2,209 research outputs found
Data Assimilation in high resolution Numerical Weather Prediction models to improve forecast skill of extreme hydrometeorological events.
No full textThe complex orography typical of the Mediterranean area supports the
formation, mainly during the fall season, of the so-called back-building
Mesoscale Convective Systems (MCS) producing torrential rainfall often
resulting into flash floods. These events are hardly predictable from a hydrometeorological
standpoint and may cause significant amount of fatalities and
socio-economic damages. Liguria region is characterized by small catchments
with very short hydrological response time, and it has been proven to be very
exposed to back-building MCSs occurrence. Indeed this region between 2011
and 2014 has been hit by three intense back-building MCSs causing a total
death toll of 20 people and several hundred million of euros of damages.
Building on the existing relationship between significant lightning activity and
deep convection and precipitation, the first part of this work assesses the
performance of the Lightning Potential Index, as a measure of the potential for
charge generation and separation that leads to lightning occurrence in clouds,
for the back-building Mesoscale Convective System which hit Genoa city (Italy)
in 2014. An ensemble of Weather Research and Forecasting simulations at
cloud-permitting grid spacing (1 km) with different microphysical
parameterizations is performed and compared to the available observational
radar and lightning data. The results allow gaining a deeper understanding of
the role of lightning phenomena in the predictability of back-building Mesoscale
Convective Systems often producing flash flood over western Mediterranean
complex topography areas. Despite these positive and promising outcomes for
the understanding highly-impacting MCS, the main forecasting issue, namely
the uncertainty in the correct reproduction of the convective field (location,
timing, and intensity) for this kind of events still remains open. Thus, the second
part of the work assesses the predictive capability, for a set of back-building
Liguria MCS episodes (including Genoa 2014), of a hydro-meteorological
forecasting chain composed by a km-scale cloud resolving WRF model,
including a 6 hour cycling 3DVAR assimilation of radar reflectivity and
conventional ground sensors data, by the Rainfall Filtered Autoregressive
Model (RainFARM) and the fully distributed hydrological model Continuum. A
rich portfolio of WRF 3DVAR direct and indirect reflectivity operators, has been
explored to drive the meteorological component of the proposed forecasting
chain. The results confirm the importance of rapidly refreshing and data
intensive 3DVAR for improving first quantitative precipitation forecast, and,
subsequently flash-floods occurrence prediction in case of back-building MCSs
events. The third part of this work devoted the improvement of severe hydrometeorological
events prediction has been undertaken in the framework of the
European Space Agency (ESA) STEAM (SaTellite Earth observation for
Atmospheric Modelling) project aiming at investigating, new areas of synergy
between high-resolution numerical atmosphere models and data from
spaceborne remote sensing sensors, with focus on Copernicus Sentinels 1, 2
and 3 satellites and Global Positioning System stations. In this context, the
Copernicus Sentinel satellites represent an important source of data, because
they provide a set of high-resolution observations of physical variables (e.g. soil
moisture, land/sea surface temperature, wind speed, columnar water vapor) to
be used in NWP models runs operated at cloud resolving grid spacing . For this
project two different use cases are analyzed: the Livorno flash flood of 9 Sept
2017, with a death tool of 9 people, and the Silvi Marina flood of 15 November
2017. Overall the results show an improvement of the forecast accuracy by
assimilating the Sentinel-1 derived wind and soil moisture products as well as
the Zenith Total Delay assimilation both from GPS stations and SAR
Interferometry technique applied to Sentinel-1 data
Investigation of the weather conditions during the collapse of the Morandi Bridge in Genoa on 14 August 2018
No full textOn 14 August 2018, Morandi Bridge in Genoa, Italy, collapsed sending vehicles and tons of rubble to the ground about 40 m below and killing 43 people. Preliminary investigations indicated poor design, questionable building practices and insufficient maintenance or a combination of these factors as a possible cause of collapse. However, at the time of collapse, a thunderstorm associated with strong winds, lightning and rain was developed over the city. While it is still not clear whether or not it played a role in this disaster, the present paper documents the weather conditions during the collapse and analyzes in detail a downburst that occurred at the time of the collapse a few kilometers from the bridge. The thunderstorm is analyzed using direct and remote measurements in an attempt to describe the evolution of the cumulonimbus cloud as it approached the coast from the sea. The detected downburst is investigated using a lidar scanner and the anemometric network in the Port of Genoa. The paper shows that the unique lidar measurements enabled a partial reconstruction of the gust front shape and displacement velocity. The Weather Research and Forecasting (WRF) simulations, carried out with three different forcing conditions, forecasted the cumuliform convection at larger scales but did not accurately replicate the downburst signature at the surface that was measured by radar, lidar, and anemometers. This result demonstrates that the localized wind conditions during the collapse time could not be operationally forecasted
Investigation of the Weather Conditions During the Collapse of the Morandi Bridge in Genoa on 14 August 2018 Using Field Observations and WRF Model
No full textOn 14 August 2018, Morandi Bridge in Genoa, Italy, collapsed to the ground that was 40 m below. This tragedy killed 43 people. Preliminary investigations indicated poor design, questionable building practices, and insufficient maintenance—or a combination of these factors—as a possible cause of the collapse. However, around the collapse time, a thunderstorm associated with strong winds, lightning, and rain also developed over the city. While it is unclear if this thunderstorm played a role in the collapse, the present study examines the weather conditions before and during the bridge collapse. The study particularly focuses on the analysis of a downburst that was observed around the collapse time and a few kilometers away from the bridge. Direct and remote sensing measurements are used to describe the evolution of the thunderstorm during its approached from the sea to the city. The Doppler lidar measurements allowed the reconstruction of the gust front shape and the evaluation of its displacement velocity of 6.6 m s−1 towards the lidar. The Weather Research and Forecasting simulations highlighted that it is still challenging to forecast localized thunderstorms with operational setups. The study has shown that assimilation of radar reflectivity improves the timing and reconstruction of the gust front observed by local measurements
How the spatial structure of extreme rainfall observed by meteo-radars can impact the estimation of the return period of extra-ordinary events?
No full textLightning Potential Index performances in multimicrophysical cloud-resolving simulations of a back-building mesoscale convective system: The Genoa 2014 event
No full textSevere weather events are responsible for hundreds of fatalities and millions of euros of damage every year on the Mediterranean basin. Lightning activity is a characteristic phenomenon of severe weather and often accompanies torrential rainfall, which, under certain conditions like terrain type, slope, drainage, and soil saturation, may turn into flash flood. Building on the existing relationship between significant lightning activity and deep convection and precipitation, the performance of the Lightning Potential Index, as a measure of the potential for charge generation and separation that leads to lightning occurrence in clouds, is here evaluated for the V-shape back-building Mesoscale Convective System which hit Genoa city (Italy) in 2014. An ensemble of Weather Research and Forecasting simulations at cloud-permitting grid spacing (1km) with different microphysical parameterizations is performed and compared to the available observational radar and lightning data. The results allow gaining a deeper understanding of the role of lightning phenomena in the predictability of V-shape back-building Mesoscale Convective Systems often producing flash flood over western Mediterranean complex topography areas. Moreover, they support the relevance of accurate lightning forecasting for the predictive ability of these severe events.SCI-STI-F
Implementation and Performance Analysis of the Lightning Potential Index as a Forecasting Tool
No full textSevere weather events are responsible for hundreds of fatalities and millions of euros of damage every year in the Mediterranean basin. Lightning activity is a characteristic phenomenon of severe weather and often accompanies torrential rainfall, which under certain conditions like terrain type, slope, drainage and soil saturation can generate flash flood. Therefore, the improvement in forecast skill for those high impact weather events is one of the main challenges in early warning systems. On the line of this need the behavior of the Lightning Potential Index (LPI) is evaluated in different case studies involving complex terrain. Such index represents a measure of the potential for charge generation and separation that lead to total lightning occurrence in clouds (both IC and CG).SCI-STI-F
A hindcast study of the Piedmont 1994 flood: the CIMA Research Foundation hydro-meteorological forecasting chain
No full textBetween the 4 th and the 6 th of November 1994, Piedmont and the western part of Liguria (two regions in north-western Italy) were hit by heavy rainfalls that caused the flooding of the Po, the Tanaro rivers and several of their tributaries, causing 70 victims and the displacement of over 2000 people. At the time of the event, no early warning system was in place and the concept of hydro-meteorological forecasting chain was in its infancy, since it was still limited to a reduced number of research applications, strongly constrained by coarse-resolution modelling capabilities both on the meteorological and the hydrological sides. In this study, the skills of the high-resolution CIMA Research Foundation operational hydro-meteorological forecasting chain are tested in the Piedmont 1994 event. The chain includes a cloud-resolving numerical weather prediction (NWP) model, a stochastic rainfall downscaling model, and a continuous distributed hydrological model. This hydro-meteorological chain is tested in a set of operational configurations, meaning that forecast products are used to initialise and force the atmospheric model at the boundaries. The set consists of four experiments with different options of the microphysical scheme, which is known to be a critical parameterisation in this kind of phenomena. Results show that all the configurations produce an adequate and timely forecast (about 2 days ahead) with realistic rainfall fields and, consequently, very good peak flow discharge curves. The added value of the high resolution of the NWP model emerges, in particular, when looking at the location of the convective part of the event, which hit the Liguria region
ANALYSIS OF THE SPATIAL STRUCTURE OF THE 4 OCTOBER 2021 EXTREME RAINFALL EVENT IN LIGURIA AND EVALUATION OF ITS IMPACT ON THE ESTIMATION OF ANNUAL MAXIMA
No full textThe paper shows the analysis of the spatial scale of rainfall produced by a back-building Mesoscale Convective System.
• The analysis is conducted combining rain gauge and radar observations.
• The results show that the spatial scale is of the same order of (or lower than) the density of rain gauge networks.
• This may significantly impact the estimation of the actual rainfall maxima and their return period
Martina Drijverová and her literary works for children (author´s portrait)
No full textThis thesis Martina Drijverova and her literatur for children (the author´s portrait) is engaged in work of writer and screenwriter Martina Drijeverová. She is an excellent writer of literature for children. In the first part of this work her story writing is mentioned and the second part deals with her fairy-tale writing. The other author´s work written for children is in the third part. The conclusion of this thesis appreciates the author´s credit in literature for chidlren. Analysis of some books are available. The supplementary part is composed of autor´s biography and her photograph, some book covers, list of the autor´s work {--} televiews, radio plays and serials, audio tapes and CDs, stage plays, books written in Braille
HERStory Makers 2022: Martina Čagalj
No full textMartina Čagalj is a PhD candidate at the University of Split studying seaweeds as a potential source of bioactive compounds. She took part in HERStory Makers 2022.What is HERStory Makers?HERStory Makers is a social media competition for female-identifying early career researchers to share their research, their career journeys, and to inspire the next generation. Winners are selected by public vote. HERStory Makers is also part of EXPLORATHON, Scotland's contribution to European Researchers' Night.In 2022-23, EXPLORATHON was supported by the Engineering & Physical Sciences Research Council [grant number EP/X020894/1].Author contributions to contentMartina Čagalj conceived, planned, and recorded the video content. Kirsty Ross edited the video content to insert HERStory Maker credits, add subtitles, and maintain video length below Twitter/X limit of 2 mins and 20 secs, prior to scheduling the social media posts.</p
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