Articles | Volume 21, issue 2
https://doi.org/10.5194/npg-21-489-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-21-489-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
The role of subsidence in a weakly unstable marine boundary layer: a case study
I. M. Mazzitelli
Dip. Ingegneria dell'Innovazione, Univ. del Salento, 73100 Lecce, Italy
M. Cassol
Multidisciplinary Institute, Fed. Rur. Univ. of Rio de Janeiro, Nova Iguaçu-RJ, CEP 26020-740, Brazil
M. M. Miglietta
CNR-ISAC Institute of Atmospheric Sciences and Climate, UOS di Lecce, 73100 Lecce, Italy
U. Rizza
CNR-ISAC Institute of Atmospheric Sciences and Climate, UOS di Lecce, 73100 Lecce, Italy
A. M. Sempreviva
CNR-ISAC Institute of Atmospheric Sciences and Climate, UOS di Lamezia Terme, 88046 Lamezia Terme, Italy
Technical University of Denmark, Wind Energy Department, Risoe Campus, Roskilde, Denmark
A. S. Lanotte
CNR-ISAC Institute of Atmospheric Sciences and Climate, UOS di Lecce, 73100 Lecce, Italy
INFN, Sez. di Lecce, 73100 Lecce, Italy
Related authors
No articles found.
Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego Saul Carrió, Stavros Dafis, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, Claudio Sanchez, and Emmanouil Flaounas
Weather Clim. Dynam., 5, 1187–1205, https://doi.org/10.5194/wcd-5-1187-2024, https://doi.org/10.5194/wcd-5-1187-2024, 2024
Short summary
Short summary
Cyclone Ianos of September 2020 was a high-impact but poorly predicted medicane (Mediterranean hurricane). A community effort of numerical modelling provides robust results to improve prediction. It is found that the representation of local thunderstorms controlled the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help us understand the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
Emmanouil Flaounas, Stavros Dafis, Silvio Davolio, Davide Faranda, Christian Ferrarin, Katharina Hartmuth, Assaf Hochman, Aristeidis Koutroulis, Samira Khodayar, Mario Marcello Miglietta, Florian Pantillon, Platon Patlakas, Michael Sprenger, and Iris Thurnherr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2809, https://doi.org/10.5194/egusphere-2024-2809, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Storm Daniel (2023) is one of the most catastrophic ones ever documented in the Mediterranean. Our results highlight the different dynamics and therefore the different predictability skill of precipitation, its extremes and impacts that have been produced in Greece and Libya, the two most affected countries. Our approach concerns a holistic analysis of the storm by articulating dynamics, weather prediction, hydrological and oceanographic implications, climate extremes and attribution theory.
Yuriy Marykovskiy, Thomas Clark, Justin Day, Marcus Wiens, Charles Henderson, Julian Quick, Imad Abdallah, Anna Maria Sempreviva, Jean-Paul Calbimonte, Eleni Chatzi, and Sarah Barber
Wind Energ. Sci., 9, 883–917, https://doi.org/10.5194/wes-9-883-2024, https://doi.org/10.5194/wes-9-883-2024, 2024
Short summary
Short summary
This paper delves into the crucial task of transforming raw data into actionable knowledge which can be used by advanced artificial intelligence systems – a challenge that spans various domains, industries, and scientific fields amid their digital transformation journey. This article underscores the significance of cross-industry collaboration and learning, drawing insights from sectors leading in digitalisation, and provides strategic guidance for further development in this area.
Emmanouil Flaounas, Leonardo Aragão, Lisa Bernini, Stavros Dafis, Benjamin Doiteau, Helena Flocas, Suzanne L. Gray, Alexia Karwat, John Kouroutzoglou, Piero Lionello, Mario Marcello Miglietta, Florian Pantillon, Claudia Pasquero, Platon Patlakas, María Ángeles Picornell, Federico Porcù, Matthew D. K. Priestley, Marco Reale, Malcolm J. Roberts, Hadas Saaroni, Dor Sandler, Enrico Scoccimarro, Michael Sprenger, and Baruch Ziv
Weather Clim. Dynam., 4, 639–661, https://doi.org/10.5194/wcd-4-639-2023, https://doi.org/10.5194/wcd-4-639-2023, 2023
Short summary
Short summary
Cyclone detection and tracking methods (CDTMs) have different approaches in defining and tracking cyclone centers. This leads to disagreements on extratropical cyclone climatologies. We present a new approach that combines tracks from individual CDTMs to produce new composite tracks. These new tracks are shown to correspond to physically meaningful systems with distinctive life stages.
Roberto Ingrosso, Piero Lionello, Mario Marcello Miglietta, and Gianfausto Salvadori
Nat. Hazards Earth Syst. Sci., 23, 2443–2448, https://doi.org/10.5194/nhess-23-2443-2023, https://doi.org/10.5194/nhess-23-2443-2023, 2023
Short summary
Short summary
Tornadoes represent disruptive and dangerous weather events. The prediction of these small-scale phenomena depends on the resolution of present weather forecast and climatic projections. This work discusses the occurrence of tornadoes in terms of atmospheric variables and provides analytical expressions for their conditional probability. These formulas represent a tool for tornado alert systems and for estimating the future evolution of tornado frequency and intensity in climate projections.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
Short summary
Short summary
The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Andrew Clifton, Sarah Barber, Andrew Bray, Peter Enevoldsen, Jason Fields, Anna Maria Sempreviva, Lindy Williams, Julian Quick, Mike Purdue, Philip Totaro, and Yu Ding
Wind Energ. Sci., 8, 947–974, https://doi.org/10.5194/wes-8-947-2023, https://doi.org/10.5194/wes-8-947-2023, 2023
Short summary
Short summary
Wind energy creates huge amounts of data, which can be used to improve plant design, raise efficiency, reduce operating costs, and ease integration. These all contribute to cheaper and more predictable energy from wind. But realising the value of data requires a digital transformation that brings
grand challengesaround data, culture, and coopetition. This paper describes how the wind energy industry could work with R&D organisations, funding agencies, and others to overcome them.
Mauro Morichetti, Sasha Madronich, Giorgio Passerini, Umberto Rizza, Enrico Mancinelli, Simone Virgili, and Mary Barth
Geosci. Model Dev., 15, 6311–6339, https://doi.org/10.5194/gmd-15-6311-2022, https://doi.org/10.5194/gmd-15-6311-2022, 2022
Short summary
Short summary
In the present study, we explore the effect of making simple changes to the existing WRF-Chem MEGAN v2.04 emissions to provide MEGAN updates that can be used independently of the land surface model chosen. The changes made to the MEGAN algorithm implemented in WRF-Chem were the following: (i) update of the emission activity factors, (ii) update of emission factor values for each plant functional type (PFT), and (iii) the assignment of the emission factor by PFT to isoprene.
Emmanouil Flaounas, Silvio Davolio, Shira Raveh-Rubin, Florian Pantillon, Mario Marcello Miglietta, Miguel Angel Gaertner, Maria Hatzaki, Victor Homar, Samira Khodayar, Gerasimos Korres, Vassiliki Kotroni, Jonilda Kushta, Marco Reale, and Didier Ricard
Weather Clim. Dynam., 3, 173–208, https://doi.org/10.5194/wcd-3-173-2022, https://doi.org/10.5194/wcd-3-173-2022, 2022
Short summary
Short summary
This is a collective effort to describe the state of the art in Mediterranean cyclone dynamics, climatology, prediction (weather and climate scales) and impacts. More than that, the paper focuses on the future directions of research that would advance the broader field of Mediterranean cyclones as a whole. Thereby, we propose interdisciplinary cooperation and additional modelling and forecasting strategies, and we highlight the need for new impact-oriented approaches to climate prediction.
Mario Marcello Miglietta and Silvio Davolio
Hydrol. Earth Syst. Sci., 26, 627–646, https://doi.org/10.5194/hess-26-627-2022, https://doi.org/10.5194/hess-26-627-2022, 2022
Short summary
Short summary
The main results emerging from the HyMeX SOP1 campaign and in the subsequent research activity in three Italian target areas are highlighted through conceptual models and through the identification of the relevant mesoscale environmental characteristics conducive to heavy rain events.
Enzo Papandrea, Stefano Casadio, Elisa Castelli, Bianca Maria Dinelli, and Mario Marcello Miglietta
Atmos. Meas. Tech., 12, 6683–6693, https://doi.org/10.5194/amt-12-6683-2019, https://doi.org/10.5194/amt-12-6683-2019, 2019
Short summary
Short summary
Lee waves have been detected in clear-sky conditions over the Mediterranean Sea using the total column water vapour (TCWV) fields. The products were generated applying the Advanced Infra-Red WAter Vapour Estimator (AIRWAVE) retrieval algorithm to the thermal infrared measurements of the Along Track Scanning Radiometer (ATSR) instrument series. A subset of the occurrences has been compared with both independent observations and model simulations.
Bjarke T. Olsen, Andrea N. Hahmann, Anna Maria Sempreviva, Jake Badger, and Hans E. Jørgensen
Wind Energ. Sci., 2, 211–228, https://doi.org/10.5194/wes-2-211-2017, https://doi.org/10.5194/wes-2-211-2017, 2017
Short summary
Short summary
Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented. The study shows that model errors are larger and agreement between models smaller at inland sites and near the surface.
Andrea Tateo, Mario Marcello Miglietta, Francesca Fedele, Micaela Menegotto, Alfonso Monaco, and Roberto Bellotti
Adv. Sci. Res., 14, 95–102, https://doi.org/10.5194/asr-14-95-2017, https://doi.org/10.5194/asr-14-95-2017, 2017
Umberto Rizza, Francesca Barnaba, Mario Marcello Miglietta, Cristina Mangia, Luca Di Liberto, Davide Dionisi, Francesca Costabile, Fabio Grasso, and Gian Paolo Gobbi
Atmos. Chem. Phys., 17, 93–115, https://doi.org/10.5194/acp-17-93-2017, https://doi.org/10.5194/acp-17-93-2017, 2017
L. Tiriolo, R. C. Torcasio, S. Montesanti, A. M. Sempreviva, C. R. Calidonna, C. Transerici, and S. Federico
Adv. Sci. Res., 12, 37–44, https://doi.org/10.5194/asr-12-37-2015, https://doi.org/10.5194/asr-12-37-2015, 2015
Short summary
Short summary
We show a study of the prediction of power production of a wind farm located in Central Italy using RAMS model for wind speed forecast.
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
F. De Biasio, M. M. Miglietta, S. Zecchetto, and A. della Valle
Adv. Sci. Res., 11, 41–48, https://doi.org/10.5194/asr-11-41-2014, https://doi.org/10.5194/asr-11-41-2014, 2014
S. Davolio, M. M. Miglietta, T. Diomede, C. Marsigli, and A. Montani
Hydrol. Earth Syst. Sci., 17, 2107–2120, https://doi.org/10.5194/hess-17-2107-2013, https://doi.org/10.5194/hess-17-2107-2013, 2013