Richard Kleeman

7.0k total citations
84 papers, 4.8k citations indexed

About

Richard Kleeman is a scholar working on Global and Planetary Change, Atmospheric Science and Oceanography. According to data from OpenAlex, Richard Kleeman has authored 84 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Global and Planetary Change, 53 papers in Atmospheric Science and 43 papers in Oceanography. Recurrent topics in Richard Kleeman's work include Climate variability and models (70 papers), Meteorological Phenomena and Simulations (44 papers) and Oceanographic and Atmospheric Processes (43 papers). Richard Kleeman is often cited by papers focused on Climate variability and models (70 papers), Meteorological Phenomena and Simulations (44 papers) and Oceanographic and Atmospheric Processes (43 papers). Richard Kleeman collaborates with scholars based in United States, Australia and Germany. Richard Kleeman's co-authors include Andrew M. Moore, William S. Kessler, Mojib Latif, Barry A. Klinger, Julian P. McCreary, Scott B. Power, Youmin Tang, Noel Keenlyside, Andrew J. Majda and Christian Eckert and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Journal of Geophysical Research Atmospheres.

In The Last Decade

Richard Kleeman

84 papers receiving 4.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard Kleeman United States 38 4.2k 3.5k 2.6k 283 209 84 4.8k
Cécile Penland United States 27 2.7k 0.7× 2.3k 0.6× 1.6k 0.6× 237 0.8× 184 0.9× 56 3.2k
Kyle L. Swanson United States 21 2.1k 0.5× 1.7k 0.5× 935 0.4× 299 1.1× 296 1.4× 40 2.9k
Bedartha Goswami India 28 2.2k 0.5× 2.0k 0.6× 680 0.3× 125 0.4× 136 0.7× 58 3.0k
Dmitri Kondrashov United States 26 1.5k 0.4× 1.5k 0.4× 854 0.3× 280 1.0× 285 1.4× 57 3.6k
Christian L. E. Franzke Germany 38 3.4k 0.8× 3.0k 0.8× 845 0.3× 251 0.9× 498 2.4× 131 4.3k
Prashant D. Sardeshmukh United States 46 6.5k 1.6× 5.9k 1.7× 3.0k 1.2× 142 0.5× 143 0.7× 98 7.1k
Joseph Tribbia United States 40 4.4k 1.1× 4.2k 1.2× 1.8k 0.7× 121 0.4× 119 0.6× 137 5.5k
Franco Molteni United Kingdom 46 8.0k 1.9× 7.6k 2.2× 2.7k 1.0× 98 0.3× 172 0.8× 114 8.8k
Grant Branstator United States 40 6.5k 1.5× 5.8k 1.7× 2.8k 1.1× 186 0.7× 122 0.6× 73 7.0k
Guolin Feng China 26 2.6k 0.6× 1.9k 0.5× 575 0.2× 219 0.8× 346 1.7× 321 3.3k

Countries citing papers authored by Richard Kleeman

Since Specialization
Citations

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

Fields of papers citing papers by Richard Kleeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Kleeman

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Kleeman. A scholar is included among the top collaborators of Richard Kleeman 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 Richard Kleeman. Richard Kleeman 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.
Kleeman, Richard. (2011). Information Theory and Dynamical System Predictability. Entropy. 13(3). 612–649. 65 indexed citations
2.
Kleeman, Richard. (2010). Spectral Analysis of Multidimensional Stochastic Geophysical Models with an Application to Decadal ENSO Variability. Journal of the Atmospheric Sciences. 68(1). 13–25. 12 indexed citations
3.
Kleeman, Richard. (2008). Limits, Variability, and General Behavior of Statistical Predictability of the Midlatitude Atmosphere. Journal of the Atmospheric Sciences. 65(1). 263–275. 19 indexed citations
4.
Zavala‐Garay, Javier, C. Zhang, Andrew M. Moore, et al.. (2008). Sensitivity of Hybrid ENSO Models to Unresolved Atmospheric Variability. Journal of Climate. 21(15). 3704–3721. 31 indexed citations
5.
Kleeman, Richard, et al.. (2007). A rigorous formalism of information transfer between dynamical system components. I. Discrete mapping. Physica D Nonlinear Phenomena. 231(1). 1–9. 28 indexed citations
6.
Kleeman, Richard. (2007). Information Flow in Ensemble Weather Predictions. Journal of the Atmospheric Sciences. 64(3). 1005–1016. 21 indexed citations
7.
Kleeman, Richard, et al.. (2005). Information Transfer between Dynamical System Components. Physical Review Letters. 95(24). 244101–244101. 137 indexed citations
8.
Tang, Youmin, Richard Kleeman, & Andrew M. Moore. (2004). A simple method for estimating variations in the predictability of ENSO. Geophysical Research Letters. 31(17). 5 indexed citations
9.
Kleeman, Richard. (2002). Measuring Dynamical Prediction Utility Using Relative Entropy. Journal of the Atmospheric Sciences. 59(13). 2057–2072. 229 indexed citations
10.
Majda, Andrew J., et al.. (2002). A framework for predictability through relative entropy. Methods and Applications of Analysis. 9(2). 140–7. 12 indexed citations
11.
Tang, Youmin & Richard Kleeman. (2002). A new strategy for assimilating SST data for ENSO predictions. Geophysical Research Letters. 29(17). 10 indexed citations
12.
Díaz, Henry F., Robert J. Allan, Martin P. Hoerling, et al.. (2000). El Nino and the Southern Oscillation. Cambridge University Press eBooks. 271 indexed citations
13.
Kleeman, Richard & Andrew M. Moore. (1999). A New Method for Determining the Reliability of Dynamical ENSO Predictions. Monthly Weather Review. 127(5). 694–705. 43 indexed citations
14.
Latif, Mojib, David L. T. Anderson, Timothy C. Barnett, et al.. (1998). A review of the predictability and prediction of ENSO. Journal of Geophysical Research Atmospheres. 103(C7). 14375–14393. 428 indexed citations
15.
Kleeman, Richard, et al.. (1997). The singular vectors of a coupled ocean-atmosphere model of ENSO. II: Sensitivity studies and dynamical interpretation. Quarterly Journal of the Royal Meteorological Society. 123(540). 983–1006. 2 indexed citations
16.
Kleeman, Richard & Scott B. Power. (1995). A Simple Atmospheric Model of Surface Heat Flux for Use in Ocean Modeling Studies. Journal of Physical Oceanography. 25(1). 92–105. 50 indexed citations
17.
Power, Scott B., Richard Kleeman, Robert Colman, & B. J. McAvaney. (1995). Modeling the Surface Heat Flux Response to Long-Lived SST Anomalies in the North Atlantic. Journal of Climate. 8(9). 2161–2180. 21 indexed citations
18.
Power, Scott B. & Richard Kleeman. (1994). Surface heat flux parameterization and the response of ocean general circulation models to high-latitude freshening. Tellus A Dynamic Meteorology and Oceanography. 46(1). 86–86. 22 indexed citations
19.
Latif, Mojib, Moritz Flügel, & Richard Kleeman. (1992). A hybrid coupled tropical atmosphere ocean model: Sensitivities and hindcast skill. Chemical Research in Toxicology. 5(2). 254–62. 4 indexed citations
20.
Kleeman, Richard. (1989). A Modeling Study of the Effect of the Andes on the Summertime Circulation of Tropical South America. Journal of the Atmospheric Sciences. 46(21). 3344–3362. 40 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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