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The ever-increasing complexity and data volumes of numerical weather prediction demands innovations in the analysis and synthesis of operational forecast data. Here we show how dynamical thinking can offer directly applicable forecast information, taking as a case study the extreme north Italian flooding of May 2023. We compare this event with historical north Italian rainfall events – in order to determine a) why it was so extreme, b) how well it was predicted, and c) how we may improve our predictions of such extremes. Lagrangian analysis shows, in line with previous work, that extreme rainfall in Italy can be caused by moist air masses originating from the North Atlantic, North Africa, and, to a lesser extent, Eastern Europe, with compounding moisture contributions from all three regions driving the May 2023 event. We identify the large-scale precursors of typical north Italian rainfall extremes based on geopotential height and integrated vapour transport fields. We show in ECMWF operational forecasts that a precursor perspective was able to identify the growing possibility of the Emilia-Romagna extreme event eight days beforehand – four days earlier than the direct precipitation forecast. Such dynamical precursors prove well-suited for identifying and interpreting predictability barriers, and could help build forecaster's understanding of unfolding extreme scenarios in the medium-range. We close by discussing the broader implications and operational potential of dynamically-rooted metrics for understanding and predicting extreme events, both in retrospect and in real-time. [ABSTRACT FROM AUTHOR]

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 from the impacted region in both time and space. Integrating and leveraging our understanding of dynamical precursors provides a new perspective on ensemble forecasting for extreme events, focused on building storylines 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 are limited, 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 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In 2015 an intense rainfall event hit the Valleys of the Trebbia, Nure, and Aveto watercourses in the Northern Apennines. In about 6 h a mesoscale convective system deployed a stunning amount of precipitation of 340 mm, with an extreme hourly rainfall intensity of >100 mm/h. It triggered debris flows along slopes and stream channels, landslides and floods, which caused serious damages. Through the optimal combination of rainfall data and radar volumes, in this work we present a detailed rainfall analysis, which will serve as a basis to create a quantitative correlation with debris flows over elementary hydrological units. We aim at providing an objective basis for future predictions, starting from the recognition of the forcing meteorological events, and then arriving at the prediction of triggering phenomena and to the debris-flow type. We further provide seven observations/case studies on the effects of extreme-precipitation events on freshwater environments in small mountain catchments. Extreme-precipitation events are becoming more frequent and widespread globally but their ecological effects are still insufficiently understood. In general, the effects of extreme events on inland-waters' ecosystems are highly context-dependent, ranging from deleterious to beneficial. We therefore highlight the necessity of further studies to characterize these effects in more depth to be able to include appropriate mitigation measures in environmental planning and stewardship. [ABSTRACT FROM AUTHOR]

The connection between extreme events and Rossby wave packets (RWP) has been increasingly documented in recent years. Rossby waves modulate mid-latitude weather, generating main precipitation spells and controlling geographical area affected. In the Mediterranean region, several case studies of extreme precipitation event (EPE) reported, as a main triggering factor, a meridionally elongated upper-level trough (i.e a breaking Rossby wave) as part of an incoming RWP. In this study we investigate the RWP characteristics leading to a very large number of EPEs that occurred between 1979 and 2015 over Northern Italy. EPE cases (more than 800) are subdivided in three categories; this allows to test the hypothesis that different EPEs are driven by different RWP dynamical evolution, which in turn, controls the interplay between large-scale vs mesoscale precipitation. We also investigate the strong seasonality of the waveguide which produces, in Spring and Autumn, a peculiar positioning of the Rossby wave which favours EPEs over target area (N-Italy). This synoptic setting is in fact highly effective in focusing water vapour transport (atmospheric river) towards the main orographic barriers of the Apennines and the Alps. [ABSTRACT FROM AUTHOR]

Keywords:, extreme precipitation, paleoflood deposit, peat bog record, Holocene, northern Apennines, climate change, water cycle.A series of record breaking precipitation events have stricken the mountainous area of Emilia-Romagna Region (northern Apennines, Italy) over the last years. As consequence, several geomorphological processes, like widespread debris flows along the slopes and hyperconcentrated flood in the stream channels, shallow landslides and overbank flooding affected the territory, causing serious damages to man-made structures. The detailed study of these recent deposits compared with fossil peat bog and lake paleodeposits can provide useful insight to support a strong match between precipitation intensity and warm climatic phases in antecedent climatic periods, as expected by the increase air water vapour holding capacity at higher temperaturesHere we present the results of the field campaign performed in summer 2017 at Lake Moo a 0.15km2 peat bog located at an altitude of 1130m a.s.l. The chosen area has been affected, during the flooding of the upper Trebbia and Nure valleys 13-14 September 2015, by several high-density flows generated by the stream that flow into the plain. Our main assumption is that, in such a small drainage basin (area <2 km2), with favourable geologic and geomorphic characteristics implying advantageous sediment transfer into lake, high density flood can be triggered only by high precipitation intensity events (HPI) lasting a sufficient amount of time for water to infiltrate and mobilize large quantities of debris. The sedimentary succession (ca. 13 m-thick) was studied through the extraction of two cores and one trench. The facies/paleoenvironmental interpretation of the sedimentary succession, characterized by clusters of coarse-grained alluvial deposits interbedded with organic-rich silty clays and peaty layers, was achieved combining sedimentological and pollen data with pedological data and radiocarbon dating (AMS 14C). Observed depositional cycles, retrieved by Lake Moo cores and trench, were put in relation with other specific paleoclimatic proxies available in literature for the North-Apennine area. This comparison illustrate that the increase of extreme paleoflood (associated with coarse-grained deposits similar to the ones observed recently) correlates well with warm phases (at millennial scale), with a maximum activity in during the holocene thermal maximum. [ABSTRACT FROM AUTHOR]