Multivariate Multi-Step Convection Nowcasting with Deep Neural Networks: The Novara Case Study

Biondi, Riccardo; Chkeir, Sandy; Anesiadou, Aikaterini; Mascitelli, Alessandra; Realini, Eugenio; Nisi, Luca; Cimarelli, Corrado

doi:10.1109/igarss46834.2022.9883665

Cited by 3 publications

(2 citation statements)

References 13 publications

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“…Many studies have been carried out with the aim of identifying regions that are most prone to weather-related hazards, and the scientific literature offers many arguments in this regard. In southern Europe, including Italy [8][9][10][11][17][18][19][20] and the Iberian Peninsula [21], the climate is strongly influenced by high insolation and proximity to the Mediterranean; therefore, some regions have among the highest hail frequencies in Europe [22]. Of course, another key issue is heavy rainfall, which shows significant frequency in terms of occurrence over Europe [23,24], with resulting floods.…”

Section: Introductionmentioning

confidence: 99%

Cultural Heritage Resilience in the Face of Extreme Weather: Lessons from the UNESCO Site of Alberobello

Mascitelli,

Prestileo,

Sonnessa

et al. 2023

Sustainability

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The study of natural disasters has become increasingly important in recent years as the frequency and impact of such events on society have risen. Italy, which has the largest number of sites on the World Heritage List, offers many examples of interactions between atmospheric phenomena and cultural heritage. The research presented here aimed to investigate the potential of one of these sites, Alberobello in the Apulia region, to respond to the stresses induced by intense weather phenomena that occurred in August 2022. Data from conventional and nonconventional sensors were employed to characterize the event. During previous studies, regions prone to meteorological risk were identified based on long-term model analyses. According to these studies, the marked area resulted in a region sensitive to convective precipitation and thus represents an interesting case study. The weather event investigated caused flooding and damage in the Alberobello surroundings; however, the UNESCO site showed a positive response. We explored the reasons by consulting the literature to outline the site’s peculiarities, especially its architectural features, building materials, and terrain morphology. The results revealed that the mutual relationship between the buildings and the environment and the dual role of cultural heritage are values that need to be protected as a resource for natural hazard mitigation.

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Section: Introductionmentioning

confidence: 99%

Cultural Heritage Resilience in the Face of Extreme Weather: Lessons from the UNESCO Site of Alberobello

Mascitelli,

Prestileo,

Sonnessa

et al. 2023

Sustainability

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“…To support the climatological findings, a shorter-term analysis on meteorological stations located in the area was also conducted. In Figure 3, the sum of the total number of extreme events [38], for the 3 year period 2016-2018, for each meteorological station, is given. The extremes are selected according to the 95th percentile of the rain events collected by the weather stations shown in Figure 3 in the period 2010-2020.…”

Section: Introductionmentioning

confidence: 99%

Multi-Sensor Data Analysis of an Intense Weather Event: The July 2021 Lake Como Case Study

Mascitelli

Petracca

Puca

et al. 2022

Water

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A comprehensive analysis of the July 2021 event that occurred on Lake Como (Italy), during which heavy hailstorms and floods affected the surroundings of Lake, is presented. The study provides a detailed analysis of the event using different observation sources currently available. The employed techniques include both conventional (rain gauges, radar, atmospheric sounding) and non-conventional (satellite-based Earth observation products, GNSS, and lightning detection network) observations for hydro-meteorological analysis. The study is split in three main topics: event description by satellite-based observations; long-term analysis by the ERA5 model and ASCAT soil water index; and short-term analysis by lightning data, GNSS delays and radar-VIL. The added value of the work is the near-real-time analysis of some of the datasets used, which opens up the potential for use in alerting systems, showing considerable application possibilities in NWP modeling, where it can also be useful for the implementation of early warning systems. The results highlight the validity of the different techniques and the consistency among the observations. This result, therefore, leads to the conclusion that a joint use of the innovative techniques with the operational ones can bring reliability in the description of events.

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Time Series Representation Learning: A Survey on Deep Learning Techniques for Time Series Forecasting

Schmieg,

Lanquillon

2024

Lecture Notes in Computer Science

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Multivariate Multi-Step Convection Nowcasting with Deep Neural Networks: The Novara Case Study

Cited by 3 publications

References 13 publications

Cultural Heritage Resilience in the Face of Extreme Weather: Lessons from the UNESCO Site of Alberobello

Cultural Heritage Resilience in the Face of Extreme Weather: Lessons from the UNESCO Site of Alberobello

Multi-Sensor Data Analysis of an Intense Weather Event: The July 2021 Lake Como Case Study

Time Series Representation Learning: A Survey on Deep Learning Techniques for Time Series Forecasting

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