Doug Nychka

2.8k total citations
38 papers, 2.0k citations indexed

About

Doug Nychka is a scholar working on Global and Planetary Change, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Doug Nychka has authored 38 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Global and Planetary Change, 17 papers in Atmospheric Science and 6 papers in Environmental Engineering. Recurrent topics in Doug Nychka's work include Climate variability and models (15 papers), Meteorological Phenomena and Simulations (13 papers) and Atmospheric and Environmental Gas Dynamics (6 papers). Doug Nychka is often cited by papers focused on Climate variability and models (15 papers), Meteorological Phenomena and Simulations (13 papers) and Atmospheric and Environmental Gas Dynamics (6 papers). Doug Nychka collaborates with scholars based in United States, Canada and Norway. Doug Nychka's co-authors include Claudia Tebaldi, Linda O. Mearns, Richard L. Smith, Ralph F. Milliff, L. Mark Berliner, Christopher K. Wikle, Thomas Bengtsson, Chris Snyder, J. Andrew Royle and C. L. Winter and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of the American Statistical Association and Journal of Climate.

In The Last Decade

Doug Nychka

36 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Doug Nychka United States 21 1.2k 853 398 250 190 38 2.0k
Fadoua Balabdaoui France 10 1.3k 1.2× 1.0k 1.2× 550 1.4× 486 1.9× 183 1.0× 21 2.7k
William Kleiber United States 19 622 0.5× 439 0.5× 531 1.3× 177 0.7× 211 1.1× 57 1.5k
Eric Gilleland United States 25 2.2k 1.9× 1.6k 1.8× 406 1.0× 522 2.1× 130 0.7× 70 2.9k
Phaedon Kyriakidis United States 31 1.2k 1.0× 571 0.7× 1.3k 3.3× 481 1.9× 325 1.7× 93 3.5k
Olivier Mestre France 22 1.3k 1.1× 1.1k 1.3× 217 0.5× 191 0.8× 126 0.7× 41 2.2k
Petra Friederichs Germany 21 1.4k 1.2× 1.2k 1.4× 244 0.6× 169 0.7× 125 0.7× 58 2.1k
Hans Wackernagel France 17 740 0.6× 561 0.7× 1.3k 3.4× 307 1.2× 313 1.6× 36 3.1k
Andreas Langousis Greece 25 1.3k 1.1× 643 0.8× 551 1.4× 786 3.1× 105 0.6× 70 2.1k
Anne‐Catherine Favre France 26 2.4k 2.1× 690 0.8× 422 1.1× 1.3k 5.3× 178 0.9× 84 3.8k
Barbara G. Brown United States 30 3.2k 2.8× 3.1k 3.7× 591 1.5× 276 1.1× 162 0.9× 78 4.7k

Countries citing papers authored by Doug Nychka

Since Specialization
Citations

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

Fields of papers citing papers by Doug Nychka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Doug Nychka

This figure shows the co-authorship network connecting the top 25 collaborators of Doug Nychka. A scholar is included among the top collaborators of Doug Nychka 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 Doug Nychka. Doug Nychka 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.
Ebert‐Uphoff, Imme, Claire Monteleoni, & Doug Nychka. (2017). Proceedings of the 7th International Workshop on Climate Informatics: CI 2017. 10 indexed citations
2.
3.
Alexeeff, Stacey, Gabriele Pfister, & Doug Nychka. (2015). A Bayesian Model for Quantifying the Change in Mortality Associated with Future Ozone Exposures Under Climate Change. Biometrics. 72(1). 281–288. 12 indexed citations
4.
Baker, Allison H., Haiying Xu, John M. Dennis, et al.. (2014). A methodology for evaluating the impact of data compression on climate simulation data. 203–214. 71 indexed citations
5.
Sain, Stephan R., Doug Nychka, & Linda Mearns. (2010). Functional ANOVA and regional climate experiments: a statistical analysis of dynamic downscaling. Environmetrics. 22(6). 700–711. 26 indexed citations
6.
Romero‐Lankao, Patricia, John Tribbia, & Doug Nychka. (2009). Testing Theories to Explore the Drivers of Cities' Atmospheric Emissions. AMBIO. 38(4). 236–244. 33 indexed citations
7.
Winter, C. L. & Doug Nychka. (2009). Forecasting skill of model averages. Stochastic Environmental Research and Risk Assessment. 24(5). 633–638. 41 indexed citations
8.
Smith, Richard L., Claudia Tebaldi, Doug Nychka, & Linda O. Mearns. (2009). Bayesian Modeling of Uncertainty in Ensembles of Climate Models. Journal of the American Statistical Association. 104(485). 97–116. 159 indexed citations
9.
Nychka, Doug, et al.. (2008). Development and greenhouse gas emissions deviate from the ‘modernization’ theory and ‘convergence’ hypothesis. Climate Research. 38. 17–29. 25 indexed citations
10.
Nychka, Doug, et al.. (2007). A framework to understand the asymptotic properties of Kriging and splines. Journal of the Korean Statistical Society. 57–76. 12 indexed citations
11.
Fuentes, Montserrat, Timothy G. F. Kittel, & Doug Nychka. (2006). Sensitivity Of Ecological Models To Their Climate Drivers: Statistical Ensembles For Forcing. Ecological Applications. 16(1). 99–116. 20 indexed citations
12.
Winter, C. L., Alberto Guadagnini, Doug Nychka, & Daniel M. Tartakovsky. (2006). Multivariate sensitivity analysis of saturated flow through simulated highly heterogeneous groundwater aquifers. Journal of Computational Physics. 217(1). 166–175. 30 indexed citations
13.
Bengtsson, Thomas, Ralph F. Milliff, Richard H. Jones, Doug Nychka, & Pearn P. Niiler. (2005). A state‐space model for ocean drifter motions dominated by inertial oscillations. Journal of Geophysical Research Atmospheres. 110(C10). 2 indexed citations
14.
Oh, Hee‐Seok, Doug Nychka, Timothy C. Brown, & Paul Charbonneau. (2004). Period Analysis of Variable Stars by Robust Smoothing. Journal of the Royal Statistical Society Series C (Applied Statistics). 53(1). 15–30. 31 indexed citations
15.
Bengtsson, Thomas, Chris Snyder, & Doug Nychka. (2003). A nonlinear filter that extends to high dimensional systems. 2 indexed citations
16.
Nychka, Doug, et al.. (2000). Confidence intervals for trend estimates with autocorrelated observations. 5 indexed citations
17.
Nychka, Doug. (2000). Challenges in Understanding the Atmosphere. Journal of the American Statistical Association. 95(451). 972–972. 1 indexed citations
18.
Nychka, Doug. (2000). Challenges in Understanding the Atmosphere. Journal of the American Statistical Association. 95(451). 972–975. 8 indexed citations
19.
Davis, Jeanine M., Brian K. Eder, Doug Nychka, & Qing Yang. (1998). Modeling the effects of meteorology on ozone in Houston using cluster analysis and generalized additive models. Atmospheric Environment. 32(14-15). 2505–2520. 92 indexed citations
20.
Chan, Kung‐Sik, D. R. Cox, Colleen D. Cutler, et al.. (1995). A personal overview of non-linear time series analysis from a chaos perspective. Commentary. Scandinavian Journal of Statistics. 22(4). 399–445. 30 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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