Alexander Kann

944 total citations
40 papers, 611 citations indexed

About

Alexander Kann is a scholar working on Atmospheric Science, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Alexander Kann has authored 40 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Atmospheric Science, 21 papers in Global and Planetary Change and 9 papers in Environmental Engineering. Recurrent topics in Alexander Kann's work include Meteorological Phenomena and Simulations (27 papers), Climate variability and models (17 papers) and Precipitation Measurement and Analysis (15 papers). Alexander Kann is often cited by papers focused on Meteorological Phenomena and Simulations (27 papers), Climate variability and models (17 papers) and Precipitation Measurement and Analysis (15 papers). Alexander Kann collaborates with scholars based in Austria, China and Slovakia. Alexander Kann's co-authors include Christoph Wittmann, Thomas Haiden, Benedikt Bica, Georg Pistotnik, Christine Gruber, Yong Wang, Irene Schicker, Jürgen Fuchsberger, Martin Steinheimer and Stjepan Ivatek‐Šahdan and has published in prestigious journals such as Monthly Weather Review, Quarterly Journal of the Royal Meteorological Society and Hydrology and earth system sciences.

In The Last Decade

Alexander Kann

38 papers receiving 590 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexander Kann Austria 12 455 402 137 71 37 40 611
Christoph Wittmann Austria 13 452 1.0× 430 1.1× 125 0.9× 50 0.7× 36 1.0× 28 588
R. K. Jenamani India 15 506 1.1× 580 1.4× 229 1.7× 45 0.6× 18 0.5× 26 810
Silvia Puca Italy 14 388 0.9× 257 0.6× 275 2.0× 162 2.3× 30 0.8× 40 572
Benedikt Bica Austria 9 341 0.7× 314 0.8× 99 0.7× 53 0.7× 32 0.9× 14 456
Georg Pistotnik Austria 10 344 0.8× 339 0.8× 87 0.6× 75 1.1× 37 1.0× 18 499
Ian Strangeways Netherlands 11 255 0.6× 290 0.7× 68 0.5× 60 0.8× 13 0.4× 47 465
Tim Raupach Switzerland 14 454 1.0× 300 0.7× 160 1.2× 83 1.2× 10 0.3× 28 624
G. Srinivasa Rao India 13 158 0.3× 355 0.9× 87 0.6× 120 1.7× 42 1.1× 36 453
Hoang Tran United States 11 298 0.7× 351 0.9× 168 1.2× 226 3.2× 18 0.5× 38 593
Gregor Gregorič Slovenia 6 604 1.3× 622 1.5× 115 0.8× 66 0.9× 12 0.3× 15 824

Countries citing papers authored by Alexander Kann

Since Specialization
Citations

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

Fields of papers citing papers by Alexander Kann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexander Kann

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Kann. A scholar is included among the top collaborators of Alexander Kann 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 Alexander Kann. Alexander Kann 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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Foelsche, Ulrich, et al.. (2021). Evaluation of Integrated Nowcasting through Comprehensive Analysis (INCA) precipitation analysis using a dense rain-gauge network in southeastern Austria. Hydrology and earth system sciences. 25(8). 4335–4356. 11 indexed citations
4.
Schicker, Irene, et al.. (2020). Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis. Meteorologische Zeitschrift. 29(4). 265–275. 4 indexed citations
5.
Schicker, Irene, et al.. (2020). Feature selection, ensemble learning, and artificial neural networks for short-range wind speed forecasts. Meteorologische Zeitschrift. 29(4). 307–322. 3 indexed citations
6.
Atencia, Aitor, Yong Wang, Alexander Kann, & Clemens Wastl. (2020). A probabilistic precipitation nowcasting system constrained by an Ensemble Prediction System.. Meteorologische Zeitschrift. 29(3). 183–202. 2 indexed citations
7.
Schlager, Christoph, Gottfried Kirchengast, Jürgen Fuchsberger, Alexander Kann, & Heimo Truhetz. (2019). A spatial evaluation of high-resolution wind fields from empirical and dynamical modeling in hilly and mountainous terrain. Geoscientific model development. 12(7). 2855–2873. 4 indexed citations
8.
Schlager, Christoph, Gottfried Kirchengast, Jürgen Fuchsberger, Alexander Kann, & Heimo Truhetz. (2018). A spatial evaluation of high-resolution wind fields from empirical and dynamical modeling in hilly and mountainous terrain. Biogeosciences (European Geosciences Union). 1 indexed citations
9.
Kann, Alexander, Yong Wang, Aitor Atencia, et al.. (2018). Seamless probabilistic analysis and forecasting: from minutes to days ahead. EGU General Assembly Conference Abstracts. 7962. 1 indexed citations
10.
Wang, Yong, et al.. (2017). On the forecast skill of a convection-permitting ensemble. Geoscientific model development. 10(1). 35–56. 27 indexed citations
11.
Kann, Alexander, et al.. (2015). Evaluation of high-resolution precipitation analyses using a dense station network. Hydrology and earth system sciences. 19(3). 1547–1559. 27 indexed citations
12.
Suklitsch, M., Alexander Kann, & Benedikt Bica. (2015). Towards an integrated probabilistic nowcasting system (En-INCA). Advances in science and research. 12(1). 51–55. 1 indexed citations
13.
Kann, Alexander, Christoph Wittmann, Benedikt Bica, & Clemens Wastl. (2015). On the Impact of NWP Model Background on Very High–Resolution Analyses in Complex Terrain. Weather and Forecasting. 30(4). 1077–1089. 9 indexed citations
14.
Kann, Alexander, et al.. (2015). High‐resolution nowcasting and its application in road maintenance: experiences from the INCA Central European area project. IET Intelligent Transport Systems. 9(5). 539–546. 2 indexed citations
15.
Kann, Alexander, et al.. (2014). Enhanced short‐range forecasting of sub‐inversion cloudiness in complex terrain. Atmospheric Science Letters. 16(1). 1–9. 3 indexed citations
16.
Haiden, Thomas, Alexander Kann, Christoph Wittmann, et al.. (2010). The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region. Weather and Forecasting. 26(2). 166–183. 250 indexed citations
17.
Herrnegger, Mathew, H. P. Nachtnebel, Benedikt Bica, Alexander Kann, & Thomas Haiden. (2010). Enhanced estimation of areal precipitation in an alpine catchment by combining a meteorological nowcasting and analysis system with a hydrological model. EGUGA. 3149. 2 indexed citations
18.
Wang, Yong, et al.. (2010). A strategy for perturbing surface initial conditions in LAMEPS. Atmospheric Science Letters. 11(2). 108–113. 19 indexed citations
19.
Reyniers, Maarten, Laurent Delobbe, Alexander Kann, et al.. (2010). The implementation of the nowcasting system INCA for Belgium: current status.
20.
Kann, Alexander, et al.. (2009). Calibrating 2-m Temperature of Limited-Area Ensemble Forecasts Using High-Resolution Analysis. Monthly Weather Review. 137(10). 3373–3387. 22 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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