Daniele Nerini

1.1k total citations
24 papers, 636 citations indexed

About

Daniele Nerini is a scholar working on Atmospheric Science, Global and Planetary Change and Artificial Intelligence. According to data from OpenAlex, Daniele Nerini has authored 24 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Atmospheric Science, 14 papers in Global and Planetary Change and 2 papers in Artificial Intelligence. Recurrent topics in Daniele Nerini's work include Meteorological Phenomena and Simulations (17 papers), Precipitation Measurement and Analysis (12 papers) and Climate variability and models (7 papers). Daniele Nerini is often cited by papers focused on Meteorological Phenomena and Simulations (17 papers), Precipitation Measurement and Analysis (12 papers) and Climate variability and models (7 papers). Daniele Nerini collaborates with scholars based in Switzerland, Finland and Australia. Daniele Nerini's co-authors include Urs Germann, Loris Foresti, Jussi Leinonen, Alexis Berne, Ioannis V. Sideris, Seppo Pulkkinen, Carlos Velasco‐Forero, Alan Seed, Nikola Bešič and Giuseppe Jurman and has published in prestigious journals such as Applied Energy, IEEE Transactions on Geoscience and Remote Sensing and Monthly Weather Review.

In The Last Decade

Daniele Nerini

21 papers receiving 623 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniele Nerini Switzerland 10 531 400 118 62 30 24 636
Dingchen Hou United States 12 661 1.2× 607 1.5× 119 1.0× 49 0.8× 5 0.2× 19 748
Clive Pierce United Kingdom 8 639 1.2× 539 1.3× 101 0.9× 85 1.4× 24 0.8× 11 712
Yumeng Tao United States 12 281 0.5× 253 0.6× 144 1.2× 113 1.8× 8 0.3× 16 521
Seppo Pulkkinen Finland 10 304 0.6× 250 0.6× 84 0.7× 57 0.9× 15 0.5× 29 411
Tim Hewson United Kingdom 18 1.0k 1.9× 917 2.3× 83 0.7× 41 0.7× 35 1.2× 32 1.1k
Kevin L. Manross United States 7 534 1.0× 437 1.1× 136 1.2× 20 0.3× 11 0.4× 10 614
Leiming Ma China 11 321 0.6× 200 0.5× 114 1.0× 17 0.3× 19 0.6× 36 419
Patrick Gatlin United States 17 1.1k 2.0× 686 1.7× 298 2.5× 20 0.3× 11 0.4× 57 1.2k
Jiaxin Xie China 9 107 0.2× 154 0.4× 145 1.2× 231 3.7× 33 1.1× 20 447

Countries citing papers authored by Daniele Nerini

Since Specialization
Citations

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

Fields of papers citing papers by Daniele Nerini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniele Nerini

This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Nerini. A scholar is included among the top collaborators of Daniele Nerini 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 Daniele Nerini. Daniele Nerini 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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Pulkkinen, Seppo, et al.. (2025). Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall. Geoscientific model development. 18(5). 1851–1878. 1 indexed citations
3.
4.
Foresti, Loris, Daniele Nerini, Aitor Atencia, et al.. (2024). A quest for precipitation attractors in weather radar archives. Nonlinear processes in geophysics. 31(2). 259–286.
5.
Nerini, Daniele, et al.. (2023). Physics-Constrained Deep Learning Postprocessing of Temperature and Humidity. 2(4). 6 indexed citations
6.
Imhoff, Ruben, Lesley De Cruz, Claudia Brauer, et al.. (2023). Scale‐dependent blending of ensemble rainfall nowcasts and numerical weather prediction in the open‐source pysteps library. Quarterly Journal of the Royal Meteorological Society. 149(753). 1335–1364. 8 indexed citations
7.
Folini, Doris, et al.. (2023). Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection. Applied Energy. 351. 121775–121775. 14 indexed citations
8.
Boettcher, Maxi, Andreas Schäfler, Michael Sprenger, et al.. (2021). Lagrangian matches between observations from aircraft, lidar and radar in a warm conveyor belt crossing orography. Atmospheric chemistry and physics. 21(7). 5477–5498. 7 indexed citations
9.
Boettcher, Maxi, Andreas Schäfler, Michael Sprenger, et al.. (2020). Lagrangian matches between observations from aircraft, lidar and radar in an orographic warmconveyor belt. elib (German Aerospace Center). 1 indexed citations
10.
Nerini, Daniele, et al.. (2020). Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events. Atmosphere. 11(3). 267–267. 68 indexed citations
11.
Sideris, Ioannis V., Loris Foresti, Daniele Nerini, & Urs Germann. (2020). NowPrecip: localized precipitation nowcasting in the complex terrain of Switzerland. Quarterly Journal of the Royal Meteorological Society. 146(729). 1768–1800. 22 indexed citations
12.
Pulkkinen, Seppo, Daniele Nerini, Carlos Velasco‐Forero, et al.. (2019). Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0). Geoscientific model development. 12(10). 4185–4219. 161 indexed citations
13.
Pulkkinen, Seppo, Daniele Nerini, Carlos Velasco‐Forero, et al.. (2019). pysteps - a Community-Driven Open-Source Library for Precipitation Nowcasting. Arcimis (State Meteorological Agency). 2 indexed citations
14.
Foresti, Loris, Ioannis V. Sideris, Daniele Nerini, Lea Beusch, & Urs Germann. (2019). Using a 10-Year Radar Archive for Nowcasting Precipitation Growth and Decay: A Probabilistic Machine Learning Approach. Weather and Forecasting. 34(5). 1547–1569. 43 indexed citations
15.
Sideris, Ioannis V., Loris Foresti, Urs Germann, & Daniele Nerini. (2019). NowPrecip: Localized precipitation nowcasting in the complex terrain of Switzerland. Repository for Publications and Research Data (ETH Zurich). 108. 3 indexed citations
16.
Nerini, Daniele, Loris Foresti, Daniel Leuenberger, Sylvain Robert, & Urs Germann. (2019). A Reduced-Space Ensemble Kalman Filter Approach for Flow-Dependent Integration of Radar Extrapolation Nowcasts and NWP Precipitation Ensembles. Monthly Weather Review. 147(3). 987–1006. 34 indexed citations
17.
Foresti, Loris, Daniele Nerini, Ioannis V. Sideris, et al.. (2018). Non-stationary radar precipitation ensembles: a stochastic nested generator and orographic precipitation growth and decay trends. EGU General Assembly Conference Abstracts. 6739. 1 indexed citations
18.
Foresti, Loris, Ioannis V. Sideris, Luca Panziera, Daniele Nerini, & Urs Germann. (2018). A 10‐year radar‐based analysis of orographic precipitation growth and decay patterns over the Swiss Alpine region. Quarterly Journal of the Royal Meteorological Society. 144(716). 2277–2301. 29 indexed citations
19.
Nerini, Daniele, Nikola Bešič, Ioannis V. Sideris, Urs Germann, & Loris Foresti. (2017). A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transform. Hydrology and earth system sciences. 21(6). 2777–2797. 58 indexed citations
20.
Nerini, Daniele, Zed Zulkafli, Li-Pen Wang, et al.. (2015). A Comparative Analysis of TRMM–Rain Gauge Data Merging Techniques at the Daily Time Scale for Distributed Rainfall–Runoff Modeling Applications. Journal of Hydrometeorology. 16(5). 2153–2168. 67 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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