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262 results on '"Marzano, F. S."'

3. Radiometeorological Forecast Model: a New Tool for Deep-Space Link Budget Optimization at Ka-band

Author

Biscarini, M., primary, Di Fabio, S., additional, Montagna, M., additional, De Sanctis, K., additional, Montopoli, M., additional, Iess, L., additional, Bernardini, L., additional, Antonelli, P., additional, Scaccia, P., additional, Milani, L., additional, Spieker, K., additional, Villalvilla, J., additional, Martellucci, A., additional, Lanucara, M., additional, and Marzano, F. S., additional

Published
2023
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7. A New Radar‐Based Statistical Model to Quantify Mass Eruption Rate of Volcanic Plumes.

Author

Mereu, L., Scollo, S., Garcia, A., Sandri, L., Bonadonna, C., and Marzano, F. S.

Subjects
VOLCANIC plumes, VOLCANIC eruptions, MARKOV chain Monte Carlo, MONTE Carlo method, STATISTICAL models
Abstract

Accurate forecasting of volcanic particle (tephra) dispersal and fallout requires a reliable estimation of key Eruption Source Parameters (ESPs) such as the Mass Eruption Rate (QM). QM is usually estimated from the Top Plume Height (HTP) using empirical and analytical models. For the first time, we combine estimates of HTP and QM derived from the same sensor (radar) with mean wind velocity values (vW) for lava‐fountain fed tephra plumes associated with 32 paroxysms of Mt. Etna (Italy) to develop a new statistical model based on a Markov Chain Monte Carlo approach for model parameter estimation. This model is especially designed for application to radar data to quickly infer QM from observed HTP and vW, and estimate the associated uncertainty. It can be easily applied and adjusted to data retrieved by radars worldwide, improving our capacity to quickly estimate QM and related uncertainties required for the tephra dispersal hazard. Plain Language Summary: New radar‐based statistical model useful to quickly infer the mass eruption rate, usually the key parameter to initialize the tephra dispersion model, from the volcanic plume height during the eruptions. Key Points: X‐band radar observations of explosive eruptions can be used to estimate the eruption source parameters and associated uncertaintiesUsing the Markov Chain Monte Carlo model can be performed the statistical analysis of time seriesStatistical parametric model to infer the mass eruption rate from the measured top plume height [ABSTRACT FROM AUTHOR]

Published
2023
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10. Monitoring subglacial volcanic eruption using ground-based C-band radar imagery

Author

Marzano, F. S., Barbieri, S., Picciotti, E., and Karlsdottir, S.

Subjects
Backscattering -- Analysis, Bayesian statistical decision theory -- Usage, Remote sensing -- Analysis, Volcanic activity prediction -- Technology application, Technology application, Business, Earth sciences, Electronics and electrical industries
Published
2010

25. Microwave Tropospheric Scintillation and Excess Attenuation Prediction for Satellite to Earth Links Using 3D High-resolution Meteorological Forecast Models: Data Validation and Case Study

Author

Marziani, A. M., primary, Consalvi, F., additional, Fusco, G., additional, Riva, C., additional, Luini, L., additional, Parodi, A., additional, Pulvirenti, L., additional, Lagasio, M., additional, Biscarini, M., additional, Pierdicca, N., additional, and Marzano, F. S., additional

Published
2019
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27. Atmospheric gas absorption knowledge in the submillimeter: Modeling, field measurements, and uncertainty quantification

Author

European Organisation for the Exploitation of Meteorological Satellites, Department of Energy (US), Swedish National Space Agency, Mattioli, V., Accadia, C., Prigent, C., Crewell, S., Geer, A., Eriksson, P., Fox, S., Pardo Carrión, Juan Ramón, Mlawer, E. J., Cadeddu, M., Bremer, M., de Breuck, C., Smette, A., Cimini, D., Turner, E., Mech, M., Marzano, F. S., Brunel, P., Vidot, J., Bennartz, R., Wehr, T., Di Michele, S., John, V. O., European Organisation for the Exploitation of Meteorological Satellites, Department of Energy (US), Swedish National Space Agency, Mattioli, V., Accadia, C., Prigent, C., Crewell, S., Geer, A., Eriksson, P., Fox, S., Pardo Carrión, Juan Ramón, Mlawer, E. J., Cadeddu, M., Bremer, M., de Breuck, C., Smette, A., Cimini, D., Turner, E., Mech, M., Marzano, F. S., Brunel, P., Vidot, J., Bennartz, R., Wehr, T., Di Michele, S., and John, V. O.

Abstract

descripción no proporcionada por scopus

Published
2019

30. Reflectivity and velocity radar data assimilation for two flash flood events in central Italy: A comparison between 3D and 4D variational methods.

Author

Mazzarella, V., Maiello, I., Ferretti, R., Capozzi, V., Picciotti, E., Alberoni, P. P., Marzano, F. S., and Budillon, G.

Subjects
RADAR meteorology, METEOROLOGICAL research, WEATHER forecasting, HYDROLOGIC cycle, PRECIPITATION forecasting, RADAR, TREND analysis
Abstract

The aim of this study is to provide an evaluation of the impact of two largely used data assimilation techniques, namely three‐ and four‐dimensional variational data assimilation systems (3D‐Var and 4D‐Var), on the forecasting of heavy precipitation events using the Weather Research and Forecasting (WRF) model. For this purpose, two flash flood events in central Italy are analysed. The first occurred on September 14, 2012 during an Intensive Observation Period of the Hydrological cycle in the Mediterranean experiment (HyMeX) campaign, while the other occurred on May 3, 2018. Radial velocity and reflectivity acquired by C‐band weather radars at Mt. Midia (central Italy) and San Pietro Capofiume (northern Italy), as well as conventional observations (SYNOP and TEMP), are assimilated into the WRF model to simulate these damaging flash flood events. In order to evaluate the impact of the 3D‐Var and 4D‐Var assimilation systems on the estimation of short‐term quantitative precipitation forecasts, several experiments are carried out using conventional observations with and without radar data. Rainfall evaluation is performed by means of point‐by‐point and filtering methodologies. The results point to a positive impact of the 4D‐Var technique compared to results without assimilation and with 3D‐Var experiments. More specifically, the 4D‐Var system produces an increase of up to 22% in terms of the Fractions Skill Score compared to 3D‐Var for the first flash flood event, while an increase of about 5% is achieved for the second event. The use of a warm start initialization results in a considerable reduction in the spin‐up time and a significant improvement in the rainfall forecast, suggesting that the initial precipitation spin‐up problem still occurs when using 4D‐Var. [ABSTRACT FROM AUTHOR]

Published
2020
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32. HyMeX-SOP1, the field campaign 1 dedicated to 2 heavy precipitation and flash flooding in 3 the northwestern Mediterranean

Author

Ducrocq, V, Braud, I., Davolio, S., Ferretti, Rossella, Flamant, C., Jansa, A., Kalthoff, N., Richard, E., Taupier Letage, I., Ayral, P. A., Belamari, S., Berne, A., Borga, M., Boudevillain, B., Bock, O., Boichard, J. L., Bouin, M. N., Bousquet, O., Bouvier, C., Chiggiato, J., Cimini, D., Corsmeier, U., Coppola, L., Cocquerez, P., Defer, E., Delanoë, J., Di Girolamo, P., Doerenbecher, A., Drobinski, P., Dufournet, Y., Fourrié, N., Gourley, J. J., Labatut, L., Lambert, D., Le Coz, J., Marzano, F. S., Molinié, G., Montani, A., Nord, G., Nuret, M., Ramage, K., Rison, B., Roussot, O., Said, F., Schwarzenboeck, A., Testor, P., Van Baelen, J., Vincendon, B., Aran, M., and Tamayo, J.

Subjects
heavy precipitation, natural hazards, field experiment
Published
2014

35. Overview of the rst HyMeX Special Observation Period over Italy: observations and model results

Author

Ferretti, Rossella, Pichelli, E., Gentile, S., Maiello, I., Cimini, D., Davolio, S., Miglietta, M. M., Panegrossi, G., Baldini, L., Pasi, F., Marzano, F. S., Zinzi, A., Mariani, S., Casaioli, M., Bartolini, G., Loglisci, N., Montani, A., Marsigli, C., Manzato, A., Pucillo, A., Ferrario, M. E., Colaiuda, V., and Rotunno, R.

Subjects
HyMex campaign, floods, Weather forecast
Published
2013

48. Atmospheric water vapour effects on SPACEBORNE Interferometric SAR imaging: an experiment to compare ground-based measurements, SPACEBORNE radiometers and numerical weather prediction model at different scales

Author

Pierdicca, N., Rocca, F., Rommen, B., Basili, Patrizia, Bonafoni, Stefania, Cimini, D., Ciotti, P., Consalvi, F., Ferretti, R., Foster, W., Marzano, F. S., Mattioli, V., Mazzoni, A., Montopoli, M., Notarpietro, R., Padmanabhan, S., Perissin, D., Pichelli, E., Reising, S., Sahoo, S., and Venuti, G.

Published
2009

50. Atmospheric water vapor effects on spaceborn interferometric SAR imaging: comparison with ground based measurementes and meteorological model simulations at different scales

Author

Pierdicca, N., Rocca, Fabio, Rommen, B., Basili, P., Bonafoni, S., Cimini, D., Ciotti, P., Consalvi, F., Ferretti, R., Foster, W., Marzano, F. S., Mattioli, V., Mazzoni, A., Montopoli, M., Notarpietro, R., Padmanabhan, S., Perissin, D., Pichelli, E., Reising, S., Sahoo, S., and Giovanna VENUTI

Subjects
SAR interferometry, water vapor, atmospheric corrections
Published
2009

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