Extreme precipitation in Northern Italy

Weather prediction is a fundamental scientific challenge and crucial to society. Predicting extreme weather events is one of the outstanding achievements of science. Despite the enormous progress made by modern meteorology, the precise prediction of certain critical phenomena, like extreme precipitation, can still be uncertain even at shorter time ranges. This research aims to identify the relevant atmospheric processes for the formation of extreme precipitation. We investigate the relationship between the predictable large-scale dynamics that create the right conditions for the genesis of extreme events, and fast small-scale processes, such as convection, which rapidly destroy predictability and pose a challenge for a correct forecast. In the aim to identify common dynamical states, we designed a systematic investigation on extreme precipitation events (EPEs), based on a very large number of episodes (> 800), which occurred between 1979 and 2015 in northern-central Italy, used as a test region. Through the optimal blending of ECMWF reanalysis of meteorological fields and high resolution gridded daily precipitation (ARCIS), we classify, with a machine learning approach, extreme precipitation events into three categories (Cat1, Cat2, Cat3). The categories do not only differ locally, successfully reflecting the precipitation processes on the region (frontal and orographic precipitation, frontal precipitation and embedded deep convection, diurnal or weakly forced convection), but also in the dynamical evolution of their precursor: the upper-level wave, and the associated wave packet. So far, this is the first attempt to classify EPEs on physical processes and make connections with predictability. We show that EPEs falling in Cat1 and Cat2 are associated with upper-level wave packets propagating from remote regions, while for EPEs in Cat3 local instability is dominating. The strongest EPEs, mostly populating Cat2, are characterised by a recurrent dynamic evolution consisting of a substantial upstream wave amplification in the N. Atlantic, arguably due to diabatic heating sources. Cat2 events are more predictable than moderate events falling into the other two categories in the region under investigation. This original result has important practical implications. It shows that not all extreme precipitation events have the same level of predictability. The uncertainty does not depend on the intensity of the phenomenon but on the particular dynamic evolution.Die Wettervorhersage ist eine grundlegende wissenschaftliche Herausforderung und für die Gesellschaft von großer Bedeutung. Die Vorhersage von Extremwetterereignissen ist eine der herausragenden Leistungen der Wissenschaft. Trotz des enormen Gesamtfortschritts der modernen Meteorologie kann die präzise Vorhersage bestimmter kritischer Phänomene, wie z. B. extremer Niederschläge, auch bei kürzeren Vorhersagezeiträumen noch unsicher sein. Diese Forschung zielt darauf ab, die relevanten atmosphärischen Prozesse für die Bildung von Extremniederschlägen zu identifizieren. Wir untersuchen die Beziehung zwischen vorhersagbarer großskaliger Dynamik, die die richtigen Bedingungen für die Bildung von Extremereignissen schafft, und schnellen kleinskaligen Prozessen, wie Konvektion, die die Vorhersagbarkeit schnell zerstören und eine Herausforderung für eine korrekte Vorhersage darstellen. Mit dem Ziel, gemeinsame dynamische Zustände zu identifizieren, haben wir eine systematische Untersuchung vieler (> 800) extremer Niederschlagsereignisse (EPEs) entworfen, die zwischen 1979 und 2015 in Nord- und Mittelitalien. Durch die optimale Kombination von ECMWF-Reanalysen meteorologischer Felder und hochaufgelöstem, gerastertem Tagesniederschlag (ARCIS) klassifizieren wir mit einem maschinellen Lernansatz extreme Niederschlagsereignisse in drei Kategorien (Cat1, Cat2, Cat3). Die Kategorien unterscheiden sich nicht nur lokal und spiegeln erfolgreich die Niederschlagsprozesse in der Region wider (frontaler und orographischer Niederschlag, frontaler Niederschlag und eingebettete tiefe Konvektion, tageszeitliche oder schwach erzwungene Konvektion), sondern auch in der dynamischen Entwicklung ihres Vorläufers: der atmosphärische Rossby-Welle und des zugehörigen Wellenpakets. Bislang ist dies der erste Versuch, EPEs nach physikalischen Prozessen zu klassifizieren und mit der Vorhersagbarkeit in Verbindung zu bringen. Wir zeigen, dass EPEs, die in Cat1 und Cat2 fallen, mit Wellenpaketen aus der oberen Atmosphäre, assoziiert sind, die sich aus entfernten Regionen ausbreiten, während bei EPEs in Cat3 lokale Instabilität dominiert. Die stärksten EPEs, die meist in Cat2 fallen, sind durch eine wiederkehrende dynamische Entwicklung gekennzeichnet, die aus einer erheblichen stromaufwärts gerichteten Wellenverstärkung im Nordatlantik besteht, die vermutlich auf diabatische Heizquellen zurückzuführen ist. Cat2-Ereignisse sind in der untersuchten Region besser vorhersagbar als gemäßigte Ereignisse, die in die beiden anderen Kategorien fallen. Dieses Ergebnis hat wichtige praktische Implikationen. Es zeigt, dass nicht alle extremen Niederschlagsereignisse den gleichen Grad an Vorhersagbarkeit haben. Die Unsicherheit hängt nicht von der Intensität des Phänomens ab, sondern von der jeweiligen dynamischen Entwicklung.La previsione del tempo è una sfida scientifica cruciale per la nostra società. La previsione di eventi meteorologici estremi è una delle conquiste più importanti della scienza. Nonostante gli enormi progressi fatti dalla meteorologia moderna, la previsione precisa di alcuni fenomeni critici, come le precipitazioni estreme, può essere incerta anche a brevi intervalli temporali. Questa ricerca mira a identificare i processi atmosferici rilevanti per la formazione di precipitazioni estreme. In particolare, lo studio approfondisce la relazione tra le dinamiche prevedibili su larga scala che creano le giuste condizioni per la genesi di eventi estremi, e i processi veloci su piccola scala, come la convezione, che distruggono rapidamente la prevedibilità e rappresentano una sfida per una corretta previsione. Al fine di identificare gli stati dinamici comuni, abbiamo realizzato un'indagine sistematica sugli eventi estremi di precipitazione (EPEs), basata su un numero molto elevato di episodi (> 800), avvenuti tra il 1979 e il 2015 nell'Italia centro-settentrionale, utilizzata come regione test. Attraverso la fusione ottimale delle rianalisi ECMWF dei campi meteorologici e delle precipitazioni giornaliere del dataset ARCIS, classifichiamo, con un approccio di machine learning, gli eventi di precipitazione estrema in tre categorie (Cat1, Cat2, Cat3). Le categorie non differiscono solo localmente, riflettendo con successo i diversi processi che danno origine alla precipitazione sulla regione (precipitazione frontale e orografica, sinergia fra precipitazione frontale e convezione profonda, convezione diurna o debolmente forzata), ma anche nell'evoluzione dinamica del loro precursore: l'onda di Rossby e il pacchetto d'onda associato. Questo risulta essere il primo tentativo di classificare gli EPE e mettere in relazione la loro prevedibilità con la particolare evoluzione dinamica. Si osserva che gli EPE che cadono in Cat1 e Cat2 sono associati a pacchetti d'onda di Rossby che si propagano da regioni remote, mentre negli EPE in Cat3 domina l'instabilità locale. Gli EPE più forti, che popolano principalmente la Cat2, sono caratterizzati da un'evoluzione dinamica ricorrente che consiste in una sostanziale amplificazione di un'onda di Rossby nell'Atlantico settentrionale, probabilmente dovuta a fonti di riscaldamento diabatico. Gli eventi Cat2 sono più prevedibili degli eventi moderati che rientrano nelle altre due categorie nella regione in esame. Questo risultato, originale in letteratura, ha importanti implicazioni pratiche. Mostra che non tutti gli eventi di precipitazione estrema hanno lo stesso livello di prevedibilità. L'incertezza non dipende dall'intensità del fenomeno ma dalla particolare evoluzione dinamica

Operational atlas of exposed mortars and conglomerates for interventions on the widespread architectural heritage

When it comes to Science Heritage, the availability of refined investigation techniques, an advanced knowledge of the characteristics of materials, the current technological capacity and the synergy of specialised operators, coordinated into multidisciplinary teams, guarantee, with the support of cutting-edge tools, excellent results for every conservative operation applied to monumental buildings of acknowledged interest. On the contrary, there are still strong limits to the likelihood that this excellence will reverberate on the multitude of interventions performed on widespread architectural heritage. The research project underway envisages the preparation of an operational atlas of reference for exposed mortars and conglomerates, based on the historical and technological knowledge of materials (particularly those available locally) complete with experimental data on constitution and performance, which is useful to support the development of compatible maintenance and conservation procedures

Detachment of Plasters in Masonry Buildings: Analysis by Acoustic Emission and Numerical Simulation

An innovative laboratory procedure is described for testing the mechanical adhesion of new dehumidified mortars applied in the restoration works. A specific adherence test was carried out on composite specimens made by stone block and repair mortar. During the laboratory test the acoustic emission (AE) technique was employed, in order to estimate the amount of energy released from fracture propagation in the adherence surface between mortar and stone. A numerical simulation follows the experimental data. The evolution of detachment process of mortar in a coupled stone brick–mortar system was analysed by AE signals, which can improve the numerical model and predict the failure mode in the adhesion surface of repair plaster

Domino: A new framework for the automated identification of weather event precursors, demonstrated for European extreme rainfall

A number of studies have investigated the large-scale drivers and upstream-precursors of extreme weather events, making it clear that the earliest warning signs of extreme events can be remote in both time and space from the impacted region. Integrating and leveraging our understanding of dynamical precursors provides a new perspective on ensemble forecasting for extreme events, focused on building story-lines of possible event evolution. This then acts as a tool for raising awareness of the conditions conducive to high-impact weather, and providing early warning of their possible development. However, operational applications of this developing knowledge-base is limited so far, perhaps for want of a clear framework for doing so. Here, we present such a framework, supported by open software tools, designed for identifying large-scale precursors of categorical weather events in an automated fashion, and for reducing them to scalar indices suitable for statistical prediction, forecast interpretation, and model validation. We demonstrate this framework by systematically analysing the precursor circulations of daily rainfall extremes across 18 regional- to national-scale European domains. We discuss the precursor rainfall dynamics for three disparate regions, and show our findings are consistent with, and extend, previous work. We provide an estimate of the predictive utility of these precursors across Europe based on logistic regression, and show that large-scale precursors can usefully predict heavy rainfall between two and six days ahead, depending on region and season. We further show how for more continental-scale applications the regionally-specific precursors can be synthesised into a minimal set of indices that drive heavy precipitation. We then provide comments and guidance for generalisation and application of our demonstrated approach to new variables, timescales and regions.Comment: 3 figure SI, 22 manuscript pages, 10 figures, submitted to QJRM

Digital image correlation applied to lime-based mortars: Shrinkage tests for durability evaluations in restoration works.

Repair mortars applied to architectural heritage buildings for preservation, maintenance, restoration, and strengthening must be carefully studied regarding the many different compatibility issues. In the case of repair interventions, two closely related aspects are especially important: the mortar composition, and the method of its application, which can strongly influence the shrinkage phenomena during the setting and hardening phases. The aim of present experimental research is to set-up a procedure by Digital Imaging Correlation (DIC) technique to deepen shrinkage phenomena in lime-based mortars, thus comparing many different materials, wrongly considered to be similar in behaviour. The technique enable not only shrinkage measurement accuracy higher than standard tests, but also to understand its mechanisms of evolution over time, by evaluating locally strain stress before micro-crack appearing. The interpretation of a large number of test results represents a significant contribution to the development of operational tools to address material selection in specific contexts

Extreme precipitation events over northern Italy. Part I: A systematic classification with machine‐learning techniques

Extreme precipitation events (EPEs) are meteorological phenomena of major concern for society. They can have different characteristics depending on the physical mechanisms responsible for their generation, which in turn depend on the large and mesoscale conditions. This work provides a systematic classification of EPEs over northern–central Italy, one of the regions in Europe with the highest frequency of these events. The EPE statistics have been deduced using the new high‐resolution precipitation dataset ArCIS (Climatological Archive for Central–Northern Italy), that gathers together a very high number of daily, quality‐controlled and homogenized observations from different networks of 11 Italian regions. Gridded precipitation is aggregated over Italian operational warning‐area units (WA). EPEs are defined as events in which daily average precipitation in at least one of the 94 WAs exceeds the 99th percentile with respect to the climate reference 1979–2015. A list of 887 events is compiled, significantly enlarging the database compared to any previous study of EPEs. EPEs are separated into three different dynamical classes: Cat1, events mainly attributable to frontal/orographic uplift; Cat2, events due to frontal uplift with (equilibrium) deep convection embedded; Cat3, events mainly generated by non‐equilibrium deep convection. A preliminary version of this classification is based on fixed thresholds of environmental parameters, but the final version is obtained using a more robust machine‐learning unsupervised K‐means clustering and random forest algorithm. All events are characterized by anomalously high integrated water vapour transport (IVT). This confirms IVT as an important large‐scale predictor, especially for Cat2 events, which is shown to be the most important category in terms of impacts and EPE area extension. Large IVT values are caused by upper‐level waves associated with remotely triggered Rossby wave packets, as shown for two example Cat2 events

A New Fracture Function Approach to QCD Initial State Radiation

Ordinary fracture functions, describing hadrons production in the deep inelastic scattering target fragmentation region, are generalized to account for the production of hadrons in arbitrary number, thus offering a renewed framework for dealing with QCD initial state radiation. We also propose a new jet-like observable which measures beam remnants and low-$p_{\perp}$ scattering fragments and derive its QCD evolution equations by using Jet Calculus. Possible implications for semi-inclusive deep inelastic scattering and hadron-hadron reactions are shortly discussed.Comment: 10 pages, 5 figures, revtex

Changes in high-intensity precipitation on the northern Apennines (Italy) as revealed by multidisciplinary data over the last 9000 years

Several record-breaking precipitation events have struck the mountainous area of the Emilia-Romagna region (northern Apennines, Italy) over the last 10 years. As a consequence, severe geomorphological processes such as debris avalanches and debris flows, shallow landslides, and over-bank flooding have affected the territory, causing severe damage to human-made structures. The unusual intensity of these phenomena prompted an investigation into their frequency in the past, beyond instrumental time. In the quest for an understanding of whether these phenomena are unprecedented in the region, peat bog and lake deposits were analyzed to infer the frequency of extreme precipitation events that may have occurred in the past. We present the results of a dedicated field campaign performed in summer 2017 at Lake Moo in the northern Apennines, a 0.15 km(2) peat bog located at an altitude of 1130 m a.s.l. During the extreme precipitation event of 13-14 September 2015, several debris flows generated by small streams affected the Lake Moo plain. In such a small drainage basin (<2 km(2)), high-density floods can be triggered only by high-intensity precipitation events. The sedimentary succession (ca. 13 m thick) was studied through the drilling of two cores and one trench. The sequence, characterized by clusters of coarse-grained alluvial deposits interbedded with organic-rich silty clays and peat layers, was analyzed by combining sedimentological, pollen, microanthracological and pedological data with radiocarbon dating (AMS C-14) in an innovative multidisciplinary approach for this area. Original data acquired during the field campaign were also correlated with other specific paleoclimatic proxies available in the literature for the northern Apennines area. We discover that the increase in extreme paleoflooding, associated with coarse-grained deposits similar to the ones observed recently, correlates well with the warm phases of the Holocene Thermal Maximum and with the ongoing warming trend observed that started at the beginning of the last century

Transverse Momentum in Semi-inclusive Deep Inelastic Scattering

Within the framework of perturbative Quantum Chromodynamics we derive transverse momentum dependent distributions describing both current and target fragmentation in semi-inclusive Deep Inelastic Scattering. We present, to leading logarithmic accuracy, the corresponding crosssections describing final state hadrons on the whole phase space. Phenomenological implications and further developments are briefly discussed.Comment: 11 pages, 5 figure