Heavy Rainfall Identification within the Framework of the LEXIS Project: The Italian Case Study

Abstract

LEXIS (Large-scale EXecution for Industry and Society) H2020 project is currently developing an advanced system for Big Data analysis that takes advantage of interacting large-scale geographically-distributed HPC infrastructure and cloud services. More specifically, LEXIS Weather and Climate Large-Scale Pilot workflows ingest data coming from different sources, like global/regional weather models, conventional and unconventional meteorological observations, application models and socio-economic impact models, in order to provide enhanced meteorological information at the European scale. In the framework of LEXIS Weather and Climate Large-scale Pilot, CIMA Research Foundation is running a 7.5 km resolution WRF (Weather Research and Forecasting) model with European coverage, radar assimilation over the Italian area, and daily updates with 48 hours forecast. WRF data is then processed by ITHACA ERDS (Extreme Rainfall Detection System - http://erds.ithacaweb.org), an early warning system for the monitoring and forecasting of heavy rainfall events. The WRF model provides more detailed information compared to GFS (Global Forecast Systems) data, the most widely used source of rainfall forecasts, implemented in ERDS also. The entire WRF - ERDS workflow was applied to two of the most severe heavy rainfall events that affected Italy in 2020. The first case study is related to an intense rainfall event that affected Toscana during the afternoon and the evening of 4th June 2020. In this case, the Italian Civil Protection issued an orange alert for thunderstorms, on a scale from yellow (low) to orange (medium) to red (high). In several locations of the northern part of the Region more than 100 mm of rainfall were recorded in 3 hours, corresponding to an estimated return period equal to or greater than 200 years. As far as the 24-hours time interval concerns, instead, the estimated return period decreases to 10-50 years. Despite the slight underestimation, WRF model was able to properly forecast the spatial distribution of the rainfall pattern. In addition, thanks to WRF data, precise information about the locations that would be affected by the event were available in the early morning, several hours before the event affected these areas. The second case study is instead related to the heavy rainfall event that affected Palermo (Southern Italy) during the afternoon of 15th July 2020. According to SIAS (Servizio Informativo Agrometeorologico Siciliano) more than 130 mm of rain fell in about 2.5 hours, producing widespread damages due to urban flooding phenomena. The event was not properly forecasted by meteorological models operational at the time of the event, and the Italian Civil Protection did not issue an alert on that area (including Palermo). During that day, in fact, only a yellow alert for thunderstorms was issued on northern-central and western Sicily. Within LEXIS, no alert was issued using GFS data due to the severe underestimation of the amount of forecasted rainfall. Conversely, a WRF modelling experiment (three nested domain with 22.5, 7.5 and 2.5 km grid spacing, innermost over Italy) was executed, by assimilating the National radar reflectivity mosaic and in situ weather stations from the Italian Civil Protection Department, and it resulted in the prediction of a peak rainfall depth of about 35 mm in 1 hour and 55 mm in 3 hours, roughly 30 km far apart the actual affected area, thus values supportive at least a yellow alert over the Palermo area. Obtained results highlight how improved rainfall forecast, made available thanks to the use of HPC resources, significantly increases the capabilities of an operational early warning system in the extreme rainfall detection. Global-scale low-resolution rainfall forecasts like GFS one are in fact widely known as good sources of information for the identification of large-scale precipitation patterns but lack precision for local-scale applications.

Full text

LEXIS (Large-scale EXecu tion for Indust ry and Society) H2020 project is currently developing an advanced system for Big Data analysis tha t takes advantage of interacting large-scale geographically-distributed HPC infrastructure and
cloud services [a].In the framework of LEXIS W eather and Clim ate Large-scale Pilot, CIMA Research Foundation is running a 3 nested domain WRF (Weather Research and Forecasting) model with European coverage, radar
assimilation over the Italian a rea (innermost domain at 2.5 km grid spacing), and daily updates with 48 hours forecast.W RF data is processed by ITHACA ERDS (Extrem e Rainfall Detection System) [b], an early warning system for the
monitoring and forecasting of heavy rainfall events.The entire WRF -ERDS workflow was applied to two of the most severe heavy rainfa ll events that affected Italy during 2020.
In the northern part of the Region more than 100 mm of rainfall were recorde d in 3hours, corresponding to an
estimated return period of abou t 200 years.The Italian Civil Protection Department issued an orange a lert for
thunderstorms.Despite the slight underestimation, WRF model was able to properly forecast the spatial
distribution of the rainfall pa ttern.Thanks to WRF data, information about the locations tha t would be affected by
the event were available in the early morning, several hours before the event affected these areas.
TOSCANA REGION – 4th June 2020
An extreme rainfall event affected Palermo (Sicily) dur ing the
afternoon of 15th July 2020:more than 130 mm of rain f ell in about 2.5
hours, producing widespread damages due to urban flooding
phenomena.
The event was not properly forecasted by meteorologica l models
operational at the time of the event, and the Italian Civil Protection did
not issue an alert on that area (including Palermo).During that d ay,
only ayellow alert for thunderstorms was issu ed on northern-central
and western Sicily, on ascale from yellow (low) to or ange (medium) to
red (high).Furthermore, in the afternoon the radar was not measur ing
due to technical problems.
Within LEXIS, no alert was issued using GFS data due to the severe
underestimation of the amount of forecasted rainfall.Conversely, a
WRF modelling experiment (three nested domains with 22.5, 7.5 and
2.5 km grid spacing, in nermost over Italy) was executed, by
assimilating the National radar reflectivity mosaic and in situ weather
stations from the Italian Civil Protection Department, and it resulted in
the prediction of apeak rain fall depth of about 35 mm in 1hour and 55
mm in 3hours, roughly 30 km far apart the actual affected area, thus
values supportive at least ayellow alert over the Palermo area.
CONSORTIUM CONTACT REFERENCES
[a] Parodi A. et al. (2021). LEXIS W eather a nd Climate Large-Scale Pilot.
https://doi.org/10.1007/978-3-030-50454-0_25
[b] http://erds.ithacaweb.org
[c] Disaster report 4-5 June 2020.CFR Toscana.Available online:
https://www.cfr.toscana.it/supports/ download/eventi/report_evento_04-05 _giugno_2020.pdf
Presenter:Paola Mazzoglio -paol a.mazzoglio@polito.it
LEXIS Coordinator:Jan Martinovic -jan.mar tinovic@vsb.cz
Co-design Manager:Olivier Terzo –olivier.terzo@linksfoundation.com
LEXIS WP7Lead:Antonio Parodi -antonio.pa rodi@cimafoundation.org
LEXIS Project Website:www.lexis -project.eu
CONCLUSIONS
Obtained results highlight how improved rainfall forecast, made available thanks to the use of HPC resources,
significantly increases the capabilities of an operational ea rly warning system in the extreme rainfall detection.
Global-scale low-resolu tion rainfall foreca sts like GFS one are in fact widely known as good sour ces of information
for the identification of large-scale precipitation patterns but lack precisi on for local-scale applications.Future
experiments will include the a ssimilation of atmospheric data from persona l weather stations at the European
scale.
PALERMO –15th July 2020
24-hr rainfall depth
recorded by rain
gauges during
4th June.
Source: [c]
24-hr
rainfall
return
period.
Source: [c]
24-hr rainfall
forecast
provided by
WRF model
during 4th June
Heavy rainfall alerts
provided by ERDS
using WRF data
as input
24-hr
forecast
at 2.5 km
resolution
Heavy
rainfall
alerts
provided by
ERDS using
WRF data
as input
Heavy Rainfall Identification within the Framework of the LEXIS Project: The Italian Case Study
Paola Mazzoglio1,2, Antonio Parodi3, Andre a Parodi3, Lorenza Bovio2, Jan Martinovic4
1Politecnico di Torino (IT ); 2ITHACA (IT); 3CIMA Research Foundation (IT); 4IT4In novations, VSB –Technical University of Ostrava (CZ)
This project has received fu nding from the Euro pean
Union’s Horizon 2020 researc h and innovation
programme under grant agreement No 825532.
START DATE
January 1st,2019
DURATION
36 months
FUNDING /OVERALL
FUNDING
€12.2M / €14M
Large-scale EXecution for
Industry & Society