Jay F. Shriver

4.8k total citations
81 papers, 2.6k citations indexed

About

Jay F. Shriver is a scholar working on Oceanography, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Jay F. Shriver has authored 81 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Oceanography, 58 papers in Global and Planetary Change and 24 papers in Atmospheric Science. Recurrent topics in Jay F. Shriver's work include Oceanographic and Atmospheric Processes (75 papers), Climate variability and models (56 papers) and Ocean Waves and Remote Sensing (27 papers). Jay F. Shriver is often cited by papers focused on Oceanographic and Atmospheric Processes (75 papers), Climate variability and models (56 papers) and Ocean Waves and Remote Sensing (27 papers). Jay F. Shriver collaborates with scholars based in United States, France and United Kingdom. Jay F. Shriver's co-authors include Brian K. Arbic, James G. Richman, Alan J. Wallcraft, Harley E. Hurlburt, E. Joseph Metzger, James J. O’Brien, Maarten C. Buijsman, Robert B. Scott, Patrick G. Timko and Bulusu Subrahmanyam and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Remote Sensing of Environment and Journal of Climate.

In The Last Decade

Jay F. Shriver

80 papers receiving 2.5k citations

Peers

Jay F. Shriver

OCEAN

GPC

ECOLO

GEOLO

Changming Dong China

Marie‐Hélène Rio France

G. Larnicol France

Gilles Garric France

T. K. Chereskin United States

Yannice Faugère France

Julie L. McClean United States

Edward D. Zaron United States

Jonathan Gula France

James G. Richman United States

Changming Dong China

Jay F. Shriver

2.1k ×0.9

OCEAN

1.2k ×0.8

GPC

1.0k ×1.0

191 ×1.6

ECOLO

70 ×0.8

GEOLO

Citations per year, relative to Jay F. Shriver Jay F. Shriver (= 1×) peers Changming Dong

Countries citing papers authored by Jay F. Shriver

Since Specialization

Citations

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

Fields of papers citing papers by Jay F. Shriver

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay F. Shriver. 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 Jay F. Shriver. The network helps show where Jay F. Shriver may publish in the future.

Co-authorship network of co-authors of Jay F. Shriver

This figure shows the co-authorship network connecting the top 25 collaborators of Jay F. Shriver. A scholar is included among the top collaborators of Jay F. Shriver 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 Jay F. Shriver. Jay F. Shriver is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Helber, Robert W., Scott Smith, Gleb Panteleev, & Jay F. Shriver. (2024). Freshwater runoff on the east Greenland shelf. Deep Sea Research Part II Topical Studies in Oceanography. 217. 105402–105402. 1 indexed citations

Arbic, Brian K., et al.. (2024). Phase‐Accurate Internal Tides in a Global Ocean Forecast Model: Potential Applications for Nadir and Wide‐Swath Altimetry. Geophysical Research Letters. 51(4). 7 indexed citations

Buijsman, Maarten C., et al.. (2024). Seasonal variability in the semidiurnal internal tide – a comparison between sea surface height and energetics. Ocean science. 20(5). 1187–1208. 2 indexed citations

Ansong, Joseph K., Brian K. Arbic, Arin D. Nelson, et al.. (2024). Surface and Sub‐Surface Kinetic Energy Wavenumber‐Frequency Spectra in Global Ocean Models and Observations. Journal of Geophysical Research Oceans. 129(6). 1 indexed citations

Arbic, Brian K., Shane Elipot, Dimitris Menemenlis, et al.. (2022). Near‐Surface Oceanic Kinetic Energy Distributions From Drifter Observations and Numerical Models. Journal of Geophysical Research Oceans. 127(10). 27 indexed citations

Arbic, Brian K., Paige Martin, Laurent Brodeau, et al.. (2022). Effects of grid spacing on high-frequency precipitation variance in coupled high-resolution global ocean–atmosphere models. Climate Dynamics. 59(9-10). 2887–2913. 4 indexed citations

Thoppil, Prasad G., Sergey Frolov, Clark Rowley, et al.. (2021). Ensemble forecasting greatly expands the prediction horizon for ocean mesoscale variability. Communications Earth & Environment. 2(1). 23 indexed citations

Carrère, Loren, Brian K. Arbic, Brian D. Dushaw, et al.. (2021). Accuracy assessment of global internal-tide models using satellite altimetry. Ocean science. 17(1). 147–180. 36 indexed citations

Ray, Richard D., Jean‐Paul Boy, Brian K. Arbic, et al.. (2021). The problematicΨ1 ocean tide. Geophysical Journal International. 227(2). 1181–1192. 4 indexed citations

10.

Barton, Neil P, E. Joseph Metzger, Carolyn A. Reynolds, et al.. (2020). The Navy's Earth System Prediction Capability: A New Global Coupled Atmosphere‐Ocean‐Sea Ice Prediction System Designed for Daily to Subseasonal Forecasting. Earth and Space Science. 8(4). 41 indexed citations

11.

Arbic, Brian K., James G. Richman, Jay F. Shriver, et al.. (2020). Statistical Comparisons of Temperature Variance and Kinetic Energy in Global Ocean Models and Observations: Results From Mesoscale to Internal Wave Frequencies. Journal of Geophysical Research Oceans. 125(5). 23 indexed citations

12.

Ansong, Joseph K., Brian K. Arbic, Matthew H. Alford, et al.. (2017). Semidiurnal internal tide energy fluxes and their variability in a Global Ocean Model and moored observations. Journal of Geophysical Research Oceans. 122(3). 1882–1900. 34 indexed citations

13.

Ansong, Joseph K., Brian K. Arbic, Matthew H. Alford, et al.. (2017). Semidiurnal Internal Tide Energy Fluxes and Their Variability in a Global Ocean Model and Moored Observations. Aquila Digital Community (University of Southern Mississippi). 1 indexed citations

14.

Arbic, Brian K., James G. Richman, Jay F. Shriver, et al.. (2017). The Global Mesoscale Eddy Available Potential Energy Field in Models and Observations. Journal of Geophysical Research Oceans. 122(11). 9126–9143. 29 indexed citations

15.

Savage, Anna C., Brian K. Arbic, James G. Richman, et al.. (2017). Frequency content of sea surface height variability from internal gravity waves to mesoscale eddies. Journal of Geophysical Research Oceans. 122(3). 2519–2538. 69 indexed citations

16.

Savage, Anna C., Brian K. Arbic, Matthew H. Alford, et al.. (2017). Spectral decomposition of internal gravity wave sea surface height in global models. Journal of Geophysical Research Oceans. 122(10). 7803–7821. 95 indexed citations

17.

Hurlburt, Harley E., E. Joseph Metzger, Robert C. Rhodes, et al.. (2002). An Operational Eddyresolving 1/16 Degree Global Ocean Nowcast/forecast System. EGS General Assembly Conference Abstracts. 1058. 2 indexed citations

18.

Shriver, Jay F., Robert C. Rhodes, Harley E. Hurlburt, et al.. (2001). A Real-time 1/16° Global Ocean Nowcast/Forecast System. AGUSM. 2001. 4 indexed citations

19.

Hurlburt, Harley E., Robert C. Rhodes, E. Joseph Metzger, et al.. (2001). An Operational Eddy Resolving Global Ocean Nowcast/Forecast System. AGU Fall Meeting Abstracts. 2001. 4 indexed citations

20.

Shriver, Jay F., et al.. (1999). The Effects of El Niño on Rainfall and Fire in Florida. 30. 20 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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