In this study we investigate convective environments and their corresponding climatological features over Europe and the United States. For this purpose, National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) data, ERA5 hybrid-sigma levels, and severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data were combined on a common grid of 0.25° and 1-h steps over the period 1979–2018. The severity of convective hazards increases with increasing instability and wind shear (WMAXSHEAR), but climatological aspects of these features differ over both domains. Environments over the United States are characterized by higher moisture, CAPE, CIN, wind shear, and midtropospheric lapse rates. Conversely, 0–3-km CAPE and low-level lapse rates are higher over Europe. From the climatological perspective severe thunderstorm environments (hours) are around 3–4 times more frequent over the United States with peaks across the Great Plains, Midwest, and Southeast. Over Europe severe environments are the most common over the south with local maxima in northern Italy. Despite having lower CAPE (tail distribution of 3000–4000 J kg−1 compared to 6000–8000 J kg−1 over the United States), thunderstorms over Europe have a higher probability for convective initiation given a favorable environment. Conversely, the lowest probability for initiation is observed over the Great Plains, but, once a thunderstorm develops, the probability that it will become severe is much higher compared to Europe. Prime conditions for severe thunderstorms over the United States are between April and June, typically from 1200 to 2200 central standard time (CST), while across Europe favorable environments are observed from June to August, usually between 1400 and 2100 UTC.

/pdf/severe-convective-storms-across-europe-and-the-united-states-1jwvebsdi2.pdf

Severe Convective Storms across Europe and the United States. Part II: ERA5 Environments Associated with Lightning, Large Hail, Severe Wind, and Tornadoes

In this study we compared 3.7 mln rawinsonde observations from 232 stations over Europe and North America with proximal vertical profiles from ERA5 and MERRA2 to examine how well reanalysis depicts observed convective parameters. Larger differences between soundings and reanalysis are found for thermodynamic theoretical parcel parameters, low-level lapse rates and low-level wind shear. In contrast, reanalysis best represents temperature and moisture variables, mid-tropospheric lapse rates, and mean wind. Both reanalyses underestimate CAPE, low-level moisture and wind shear, particularly when considering extreme values. Overestimation is observed for low-level lapse rates, mid-tropospheric moisture and the level of free convection. Mixed-layer parcels have overall better accuracy when compared to most-unstable, especially considering convective inhibition and lifted condensation level. Mean absolute error for both reanalyses has been steadily decreasing over the last 39 years for almost every analyzed variable. Compared to MERRA2, ERA5 has higher correlations and lower mean absolute errors. MERRA2 is typically drier and less unstable over central Europe and the Balkans, with the opposite pattern over western Russia. Both reanalyses underestimate CAPE and CIN over the Great Plains. Reanalyses are more reliable for lower elevations stations and struggle along boundaries such as coastal zones and mountains. Based on the results from this and prior studies we suggest that ERA5 is likely one of the most reliable available reanalysis for exploration of convective environments, mainly due to its improved resolution. For future studies we also recommend that computation of convective variables should use model levels that provide more accurate sampling of the boundary-layer conditions compared to less numerous pressure levels.

/pdf/comparison-of-convective-parameters-derived-from-era5-and-4u16yovw6u.pdf

Comparison of Convective Parameters Derived from ERA5 and MERRA-2 with Rawinsonde Data over Europe and North America

Uncertainty exists concerning the links between synoptic-scale processes and tornado outbreaks. With continuously improving computer technology, a large number of high-resolution model simulations can be conducted to study these outbreaks to the storm scale, to determine the degree to which synoptic-scale processes appear to influence the occurrence of tornado outbreaks, and to determine how far in advance these processes are important. To this end, 50 tornado outbreak simulations are compared with 50 primarily nontornadic outbreak simulations initialized with synoptic-scale input using the Weather Research and Forecasting (WRF) mesoscale model to determine if the model is able to distinguish the outbreak type 1, 2, and 3 days in advance of the event. The model simulations cannot resolve tornadoes explicitly; thus, the use of meteorological covariates (in the form of numerous severe-weather parameters) is necessary to determine whether or not the model is predicting a tornado outbreak. Results indicate that, using the covariates, the WRF model can discriminate outbreak type consistently at least up to 3 days in advance. The severe-weather parameters that are most helpful in discriminating between outbreak types include low-level and deep-layer shear variables and the lifting condensation level. An analysis of the spatial structures and temporal evolution, as well as the magnitudes, of the severe-weather parameters is critical to diagnose the outbreak type correctly. Thermodynamic instability parameters are not helpful in distinguishing the outbreak type, primarily because of a strong seasonal dependence and convective modification in the simulations.

Evaluation of WRF forecasts of tornadic and nontornadic outbreaks when initialized with synoptic-scale input: The utility of “base-state” parameters

Abstract. A large number of intense cyclones occur every year in the Mediterranean basin, one of the climate change hotspots. Producing a broad range of severe socio-economic and environmental impacts in such a densely populated region, Mediterranean cyclones call for coordinated and interdisciplinary research efforts. This article aims at supporting these efforts by reviewing the status of knowledge in the broad field of Mediterranean cyclones. First, we focus on the climatology of Mediterranean cyclone tracks, their relationship to large-scale atmospheric circulation and their future trends. Second, we discuss the dynamics and atmospheric processes that govern the genesis and development of Mediterranean cyclones. Then, we present the different subtypes of Mediterranean cyclones, devoting special attention to medicanes, i.e. cyclones with tropical characteristics and subjects of numerous recent studies. In a subsequent section, we review the state of the art in forecasting cyclones and relevant high-impact weather, and we discuss in detail the challenges and recent efforts to increase their forecast skill. Finally, we discuss the main impacts produced by cyclones, namely heavy precipitation, windstorms, dust transport, storm surges and sea wave extremes. In the last section of this review article, we thoroughly outline the future directions of research that would advance the broader field of Mediterranean cyclones. 

Mediterranean cyclones: current knowledge and open questions on dynamics, prediction, climatology and impacts

Tornadic environments in the Iberian Peninsula and the Balearic Islands based on ERA5 reanalysis

In this study, mesoscale environments associated with 57 significant tornadoes occurring over Italy in the period 2000–2018 are analyzed. The role of the vertical Wind Shear in the lower and middle troposphere, in terms of low-level shear (LLS) and deep-level shear (DLS), and of the convective available potential energy (CAPE) as possible precursors of significant tornadoes is statistically investigated. Wind shear and CAPE data are extracted from the ERA-5 and ERA-Interim reanalyses. Overall, the study indicates that: (a) values of these variables in the two uppermost quartiles of their statistical distribution significantly increases the probability of tornado occurrences; (b) the probability increases for increasing values of LLS and DLS, and (c) is maximum when either wind shear or CAPE are large. These conclusions hold for both the reanalysis datasets and do not depend upon the season and/or the considered area. With the possible exception of weak tornadoes, which are not included in our study, our results show that large wind shear, in the presence of medium-to-high values of CAPE, are reliable precursors of tornadoes.

https://www.mdpi.com/2073-4433/11/3/301/pdf

A Statistical Investigation of Mesoscale Precursors of Significant Tornadoes: The Italian Case Study

Synoptic patterns and mesoscale precursors of Italian tornadoes

Characteristics of extratropical cyclones that cause tornadoes in Italy are investigated. Tornadoes between 2007 and 2016 are analyzed, and statistical analysis of the associated cyclone structures and environments is performed using the JRA-55 reanalysis. Tornadoes are distributed sporadically around the cyclone location within a window of 10° × 10°. The difference in the cyclone tracks partially explains the seasonal variability in the distribution of tornadoes. The highest number of tornadoes occur south of the cyclone centers, mainly in the warm sector, while a few are observed along the cold front. Composite mesoscale parameters are examined to identify the environmental conditions associated with tornadoes in different seasons. Potential instability is favorable to tornado development in autumn. The highest convective available potential energy (CAPE) in this season is associated with relatively high-temperature and humidity at low-levels, mainly due to the strong evaporation over the warm Mediterranean Sea. Upper-level potential vorticity (PV) anomalies and the associated cold air reduce the static stability above the cyclone center, mainly in spring and winter. On average, the values of CAPE are lower than for US tornadoes and comparable with those occurring in Japan, while storm relative helicity (SREH) is comparable with US tornadoes and higher than Japanese tornadoes, indicating that the environmental conditions for Italian tornadoes have peculiar characteristics. Overall, the conditions emerging in this study are close to the high-shear, low-CAPE environments typical of cool-season tornadoes in the Southeastern US.

Characteristics of Extratropical Cyclones That Cause Tornadoes in Italy: A Preliminary Study

Abstract. A methodological approach is proposed to provide an analytical (exponential-like) expression for the probability of occurrence of tornadoes as a function of the convective available potential energy and the wind shear (or, alternatively, the storm relative helicity). The resulting expression allows the probability of tornado occurrence to be calculated using variables that are computed by weather prediction and climate models, thus compensating for the lack of resolution needed to resolve these phenomena in numerical simulations.


Brief communication: Towards a universal formula for the probability of tornadoes

&amp;lt;p&amp;gt;The dynamics of tornadoes include large vorticity in the lower troposphere and an intense updraft, whose combination may result in their formation. In this study we investigate the possibility of using a statistical relation for their description. In fact, the nonlinearity, complexity and fine scale of these processes presently prevents their simulation in the atmospheric circulation models currently used for weather forecasts and climate projections. Here we use a large dataset of tornadoes observed in the USA and Europe and the data of ERA5 (ECMWF ReAnalysis 5) to establish a statistical link between the occurrence of tornadoes and factors whose values can be extracted from atmospheric circulation models. The values of CAPE (convective available potential energy), WS (wind shear in the lower troposphere), SRH (storm relative helicity) and LCL (lifting condensation level) of the high resolution (about 30km) ERA5 data have been considered. The analysis shows all these variables are significantly linked to the formation of tornadoes with WS and CAPE being the most relevant ones. The analysis is an extension of a former study (Ingrosso et al., 2020, &amp;lt;strong&amp;gt;10.3390/atmos11030301&amp;lt;/strong&amp;gt;) based on a dataset of tornadoes events much larger than previously, on higher resolution atmospheric data, and more prognostic variables. The results provide a new expression for the probability of occurrence of tornadoes that can be used for forecasting their likelihood with potential applications to their predictions and future changes of their frequency.&amp;lt;/p&amp;gt; 

Roberto Ingrosso

Papers

A Statistical Investigation of Mesoscale Precursors of Significant Tornadoes: The Italian Case Study

Synoptic patterns and mesoscale precursors of Italian tornadoes

Characteristics of Extratropical Cyclones That Cause Tornadoes in Italy: A Preliminary Study

Brief communication: Towards a universal formula for the probability of tornadoes

Factors leading to the formation of tornadoes: statistical links emerging from a large dataset