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The article discusses a workshop on Rossby waves, heat waves, and compound extreme events held in Italy in November 2023. Experts from various fields gathered to discuss research, challenges, and networking opportunities related to the interplay between atmospheric dynamics, Rossby waves, and heat waves. The workshop highlighted the need for collaboration across disciplines to advance understanding of the complex interactions between atmospheric Rossby waves and spatially compounding extreme events, such as heat waves. Key scientific questions and challenges were identified, including the predictability of heat waves, the role of blocking and topography, and the statistical treatment of spatially compounding extreme events. The workshop emphasized the importance of integrating different methodologies and metrics for characterizing Rossby waves and extreme events to enhance predictability and advance climate modeling efforts. [Extracted from the article]

Reanalysis and observational data are used to identify the precursors of summertime heat waves over the Eastern Mediterranean. After compiling a list of heat waves using objective criteria, we identify robust precursors present 7–10 days before the onset of the heat wave, longer than the typical horizon for trustworthy weather forecasts. If these precursors are present, there is a significant warming over the Eastern Mediterranean over the following 10 days that persists for weeks after. These precursors include a weakened Indian monsoon, a strengthened Sahelian monsoon, warm Western/Central Mediterranean sea‐surface temperatures, and a midlatitude low‐pressure system from the west. Further, horizontal temperature advection is the proximate cause of the heat wave in the days before the extreme; in particular, a weakening of the Etesian winds that would otherwise advect relatively cool maritime air inland accounts for around half of the warming. There has been a clear tendency for more heat extremes in recent years. These results have implications for forecasting anomalous summer temperatures in the Eastern Mediterranean, and the framework developed here can also be applied in other regions. [ABSTRACT FROM AUTHOR]

Rainfall in the Eastern Mediterranean is strongly modulated by complex topography and localized mesoscale processes. General circulation models (GCMs) struggle to capture daily precipitation variability in the region, both in time and in space. Rain in the Eastern Mediterranean occurs within a hierarchy of scales, as synoptic scale structures often drive local rainfall patterns. Daily rain prediction in the region can therefore benefit from analog downscaling—a nonlinear regression of a high‐resolution predictand from past synoptic‐scale predictors. We present a multiscaled downscaling algorithm of daily rain over Israel. The underlying goal is to create a mechanism‐based tool that will improve the analysis and prediction of precipitation on short time scales in models that cannot produce the field explicitly. We train the algorithm using coarse grid ERA5 reanalysis data and measurements from 21 rain gauges. The routine uses a k‐nearest neighbours algorithm to find the most similar past instances (i.e., analogs) for every predicted day. Analog selection is performed in two steps, based on scale (synoptic and local), as to not overshadow correlative but local predictors. The algorithm also includes several unique aspects tailored to Mediterranean climate: subdaily predictors of cyclone life cycles; representation of upper level cyclonic drivers; and the inclusion of rainfall potential using the Modified K‐Index (MKI). The proposed algorithm has better accuracy (66% correct predictions) compared to non‐downscaled reanalysis and climatological predictions. It better captures the spatial rainfall variance, mitigates the "drizzle bias," and improves skill in extreme event prediction. However, it underestimates very rainy events and has trouble fully representing the spatial variance in the region. Nonetheless, our algorithm represents the potential for computationally inexpensive downscaling of daily precipitation in the Mediterranean with various possible applications, for example, characterization of droughts and storms, linking hydrological and synoptic scale processes and introducing uncertainty estimates using large ensembles. [ABSTRACT FROM AUTHOR]

Extreme weather, such as heavy precipitation and strong winds, can co-occur, resulting in larger socio-economic impacts than the linear sum of their components. These are termed "compound extremes" and are challenging to forecast even a few days before. With this aim, we investigate the "wet" and "windy" extremes associated with Eastern Mediterranean cyclones in winter. We combine insights from a synoptic classification algorithm, traditional atmospheric analysis techniques, and dynamical systems theory. In phase space, the latter quantifies atmospheric states' co-recurrence ratio (α) and persistence (Θ-1). We base the analysis on ERA5 at various pressure levels and time lags. Our analysis is two-fold; first, we define compound dynamical extremes (CDE) based on upper and lower deciles of α and Θ-1, linking them to the synoptic patterns. We find that CDEs are related to the depth and location of the surface cyclone and upper-level trough. Then, we show that high co-recurrence and persistence are associated with heavier precipitation and stronger wind speed. Second, we define compound extremes (CE), the upper 5% of precipitation intensity and wind velocity co-occurring simultaneously. We link these back to the dynamical system metrics anomalies. Finally, we compare CEs with individual extremes and cyclone climatology. We find that CEs display significantly higher co-recurrence and persistence than individual extremes. Indeed, days with high co-recurrence and persistence anomalies are ~2-18 times more likely to be allied with extreme weather, depending on the extreme type, than low co-recurrence and persistence. Moreover, we show that the upper levels are significantly more persistent than the surface flow during a CE. The mid-February 2012 "wet" and "windy" CE case-study strengthened the abovementioned climatological findings. To conclude, the dynamical systems viewpoint is a valuable complement to understanding the dynamics of CEs in the Eastern Mediterranean. We foresee it to be fruitfully applied to other CEs and regions. [ABSTRACT FROM AUTHOR]

Gaining a holistic understanding of extreme weather, from its physical drivers to its impacts on society and ecosystems, is key to supporting future risk reduction and preparedness measures. Here, we provide an overview of the state of the art, knowledge gaps and key open questions in the study of extreme weather events over the vulnerable eastern Mediterranean. This region is situated in a transition zone between subtropical and mid-latitude climates. The large-scale atmospheric circulation and its interaction with regional synoptic systems (i.e., Cyprus Lows, Red Sea Troughs, Persian Troughs, "Sharav" Lows) and high-pressure systems mainly govern extreme weather. Complex orographic features further play an important role in the generation of extreme weather. Most extreme weather events, including heavy precipitation, cold spells, floods and windstorms, are associated with Cyprus Lows or active Red Sea Troughs, whereas heat waves are related with either Persian Troughs and sub-tropical high-pressure systems in summer or the Sharav Low during springtime. In future decades, heat waves and droughts are projected to significantly increase in both frequency and intensity. Changes in heavy precipitation may vary in sign and magnitude depending on the scale, severity and region of interest. There are still relatively large uncertainties concerning the physical understanding and the projected changes of cold spells, windstorms and compound extremes, as these types of events received comparatively little attention in the literature. We further identify knowledge gaps that relate to the societal impacts of extreme weather. These gaps mainly relate to the effects extreme weather may have on mortality, morbidity and infrastructure in the eastern Mediterranean. Research is currently limited in this context, and we recommend strengthening the database of analyzed case studies. We trust that this can only be suitably accomplished by inter-disciplinary and international regional collaboration (in spite of political unrest). [ABSTRACT FROM AUTHOR]

Characterizing the interaction between meteorological variables such as humidity, wind speed, cloud cover, and precipitation with the atmospheric electric field is vital for improving the nowcast of extreme weather events such as heavy precipitation. With this aim, we provide minute-scale electric field observations in southern Israel. These were taken during low-pressure weather systems in winter, often termed 'Cyprus Lows.' We focus only on precipitating ('wet') events, where rain was measured at the surface during and after the cold front's passage. The mean |PG| values for 'wet' Cyprus Lows are higher (Hundreds to thousands V m−1) compared with the mean fair-weather values (∼100–200 V m−1, and exhibit a sharp and rapid increase of the |PG| of up to tens of V m−1 min−1 during the arrival of the cold front and hundreds of V m−1 min−1 during precipitation. Then, we analyzed selected case studies in detail. The response of the |PG| to thunderstorm clouds, i.e., Cumulonimbus, is an increase to values of thousands of V m−1. The temporal evolution of the |PG| allowed us to identify the type of cloud and its life cycle stage. We suggest that using state-of-the-art 1 Hz measurements of the |PG| and deducing cloud patterns at strategic locations, such as in arid regions like southern Israel, may improve the nowcasting capabilities of localized heavy precipitation events. • Meteorological Interaction : Exploring the relationship between Met-parameters with the atmospheric electric field to improve the forecast • Observational Data : High-resolution electric field observations were during winter low-pressure systems • Electric Field Variation - Wet : Mean potential gradient values 'wet' events are significantly higher than fair weather values. • Electric Field Variation - Wet : Mean potential gradient values 'wet' events are significantly higher than fair weather values. • Cloud Analysis : potential gradient responses to storm clouds reaching thousands of V m−1, allowing identification of cloud types and life cycle stages. • Now-casting and Global Applicability : The methodologies and findings may enhance the now-casting of localized heavy precipitation events. [ABSTRACT FROM AUTHOR]