Stefano Alessandrini

3.7k total citations
92 papers, 2.6k citations indexed

About

Stefano Alessandrini is a scholar working on Atmospheric Science, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Stefano Alessandrini has authored 92 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Atmospheric Science, 44 papers in Environmental Engineering and 37 papers in Global and Planetary Change. Recurrent topics in Stefano Alessandrini's work include Meteorological Phenomena and Simulations (43 papers), Wind and Air Flow Studies (36 papers) and Atmospheric chemistry and aerosols (22 papers). Stefano Alessandrini is often cited by papers focused on Meteorological Phenomena and Simulations (43 papers), Wind and Air Flow Studies (36 papers) and Atmospheric chemistry and aerosols (22 papers). Stefano Alessandrini collaborates with scholars based in United States, Italy and Denmark. Stefano Alessandrini's co-authors include Luca Delle Monache, Simone Sperati, Guido Cervone, Enrico Ferrero, Pierre Pinson, Branko Kosović, Sue Ellen Haupt, Maria Teresa Vespucci, Rajesh Kumar and Tyler McCandless and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Applied Energy and Atmospheric Environment.

In The Last Decade

Stefano Alessandrini

90 papers receiving 2.5k citations

Peers

Stefano Alessandrini

EEE

GPC

Athanasios Sfetsos Greece

Ramendra Prasad Fiji

Manajit Sengupta United States

Nawin Raj Australia

C. Casanova‐Mateo Spain

Alberto Troccoli United Kingdom

Mehmet Bilgili Türkiye

José A. Ruiz‐Arias Spain

Rubén Urraca Spain

Pierre Ineichen Switzerland

Athanasios Sfetsos Greece

Stefano Alessandrini

722 ×0.7

EEE

316 ×0.3

459 ×0.5

369 ×0.5

GPC

404 ×0.7

Citations per year, relative to Stefano Alessandrini Stefano Alessandrini (= 1×) peers Athanasios Sfetsos

Countries citing papers authored by Stefano Alessandrini

Since Specialization

Citations

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

Fields of papers citing papers by Stefano Alessandrini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefano Alessandrini

This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Alessandrini. A scholar is included among the top collaborators of Stefano Alessandrini 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 Stefano Alessandrini. Stefano Alessandrini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kumar, Rajesh, Piyush Bhardwaj, Cenlin He, et al.. (2025). A long-term high-resolution air quality reanalysis with a public-facing air quality dashboard over the Contiguous United States (CONUS). Earth system science data. 17(5). 1807–1834. 1 indexed citations

Lee, Jared A., Stefano Alessandrini, Ju‐Hye Kim, et al.. (2024). Comparison of CAMS and CMAQ analyses of surface-level PM2.5 and O3 over the conterminous United States (CONUS). Atmospheric Environment. 338. 120833–120833. 1 indexed citations

Ferrero, Enrico, et al.. (2024). Lagrangian model with heat-carrying particles. Advances in science and research. 21. 19–25.

Alessandrini, Stefano, et al.. (2024). Comparing machine learning and inverse modeling approaches for the source term estimation. Air Quality Atmosphere & Health. 17(10). 2169–2186. 1 indexed citations

Alessandrini, Stefano, Ju‐Hye Kim, Pedro A. Jiménez, et al.. (2023). A Gridded Solar Irradiance Ensemble Prediction System Based on WRF-Solar EPS and the Analog Ensemble. Atmosphere. 14(3). 567–567. 4 indexed citations

Ferrero, Enrico, et al.. (2022). A 3D Lagrangian stochastic particle model for the concentration variance dispersion. 3(1-4). 4 indexed citations

Bodini, Nicola, Weiming Hu, Mike Optis, Guido Cervone, & Stefano Alessandrini. (2021). Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble. Wind energy science. 6(6). 1363–1377. 7 indexed citations

Amicarelli, Andrea, Stefano Alessandrini, Giordano Agate, et al.. (2021). A dry deposition scheme for particulate matter coupled with a well-known Lagrangian Stochastic model for pollutant dispersion. Environmental Fluid Mechanics. 21(2). 433–463. 5 indexed citations

Ghude, Sachin D., Rajesh Kumar, Chinmay Jena, et al.. (2020). Evaluation of PM<sub>2.5</sub> Forecast using Chemical Data Assimilation in the WRF-Chem Model: A Novel Initiative Under the Ministry of Earth Sciences Air Quality Early Warning System for Delhi, India. Current Science. 118(11). 1803–1803. 37 indexed citations

10.

Haupt, Sue Ellen, et al.. (2020). Combining Physical Modeling with Artificial Intelligence for Solar Power Forecasting. 2051–2053. 3 indexed citations

11.

Giovannini, Lorenzo, Pedro A. Jiménez, Branko Kosović, et al.. (2019). Turbulence parameterizations for dispersion in sub-kilometer horizontally non-homogeneous flows. Atmospheric Research. 228. 122–136. 25 indexed citations

12.

Monache, Luca Delle, Stefano Alessandrini, Irina V. Djalalova, James M. Wilczak, & Jason C. Knievel. (2018). Air Quality Predictions with an Analog Ensemble. 3 indexed citations

13.

Ferrero, Enrico, et al.. (2017). Model chain for buoyant plume dispersion. International Journal of Environment and Pollution. 62(2/3/4). 200–200. 6 indexed citations

14.

Alessandrini, Stefano, François Vandenberghe, & Joshua P. Hacker. (2017). Definition of typical-day dispersion patterns as a consequence of a hazardous release. International Journal of Environment and Pollution. 62(2/3/4). 305–305. 6 indexed citations

15.

Cervone, Guido, et al.. (2016). Analog Ensemble (AnEn): Optimal Predictor Weighting and Exploitation of Spatial Characteristics in AnEn Generation. AGUFM. 2016. 1 indexed citations

16.

Dinku, Tufa, et al.. (2015). A description and evaluation of FAO satellite rainfall estimation algorithm. Atmospheric Research. 163. 48–60. 14 indexed citations

17.

Mortarini, Luca, et al.. (2014). Analytical offline approach for concentration fluctuations and higher order concentration moments. International Journal of Environment and Pollution. 55(1/2/3/4). 58–58. 6 indexed citations

18.

Alessandrini, Stefano, et al.. (2014). Comparison of the economic impact of different wind power forecast systems for producers. Advances in science and research. 11(1). 49–53. 33 indexed citations

19.

Alessandrini, Stefano, et al.. (2011). An application of ensemble/multi model approach for wind power production forecasting. Advances in science and research. 6(1). 35–37. 9 indexed citations

20.

Pirovano, Guido, Isabelle Coll, Marco Bedogni, et al.. (2007). On the influence of meteorological input on photochemical modelling of a severe episode over a coastal area. Atmospheric Environment. 41(30). 6445–6464. 25 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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