Michael Scheuerer

1.9k total citations
39 papers, 1.3k citations indexed

About

Michael Scheuerer is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Michael Scheuerer has authored 39 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Atmospheric Science, 30 papers in Global and Planetary Change and 12 papers in Environmental Engineering. Recurrent topics in Michael Scheuerer's work include Meteorological Phenomena and Simulations (29 papers), Climate variability and models (26 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Michael Scheuerer is often cited by papers focused on Meteorological Phenomena and Simulations (29 papers), Climate variability and models (26 papers) and Atmospheric and Environmental Gas Dynamics (7 papers). Michael Scheuerer collaborates with scholars based in United States, Germany and Norway. Michael Scheuerer's co-authors include Thomas M. Hamill, Thordis L. Thorarinsdottir, Florian Pappenberger, Martin Schlather, Rochelle P. Worsnop, Gary T. Bates, Robert Schaback, Matthew B. Switanek, Richard Swinbank and Tim Hewson and has published in prestigious journals such as Water Resources Research, Geophysical Research Letters and Monthly Weather Review.

In The Last Decade

Michael Scheuerer

35 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Scheuerer United States 19 875 857 266 147 111 39 1.3k
Peter Dueben United Kingdom 17 810 0.9× 669 0.8× 310 1.2× 95 0.6× 50 0.5× 32 1.2k
William Kleiber United States 19 439 0.5× 622 0.7× 531 2.0× 111 0.8× 177 1.6× 57 1.5k
Stephan Rasp Germany 15 942 1.1× 819 1.0× 305 1.1× 112 0.8× 57 0.5× 24 1.4k
Dorit Hammerling United States 16 436 0.5× 617 0.7× 356 1.3× 19 0.1× 58 0.5× 56 1.2k
Thordis L. Thorarinsdottir Norway 18 744 0.9× 926 1.1× 310 1.2× 178 1.2× 180 1.6× 41 1.4k
Pierre Ailliot France 15 307 0.4× 316 0.4× 154 0.6× 140 1.0× 47 0.4× 44 812
Yongxiang Huang China 20 252 0.3× 371 0.4× 288 1.1× 101 0.7× 54 0.5× 75 1.2k
Milija Županski United States 24 1.4k 1.6× 1.2k 1.4× 287 1.1× 24 0.2× 70 0.6× 68 1.6k
Kaifeng Bi China 2 359 0.4× 274 0.3× 165 0.6× 97 0.7× 24 0.2× 3 785

Countries citing papers authored by Michael Scheuerer

Since Specialization
Citations

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

Fields of papers citing papers by Michael Scheuerer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Scheuerer

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Scheuerer. A scholar is included among the top collaborators of Michael Scheuerer 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 Michael Scheuerer. Michael Scheuerer 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
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2.
Towler, Erin, Nachiketa Acharya, Mimi Hughes, et al.. (2025). Implementing and Evaluating National Water Model Ensemble Streamflow Predictions Using Postprocessed Precipitation Forecasts. Journal of Hydrometeorology. 26(4). 385–399.
3.
4.
Scheuerer, Michael, et al.. (2024). Probabilistic rainy season onset prediction over the greater horn of africa based on long-range multi-model ensemble forecasts. Climate Dynamics. 62(5). 3587–3604. 2 indexed citations
5.
Scheuerer, Michael, et al.. (2023). A Multi-Temporal-Scale Modulation Mechanism for the Postprocessing of Precipitation Ensemble Forecasts: Benefits for Streamflow Forecasting. Journal of Hydrometeorology. 24(4). 659–673. 4 indexed citations
6.
Kleiber, William, et al.. (2020). Beyond univariate calibration: verifying spatial structure in ensembles of forecast fields. Nonlinear processes in geophysics. 27(3). 411–427. 1 indexed citations
7.
Hamill, Thomas M. & Michael Scheuerer. (2020). Improving Ensemble Weather Prediction System Initialization: Disentangling the Contributions from Model Systematic Errors and Initial Perturbation Size. Monthly Weather Review. 149(1). 77–90. 1 indexed citations
8.
Scheuerer, Michael, et al.. (2020). Precipitation Downscaling with Gibbs Sampling: An Improved Method for Producing Realistic, Weather-Dependent, and Anisotropic Fields. Journal of Hydrometeorology. 21(11). 2487–2505. 2 indexed citations
9.
Scheuerer, Michael, Matthew B. Switanek, Rochelle P. Worsnop, & Thomas M. Hamill. (2020). Using Artificial Neural Networks for Generating Probabilistic Subseasonal Precipitation Forecasts over California. Monthly Weather Review. 148(8). 3489–3506. 59 indexed citations
10.
Worsnop, Rochelle P., Michael Scheuerer, & Thomas M. Hamill. (2019). Extended-Range Probabilistic Fire-Weather Forecasting Based on Ensemble Model Output Statistics and Ensemble Copula Coupling. Monthly Weather Review. 148(2). 499–521. 14 indexed citations
11.
Worsnop, Rochelle P., Michael Scheuerer, Thomas M. Hamill, & Julie K. Lundquist. (2018). Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing. Wind energy science. 3(1). 371–393. 18 indexed citations
12.
Worsnop, Rochelle P., Michael Scheuerer, Thomas M. Hamill, & Julie K. Lundquist. (2018). Generating wind power scenarios for probabilistic ramp event prediction using multivariate statistical post-processing. 1 indexed citations
13.
Scheuerer, Michael, et al.. (2018). Probabilistic Forecasting of Snowfall Amounts Using a Hybrid between a Parametric and an Analog Approach. Monthly Weather Review. 147(3). 1047–1064. 3 indexed citations
14.
Swinbank, Richard, Piers Buchanan, Lizzie S. R. Froude, et al.. (2015). The TIGGE Project and Its Achievements. Bulletin of the American Meteorological Society. 97(1). 49–67. 196 indexed citations
15.
Scheuerer, Michael & Thomas M. Hamill. (2014). National Oceanic and Atmospheric Administration (NOAA), Earth System Research Laboratory,. 21 indexed citations
16.
Thorarinsdottir, Thordis L., et al.. (2014). Assessing the Calibration of High-Dimensional Ensemble Forecasts Using Rank Histograms. Journal of Computational and Graphical Statistics. 25(1). 105–122. 55 indexed citations
17.
Scheuerer, Michael, Robert Schaback, & Martin Schlather. (2013). Interpolation of spatial data – A stochastic or a deterministic problem?. European Journal of Applied Mathematics. 24(4). 601–629. 60 indexed citations
18.
Scheuerer, Michael & Martin Schlather. (2012). Covariance Models for Divergence-Free and Curl-Free Random Vector Fields. Stochastic Models. 28(3). 433–451. 11 indexed citations
19.
Scheuerer, Michael. (2010). Regularity of the sample paths of a general second order random field. Stochastic Processes and their Applications. 120(10). 1879–1897. 22 indexed citations
20.
Scheuerer, Michael. (2010). An alternative procedure for selecting a good value for the parameter c in RBF-interpolation. Advances in Computational Mathematics. 34(1). 105–126. 69 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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