Articles | Volume 19, issue 8
https://doi.org/10.5194/nhess-19-1839-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-19-1839-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The impact of lightning and radar reflectivity factor data assimilation on the very short-term rainfall forecasts of RAMS@ISAC: application to two case studies in Italy
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Rosa Claudia Torcasio
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Elenio Avolio
ISAC-CNR, zona Industriale comparto 15, 88046, Lamezia Terme, Italy
Olivier Caumont
CNRM UMR 3589, University of Toulouse, Météo-France, CNRS, 42 avenue G. Coriolis, 31057 Toulouse, France
Mario Montopoli
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Luca Baldini
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
Gianfranco Vulpiani
Dipartimento Protezione Civile Nazionale Ufficio III – Attività Tecnico Scientifiche per la Previsione e Prevenzione dei Rischi, 00189, Rome, Italy
Stefano Dietrich
ISAC-CNR, via del Fosso del Cavaliere 100, 00133 Rome, Italy
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Cited
18 citations as recorded by crossref.
- Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method—A Case Study of a Mesoscale Convective System R. Gan et al. 10.1007/s13351-021-0092-4
- Overview towards improved understanding of the mechanisms leading to heavy precipitation in the western Mediterranean: lessons learned from HyMeX S. Khodayar et al. 10.5194/acp-21-17051-2021
- Application of Lightning Data Assimilation for the 10 October 2018 Case Study over Sardinia R. Torcasio et al. 10.3390/atmos11050541
- Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy V. Capecchi et al. 10.3390/w13131727
- An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system H. Wang et al. 10.1016/j.atmosres.2020.104994
- Investigating 3D and 4D variational rapid-update-cycling assimilation of weather radar reflectivity for a heavy rain event in central Italy V. Mazzarella et al. 10.5194/nhess-21-2849-2021
- The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6 A. Caldas-Alvarez et al. 10.5194/wcd-2-561-2021
- Characterizing Consecutive Flooding Events after the 2017 Mt. Salto Wildfires (Southern Italy): Hazard and Emergency Management Implications G. Esposito et al. 10.3390/w11122663
- Assimilation of the Maximum Vertical Velocity Converted From Total Lightning Data Through the EnSRF Method R. Gan et al. 10.1029/2020JD034300
- Impacts of the radar data assimilation frequency and large-scale constraint on the short-term precipitation forecast of a severe convection case E. Lin et al. 10.1016/j.atmosres.2021.105590
- Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms Y. Chen et al. 10.3390/rs12071165
- Lightning data assimilation in the WRF-ARW model for short-term rainfall forecasts of three severe storm cases in Italy A. Comellas Prat et al. 10.1016/j.atmosres.2020.105246
- Multiple tornadoes in the Italian Ionian regions: Observations, sensitivity tests and mesoscale analysis of convective storm environmental parameters E. Avolio & M. Miglietta 10.1016/j.atmosres.2021.105800
- A Scheme to Suppress Spurious Convection by Assimilating the "Zero" Column Maximum Vertical Velocity R. Gan et al. 10.1029/2021JD035536
- Potential use of the GLM for nowcasting and data assimilation E. Vendrasco et al. 10.1016/j.atmosres.2020.105019
- Impact of Radar Reflectivity and Lightning Data Assimilation on the Rainfall Forecast and Predictability of a Summer Convective Thunderstorm in Southern Italy S. Federico et al. 10.3390/atmos12080958
- The impact of lightning and radar reflectivity factor data assimilation on the very short-term rainfall forecasts of RAMS@ISAC: application to two case studies in Italy S. Federico et al. 10.5194/nhess-19-1839-2019
- The Precipitation Structure of the Mediterranean Tropical-Like Cyclone Numa: Analysis of GPM Observations and Numerical Weather Prediction Model Simulations A. Marra et al. 10.3390/rs11141690
16 citations as recorded by crossref.
- Assimilation of Radar and Cloud-to-Ground Lightning Data Using WRF-3DVar Combined with the Physical Initialization Method—A Case Study of a Mesoscale Convective System R. Gan et al. 10.1007/s13351-021-0092-4
- Overview towards improved understanding of the mechanisms leading to heavy precipitation in the western Mediterranean: lessons learned from HyMeX S. Khodayar et al. 10.5194/acp-21-17051-2021
- Application of Lightning Data Assimilation for the 10 October 2018 Case Study over Sardinia R. Torcasio et al. 10.3390/atmos11050541
- Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy V. Capecchi et al. 10.3390/w13131727
- An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system H. Wang et al. 10.1016/j.atmosres.2020.104994
- Investigating 3D and 4D variational rapid-update-cycling assimilation of weather radar reflectivity for a heavy rain event in central Italy V. Mazzarella et al. 10.5194/nhess-21-2849-2021
- The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6 A. Caldas-Alvarez et al. 10.5194/wcd-2-561-2021
- Characterizing Consecutive Flooding Events after the 2017 Mt. Salto Wildfires (Southern Italy): Hazard and Emergency Management Implications G. Esposito et al. 10.3390/w11122663
- Assimilation of the Maximum Vertical Velocity Converted From Total Lightning Data Through the EnSRF Method R. Gan et al. 10.1029/2020JD034300
- Impacts of the radar data assimilation frequency and large-scale constraint on the short-term precipitation forecast of a severe convection case E. Lin et al. 10.1016/j.atmosres.2021.105590
- Case Study of a Retrieval Method of 3D Proxy Reflectivity from FY-4A Lightning Data and Its Impact on the Assimilation and Forecasting for Severe Rainfall Storms Y. Chen et al. 10.3390/rs12071165
- Lightning data assimilation in the WRF-ARW model for short-term rainfall forecasts of three severe storm cases in Italy A. Comellas Prat et al. 10.1016/j.atmosres.2020.105246
- Multiple tornadoes in the Italian Ionian regions: Observations, sensitivity tests and mesoscale analysis of convective storm environmental parameters E. Avolio & M. Miglietta 10.1016/j.atmosres.2021.105800
- A Scheme to Suppress Spurious Convection by Assimilating the "Zero" Column Maximum Vertical Velocity R. Gan et al. 10.1029/2021JD035536
- Potential use of the GLM for nowcasting and data assimilation E. Vendrasco et al. 10.1016/j.atmosres.2020.105019
- Impact of Radar Reflectivity and Lightning Data Assimilation on the Rainfall Forecast and Predictability of a Summer Convective Thunderstorm in Southern Italy S. Federico et al. 10.3390/atmos12080958
2 citations as recorded by crossref.
- The impact of lightning and radar reflectivity factor data assimilation on the very short-term rainfall forecasts of RAMS@ISAC: application to two case studies in Italy S. Federico et al. 10.5194/nhess-19-1839-2019
- The Precipitation Structure of the Mediterranean Tropical-Like Cyclone Numa: Analysis of GPM Observations and Numerical Weather Prediction Model Simulations A. Marra et al. 10.3390/rs11141690
Latest update: 09 Jun 2023
Short summary
This study shows the possibility to improve the weather forecast at the very short range (0–3 h) using lightning and/or radar reflectivity observations. We consider two challenging events that occurred over Italy, named Serrano and Livorno, characterized by moderate and exceptional rainfall, respectively.
The improvement given to the forecast by using the lightning and/or radar reflectivity observations is considerable. The best performance is obtained when using both data.
This study shows the possibility to improve the weather forecast at the very short range (0–3 h)...
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