Stefano Alessandrini

Proj Scientist III

Information

Bio

Stefano Alessandrini is currently a Project Scientist III and science deputy director of the Weather System Assessment Program (WSAP) with the National Center for Atmospheric Research (NCAR), Boulder, Colorado. His main research areas of interest are wind and solar energy probabilistic forecasting, application of air pollution models, environmental physics, turbulence, mesoscale modeling. He has published more than 50 articles regarding probabilistic forecasting of renewable energies and stochastic Lagrangian particle models. He earned a Laurea (M.S.) in Physics with Summa Cum Laude from the University of Milano, Italy (1996), and his Ph.D. at the University of Piemonte Orientale (Italy) (2011) with a topic regarding Lagrangian particle models. Before joining NCAR, he has worked for 12 years in Italy at RSE (Ricerca sul Sistema Energetico) carrying out research activities on mesoscale modeling and probabilistic forecasting of renewable energies. in 2013, he has been the Italian representative for the European Cost action “WIRE” (Weather Intelligence for Renewable Energies).

Publications

Peer-reviewed Journal Articles (55, published, in press, accepted)

1. Zardi, D.; Falocchi, M.; Giovannini, L.; Tirler, W.; Tomasi, E.; Antonacci, G.; Ferrero, E.; Alessandrini, S.; Jimenez, P.A.; Kosovic, B.; et al. The Bolzano Tracer Experiment (BTEX). Bull. Am. Meteorol. Soc. 2020, doi:10.1175/bams-d-19-0024.1.
2. Kumar, R.; Ghude, S.D.; Biswas, M.; Jena, C.; Alessandrini, S.; Debnath, S.; Kulkarni, S.; Sperati, S.; Soni, V.K.; Nanjundiah, R.S.; et al. Enhancing Accuracy of Air Quality and Temperature Forecasts During Paddy Crop Residue Burning Season in Delhi Via Chemical Data Assimilation. J. Geophys. Res. Atmos. 2020, doi:10.1029/2020JD033019.
3. Kumar, R.; Lee, J.A.; Delle Monache, L.; Alessandrini, S. Effect of Meteorological Variability on Fine Particulate Matter Simulations Over the Contiguous United States. J. Geophys. Res. Atmos. 2019, 124, doi:10.1029/2018JD029637.
4. Alessandrini, S.; Mccandless, T. energies The Schaake Shu ffl e Technique to Combine Solar and Wind Power Probabilistic Forecasting. 2020.
5. Haupt, S.E.; McCandless, T.C.; Dettling, S.; Alessandrini, S.; Lee, J.A.; Linden, S.; Petzke, W.; Brummet, T.; Nguyen, N.; Kosović, B.; et al. Combining Artificial Intelligence with Physics-Based Methods for Probabilistic Renewable Energy Forecasting. Energies 2020, doi:10.3390/en13081979.
6. Kosovic, B.; Haupt, S.E.; Adriaansen, D.; Alessandrini, S.; Wiener, G.; Monache, L.D.; Liu, Y.; Linden, S.; Jensen, T.; Cheng, W.; et al. A comprehensive wind power forecasting system integrating artificial intelligence and numerical weather prediction. Energies 2020, 16, doi:10.3390/en13061372.
7. Lewis, W.E.; Rozoff, C.; Alessandrini, S.; Delle Monache, L. Performance of the HWRF Rapid Intensification Analog Ensemble (HWRF RI-AnEn) during the 2017 and 2018 HFIP Real-Time Demonstrations. Weather Forecast. 2020, 841–856, doi:10.1175/waf-d-19-0037.1.
8. Delle Monache, L.; Alessandrini, S.; Djalalova, I.; Wilczak, J.; Knievel, J.C.; Kumar, R. Improving Air Quality Predictions over the United States with an Analog Ensemble. Weather Forecast. 2020, 1–49, doi:10.1175/waf-d-19-0148.1.
9. Cloud, K.A.; Reich, B.J.; Rozoff, C.M.; Alessandrini, S.; Lewis, W.E.; Delle Monache, L. A Feed Forward Neural Network Based on Model Output Statistics for Short-Term Hurricane Intensity Prediction. Weather Forecast. 2019, doi:10.1175/waf-d-18-0173.1.
10. Alessandrini, S.; Sperati, S.; Delle Monache, L. Improving the Analog Ensemble Wind Speed Forecasts for Rare Events. Mon. Weather Rev. 2019, 147, 2677–2692, doi:10.1175/mwr-d-19-0006.1.
11. Ferrero, E.; Alessandrini, S.; Anderson, B.; Tomasi, E.; Jimenez, P.; Meech, S. Lagrangian simulation of smoke plume from fire and validation using ground-based lidar and aircraft measurements. Atmos. Environ. 2019, doi:10.1016/j.atmosenv.2019.06.049.
12. Tomasi, E.; Giovannini, L.; Falocchi, M.; Antonacci, G.; Jiménez, P.A.; Kosovic, B.; Alessandrini, S.; Zardi, D.; Delle Monache, L.; Ferrero, E. Turbulence parameterizations for dispersion in sub-kilometer horizontally non-homogeneous flows. Atmos. Res. 2019, doi:10.1016/j.atmosres.2019.05.018.
13. Yang, D.; Alessandrini, S. An ultra-fast way of searching weather analogs for renewable energy forecasting. Sol. Energy 2019, 185, 255–261, doi:10.1016/j.solener.2019.03.068.
14. Kumar, R.; Delle Monache, L.; Bresch, J.; Saide, P.E.; Tang, Y.; Liu, Z.; da Silva, A.M.; Alessandrini, S.; Pfister, G.; Edwards, D.; et al. Toward Improving Short-Term Predictions of Fine Particulate Matter Over the United States Via Assimilation of Satellite Aerosol Optical Depth Retrievals. J. Geophys. Res. Atmos. 2019, 124, 2753–2773, doi:10.1029/2018JD029009.
15. Kumar, R.; Lee, J.A.; Delle Monache, L.; Alessandrini, S. Effect of Meteorological Variability on Fine Particulate Matter Simulations Over the Contiguous United States. J. Geophys. Res. Atmos. 2019, doi:10.1029/2018JD029637.
16. Yang, J.; Astitha, M.; Delle Monache, L.; Alessandrini, S. An Analog Technique to Improve Storm Wind Speed Prediction Using a Dual NWP Model Approach. Mon. Weather Rev. 2018, 146, 4057–4077, doi:10.1175/MWR-D-17-0198.1.
17. Alessandrini, S.; Monache, L.D.; Rozoff, C.M.; Lewis, W.E. Probabilistic prediction of tropical cyclone intensity with an analog ensemble. Mon. Weather Rev. 2018, 146, 1723–1744, doi:10.1175/MWR-D-17-0314.1.
18. Ferrero, E.; Alessandrini, S.; Vandenberghe, F. Assessment of Planetary-Boundary-Layer Schemes in the Weather Research and Forecasting Model Within and Above an Urban Canopy Layer. Boundary-Layer Meteorol. 2018, doi:10.1007/s10546-018-0349-3.
19. Cervone, G.; Clemente-Harding, L.; Alessandrini, S.; Delle Monache, L. Short-term photovoltaic power forecasting using Artificial Neural Networks and an Analog Ensemble. Renew. Energy 2017, 108, doi:10.1016/j.renene.2017.02.052.
20. Sperati, S.; Alessandrini, S.; Delle Monache, L. Gridded probabilistic weather forecasts with an analog ensemble. Q. J. R. Meteorol. Soc. 2017, 143, doi:10.1002/qj.3137.
21. Keller, J.D.; Monache, L.D.; Alessandrini, S. Statistical downscaling of a high-resolution precipitation reanalysis using the analog ensemble method. J. Appl. Meteorol. Climatol. 2017, 56, doi:10.1175/JAMC-D-16-0380.1.
22. Alessandrini, S.; Vandenberghe, F.; Hacker, J.P. Definition of typical-day dispersion patterns as a consequence of a hazardous release. Int. J. Environ. Pollut. 2017, 62, doi:10.1504/IJEP.2017.089416.
23. Amicarelli, A.; Leuzzi, G.; Monti, P.; Alessandrini, S.; Ferrero, E. A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions. Environ. Fluid Mech. 2017, doi:10.1007/s10652-017-9516-1.
24. Ferrero, E.; Alessandrini, S.; Anfossi, D. Lagrangian simulations of the plume rise in strong capping inversion. Int. J. Environ. Pollut. 2017, 62, 184–199, doi:10.1504/IJEP.2017.089405.
25. Bisignano, A.; Mortarini, L.; Ferrero, E.; Alessandrini, S. Model chain for buoyant plume dispersion. Int. J. Environ. Pollut. 2017, 62, doi:10.1504/IJEP.2017.089406.
26. Jiménez, P.A.; Alessandrini, S.; Haupt, S.E.; Deng, A.; Kosovic, B.; Lee, J.A.; Monache, L.D. The role of unresolved clouds on short-range global horizontal irradiance predictability. Mon. Weather Rev. 2016, 144, doi:10.1175/MWR-D-16-0104.1.
27. Davò, F.; Alessandrini, S.; Sperati, S.; Delle Monache, L.; Airoldi, D.; Vespucci, M.T. Post-processing techniques and principal component analysis for regional wind power and solar irradiance forecasting. Sol. Energy 2016, 134, doi:10.1016/j.solener.2016.04.049.
28. Sperati, S.; Alessandrini, S.; Delle Monache, L. An application of the ECMWF Ensemble Prediction System for short-term solar power forecasting. Sol. Energy 2016, 133, doi:10.1016/j.solener.2016.04.016.
29. Ferrero, E.; Alessandrini, S.; Balanzino, A. Impact of the electric vehicles on the air pollution from a highway. Appl. Energy 2016, 169, doi:10.1016/j.apenergy.2016.01.098.
30. Alessandrini, S.; Delle Monache, L.; Sperati, S.; Cervone, G. An analog ensemble for short-term probabilistic solar power forecast. Appl. Energy 2015, 157, doi:10.1016/j.apenergy.2015.08.011.
31. Sperati, S.; Alessandrini, S.; Pinson, P.; Kariniotakis, G. The “Weather intelligence for renewable energies” benchmarking exercise on short-term forecasting of wind and solar power generation. Energies 2015, 8, doi:10.3390/en8099594.
32. Junk, C.; Monache, L.D.; Alessandrini, S. Analog-based ensemble model output statistics. Mon. Weather Rev. 2015, 143, 2909–2917, doi:10.1175/MWR-D-15-0095.1.
33. Michiorri, A.; Nguyen, H.M.; Alessandrini, S.; Bremnes, J.B.; Dierer, S.; Ferrero, E.; Nygaard, B.E.; Pinson, P.; Thomaidis, N.; Uski, S. Forecasting for dynamic line rating. Renew. Sustain. Energy Rev. 2015, 52, 1713–1730, doi:10.1016/j.rser.2015.07.134.
34. Alessandrini, S.; Delle Monache, L.; Sperati, S.; Nissen, J.N. A novel application of an analog ensemble for short-term wind power forecasting. Renew. Energy 2015, 76, doi:10.1016/j.renene.2014.11.061.
35. Dinku, T.; Alessandrini, S.; Evangelisti, M.; Rojas, O. A description and evaluation of FAO satellite rainfall estimation algorithm. Atmos. Res. 2015, 163, doi:10.1016/j.atmosres.2015.01.020.
36. Junk, C.; Monache, L.D.; Alessandrini, S.; Cervone, G.; Von Bremen, L. Predictor-weighting strategies for probabilistic wind power forecasting with an analog ensemble. Meteorol. Zeitschrift 2015, 24, 361–379, doi:10.1127/metz/2015/0659.
37. Alessandrini, S.; Davò, F.; Sperati, S.; Benini, M.; Delle Monache, L. Comparison of the economic impact of different wind power forecast systems for producers. Adv. Sci. Res. 2014, 11, 49–53, doi:10.5194/asr-11-49-2014.
38. Bisignano, A.; Mortarini, L.; Ferrero, E.; Alessandrini, S. Analytical offline approach for concentration fluctuations and higher order concentration moments. Int. J. Environ. Pollut. 2014, 55, 58–66, doi:10.1504/IJEP.2014.065905.
39. Alessandrini, S.; Sperati, S.; Pinson, P. A comparison between the ECMWF and COSMO Ensemble Prediction Systems applied to short-term wind power forecasting on real data. Appl. Energy 2013, 107, 271–280, doi:10.1016/j.apenergy.2013.02.041.
40. Alessandrini, S.; Ferrero, E.; Anfossi, D. A new Lagrangian method for modelling the buoyant plume rise. Atmos. Environ. 2013, 77, doi:10.1016/j.atmosenv.2013.04.070.
41. Ferrero, E.; Mortarini, L.; Alessandrini, S.; Lacagnina, C. Application of a Bivariate Gamma Distribution for a Chemically Reacting Plume in the Atmosphere. Boundary-Layer Meteorol. 2013, 147, doi:10.1007/s10546-012-9775-9.
42. Ferrero, E.; Mortarini, L.; Alessandrini, S.; Lacagnina, C. A fluctuating plume model for pollutants dispersion with chemical reactions. Int. J. Environ. Pollut. 2012, 48, doi:10.1504/IJEP.2012.049646.
43. Alessandrini, S.; Balanzino, A.; Ferrero, E.; Riva, M. Lagrangian modelling evaluation of the NOx pollution reduction due to electric vehicles introduction. Int. J. Environ. Pollut. 2012, 50, doi:10.1504/IJEP.2012.051193.
44. Alessandrini, S.; Pinson, P.; Hagedorn, R.; Decimi, G.; Sperati, S. An application of ensemble/multi model approach for wind power production forecasting. Adv. Sci. Res 2011, 6, 2010, doi:10.5194/asr-6-35-2011.
45. Alessandrini, S.; Ferrero, E. A Lagrangian particle model with chemical reactions: application in real atmosphere. Int. J. Environ. Pollut. 2011, 47, 97, doi:10.1504/IJEP.2011.047350.
46. Balanzino, A.; Ferrero, E.; Pirovano, G.; Pertot, C.; Causà, M.; Alessandrini, S.; Costa, M.P. Annual simulation of secondary pollution over northern Italy. Int. J. Environ. Pollut. 2011, 45, doi:10.1504/IJEP.2011.040280.
47. Alessandrini, S.; Ferrero, E.; Belfiore, G. A Lagrangian dispersion model with chemical reactions. Int. J. Environ. Pollut. 2011, 44, doi:10.1504/IJEP.2011.038417.
48. Alessandrini, S.; Ferrero, E.; Pertot, C.; Castelli, S.T.; Orlandi, E. Turbulence closure in atmospheric circulation model and its influence on the dispersion. Int. J. Environ. Pollut. 2010, 40, 36–48, doi:10.1504/IJEP.2010.030881.
49. Alessandrini, S.; Ferrero, E. A hybrid Lagrangian-Eulerian particle model for reacting pollutant dispersion in non-homogeneous non-isotropic turbulence. Phys. A Stat. Mech. its Appl. 2009, 388, doi:10.1016/j.physa.2008.12.015.
50. Pirovano, G.; Coll, I.; Bedogni, M.; Alessandrini, S.; Costa, M.P.; Gabusi, V.; Lasry, F.; Menut, L.; Vautard, R. On the influence of meteorological input on photochemical modelling of a severe episode over a coastal area. Atmos. Environ. 2007, 41, doi:10.1016/j.atmosenv.2007.04.011.
51. Anfossi, D.; Alessandrini, S.; Trini Castelli, S.; Ferrero, E.; Oettl, D.; Degrazia, G. Tracer dispersion simulation in low wind speed conditions with a new 2D Langevin equation system. Atmos. Environ. 2006, 40, doi:10.1016/j.atmosenv.2006.05.081.
52. Alessandrini, S.; Ferrero, E.; Pertot, C.; Orlandi, E. Comparison of different dispersion models with tracer experiment. Nuovo Cim. della Soc. Ital. di Fis. C 2005, 28, doi:10.1393/ncc/i2005-10187-0.
53. Alessandrini, S.; Ferrero, E.; Castelli, S.T.; Anfossi, D. Influence of turbulence closure on the simulation of flow and dispersion in complex terrain. Int. J. Environ. Pollut. 2005, 24, doi:10.1504/IJEP.2005.007391.
54. Ferrero, E.; Anfossi, D.; Brusasca, G.; Tinarelli, G.; Alessandrini, S.; Trini Castelli, S. Simulation of atmospheric dispersion in the convective boundary layer: Comparison between two Lagrangian particle models. Int. J. Environ. Pollut. 1997, 8.
55. Anfossi, D.; Ferrero, E.; Tinarelli, G.; Alessandrini, S. A simplified version of the correct boundary conditions for skewed turbulence in Lagrangian particle models. Atmos. Environ. 1997, 31, doi:10.1016/1352-2310(96)00140-9.

Publications and Presentations (42)
Title	Source	Date
Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem	Atmospheric Environment	2021-02-01
Estimation of PM2.5 concentrations in New York State: Understanding the influence of vertical mixing on surface PM2.5 using machine learning	Atmosphere	2020-11-30
Verification of deterministic solar forecasts	Solar Energy	2020-11-01
Enhancing accuracy of air quality and temperature forecasts during paddy crop residue burning season in Delhi via chemical data assimilation	Journal of Geophysical Research: Atmospheres	2020-09-16
A novel ensemble design for probabilistic predictions of fine particulate matter over the contiguous United States (CONUS)	Journal of Geophysical Research: Atmospheres	2020-08-27
Evaluation of PM2.5 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	2020-06-01
The Schaake Shuffle technique to combine solar and wind power probabilistic forecasting	Energies	2020-05-15
Performance of the HWRF rapid intensification analog ensemble (HWRF RI-AnEn) during the 2017 and 2018 HFIP real-time demonstrations	Weather and Forecasting	2020-04-15
Combining artificial intelligence with physics-based methods for probabilistic renewable energy forecasting	Energies	2020-04-02
A comprehensive wind power forecasting system integrating artificial intelligence and numerical weather prediction	Energies	2020-03-16
Turbulence parameterizations for dispersion in sub-kilometer horizontally non-homogeneous flows	Atmospheric Research	2019-11-01
Lagrangian simulation of smoke plume from fire and validation using ground-based lidar and aircraft measurements	Atmospheric Environment	2019-09-01
A feed forward neural network based on model output statistics for short-term hurricane intensity prediction	Weather and Forecasting	2019-08-01
Improving the analog ensemble wind speed forecasts for rare events	Monthly Weather Review	2019-07-01
An ultra-fast way of searching weather analogs for renewable energy forecasting	Solar Energy	2019-06-01
Effect of meteorological variability on fine particulate matter simulations over the contiguous United States	Journal of Geophysical Research: Atmospheres	2019-05-27
Toward improving short‐term predictions of fine particulate matter over the United States via assimilation of satellite aerosol optical depth retrievals	Journal of Geophysical Research: Atmospheres	2019-03-16
A Lagrangian dispersion model with a stochastic equation for the temperature fluctuations	International Journal of Environment and Pollution	2019-01-01
Atmospheric chemistry: A quiet revolution helping people mitigate risks of air pollution	14th iCACGP Symposium and 15th IGAC Science Conference	2018-09-24
Assessment of planetary-boundary-layer schemes in the Weather Research and Forecasting Model within and above an urban canopy layer	Boundary-Layer Meteorology	2018-08-01
Probabilistic prediction of tropical cyclone intensity with an analog ensemble	Monthly Weather Review	2018-06-01
Gridded probabilistic weather forecasts with an analog ensemble	Quarterly Journal of the Royal Meteorological Society	2017-10-11
A stochastic Lagrangian micromixing model for the dispersion of reactive scalars in turbulent flows: role of concentration fluctuations and improvements to the conserved scalar theory under non-homogeneous conditions	Environmental Fluid Mechanics	2017-08-04
Short-term photovoltaic power forecasting using Artificial Neural Networks and an Analog Ensemble	Renewable Energy	2017-08-01
Statistical downscaling of a high-resolution precipitation reanalysis using the analog ensemble method	Journal of Applied Meteorology and Climatology	2017-07-01
Lagrangian simulations of the plume rise in strong capping inversion	International Journal of Environment and Pollution	2017-03-01
Definition of typical-day dispersion patterns as a consequence of a hazardous release	International Journal of Environment and Pollution	2017-03-01
Model chain for buoyant plume dispersion	International Journal of Environment and Pollution	2017-03-01
The role of unresolved clouds on short-range global horizontal irradiance predictability	Monthly Weather Review	2016-09-01
An application of the ECMWF Ensemble Prediction System for short-term solar power forecasting	Solar Energy	2016-08-01
The Sun4Cast® Solar Power Forecasting System: The Result of the Public-Private-Academic Partnership to Advance Solar Power Forecasting	NCAR Technical Note	2016-06-16
Post-processing techniques and principal component analysis for regional wind power and solar irradiance forecasting	Solar Energy	2016-05-18
Impact of the electric vehicles on the air pollution from a highway	Applied Energy	2016-05-01
Forecasting for dynamic line rating	Renewable and Sustainable Energy Reviews	2015-12-01
An analog ensemble for short-term probabilistic solar power forecast	Applied Energy	2015-11-01
A description and evaluation of FAO satellite rainfall estimation algorithm	Atmospheric Research	2015-09-15
The "weather intelligence for renewable energies" benchmarking exercise on short-term forecasting of wind and solar power generation	Energies	2015-09-03
Predictor-weighting strategies for probabilistic wind power forecasting with an analog ensemble	Meteorologische Zeitschrift	2015-07-21
Analog-based ensemble model output statistics	Monthly Weather Review	2015-07-01
A novel application of an analog ensemble for short-term wind power forecasting	Renewable Energy	2015-04-01
Comparison of the economic impact of different wind power forecast systems for producers	Advances in Science and Research	2014-05-19
Probabilistic wind and solar power predictions	Renewable Energy Integration	2014-01-01

Curriculum Vitae

StefanoAlessandrini_CV.docx

Education

Degree	School Name	Country	Field of Study
PhD	Università degli Studi del Piemonte Orientale Amedeo Avogadro	Italy	Geophysics
MS	Universita' Statale	Italy	Physics

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