Lightning data assimilation in the WRF-ARW model for short-term rainfall forecasts of three severe storm cases in Italy

Comellas Prat, Albert; Federico, Stefano; Torcasio, Rosa Claudia; Fierro, Alex O.; Dietrich, Stefano

doi:10.1016/j.atmosres.2020.105246

i

Lightning data assimilation in the WRF-ARW model for short-term rainfall forecasts of three severe storm cases in Italy

2021
By Comellas Prat, Albert ; Federico, Stefano ; Torcasio, Rosa Claudia ; ...

Details

Journal Title:

Atmospheric Research
Personal Author:

Comellas Prat, Albert ; Federico, Stefano ; Torcasio, Rosa Claudia ; Fierro, Alex O. ; Dietrich, Stefano
NOAA Program & Office:

NWS (National Weather Service)
Description:

This study analyses the impact of total lightning data assimilation on cloud-resolving short-term (3 and 6 h) precipitation forecasts of three heavy rainfall events that occurred recently in Italy by providing an evaluation of forecast skill using statistical scores for 3-hourly thresholds against observational data from a dense rain gauge network. The experiments are performed with two initial and boundary conditions datasets as a sensitivity test. The three rainfall events have been chosen to better represent the convective regime spectrum: from a short-lived and localised thunderstorm to a long-lived and widespread event, along with a case that had elements of both.
Keywords:

Atmospheric Science
Source:

Atmospheric Research, 247, 105246
DOI:

https://doi.org/10.1016/j.atmosres.2020.105246
ISSN:

0169-8095
Format:

PDF
Publisher:

Elsevier BV
Document Type:

Journal Article
Funding:

Grant no. NA16NWS4680024 ; Grant no. NA18NWS4680063
Rights Information:

Accepted Manuscript
Compliance:

Library
Main Document Checksum:

urn:sha256:bd12e95e047bb301b8f8d1b5cd3ad44900ed16c01a29f4a19bd3307c72d68b06
Download URL:

https://repository.library.noaa.gov/view/noaa/57981/noaa_57981_DS1.pdf
File Type:

[PDF - 5.85 MB ]

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