Articles | Volume 21, issue 11
https://doi.org/10.5194/hess-21-5459-2017
https://doi.org/10.5194/hess-21-5459-2017
Research article
 | 
07 Nov 2017
Research article |  | 07 Nov 2017

Impact of multiple radar reflectivity data assimilation on the numerical simulation of a flash flood event during the HyMeX campaign

Ida Maiello, Sabrina Gentile, Rossella Ferretti, Luca Baldini, Nicoletta Roberto, Errico Picciotti, Pier Paolo Alberoni, and Frank Silvio Marzano

Related authors

A meteorological–hydrological regional ensemble forecast for an early-warning system over small Apennine catchments in Central Italy
Rossella Ferretti, Annalina Lombardi, Barbara Tomassetti, Lorenzo Sangelantoni, Valentina Colaiuda, Vincenzo Mazzarella, Ida Maiello, Marco Verdecchia, and Gianluca Redaelli
Hydrol. Earth Syst. Sci., 24, 3135–3156, https://doi.org/10.5194/hess-24-3135-2020,https://doi.org/10.5194/hess-24-3135-2020, 2020
Short summary
Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy
Vincenzo Mazzarella, Ida Maiello, Vincenzo Capozzi, Giorgio Budillon, and Rossella Ferretti
Adv. Sci. Res., 14, 271–278, https://doi.org/10.5194/asr-14-271-2017,https://doi.org/10.5194/asr-14-271-2017, 2017
Short summary
Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF–3DVAR
I. Maiello, R. Ferretti, S. Gentile, M. Montopoli, E. Picciotti, F. S. Marzano, and C. Faccani
Atmos. Meas. Tech., 7, 2919–2935, https://doi.org/10.5194/amt-7-2919-2014,https://doi.org/10.5194/amt-7-2919-2014, 2014
Overview of the first HyMeX Special Observation Period over Italy: observations and model results
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

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Distribution, trends, and drivers of flash droughts in the United Kingdom
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025,https://doi.org/10.5194/hess-29-1295-2025, 2025
Short summary
Are dependencies of extreme rainfall on humidity more reliable in convection-permitting climate models?
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025,https://doi.org/10.5194/hess-29-1201-2025, 2025
Short summary
Leveraging a radar-based disdrometer network to develop a probabilistic precipitation phase model in eastern Canada
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025,https://doi.org/10.5194/hess-29-1135-2025, 2025
Short summary
Assessment of seasonal soil moisture forecasts over the Central Mediterranean
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025,https://doi.org/10.5194/hess-29-925-2025, 2025
Short summary
Do land models miss key soil hydrological processes controlling soil moisture memory?
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025,https://doi.org/10.5194/hess-29-547-2025, 2025
Short summary

Cited articles

Barker, D. M., Huang, W., Guo, Y.-G., and Bourgeois, A.: A three-dimensional variational (3-D-Var) data assimilation system for use with MM5, NCAR Tech. Note, NCAR/TN-453+STR, UCAR Communications, Boulder, CO, 68 pp., 2003.
Barker, D. M., Huang, W., Guo, Y.-R., Bourgeois, A., and Xiao, Q.: A three-dimensional variational (3-D-Var) data assimilation system for use with MM5: implementation and initial results, Mon. Weather Rev., 132, 897–914, 2004.
Daley, R.: Atmospheric Data Analysis, Cambridge University Press, Cambridge, UK, 1991.
Das, M. K., Chowdhury, M. A. M., Das, S., Debsarma, S. K., and Karmakar, S.: Assimilation of Doppler weather radar data and their impacts on the simulation of squall events during premonsoon season, Nat. Hazards, 77, 901–931, https://doi.org/10.1007/s11069-015-1634-9, 2015.
Davis, A. C., Brown, B., and Bullock, R.: Object-Based verification of precipitation forecasts, Part I: Methodology and application to mesoscale rain areas, Mon. Weather Rev., 134, 1772–1784, 2006a.
Download
Short summary
In this paper the impact of multiple radar reflectivity data assimilation on a flash flood event occurred during SOP1 of the HyMeX campaign has been evaluated: the aim is to build a regionally tuned numerical prediction model and decision-support system for environmental civil protection services within the central Italian regions. The results are encouraging, but a significant number of flash flood cases and a deeper analysis of the meteorology of the region are necessary.
Share