Emily Becker

8.1k total citations · 2 hit papers
43 papers, 4.1k citations indexed

About

Emily Becker is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Emily Becker has authored 43 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Global and Planetary Change, 32 papers in Atmospheric Science and 14 papers in Oceanography. Recurrent topics in Emily Becker's work include Climate variability and models (35 papers), Meteorological Phenomena and Simulations (28 papers) and Tropical and Extratropical Cyclones Research (13 papers). Emily Becker is often cited by papers focused on Climate variability and models (35 papers), Meteorological Phenomena and Simulations (28 papers) and Tropical and Extratropical Cyclones Research (13 papers). Emily Becker collaborates with scholars based in United States, Australia and Peru. Emily Becker's co-authors include Huug van den Dool, Qin Zhang, Malaquías Peña, Wanqiu Wang, Jesse Meng, David Behringer, Sudhir Nadiga, Mingyue Chen, Mark Iredell and Jiande Wang and has published in prestigious journals such as Nature, Journal of Climate and Geophysical Research Letters.

In The Last Decade

Emily Becker

42 papers receiving 4.1k citations

Hit Papers

The NCEP Climate Forecast System Version 2 2013 2026 2017 2021 2013 2022 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emily Becker United States 19 3.3k 3.0k 1.4k 331 326 43 4.1k
Malaquías Peña United States 16 3.5k 1.1× 3.4k 1.1× 1.4k 1.0× 357 1.1× 320 1.0× 43 4.3k
Sudhir Nadiga United States 7 3.1k 0.9× 3.0k 1.0× 1.4k 1.1× 301 0.9× 287 0.9× 9 3.9k
David Behringer United States 21 3.2k 1.0× 3.0k 1.0× 2.1k 1.6× 279 0.8× 243 0.7× 36 4.4k
Xingren Wu United States 17 2.5k 0.8× 2.9k 0.9× 1.1k 0.8× 244 0.7× 253 0.8× 41 3.6k
Shrinivas Moorthi United States 19 4.5k 1.4× 4.5k 1.5× 1.7k 1.3× 353 1.1× 305 0.9× 38 5.5k
Rein Haarsma Netherlands 41 3.5k 1.1× 3.4k 1.1× 1.5k 1.1× 164 0.5× 199 0.6× 107 4.5k
Enrico Scoccimarro Italy 35 3.3k 1.0× 2.7k 0.9× 1.2k 0.9× 187 0.6× 274 0.8× 105 4.0k
Yu-Tai Hou United States 10 2.3k 0.7× 2.3k 0.7× 901 0.7× 263 0.8× 217 0.7× 12 3.0k
Mark Iredell United States 11 2.2k 0.7× 2.4k 0.8× 976 0.7× 254 0.8× 226 0.7× 18 3.3k
Patrick Tripp United States 3 2.0k 0.6× 2.0k 0.7× 874 0.6× 226 0.7× 216 0.7× 3 2.6k

Countries citing papers authored by Emily Becker

Since Specialization
Citations

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

Fields of papers citing papers by Emily Becker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emily Becker

This figure shows the co-authorship network connecting the top 25 collaborators of Emily Becker. A scholar is included among the top collaborators of Emily Becker 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 Emily Becker. Emily Becker 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.
Sutton, Margaret, Sarah M. Larson, & Emily Becker. (2024). New insights on ENSO teleconnection asymmetry and ENSO forced atmospheric circulation variability over North America. Climate Dynamics. 62(5). 3189–3206. 3 indexed citations
2.
L’Heureux, Michelle, Emily Becker, Brian Brettschneider, et al.. (2024). How Well Do Seasonal Climate Anomalies Match Expected El Niño–Southern Oscillation (ENSO) Impacts?. Bulletin of the American Meteorological Society. 105(8). E1542–E1551. 4 indexed citations
3.
Becker, Emily, et al.. (2024). Subseasonal Variability of U.S. Coastal Sea Level from MJO and ENSO Teleconnection Interference. Weather and Forecasting. 39(2). 441–458.
4.
Tippett, Michael K. & Emily Becker. (2024). Trends, Skill, and Sources of Skill in Initialized Climate Forecasts of Global Mean Temperature. Geophysical Research Letters. 51(16). 5 indexed citations
5.
Jacox, Michael G., Michael A. Alexander, Dillon J. Amaya, et al.. (2022). Global seasonal forecasts of marine heatwaves. Nature. 604(7906). 486–490. 149 indexed citations breakdown →
6.
Pegion, Kathy, Emily Becker, & Ben P. Kirtman. (2022). Understanding Predictability of Daily Southeast U.S. Precipitation Using Explainable Machine Learning. NOAA Institutional Repository. 1(4). 10 indexed citations
7.
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
8.
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
9.
Becker, Emily, et al.. (2019). The Subseasonal Experiment (SubX): A Multi-Model Subseasonal Prediction Experiment. AGU Fall Meeting Abstracts. 2019. 2 indexed citations
10.
Wang, Shih‐Yu, et al.. (2019). Climate diagnostics of the extreme floods in Peru during early 2017. Climate Dynamics. 54(1-2). 935–945. 20 indexed citations
11.
Becker, Emily & Huug M. van den Dool. (2018). Assessing Probabilistic Forecasts of S2S Climate Extremes Using the NMME. AGU Fall Meeting Abstracts. 2018. 1 indexed citations
12.
L’Heureux, Michelle, Michael K. Tippett, K. Takahashi, et al.. (2018). Strength Outlooks for the El Niño–Southern Oscillation. Weather and Forecasting. 34(1). 165–175. 20 indexed citations
13.
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
14.
Alexander, Michael A., Charles A. Stock, Michael G. Jacox, et al.. (2017). More reliable coastal SST forecasts from the North American multimodel ensemble. Climate Dynamics. 53(12). 7153–7168. 34 indexed citations
15.
Givati, Amir, et al.. (2017). The Advantage of Using International Multimodel Ensemble for Seasonal Precipitation Forecast over Israel. Advances in Meteorology. 2017. 1–11. 11 indexed citations
16.
L’Heureux, Michelle, K. Takahashi, Andrew Watkins, et al.. (2016). Observing and Predicting the 2015/16 El Niño. Bulletin of the American Meteorological Society. 98(7). 1363–1382. 266 indexed citations
17.
Becker, Emily & Huug M. van den Dool. (2014). Probabilistic Forecasting with Nmme. AGU Fall Meeting Abstracts. 2014. 1 indexed citations
18.
Saha, Suranjana, Shrinivas Moorthi, Xingren Wu, et al.. (2013). The NCEP Climate Forecast System Version 2. Journal of Climate. 27(6). 2185–2208. 2599 indexed citations breakdown →
19.
Becker, Emily, Ernesto Hugo Berbery, & R. Wayne Higgins. (2011). Modulation of Cold-Season U.S. Daily Precipitation by the Madden–Julian Oscillation. Journal of Climate. 24(19). 5157–5166. 49 indexed citations
20.
Higgins, R. Wayne, et al.. (2010). Intercomparison of Daily Precipitation Statistics over the United States in Observations and in NCEP Reanalysis Products. Journal of Climate. 23(17). 4637–4650. 36 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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