Scott Sandgathe

461 total citations
26 papers, 294 citations indexed

About

Scott Sandgathe is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Scott Sandgathe has authored 26 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Atmospheric Science, 18 papers in Global and Planetary Change and 8 papers in Environmental Engineering. Recurrent topics in Scott Sandgathe's work include Meteorological Phenomena and Simulations (16 papers), Climate variability and models (13 papers) and Tropical and Extratropical Cyclones Research (4 papers). Scott Sandgathe is often cited by papers focused on Meteorological Phenomena and Simulations (16 papers), Climate variability and models (13 papers) and Tropical and Extratropical Cyclones Research (4 papers). Scott Sandgathe collaborates with scholars based in United States. Scott Sandgathe's co-authors include Caren Marzban, Eugenia Kalnay, Hil Lyons, James D. Doyle, Andrew Gelman, Cavan Reilly, Phillip N. Price, Johnna M. Infanti, G. L. Geernaert and Ning Li and has published in prestigious journals such as Biometrics, Monthly Weather Review and Bulletin of the American Meteorological Society.

In The Last Decade

Scott Sandgathe

20 papers receiving 272 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Scott Sandgathe United States 8 234 215 70 26 14 26 294
Guangzhen Cao China 8 190 0.8× 215 1.0× 96 1.4× 17 0.7× 35 2.5× 30 324
P. Golé France 9 251 1.1× 158 0.7× 82 1.2× 8 0.3× 13 0.9× 21 343
C. A. F. Marques Portugal 10 169 0.7× 235 1.1× 53 0.8× 53 2.0× 15 1.1× 26 335
Martin Göber Germany 7 212 0.9× 207 1.0× 44 0.6× 14 0.5× 5 0.4× 11 281
Lizzie S. R. Froude United Kingdom 8 409 1.7× 393 1.8× 36 0.5× 34 1.3× 6 0.4× 11 448
Thomas Krennert Austria 6 285 1.2× 281 1.3× 60 0.9× 28 1.1× 6 0.4× 8 384
Sanggyun Lee South Korea 11 306 1.3× 148 0.7× 51 0.7× 50 1.9× 38 2.7× 19 415
Valentine Anantharaj United States 11 233 1.0× 214 1.0× 68 1.0× 17 0.7× 18 1.3× 41 340
John Halley Gotway United States 7 315 1.3× 300 1.4× 46 0.7× 20 0.8× 6 0.4× 12 360
David A. Unger United States 9 253 1.1× 302 1.4× 27 0.4× 65 2.5× 12 0.9× 14 351

Countries citing papers authored by Scott Sandgathe

Since Specialization
Citations

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

Fields of papers citing papers by Scott Sandgathe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Scott Sandgathe

This figure shows the co-authorship network connecting the top 25 collaborators of Scott Sandgathe. A scholar is included among the top collaborators of Scott Sandgathe 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 Scott Sandgathe. Scott Sandgathe 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.
Marzban, Caren, Robert Tardif, & Scott Sandgathe. (2020). Sensitivity Analysis of the Spatial Structure of Forecasts in Mesoscale Models: Noncontinuous Model Parameters. Monthly Weather Review. 148(4). 1717–1735.
2.
Marzban, Caren, et al.. (2018). On the effect of model parameters on forecast objects. Geoscientific model development. 11(4). 1577–1590. 3 indexed citations
3.
Sandgathe, Scott, et al.. (2018). Bridging the Gap between Climate and Weather. Bulletin of the American Meteorological Society. 99(11). ES191–ES193.
4.
Marzban, Caren, et al.. (2018). A methodology for sensitivity analysis of spatial features in forecasts: the stochastic kinetic energy backscatter scheme. Meteorological Applications. 26(3). 454–467. 4 indexed citations
5.
Clune, Thomas L., et al.. (2017). Position paper on high performance computing needs in Earth system prediction.. National Oceanic and Atmospheric Administration (NOAA) - NOAA Central Library. 2 indexed citations
6.
Eleuterio, Daniel P., G. L. Geernaert, Patrick A. Harr, et al.. (2016). The National Earth System Prediction Capability: Coordinating the Giant. Bulletin of the American Meteorological Society. 98(2). 239–252. 7 indexed citations
7.
Shafer, Mark, Cecilia M. Bitz, Andy Brown, et al.. (2015). Developing a U.S. Research Agenda to Advance Subseasonal to Seasonal Forecasting. AGU Fall Meeting Abstracts. 2015. 1 indexed citations
8.
Cornuelle, Bruce D., et al.. (2014). Issues and Challenges with Using Ensemble-Based Prediction to Probe the Weather–Climate Interface. Bulletin of the American Meteorological Society. 95(11). ES213–ES215. 2 indexed citations
9.
Marzban, Caren, Scott Sandgathe, & James D. Doyle. (2014). Model Tuning with Canonical Correlation Analysis. Monthly Weather Review. 142(5). 2018–2027. 5 indexed citations
10.
Marzban, Caren, et al.. (2014). Variance-Based Sensitivity Analysis: Preliminary Results in COAMPS. Monthly Weather Review. 142(5). 2028–2042. 7 indexed citations
11.
Sandgathe, Scott, et al.. (2013). Designing Multimodel Ensembles Requires Meaningful Methodologies. Bulletin of the American Meteorological Society. 94(12). ES183–ES185. 2 indexed citations
12.
Eleuterio, Daniel P. & Scott Sandgathe. (2012). The Earth System Prediction Capability program. 91. 1–3. 1 indexed citations
13.
Sandgathe, Scott, et al.. (2011). National Unified Operational Prediction Capability Initiative. Bulletin of the American Meteorological Society. 92(10). 1347–1351. 6 indexed citations
14.
Marzban, Caren & Scott Sandgathe. (2009). Verification with Variograms. Weather and Forecasting. 24(4). 1102–1120. 27 indexed citations
15.
Marzban, Caren, Scott Sandgathe, & Hil Lyons. (2008). An Object-Oriented Verification of Three NWP Model Formulations via Cluster Analysis: An Objective and a Subjective Analysis. Monthly Weather Review. 136(9). 3392–3407. 11 indexed citations
16.
Marzban, Caren & Scott Sandgathe. (2008). Cluster Analysis for Object-Oriented Verification of Fields: A Variation. Monthly Weather Review. 136(3). 1013–1025. 25 indexed citations
17.
Reilly, Cavan, Phillip N. Price, Andrew Gelman, & Scott Sandgathe. (2004). Using Image and Curve Registration for Measuring the Goodness of Fit of Spatial and Temporal Predictions. Biometrics. 60(4). 954–964. 7 indexed citations
18.
Sandgathe, Scott. (1987). Opportunities for Tropical Cyclone Motion Research in the Northwest Pacific Region.. 4 indexed citations
19.
Elsberry, Russell L., et al.. (1984). Short-Term Oceanic Response Predicted by a Mixed Layer Model Forced with a Sector Atmospheric Model. Journal of Physical Oceanography. 14(1). 79–91. 2 indexed citations
20.
Sandgathe, Scott. (1981). A numerical study of the role of air-sea fluxes in extratropical cyclogenesis.. Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School). 3 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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