S. Cocke

1.5k total citations
42 papers, 853 citations indexed

About

S. Cocke is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, S. Cocke has authored 42 papers receiving a total of 853 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Atmospheric Science, 34 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in S. Cocke's work include Climate variability and models (30 papers), Meteorological Phenomena and Simulations (26 papers) and Tropical and Extratropical Cyclones Research (16 papers). S. Cocke is often cited by papers focused on Climate variability and models (30 papers), Meteorological Phenomena and Simulations (26 papers) and Tropical and Extratropical Cyclones Research (16 papers). S. Cocke collaborates with scholars based in United States, South Korea and Brazil. S. Cocke's co-authors include T. E. LaRow, D. W. Shin, T. N. Krishnamurti, James J. O’Brien, Eric P. Chassignet, Richard J. Pasch, H. S. Bedi, T. S. V. Vijaya Kumar, Jean‐Paul Pinelli and J. T. Schoof and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Climate and Geophysical Research Letters.

In The Last Decade

S. Cocke

38 papers receiving 807 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Cocke United States 17 717 701 130 121 87 42 853
Gregor Gregorič Slovenia 6 622 0.9× 604 0.9× 89 0.7× 115 1.0× 36 0.4× 15 824
Shakeel Asharaf United States 10 496 0.7× 473 0.7× 123 0.9× 159 1.3× 72 0.8× 17 673
Hsi‐Yen Ma United States 21 1.4k 2.0× 1.4k 1.9× 115 0.9× 89 0.7× 17 0.2× 56 1.5k
Ivan Güttler Croatia 13 369 0.5× 355 0.5× 76 0.6× 95 0.8× 24 0.3× 29 536
Hongxiong Xu China 17 486 0.7× 494 0.7× 85 0.7× 58 0.5× 17 0.2× 49 623
Stefano Mariani Italy 12 425 0.6× 411 0.6× 65 0.5× 83 0.7× 18 0.2× 29 612
B. LAL India 3 853 1.2× 691 1.0× 105 0.8× 133 1.1× 93 1.1× 5 939
Noriko N. Ishizaki Japan 16 743 1.0× 657 0.9× 189 1.5× 43 0.4× 43 0.5× 45 864
Evert I. F. de Bruijn Netherlands 6 984 1.4× 984 1.4× 102 0.8× 176 1.5× 39 0.4× 12 1.1k
Joel Main United States 4 543 0.8× 389 0.6× 39 0.3× 75 0.6× 67 0.8× 9 671

Countries citing papers authored by S. Cocke

Since Specialization
Citations

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

Fields of papers citing papers by S. Cocke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Cocke

This figure shows the co-authorship network connecting the top 25 collaborators of S. Cocke. A scholar is included among the top collaborators of S. Cocke 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 S. Cocke. S. Cocke 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.
Cocke, S., et al.. (2024). Unveiling the pivotal influence of sea spray heat fluxes on hurricane rapid intensification. Environmental Research Letters. 19(11). 114058–114058.
2.
Shin, D. W., S. Cocke, & Baek‐Min Kim. (2022). A Systematic Revision of the NFIP Claims Hazard Data in Florida for Flood Risk Assessment. Applied Sciences. 12(7). 3537–3537. 3 indexed citations
3.
Cocke, S., et al.. (2020). Automated Spectroscopic Detection And Mapping Using ALMA and Machine LearningTechniques. SMU Scholar (Southern Methodist University). 3(1). 12. 1 indexed citations
4.
Pinelli, Jean‐Paul, et al.. (2020). Uncertainty Reduction Through Data Management in the Development, Validation, Calibration, and Operation of a Hurricane Vulnerability Model. International Journal of Disaster Risk Science. 11(6). 790–806. 18 indexed citations
5.
Shin, D. W., S. Cocke, Guillermo A. Baigorria, et al.. (2020). Future Crop Yield Projections Using a Multi-model Set of Regional Climate Models and a Plausible Adaptation Practice in the Southeast United States. Atmosphere. 11(12). 1300–1300. 5 indexed citations
6.
Velho, Haroldo Fraga de Campos, et al.. (2016). Tracking the model: Data assimilation by artificial neural network. 403–410. 13 indexed citations
7.
Velho, Haroldo Fraga de Campos, et al.. (2015). Data assimilation by artificial neural networks for the global FSU atmospheric model: Surface pressure. 1–6. 6 indexed citations
8.
Johnson, Timothy J., Jean‐Paul Pinelli, & S. Cocke. (2015). Probabilistic treatment of storm rotation and wind-driven rain deposition in a hurricane model. Open Collections. 2 indexed citations
9.
Lim, Young‐Kwon, S. Cocke, D. W. Shin, et al.. (2009). Downscaling large-scale NCEP CFS to resolve fine-scale seasonal precipitation and extremes for the crop growing seasons over the southeastern United States. Climate Dynamics. 35(2-3). 449–471. 11 indexed citations
10.
Shin, D. W., Guillermo A. Baigorria, S. Cocke, et al.. (2009). Assessing Maize and Peanut Yield Simulations with Various Seasonal Climate Data in the Southeastern United States. Journal of Applied Meteorology and Climatology. 49(4). 592–603. 31 indexed citations
11.
Cocke, S., et al.. (2007). Articles : Assimilation of TRMM Rain Rate into Global Analysis and its Impact on the Summer Mean Circulation over Tropics. 43(4). 397–409. 1 indexed citations
12.
Shin, D. W., S. Cocke, & T. E. LaRow. (2007). Diurnal cycle of precipitation in a climate model. Journal of Geophysical Research Atmospheres. 112(D13). 18 indexed citations
13.
Cocke, S., et al.. (2006). Feasibility of Rainfall Nudging for the Improvement of Divergent Circulation in NCEP/DOE Reanalysis II over the Tropics. 한국기상학회 학술대회 논문집. 170–171.
14.
Cocke, S., et al.. (2006). The NCAR CCM as a Numerical Weather Prediction Model. Monthly Weather Review. 134(7). 1954–1971.
15.
LaRow, T. E., S. Cocke, & D. W. Shin. (2005). Multiconvective Parameterizations as a Multimodel Proxy for Seasonal Climate Studies. Journal of Climate. 18(15). 2963–2978. 8 indexed citations
16.
Nunes, Ana M. B. & S. Cocke. (2004). Implementing a physical initialization procedure in a regional spectral model: impact on the short-range rainfall forecasting over South America. Tellus A Dynamic Meteorology and Oceanography. 56(2). 125–125. 7 indexed citations
17.
Shin, D. W., S. Cocke, & T. E. LaRow. (2003). Ensemble Configurations for Typhoon Precipitation Forecasts. Journal of the Meteorological Society of Japan Ser II. 81(4). 679–696. 5 indexed citations
18.
Krishnamurti, T. N., Kusala Rajendran, T. S. V. Vijaya Kumar, et al.. (2003). Improved Skill for the Anomaly Correlation of Geopotential Heights at 500 hPa. Monthly Weather Review. 131(6). 1082–1102. 54 indexed citations
19.
Cocke, S. & T. E. LaRow. (2000). Seasonal Predictions Using a Regional Spectral Model Embedded within a Coupled Ocean–Atmosphere Model. Monthly Weather Review. 128(3). 689–708. 87 indexed citations
20.
Krishnamurti, T. N., et al.. (1984). Details of Low Latitude Medium Range Numerical Weather Prediction Using a Global Spectral Model. Journal of the Meteorological Society of Japan Ser II. 62(4). 613–649. 84 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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