Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones’ heavy rainfall. To this end, we use reanalysis da-ta, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cy-clone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterrane-an rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones’ centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-hourly accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and pro-cesses that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set perspectives for a deeper analysis of the favourable atmospheric conditions that yield high impact weather

The FLASH project: using lightning data to better understand and predict flash floods

The FLASH project was implemented from 2006 to 2010 underthe EU FP6 framework. The project focused on using lightning observations to better understand and predict convective storms that result in flash floods. As part of the project 23 case studies of flash floods in the Mediterranean region were examined. For the analysis of these storms lightning data from the ZEUS network were used together with satellite derived rainfall estimates in orderto understand the storm development and electrification. In addition, these case studies were simulated using mesoscale meteorological models to better understand the meteorological and synoptic conditions leading up to these intense storms. As part of this project tools for short term predictions (nowcasts) of intenseconvection across the Mediterranean and Europe, and long term forecasts (a few days) of the likelihood of intense convection were developed. The project also focused on educationaloutreach through our website http://flashproject.orgsupplying real time lightning observations, real time experimental nowcasts, forecasts and educational materials. While flash floods and intense thunderstorms cannot be preventedas the climate changes, long-range regional lightning networks can supply valuable data, in realtime, for warningend-users and stakeholders of imminent intense rainfall and possible flash floods

Numerical simulation of Tehran dust storm on 2 june 2014: A case study of agricultural abandoned lands as emission sources

On 2 June 2014, at about 13 UTC, a dust storm arrived in Tehran as a severe hazard that caused injures, deaths, failures in power supply, and traffic disruption. Such an extreme event is not considered as common for the Tehran area, which has raised the question of the dust storm’s origin and the need for increasing citizens’ preparedness during such events. The analysis of the observational data and numerical simulations using coupled dust-atmospheric models showed that intensive convective activity occurred over the south and southwest of Tehran, which produced cold downdrafts and, consequently, high-velocity surface winds. Different dust source masks were used as an input for model hindcasts of the event (forecasts of the past event) to show the capability of the numerical models to perform high-quality forecasts in such events and to expand the knowledge on the storm’s formation and progression. In addition to the proven capability of the models, if engaged in operational use to contribute to the establishment of an early warning system for dust storms, another conclusion appeared as a highlight of this research: abandoned agricultural areas south of Tehran were responsible for over 50% of the airborne dust concentration within the dust storm that surged through Tehran. Such a dust source in the numerical simulation produced a PM10 surface dust concentration of several thousand µm/m3, which classifies it as a dust source hot-spot. The produced evidence indivisibly links issues of land degradation, extreme weather, environmental protection, and health and safety

Long-Term Patterns and Trends of Shortwave Global Irradiance over the Euro-Mediterranean Region

The spatiotemporal patterns and trends of shortwave global irradiance (SWGI) are a crucial factor affecting not only the climate but also sectors of the economy. In this work, the ERA5-Land reanalysis dataset is employed and evaluated against in situ measurements from a dense network of surface stations operated by the National Observatory of Athens over Greece, revealing a good agreement between the two datasets. Then, the spatiotemporal variability of SWGI is investigated over the Euro-Mediterranean region (10° W–42° E and 30° N–52° N) for a 40-year period (1981–2020). SWGI exhibits a smooth latitudinal variability from north to south of −5.4 W/m2/degree on an annual scale, while it varies significantly on a seasonal basis and is almost four times lower in the winter than in the summer. The SWGI trend during the analyzed period was found to be positive and statistically significant at the 95% confidence level. Spring and summer are the periods where positive and the strongest rates of SWGI trends are evident, while in the winter and autumn, negative or neutral trends were found. The increasing SWGI trend shows a slowdown during the beginning of the 2000s in all seasons, except autumn. The SWGI trend decreases by about −0.06 W/m2/decade every 100 m of elevation increase

Heavy rainfall in Mediterranean cyclones, Part II: Water budget, precipitation efficiency and remote water sources

In this study, we use convection-permitting high resolution (3 km) simulations to quantify and analyse the water budget, precipitation efficiency and water sources of 100 intense Mediterranean cyclones. To this end, we calculate the water content, advection and microphysical processes of water vapour and rain water by implementing new diagnostics to the Weather Research and Forecasting (WRF) model. The 100 intense cyclones have been randomly selected from a 500 intense cyclones dataset, identified and tracked in an 11-year time period in part I of this study. Results are presented in a composite approach showing that most rainfall takes place to the north-east side of the cyclones, close to their centre. Rainfall location is concomitant to the area of horizontal moisture flux convergence and is quasi-equal to the amount of water vapour loss due to microphysical processes. Similar results were found regardless if cyclones produce high or low rainfall amounts. Vertical profiles of the water budget terms revealed deeper clouds for the cyclones producing high rainfall, consistent with higher values of vertical advection of both water vapour and rain water. Finally, cyclones were analysed with respect to their precipitation efficiency, i.e. the ratio between the rainwater produced in an atmospheric column and the consequent rainfall, and showed that cyclones tend to be more efficient when their rainfall production takes place over land. Therefore, there is a complex relation between water vapour advection, precipitation efficiency and rainfall which is discussed through the comparison of two tropical-like cyclones with two cyclones that produced low rainfall amounts. Finally, our analysis is complemented by applying a Lagrangian approach to all 100 cyclones in order to quantify the water vapour source regions that contribute to the cyclones’ rainfall due to local surface evaporation. Results showed that these regions are located over both the Atlantic and the Mediterranean, however we show that cyclones producing high rainfall are related with higher water transport from both the subtropical Atlantic and the Mediterranean Sea.Fil: Flaounas, Emmanouil. National Observatory; GreciaFil: Fita Borrell, Lluís. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Lagouvardos, Konstantinos. National Observatory; GreciaFil: Kotroni, Vassiliki. National Obsevatory ; Greci

Investigating the Role of Extreme Synoptic Patterns and Complex Topography During Two Heavy Rainfall Events in Crete in February 2019

During February 2019, two severe storms affected the island of Crete, located in south Greece. Both storms produced excessive rainfall, provoking severe damages, especially in the western part of Crete. The role of the prevailing synoptic patterns and the interaction of the flow with the high mountains of Crete were investigated. For this purpose, a variety of observational and numerical model data were exploited, including data from a dense rain gauge network, satellite imagery, and model analysis of various parameters describing the stability of the impinging flow. The first storm was a long-lasting event, with convective outbreaks embedded in a more stratiform rainfall pattern. The second storm was brief but mostly convection dominated. The analysis of the available data underlined the role of the low-level convergence upstream of the mountains during both storms, highlighting similarities and differences, as well as the role of the stability of the impinging flow. High soil moisture content was also evidenced as a key ingredient for the severe flooding that occurred during the second storm. This work complements similar studies on the role of Mediterranean islands and their topography on the spatial and temporal distribution of extreme rainfall

Insights into the convective evolution of Mediterranean tropical-like cyclones

International audienceThis study aims at understanding how deep convection is organized and contributes to the intensification of nine Mediterranean tropical-like cyclones which developed between 2005 and 2018. Through a multi-satellite approach, a combination of infrared and microwave diagnostics provides insights into the temporal and spatial evolution of deep convection. ERA5 reanalysis complements the remote-sensing observations and is used to compute the vertical wind shear and vortex tilt to investigate their interactions with deep convection. Results show that vertical wind shear and topography have an important impact on the organization of deep convection and the symmetry of the cyclones. Only a fraction of these cyclones experienced intense convective activity close to their centres and we show that persistent deep convection in the upshear quadrants led to intensification periods. Convective activity solely in the downshear quadrants was not linked to intensification periods, while short-lived hurricane-like structures develop only during symmetric convective activity, leading to cyclone intensification in some of the cases. Finally, a classification of the Mediterranean tropical-like cyclones is proposed based on the evolution of deep convection and their intensification periods

Dead Fuel Moisture Content (DFMC) Estimation Using MODIS and Meteorological Data: The Case of Greece

The frequent occurrence of large and high-intensity wildfires in the Mediterranean region poses a major threat to people and the environment. In this context, the estimation of dead fine fuel moisture content (DFMC) has become an integrated part of wildfire management since it provides valuable information for the flammability status of the vegetation. This study investigates the effectiveness of a physically based fuel moisture model in estimating DFMC during severe fire events in Greece. Our analysis considers two approaches, the satellite-based (MODIS DFMC model) and the weather station-based (AWSs DFMC model) approach, using a fuel moisture model which is based on the relationship between the fuel moisture of the fine fuels and the water vapor pressure deficit (D). During the analysis we used weather station data and MODIS satellite data from fourteen wildfires in Greece. Due to the lack of field measurements, the models’ performance was assessed only in the case of the satellite data by using weather observations obtained from the network of automated weather stations operated by the National Observatory of Athens (NOA). Results show that, in general, the satellite-based model achieved satisfactory accuracy in estimating the spatial distribution of the DFMC during the examined fire events. More specifically, the validation of the satellite-derived DFMC against the weather-station based DFMC indicated that, in all cases examined, the MODIS DFMC model tended to underestimate DFMC, with MBE ranging from −0.3% to −7.3%. Moreover, in all of the cases examined, apart from one (Sartis’ fire case, MAE: 8.2%), the MAE of the MODIS DFMC model was less than 2.2%. The remaining numerical results align with the existing literature, except for the MAE case of 8.2%. The good performance of the satellite based DFMC model indicates that the estimation of DFMC is feasible at various spatial scales in Greece. Presently, the main drawback of this approach is the occurrence of data gaps in the MODIS satellite imagery. The examination and comparison of the two approaches, regarding their operational use, indicates that the weather station-based approach meets the requirements for operational DFMC mapping to a higher degree compared to the satellite-based approach

Symbolic Value-Flow Static Analysis: Deep, Precise, Complete Modeling of Ethereum Smart Contracts

We present a static analysis approach that combines concrete values and symbolic expressions. This symbolic value-flow (”symvalic”) analysis models program behavior with high precision, e.g., full path sensitivity. To achieve deep modeling of program semantics, the analysis relies on a symbiotic relationship between a traditional static analysis fixpoint computation and a symbolic solver: the solver does not merely receive a complex “path condition” to solve, but is instead invoked repeatedly (often tens or hundreds of thousands of times), in close cooperation with the flow computation of the analysis. The result of the symvalic analysis architecture is a static modeling of program behavior that is much more complete than symbolic execution, much more precise than conventional static analysis, and domain-agnostic: no special-purpose definition of anti-patterns is necessary in order to compute violations of safety conditions with high precision. We apply the analysis to the domain of Ethereum smart contracts. This domain represents a fundamental challenge for program analysis approaches: despite numerous publications, research work has not been effective at uncovering vulnerabilities of high real-world value. In systematic comparison of symvalic analysis with past tools, we find significantly increased completeness (shown as 83-96% statement coverage and more true error reports) combined with much higher precision, as measured by rate of true positive reports. In terms of real-world impact, since the beginning of 2021, the analysis has resulted in the discovery and disclosure of several critical vulnerabilities, over funds in the many millions of dollars. Six separate bug bounties totaling over $350K have been awarded for these disclosures