Chris Snyder

14.6k total citations · 1 hit paper
130 papers, 9.8k citations indexed

About

Chris Snyder is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography. According to data from OpenAlex, Chris Snyder has authored 130 papers receiving a total of 9.8k indexed citations (citations by other indexed papers that have themselves been cited), including 102 papers in Atmospheric Science, 88 papers in Global and Planetary Change and 30 papers in Oceanography. Recurrent topics in Chris Snyder's work include Meteorological Phenomena and Simulations (88 papers), Climate variability and models (84 papers) and Tropical and Extratropical Cyclones Research (33 papers). Chris Snyder is often cited by papers focused on Meteorological Phenomena and Simulations (88 papers), Climate variability and models (84 papers) and Tropical and Extratropical Cyclones Research (33 papers). Chris Snyder collaborates with scholars based in United States, France and Canada. Chris Snyder's co-authors include Thomas M. Hamill, Fuqing Zhang, Richard Rotunno, Jeffrey S. Whitaker, David C. Dowell, Juanzhen Sun, Thomas Bengtsson, J. G. Anderson, Riwal Plougonven and Xuguang Wang and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, The Science of The Total Environment and Geophysical Research Letters.

In The Last Decade

Chris Snyder

124 papers receiving 9.4k citations

Hit Papers

Distance-Dependent Filtering of Background Error Covarian... 2001 2026 2009 2017 2001 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chris Snyder United States 52 8.7k 7.5k 1.8k 1.4k 473 130 9.8k
Dale Barker United States 28 12.4k 1.4× 10.6k 1.4× 1.7k 1.0× 2.7k 1.9× 375 0.8× 45 14.6k
Xiang‐Yu Huang China 25 8.9k 1.0× 7.6k 1.0× 1.3k 0.8× 2.0k 1.4× 369 0.8× 103 10.9k
Andrew C. Lorenc United Kingdom 32 5.4k 0.6× 4.8k 0.6× 1.4k 0.8× 1.0k 0.7× 274 0.6× 63 6.2k
Craig H. Bishop United States 40 5.4k 0.6× 4.9k 0.7× 1.3k 0.7× 986 0.7× 142 0.3× 128 6.1k
A. J. Simmons United Kingdom 54 10.2k 1.2× 10.0k 1.3× 2.8k 1.6× 846 0.6× 899 1.9× 107 12.5k
Fuqing Zhang United States 69 14.2k 1.6× 11.4k 1.5× 3.0k 1.7× 1.5k 1.1× 1.0k 2.2× 306 15.5k
John Derber United States 30 5.7k 0.7× 5.1k 0.7× 1.3k 0.8× 948 0.7× 313 0.7× 60 6.5k
Dick Dee United Kingdom 40 6.0k 0.7× 6.0k 0.8× 1.6k 0.9× 903 0.6× 301 0.6× 80 7.6k
Jeffrey S. Whitaker United States 39 7.2k 0.8× 6.9k 0.9× 1.5k 0.8× 1.2k 0.9× 100 0.2× 87 8.3k
William C. Skamarock United States 44 11.2k 1.3× 8.6k 1.2× 1.5k 0.8× 2.3k 1.6× 505 1.1× 99 13.3k

Countries citing papers authored by Chris Snyder

Since Specialization
Citations

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

Fields of papers citing papers by Chris Snyder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chris Snyder

This figure shows the co-authorship network connecting the top 25 collaborators of Chris Snyder. A scholar is included among the top collaborators of Chris Snyder 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 Chris Snyder. Chris Snyder 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
2.
Schwartz, Craig S., et al.. (2025). A First Step toward Global Ensemble-Based Data Assimilation at Convection-Allowing Scales Using MPAS and JEDI. Monthly Weather Review. 153(10). 2139–2166.
4.
Snyder, Chris, et al.. (2024). Conformal Prediction and Large Language Models for Medical Coding. American Journal of Clinical Pathology. 162(Supplement_1). S171–S172.
5.
Liu, Zhiquan, Chris Snyder, Junmei Ban, et al.. (2022). Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 1.0.0): EnVar implementation and evaluation. Geoscientific model development. 15(20). 7859–7878. 7 indexed citations
6.
Snyder, Chris, et al.. (2021). Conflicting Advice between Spiritual Leaders, Friends and Family, and Mental Health Providers: Impacts on Mental Health Treatment-Seeking Behaviors. Journal of Religion and Health. 60(4). 2608–2619. 3 indexed citations
7.
Xu, Dongmei, et al.. (2016). A method for retrieving clouds with satellite infrared radiancesusing the particle filter. Geoscientific model development. 9(11). 3919–3932. 14 indexed citations
8.
Tardif, Robert, Gregory J. Hakim, & Chris Snyder. (2014). Coupled atmosphere–ocean data assimilation experiments with a low-order model and CMIP5 model data. Climate Dynamics. 45(5-6). 1415–1427. 26 indexed citations
9.
Muraki, David J. & Chris Snyder. (2007). Vortex Dipoles for Surface Quasigeostrophic Models. Journal of the Atmospheric Sciences. 64(8). 2961–2967. 18 indexed citations
10.
Snyder, Chris, et al.. (2005). Pro PHP Security. Apress eBooks. 1 indexed citations
11.
Snyder, Chris, et al.. (2005). Pro PHP Security (Pro). Apress eBooks.
12.
Caya, Alain, Juanzhen Sun, & Chris Snyder. (2005). A Comparison between the 4DVAR and the Ensemble Kalman Filter Techniques for Radar Data Assimilation. Monthly Weather Review. 133(11). 3081–3094. 169 indexed citations
13.
Zhang, Fuqing, et al.. (2004). Mesoscale Predictability of Moist Baroclinic Waves: Experiments with Parameterized Convection. Journal of the Atmospheric Sciences. 61(14). 1794–1804. 76 indexed citations
14.
Zhang, Fuqing, Chris Snyder, & Juanzhen Sun. (2004). Impacts of Initial Estimate and Observation Availability on Convective-Scale Data Assimilation with an Ensemble Kalman Filter. Monthly Weather Review. 132(5). 1238–1253. 455 indexed citations
15.
Hamill, Thomas M., Chris Snyder, & Jeffrey S. Whitaker. (2003). Approximate analysis error covariance singular vectors in a simple GCM. EGS - AGU - EUG Joint Assembly. 13876. 1 indexed citations
16.
Hamill, Thomas M., Chris Snyder, & Jeffrey S. Whitaker. (2003). Ensemble Forecasts and the Properties of Flow-Dependent Analysis-Error Covariance Singular Vectors. Monthly Weather Review. 131(8). 1741–1758. 40 indexed citations
17.
Snyder, Chris, Thomas M. Hamill, & Stanley B. Trier. (2002). Linear Evolution of Error Covariances in a Quasigeostrophic Model. Monthly Weather Review. 131(1). 189–205. 43 indexed citations
18.
Hamill, Thomas M. & Chris Snyder. (2002). Using Improved Background-Error Covariances from an Ensemble Kalman Filter for Adaptive Observations. Monthly Weather Review. 130(6). 1552–1572. 80 indexed citations
19.
Joly, Alain, D. P. Jorgensen, Melvyn A. Shapiro, et al.. (1997). The Fronts and Atlantic Storm-Track Experiment (FASTEX): Scientific Objectives and Experimental Design. Bulletin of the American Meteorological Society. 78(9). 1917–1940. 139 indexed citations
20.
Wiegel, Robert L., Chris Snyder, & Jack E. Williams. (1958). Water gravity waves generated by a moving low pressure area. Transactions American Geophysical Union. 39(2). 224–236. 6 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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