George S. Young

18.3k total citations · 2 hit papers
140 papers, 5.3k citations indexed

About

George S. Young is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, George S. Young has authored 140 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Atmospheric Science, 65 papers in Global and Planetary Change and 33 papers in Oceanography. Recurrent topics in George S. Young's work include Meteorological Phenomena and Simulations (70 papers), Climate variability and models (48 papers) and Wind and Air Flow Studies (29 papers). George S. Young is often cited by papers focused on Meteorological Phenomena and Simulations (70 papers), Climate variability and models (48 papers) and Wind and Air Flow Studies (29 papers). George S. Young collaborates with scholars based in United States, Tunisia and Canada. George S. Young's co-authors include C. W. Fairall, James B. Edson, E. F. Bradley, David P. Rogers, Sue Ellen Haupt, J. S. Godfrey, Gary A. Wick, Todd D. Sikora, William M. Frank and Richard H. Johnson and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Renewable and Sustainable Energy Reviews and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

George S. Young

134 papers receiving 5.0k citations

Hit Papers

Bulk parameterization of air‐sea fluxes for Tropical Ocea... 1996 2026 2006 2016 1996 1996 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
George S. Young United States 33 3.5k 3.0k 2.6k 738 319 140 5.3k
Philippe Drobinski France 39 3.1k 0.9× 3.4k 1.1× 578 0.2× 883 1.2× 262 0.8× 175 4.5k
Dick Dee United Kingdom 40 6.0k 1.7× 6.0k 2.0× 1.6k 0.6× 903 1.2× 223 0.7× 80 7.6k
Yign Noh South Korea 25 7.0k 2.0× 6.1k 2.1× 1.6k 0.6× 1.4k 1.9× 255 0.8× 75 8.1k
O. Gill United States 5 7.0k 2.0× 5.9k 2.0× 903 0.3× 1.7k 2.4× 406 1.3× 7 8.5k
B. Klemp 3 7.0k 2.0× 5.9k 2.0× 903 0.3× 1.7k 2.4× 406 1.3× 4 8.5k
Laurent Bertino Norway 35 2.9k 0.8× 2.0k 0.7× 2.0k 0.8× 506 0.7× 101 0.3× 126 4.4k
Fedor Mesinger United States 20 3.7k 1.1× 3.6k 1.2× 879 0.3× 572 0.8× 114 0.4× 48 5.1k
Clayton A. Paulson United States 28 2.7k 0.8× 2.4k 0.8× 2.4k 0.9× 552 0.7× 126 0.4× 69 4.3k
Stuart D. Smith Canada 34 3.5k 1.0× 1.7k 0.6× 3.4k 1.3× 363 0.5× 182 0.6× 78 5.5k
Xiang‐Yu Huang China 25 8.9k 2.5× 7.6k 2.5× 1.3k 0.5× 2.0k 2.8× 756 2.4× 103 10.9k

Countries citing papers authored by George S. Young

Since Specialization
Citations

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

Fields of papers citing papers by George S. Young

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of George S. Young

This figure shows the co-authorship network connecting the top 25 collaborators of George S. Young. A scholar is included among the top collaborators of George S. Young 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 George S. Young. George S. Young 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.
Lee, Jared A., et al.. (2024). Identifying wind regimes near Kuwait using self-organizing maps. Journal of Renewable and Sustainable Energy. 16(2).
2.
Li, Jia, et al.. (2023). A Machine Learning Paradigm for Studying Pictorial Realism: How Accurate are Constable's Clouds?. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(1). 33–42. 3 indexed citations
3.
Hu, Weiming, Guido Cervone, George S. Young, & Luca Delle Monache. (2023). Machine Learning Weather Analogs for Near-Surface Variables. Boundary-Layer Meteorology. 186(3). 711–735. 4 indexed citations
4.
Stensrud, David J., George S. Young, & Matthew R. Kumjian. (2022). Wide Horizontal Convective Rolls over Land. Monthly Weather Review. 150(11). 2999–3010. 2 indexed citations
5.
Markowski, Paul, et al.. (2020). The Orinoco Low‐Level Jet: An Investigation of Its Mechanisms of Formation Using the WRF Model. Journal of Geophysical Research Atmospheres. 125(13). 17 indexed citations
6.
Greybush, Steven J., et al.. (2019). Lake-Effect Snowbands in Baroclinic Environments. Weather and Forecasting. 34(6). 1657–1674. 6 indexed citations
7.
Bieringer, Paul E., et al.. (2017). Paradigms and commonalities in atmospheric source term estimation methods. Atmospheric Environment. 156. 102–112. 36 indexed citations
8.
Hanna, Steven R. & George S. Young. (2016). The need for harmonization of methods for finding locations and magnitudes of air pollution sources using observations of concentrations and wind fields. Atmospheric Environment. 148. 361–363. 6 indexed citations
9.
McCandless, Tyler, Sue Ellen Haupt, & George S. Young. (2011). The Effects of Imputing Missing Data on Ensemble Temperature Forecasts. Journal of Computers. 6(2). 13 indexed citations
10.
Young, George S., et al.. (2002). Measurements Of Thermal Updraft Intensity Over Complex Terrain Using American White Pelicans And A Simple Boundary-Layer Forecast Model. Boundary-Layer Meteorology. 104(2). 167–199. 32 indexed citations
11.
Young, George S.. (2000). SAR Signatures of the Marine Atmospheric Boundary Layer: Implications for Numerical Forecasting. Johns Hopkins APL technical digest. 21(1). 27–32. 4 indexed citations
12.
Young, George S., et al.. (2000). Observations of the Entrainment Zone in a Rapidly Entraining Boundary Layer. Journal of the Atmospheric Sciences. 57(18). 3145–3160. 14 indexed citations
13.
Young, George S., et al.. (1996). Use of obliquely rotated principal component analysis to identify coherent structures. Boundary-Layer Meteorology. 80(1-2). 19–47. 3 indexed citations
14.
Fairall, C. W., E. F. Bradley, J. S. Godfrey, et al.. (1996). Cool‐skin and warm‐layer effects on sea surface temperature. Journal of Geophysical Research Atmospheres. 101(C1). 1295–1308. 649 indexed citations breakdown →
15.
Young, George S., et al.. (1993). Buoyant Forcing within the Marine Stratocumulus-topped Boundary Layer. Journal of the Atmospheric Sciences. 50(16). 2759–2771. 9 indexed citations
16.
Arritt, Raymond W., James M. Wilczak, & George S. Young. (1992). Observations and Numerical Modeling of an Elevated Mixed Layer. Monthly Weather Review. 120(12). 2869–2880. 20 indexed citations
17.
Sturm, James T., Daniel Hankins, & George S. Young. (1990). Thoracic aortography following blunt chest trauma. The American Journal of Emergency Medicine. 8(2). 92–96. 43 indexed citations
18.
Young, George S.. (1988). Turbulence Structure of the Convective Boundary Layer. Part I. Variability of Normalized Turbulence Statistics. Journal of the Atmospheric Sciences. 45(4). 719–726. 52 indexed citations
19.
Young, George S.. (1986). The Dynamics of Thermals and Their Contribution to Mixed Layer Processes. Digital Collections of Colorado (Colorado State University). 2 indexed citations
20.
Johnson, Richard H. & George S. Young. (1983). Heat and Moisture Budgets of Tropical Mesoscale Anvil Clouds. Journal of the Atmospheric Sciences. 40(9). 2138–2147. 74 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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