea and Japan. Curtis J. Seaman's co-authors include Steven D. Miller, Daniel T. Lindsey, Donald W. Hillger, Yoo‐Jeong Noh, Thomas H. Vonder Haar, Thomas J. Kopp, Jeremy E. Solbrig, William Straka, Andrew K. Heidinger and Thomas Lee and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Scientific Reports and Bulletin of the American Meteorological Society.

In The Last Decade

Curtis J. Seaman

25 papers receiving 515 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Curtis J. Seaman United States 13 428 304 88 81 55 25 531
Thomas J. Kopp United States 9 475 1.1× 316 1.0× 94 1.1× 91 1.1× 86 1.6× 10 570
Gabriela Seiz Switzerland 13 337 0.8× 303 1.0× 107 1.2× 54 0.7× 112 2.0× 27 511
Ulrich Hamann Switzerland 10 534 1.2× 503 1.7× 77 0.9× 68 0.8× 94 1.7× 19 748
A. Sairouni Spain 11 198 0.5× 241 0.8× 82 0.9× 44 0.5× 68 1.2× 19 386
Andi Walther United States 12 825 1.9× 590 1.9× 93 1.1× 88 1.1× 88 1.6× 27 958
Leiku Yang China 15 581 1.4× 548 1.8× 80 0.9× 68 0.8× 129 2.3× 59 721
África Barreto Spain 15 571 1.3× 542 1.8× 33 0.4× 91 1.1× 59 1.1× 48 681
Frederick R. Mosher United States 10 392 0.9× 367 1.2× 47 0.5× 36 0.4× 49 0.9× 23 503
H. Le Gléau France 6 296 0.7× 248 0.8× 56 0.6× 31 0.4× 43 0.8× 7 382
Harumi Isaka France 16 448 1.0× 362 1.2× 97 1.1× 40 0.5× 85 1.5× 41 554

Countries citing papers authored by Curtis J. Seaman

Since Specialization
Citations

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

Fields of papers citing papers by Curtis J. Seaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Curtis J. Seaman

This figure shows the co-authorship network connecting the top 25 collaborators of Curtis J. Seaman. A scholar is included among the top collaborators of Curtis J. Seaman 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 Curtis J. Seaman. Curtis J. Seaman 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.
Rogers, Matthew A., et al.. (2023). VIIRS after 10 Years—A Perspective on Benefits to Forecasters and End-Users. Remote Sensing. 15(4). 976–976. 5 indexed citations
2.
Seaman, Curtis J., et al.. (2023). Multispectral Satellite Imagery Products for Fire Weather Applications. Journal of Atmospheric and Oceanic Technology. 40(6). 719–738. 2 indexed citations
3.
Hillger, Donald W., et al.. (2022). Ten Years of VIIRS EDR Imagery Validation and User Interactions. Remote Sensing. 14(17). 4167–4167. 5 indexed citations
4.
Noh, Yoo‐Jeong, John M. Haynes, Steven D. Miller, et al.. (2022). A Framework for Satellite-Based 3D Cloud Data: An Overview of the VIIRS Cloud Base Height Retrieval and User Engagement for Aviation Applications. Remote Sensing. 14(21). 5524–5524. 12 indexed citations
5.
6.
Miller, Steven D., Steven H. D. Haddock, William Straka, et al.. (2021). Honing in on bioluminescent milky seas from space. Scientific Reports. 11(1). 15443–15443. 14 indexed citations
7.
Straka, William, Ivan Csiszar, Shobha Kondragunta, et al.. (2021). Satellite Fire Products: More Valuable Now Than Ever with Longer Fire Seasons. 699–702. 1 indexed citations
8.
Miller, Steven D., Daniel T. Lindsey, Curtis J. Seaman, & Jeremy E. Solbrig. (2020). GeoColor: A Blending Technique for Satellite Imagery. Journal of Atmospheric and Oceanic Technology. 37(3). 429–448. 19 indexed citations
9.
Miller, Steven D., William Straka, Jia Yue, et al.. (2018). The Dark Side of Hurricane Matthew: Unique Perspectives from the VIIRS Day/Night Band. Bulletin of the American Meteorological Society. 99(12). 2561–2574. 21 indexed citations
10.
Seaman, Curtis J., Yoo‐Jeong Noh, Steven D. Miller, Andrew K. Heidinger, & Daniel T. Lindsey. (2017). Cloud-Base Height Estimation from VIIRS. Part I: Operational Algorithm Validation against CloudSat. Journal of Atmospheric and Oceanic Technology. 34(3). 567–583. 25 indexed citations
11.
Seaman, Curtis J., et al.. (2017). Visible Infrared Imaging Radiometer Suite (VIIRS) Imagery Environmental Data Record (EDR) user's guide. Version 1.3. National Oceanic and Atmospheric Administration (NOAA) - NOAA Central Library. 9 indexed citations
12.
Noh, Yoo‐Jeong, J. M. Forsythe, Steven D. Miller, et al.. (2016). Cloud-Base Height Estimation from VIIRS. Part II: A Statistical Algorithm Based on A-Train Satellite Data. Journal of Atmospheric and Oceanic Technology. 34(3). 585–598. 45 indexed citations
13.
Hillger, Donald W., Curtis J. Seaman, Steven D. Miller, et al.. (2015). User Validation of VIIRS Satellite Imagery. Remote Sensing. 8(1). 11–11. 11 indexed citations
14.
15.
Hillger, Donald W., et al.. (2014). Suomi NPP VIIRS Imagery evaluation. Journal of Geophysical Research Atmospheres. 119(11). 6440–6455. 31 indexed citations
16.
Hillger, Donald W., Thomas J. Kopp, Thomas Lee, et al.. (2013). First-Light Imagery from Suomi NPP VIIRS. Bulletin of the American Meteorological Society. 1089512689–1089512689. 136 indexed citations
17.
Seaman, Curtis J. & Steven D. Miller. (2013). VIIRS Captures Aurora Motions. Bulletin of the American Meteorological Society. 94(10). 1491–1493. 7 indexed citations
18.
Noh, Yoo‐Jeong, Curtis J. Seaman, Thomas H. Vonder Haar, David Hudak, & Peter Rodriguez. (2011). Comparisons and analyses of aircraft and satellite observations for wintertime mixed-phase clouds. Journal of Geophysical Research Atmospheres. 116(D18). 28 indexed citations
19.
Seaman, Curtis J., Manajit Sengupta, & Thomas H. Vonder Haar. (2010). Mesoscale satellite data assimilation: impact of cloud-affected infrared observations on a cloud-free initial model state. Tellus A Dynamic Meteorology and Oceanography. 62(3). 298–318. 12 indexed citations
20.
Seaman, Curtis J., Manajit Sengupta, & Thomas H. Vonder Haar. (2010). Mesoscale satellite data assimilation: impact of cloud-affected infrared observations on a cloud-free initial model state. Tellus A Dynamic Meteorology and Oceanography. 10 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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