Katherine Dagon

1.0k total citations
21 papers, 432 citations indexed

About

Katherine Dagon is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, Katherine Dagon has authored 21 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Global and Planetary Change, 16 papers in Atmospheric Science and 3 papers in Water Science and Technology. Recurrent topics in Katherine Dagon's work include Climate Change and Geoengineering (9 papers), Climate variability and models (8 papers) and Atmospheric Ozone and Climate (8 papers). Katherine Dagon is often cited by papers focused on Climate Change and Geoengineering (9 papers), Climate variability and models (8 papers) and Atmospheric Ozone and Climate (8 papers). Katherine Dagon collaborates with scholars based in United States, United Kingdom and China. Katherine Dagon's co-authors include Daniel P. Schrag, Simone Tilmes, J. B. Marston, Jadwiga H. Richter, Steven M. Tobias, Ben Kravitz, Wei Cheng, Isla R. Simpson, David M. Lawrence and Douglas G. MacMartin and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Astrophysical Journal and Journal of Climate.

In The Last Decade

Katherine Dagon

19 papers receiving 426 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katherine Dagon United States 12 341 258 80 31 30 21 432
S. V. Kostrykin Russia 11 536 1.6× 483 1.9× 27 0.3× 21 0.7× 14 0.5× 35 621
A. Kalimeris Greece 11 186 0.5× 132 0.5× 107 1.3× 10 0.3× 10 0.3× 24 358
Pablo O. Canziani Argentina 16 414 1.2× 454 1.8× 156 1.9× 7 0.2× 13 0.4× 61 650
Gabriela Aznar–Siguán Spain 10 145 0.4× 81 0.3× 197 2.5× 21 0.7× 17 0.6× 11 426
Martin S. Singh Australia 18 801 2.3× 769 3.0× 38 0.5× 14 0.5× 8 0.3× 40 892
Julio C. Maŕın Chile 12 199 0.6× 250 1.0× 56 0.7× 7 0.2× 27 0.9× 36 381
Longtao Wu United States 15 626 1.8× 697 2.7× 52 0.7× 13 0.4× 32 1.1× 40 792
Anne-Laure Collard France 11 399 1.2× 437 1.7× 208 2.6× 20 0.6× 2 0.1× 25 635
J. S. Boyle United States 9 753 2.2× 698 2.7× 53 0.7× 39 1.3× 13 0.4× 9 850
Naomi Goldenson United States 11 257 0.8× 226 0.9× 36 0.5× 64 2.1× 10 0.3× 20 370

Countries citing papers authored by Katherine Dagon

Since Specialization
Citations

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

Fields of papers citing papers by Katherine Dagon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katherine Dagon

This figure shows the co-authorship network connecting the top 25 collaborators of Katherine Dagon. A scholar is included among the top collaborators of Katherine Dagon 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 Katherine Dagon. Katherine Dagon 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.
Ullrich, Paul, Elizabeth A. Barnes, William D. Collins, et al.. (2025). Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models. SHILAP Revista de lepidopterología. 2(1). 3 indexed citations
3.
4.
Kennedy, Daniel, Katherine Dagon, David M. Lawrence, et al.. (2024). Land Processes Can Substantially Impact the Mean Climate State. Geophysical Research Letters. 51(21). 5 indexed citations
5.
Pokhrel, Yadu, Ben Livneh, Lifeng Luo, et al.. (2024). Toward Understanding Parametric Controls on Runoff Sensitivity to Climate in the Community Land Model: A Case Study Over the Colorado River Headwaters. Water Resources Research. 60(12). 2 indexed citations
6.
Touma, Danielle, James W. Hurrell, Mari R. Tye, & Katherine Dagon. (2023). The Impact of Stratospheric Aerosol Injection on Extreme Fire Weather Risk. Earth s Future. 11(6). 6 indexed citations
7.
Molina, María J., Jadwiga H. Richter, Anne A. Glanville, et al.. (2023). Subseasonal Representation and Predictability of North American Weather Regimes Using Cluster Analysis. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2(2). 9 indexed citations
8.
Dagon, Katherine, et al.. (2022). Machine Learning‐Based Detection of Weather Fronts and Associated Extreme Precipitation in Historical and Future Climates. Journal of Geophysical Research Atmospheres. 127(21). 11 indexed citations
9.
Cheng, Yifan, K. N. Musselman, Sean Swenson, et al.. (2022). Moving Land Models Toward More Actionable Science: A Novel Application of the Community Terrestrial Systems Model Across Alaska and the Yukon River Basin. Water Resources Research. 59(1). 12 indexed citations
10.
Tye, Mari R., Katherine Dagon, María J. Molina, et al.. (2022). Indices of extremes: geographic patterns of change in extremes and associated vegetation impacts under climate intervention. Earth System Dynamics. 13(3). 1233–1257. 32 indexed citations
11.
12.
Xu, Yangyang, Lei Lin, Simone Tilmes, et al.. (2020). Climate engineering to mitigate the projected 21st-century terrestrial drying of the Americas: a direct comparison of carbon capture and sulfur injection. Earth System Dynamics. 11(3). 673–695. 15 indexed citations
13.
Dagon, Katherine, Benjamin M. Sanderson, Rosie A. Fisher, & David M. Lawrence. (2020). A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5. SHILAP Revista de lepidopterología. 6(2). 223–244. 46 indexed citations
14.
Kravitz, Ben, Douglas G. MacMartin, Simone Tilmes, et al.. (2019). Comparing Surface and Stratospheric Impacts of Geoengineering With Different SO2 Injection Strategies. Journal of Geophysical Research Atmospheres. 124(14). 7900–7918. 71 indexed citations
15.
Kravitz, Ben, Douglas G. MacMartin, Simone Tilmes, et al.. (2019). Comparing surface and stratospheric impacts of geoengineering with different SO 2 injection strategies. AGU Fall Meeting Abstracts. 2019. 4 indexed citations
16.
Cheng, Wei, Douglas G. MacMartin, Katherine Dagon, et al.. (2019). Soil Moisture and Other Hydrological Changes in a Stratospheric Aerosol Geoengineering Large Ensemble. Journal of Geophysical Research Atmospheres. 124(23). 12773–12793. 49 indexed citations
17.
Dagon, Katherine & Daniel P. Schrag. (2019). Quantifying the effects of solar geoengineering on vegetation. Climatic Change. 153(1-2). 235–251. 29 indexed citations
18.
Dagon, Katherine & Daniel P. Schrag. (2017). Regional Climate Variability Under Model Simulations of Solar Geoengineering. Journal of Geophysical Research Atmospheres. 122(22). 18 indexed citations
19.
Dagon, Katherine & Daniel P. Schrag. (2016). Exploring the Effects of Solar Radiation Management on Water Cycling in a Coupled Land–Atmosphere Model*. Journal of Climate. 29(7). 2635–2650. 33 indexed citations
20.
Tobias, Steven M., Katherine Dagon, & J. B. Marston. (2011). ASTROPHYSICAL FLUID DYNAMICS VIA DIRECT STATISTICAL SIMULATION. The Astrophysical Journal. 727(2). 127–127. 55 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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