Dan C. Collins

1.6k total citations
21 papers, 920 citations indexed

About

Dan C. Collins is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Dan C. Collins has authored 21 papers receiving a total of 920 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Global and Planetary Change, 14 papers in Atmospheric Science and 3 papers in Oceanography. Recurrent topics in Dan C. Collins's work include Climate variability and models (15 papers), Meteorological Phenomena and Simulations (13 papers) and Atmospheric and Environmental Gas Dynamics (4 papers). Dan C. Collins is often cited by papers focused on Climate variability and models (15 papers), Meteorological Phenomena and Simulations (13 papers) and Atmospheric and Environmental Gas Dynamics (4 papers). Dan C. Collins collaborates with scholars based in United States, Australia and Malaysia. Dan C. Collins's co-authors include Michelle L’Heureux, Roni Avissar, Nathaniel C. Johnson, Emily E. Riddle, Steven B. Feldstein, Zeng‐Zhen Hu, Emily Becker, Jean‐Michel Perraud, Adam Smith and Brent Henderson and has published in prestigious journals such as Journal of Climate, Journal of Hydrology and Monthly Weather Review.

In The Last Decade

Dan C. Collins

21 papers receiving 903 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dan C. Collins United States 11 742 664 230 176 95 21 920
Gregor Gregorič Slovenia 6 622 0.8× 604 0.9× 89 0.4× 115 0.7× 66 0.7× 15 824
J. Steppeler Germany 9 621 0.8× 711 1.1× 102 0.4× 143 0.8× 81 0.9× 29 934
Cheng‐Shang Lee Taiwan 22 926 1.2× 1.0k 1.5× 361 1.6× 129 0.7× 86 0.9× 56 1.2k
H. Douville France 13 635 0.9× 529 0.8× 188 0.8× 254 1.4× 270 2.8× 14 908
G. Doms Germany 4 572 0.8× 601 0.9× 84 0.4× 107 0.6× 79 0.8× 6 784
S. Cocke United States 17 717 1.0× 701 1.1× 130 0.6× 121 0.7× 39 0.4× 42 853
Michel Desgagné Canada 11 552 0.7× 645 1.0× 71 0.3× 120 0.7× 86 0.9× 15 851
Matthias Raschendorfer Germany 5 830 1.1× 855 1.3× 44 0.2× 174 1.0× 65 0.7× 7 1.0k
Stefano Mariani Italy 12 425 0.6× 411 0.6× 65 0.3× 83 0.5× 70 0.7× 29 612
Koyuru Iwanami Japan 14 824 1.1× 1.5k 2.2× 78 0.3× 497 2.8× 170 1.8× 64 1.6k

Countries citing papers authored by Dan C. Collins

Since Specialization
Citations

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

Fields of papers citing papers by Dan C. Collins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dan C. Collins. 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 Dan C. Collins. The network helps show where Dan C. Collins may publish in the future.

Co-authorship network of co-authors of Dan C. Collins

This figure shows the co-authorship network connecting the top 25 collaborators of Dan C. Collins. A scholar is included among the top collaborators of Dan C. Collins 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 Dan C. Collins. Dan C. Collins 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.
Robertson, Andrew W., Michael K. Tippett, Rémi Cousin, et al.. (2023). A Multimodel Real-Time System for Global Probabilistic Subseasonal Forecasts of Precipitation and Temperature. Weather and Forecasting. 38(6). 921–935. 4 indexed citations
2.
3.
Mariotti, Annarita, Cory Baggett, Elizabeth A. Barnes, et al.. (2020). Windows of Opportunity for Skillful Forecasts Subseasonal to Seasonal and Beyond. Bulletin of the American Meteorological Society. 101(5). E608–E625. 189 indexed citations
4.
Mariotti, Annarita, Cory Baggett, Elizabeth A. Barnes, et al.. (2020). Forecasts of Opportunity: Opening Windows of Skill, Subseasonal and Beyond. Bulletin of the American Meteorological Society. 101(7). 597–601. 3 indexed citations
5.
Richter, Jadwiga H., Kathy Pegion, Lantao Sun, et al.. (2020). Subseasonal Prediction with and without a Well-Represented Stratosphere in CESM1. Weather and Forecasting. 35(6). 2589–2602. 19 indexed citations
6.
Becker, Emily, et al.. (2019). The Subseasonal Experiment (SubX): A Multi-Model Subseasonal Prediction Experiment. AGU Fall Meeting Abstracts. 2019. 2 indexed citations
7.
Strazzo, Sarah, Dan C. Collins, Andrew Schepen, et al.. (2018). Application of a Hybrid Statistical–Dynamical System to Seasonal Prediction of North American Temperature and Precipitation. Monthly Weather Review. 147(2). 607–625. 60 indexed citations
8.
9.
Collins, Dan C., et al.. (2016). Sensitivity of Calibrated Week-2 Probabilistic Forecast Skill to Reforecast Sampling of the NCEP Global Ensemble Forecast System. Weather and Forecasting. 31(4). 1093–1107. 4 indexed citations
10.
Collins, Dan C., et al.. (2015). Contribution of phenology and soil moisture to atmospheric variability in ECHAM5/JSBACH model. Climate Dynamics. 45(9-10). 2329–2336. 8 indexed citations
11.
Renzullo, Luigi J., Albert I. J. M. van Dijk, Jean‐Michel Perraud, et al.. (2014). Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment. Journal of Hydrology. 519. 2747–2762. 120 indexed citations
12.
Liu, Yunyun, Zeng‐Zhen Hu, Arun Kumar, et al.. (2014). Tropospheric biennial oscillation of summer monsoon rainfall over East Asia and its association with ENSO. Climate Dynamics. 45(7-8). 1747–1759. 15 indexed citations
13.
Johnson, Nathaniel C., Dan C. Collins, Steven B. Feldstein, Michelle L’Heureux, & Emily E. Riddle. (2013). Skillful Wintertime North American Temperature Forecasts out to 4 Weeks Based on the State of ENSO and the MJO*. Weather and Forecasting. 29(1). 23–38. 85 indexed citations
14.
Riddle, Emily E., et al.. (2012). The impact of the MJO on clusters of wintertime circulation anomalies over the North American region. Climate Dynamics. 40(7-8). 1749–1766. 128 indexed citations
15.
L’Heureux, Michelle, Dan C. Collins, & Zeng‐Zhen Hu. (2012). Linear trends in sea surface temperature of the tropical Pacific Ocean and implications for the El Niño-Southern Oscillation. Climate Dynamics. 40(5-6). 1223–1236. 100 indexed citations
16.
Unger, David A., Huug van den Dool, Edward A. O’Lenic, & Dan C. Collins. (2009). Ensemble Regression. Monthly Weather Review. 137(7). 2365–2379. 39 indexed citations
17.
Corrigan, Robert M. & Dan C. Collins. (2004). The possible effects of bait container design on mouse feeding activity in real-world structural baiting situations. eScholarship (California Digital Library). 21(21). 1 indexed citations
18.
Collins, Dan C., C. J. C. Reason, & Fredolin Tangang. (2004). Predictability of Indian Ocean sea surface temperature using canonical correlation analysis. Climate Dynamics. 22(5). 481–497. 33 indexed citations
19.
Collins, Dan C., et al.. (1995). Environmental water flows. 1995. 241–277. 2 indexed citations
20.
Collins, Dan C. & Roni Avissar. (1994). An Evaluation with the Fourier Amplitude Sensitivity Test (FAST) of Which Land-Surface Parameters Are of Greatest Importance in Atmospheric Modeling. Journal of Climate. 7(5). 681–703. 97 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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