Jan D. Keller

1.2k total citations
25 papers, 720 citations indexed

About

Jan D. Keller is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Jan D. Keller has authored 25 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Atmospheric Science, 19 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in Jan D. Keller's work include Meteorological Phenomena and Simulations (20 papers), Climate variability and models (17 papers) and Atmospheric and Environmental Gas Dynamics (6 papers). Jan D. Keller is often cited by papers focused on Meteorological Phenomena and Simulations (20 papers), Climate variability and models (17 papers) and Atmospheric and Environmental Gas Dynamics (6 papers). Jan D. Keller collaborates with scholars based in Germany, United States and United Kingdom. Jan D. Keller's co-authors include Sabrina Wahl, Andreas Hense, Susanne Crewell, Christoph Bollmeyer, Christian Ohlwein, Petra Friederichs, Ieda Pscheidt, Stefan Kneifel, Jessica Keune and S. Steinke and has published in prestigious journals such as Journal of Climate, Renewable Energy and Solar Energy.

In The Last Decade

Jan D. Keller

24 papers receiving 700 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan D. Keller Germany 14 459 442 117 95 75 25 720
Sabrina Wahl Germany 8 288 0.6× 287 0.6× 87 0.7× 78 0.8× 62 0.8× 10 488
Raquel Lorente‐Plazas Spain 16 505 1.1× 515 1.2× 92 0.8× 93 1.0× 59 0.8× 30 736
William Y. Y. Cheng United States 14 514 1.1× 483 1.1× 144 1.2× 195 2.1× 84 1.1× 19 743
Juan Antonio Añel Spain 16 544 1.2× 554 1.3× 60 0.5× 63 0.7× 39 0.5× 56 810
Verónica Torralba Spain 14 603 1.3× 675 1.5× 126 1.1× 246 2.6× 175 2.3× 29 1.0k
Llorenç Lledó Spain 12 362 0.8× 389 0.9× 87 0.7× 200 2.1× 140 1.9× 25 651
Claudia Gutiérrez Spain 12 189 0.4× 256 0.6× 69 0.6× 91 1.0× 59 0.8× 25 475
Yuanfu Xie United States 12 285 0.6× 288 0.7× 80 0.7× 175 1.8× 55 0.7× 33 658
Emmanuel Chilekwu Okogbue Nigeria 13 162 0.4× 303 0.7× 121 1.0× 60 0.6× 42 0.6× 37 524
Uwe Pfeifroth Germany 13 310 0.7× 433 1.0× 69 0.6× 102 1.1× 44 0.6× 22 654

Countries citing papers authored by Jan D. Keller

Since Specialization
Citations

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

Fields of papers citing papers by Jan D. Keller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan D. Keller. 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 Jan D. Keller. The network helps show where Jan D. Keller may publish in the future.

Co-authorship network of co-authors of Jan D. Keller

This figure shows the co-authorship network connecting the top 25 collaborators of Jan D. Keller. A scholar is included among the top collaborators of Jan D. Keller 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 Jan D. Keller. Jan D. Keller 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.
Schaffernicht, Erik Jan, et al.. (2023). Postprocessing of NWP Precipitation Forecasts Using Deep Learning. Weather and Forecasting. 38(3). 487–497. 14 indexed citations
2.
Brune, Sebastian & Jan D. Keller. (2022). Statistical post-processing of reanalysis wind speeds at hub heights using a diagnostic wind model and neural networks. Wind energy science. 7(5). 1905–1918. 1 indexed citations
3.
Keller, Jan D., Daryl Kleist, Stephen English, et al.. (2022). Current Challenges and Future Directions in Data Assimilation and Reanalysis. Bulletin of the American Meteorological Society. 104(4). E756–E767. 13 indexed citations
4.
Keller, Jan D., et al.. (2022). A review on irrigation parameterizations in Earth system models. Frontiers in Water. 4. 9 indexed citations
5.
Keller, Jan D., et al.. (2021). How to visualize the Urban Heat Island in Gridded Datasets?. Advances in science and research. 18. 41–49. 2 indexed citations
6.
Frank, Christopher W., Frank Kaspar, Jan D. Keller, et al.. (2020). FAIR: a project to realize a user-friendly exchange of open weather data. Advances in science and research. 17. 183–190. 4 indexed citations
7.
Keller, Jan D. & Sabrina Wahl. (2020). Representation of Climate in Reanalyses: An Intercomparison for Europe and North America. Journal of Climate. 34(5). 1667–1684. 32 indexed citations
8.
Kaspar, Frank, Michael Borsche, Stephanie Fiedler, et al.. (2020). Regional atmospheric reanalysis activities at Deutscher Wetterdienst: review of evaluation results and application examples with a focus on renewable energy. Advances in science and research. 17. 115–128. 31 indexed citations
9.
Schultz, Martin, Felix Kleinert, Lukas Hubert Leufen, et al.. (2019). DeepRain - Improved local-scale prediction of precipitation through deep learning. EGU General Assembly Conference Abstracts. 13625. 1 indexed citations
10.
Frank, Christopher W., Bernhard Pospichal, Sabrina Wahl, et al.. (2019). The added value of high resolution regional reanalyses for wind power applications. Renewable Energy. 148. 1094–1109. 37 indexed citations
11.
Rinke, Annette, Susanne Crewell, Marion Maturilli, et al.. (2019). Trends of Vertically Integrated Water Vapor over the Arctic during 1979–2016: Consistent Moistening All Over?. Journal of Climate. 32(18). 6097–6116. 50 indexed citations
12.
Keller, Jan D., et al.. (2018). Editorial Celebrating 25 Years of the IEEE Transactions on Fuzzy Systems. IEEE Transactions on Fuzzy Systems. 26(1). 1–5. 14 indexed citations
13.
Keller, Jan D., Luca Delle Monache, & Stefano Alessandrini. (2017). Statistical Downscaling of a High-Resolution Precipitation Reanalysis Using the Analog Ensemble Method. Journal of Applied Meteorology and Climatology. 56(7). 2081–2095. 17 indexed citations
14.
Wahl, Sabrina, Christoph Bollmeyer, Susanne Crewell, et al.. (2017). A novel convective-scale regional reanalysis COSMO-REA2: Improving the representation of precipitation. Meteorologische Zeitschrift. 26(4). 345–361. 69 indexed citations
15.
Schraff, Christoph, et al.. (2016). Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments. Tellus A Dynamic Meteorology and Oceanography. 68(1). 32209–32209. 19 indexed citations
16.
Weißmann, Martin, Martin Göber, Cathy Hohenegger, et al.. (2014). Initial phase of the Hans-Ertel Centre for Weather Research – A virtual centre at the interface of basic and applied weather and climate research. Meteorologische Zeitschrift. 23(3). 193–208. 34 indexed citations
17.
Kneifel, Stefan, S. Steinke, Christian Ohlwein, et al.. (2012). Retrospective analysis of regional climate: The German reanalysis project - potential of remote sensing observations. 3689–3692. 1 indexed citations
18.
Keller, Jan D., Andreas Hense, & A. Rhodin. (2010). Estimating Uncertainty in Atmospheric Models - Application and new Approaches of Lyapunov Vector Estimations. AGU Fall Meeting Abstracts. 2010. 1 indexed citations
19.
Keller, Jan D., Andreas Hense, Luis Kornblueh, & A. Rhodin. (2010). On the Orthogonalization of Bred Vectors. Weather and Forecasting. 25(4). 1219–1234. 10 indexed citations
20.
Keller, Jan D., Luis Kornblueh, Andreas Hense, & A. Rhodin. (2008). Towards a GME ensemble forecasting system: Ensemble initialization using the breeding technique. Meteorologische Zeitschrift. 17(6). 707–718. 11 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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