A Statistical Model for Large and Very Large Hail: Development, Global Climate Applications and Use in Forecasting

We have developed additive regression convective hazard models (AR-CHaMo) for predicting the occurrence of large (≥ 2 cm), very large hail (≥ 5 cm) and lightning. The models were trained using hail reports, lightning observations and parameters calculated from the ERA5 reanalysis across three different regions: Europe, the United States and Australia. The AR-CHaMo models take convective initiation explicitly into account meaning that the probability of (very) large hail is computed as the product of the probability of a thunderstorm occurring and the conditional probability of (very) large hail given a storm. AR-CHaMo outputs the probability of (very) large hail and lightning as a function of environmental predictors from the ERA5 reanalysis. While developing AR-CHaMo, we showed that a commonly used parameter such as the Convective Available Potential Energy (CAPE) should not be used as a proxy for hail worldwide as it may not fully address the fundamental physical mechanisms behind hail formation, especially across sub-tropical regions. We found the amount of CAPE released above the -10° C isotherm to outperform CAPE and to be the only instability-related parameter that can perform well regardless of the geographical region. These findings were possible thanks to the large number of (experimental) parameters,172, that were computed from ERA5 and tested within the logistic models. The AR-CHaMo models were used for two main purposes: firstly to reconstruct the long-term climatology and the associated trends in Europe, the U.S. and globally, and secondly for medium-range forecasting. The reconstruction of the long-term climatology between 1950 and 2021 across Europe and the U.S. allowed us to map the regional hotspots of (very) large hail. In the U.S., large and very large hail are most common in the Great Plains with a maximum between north-western Kansas, north-eastern Colorado and south-western Nebraska while in Europe the hotspots are northern Italy, south-western France and eastern Spain. Between 1950 and 2021, the frequency of (very) large hail has increased across most of Europe while trends are comparatively smaller in the U.S. The strongest increase is found in northern Italy where hail ≥ 5 cm is now (2012–2021) modelled to be three times more frequent than it was in the 1950s. The extension of the analysis to global scale for the period 1992–2022 showed that the positive trends detected in southern Europe are not only stronger than those in the U.S. but the strongest on a global scale. Such positive trends are driven by a local increase in low-level moisture, and consequently higher buoyancy, rather than by changes in tropospheric flow patterns. On a global scale, very large hail is most frequent across the Great Plains of the U.S., the tri-border region between Argentina, Paraguay and Brazil, and to lesser extent in South Africa. Local hotspots exist in Australia and parts of Asia but, overall, hail ≥ 5 cm is much less frequent there. During the past 30 years, very large hail is modelled to have decreased across most of the southern hemisphere especially across South America and equatorial Africa while areas of positive trends are limited to Europe and parts of the U.S. The trends of AR-CHaMo were compared to those in hail loss events across Central Europe, the U.S. and Australia. Although the number of hail loss events has increased in each of these regions, the drivers of these trends might differ. In Europe, trends in hail loss events show similarities to increases in the modelled frequency of very large hail. In the U.S., the number of hail loss events increases stronger than the modelled frequency of hail ≥ 5 cm, and in Australia the trends even show opposite signs. Increases in hail loss events are mainly driven by non-meteorological factors, namely socio-economic factors as well as more exposure with higher vulnerabilities. However, the similarities of the trend curves in Europe indicate that, here, meteorological factors might play a more important role than across the U.S. and Australia. A second application of the AR-CHaMo models involved forecasting. When applied to the ECMWF reforecasts for the period 2008–2019, AR-CHaMo proved to be skillful in predicting large hail up to 108 hours in advance. In addition, the comparison with existing composite metrics for hail forecasting showed that AR-CHaMo outperforms the product of CAPE and Deep Layer Shear (CAPESHEAR, at all lead times) and the Significant Hail Parameter (SHP, at short to medium lead times). In conclusion, the AR-CHaMo models were applied to the deterministic runs from the ECMWF IFS, GFS and ICON-EU models to yield daily probabilistic forecasts of lightning, hail ≥ 2 cm and hail ≥ 5 cm on a pan European scale. Forecasts are publicly available on the website stormforecast.eu and provide the first open- access probabilistic tool for (very) large hail forecasting. It is aimed that this tool will help forecasters in the prediction of these hazards across the whole of Europe

SRF and SRFΔ5 Splicing Isoform Recruit Corepressor LSD1/KDM1A Modifying Structural Neuroplasticity and Environmental Stress Response

Ten to 20% of western countries population suffers from major depression disorder (MDD). Stressful life events represent the main environmental risk factor contributing to the onset of MDD and other stress-related neuropsychiatric disorders. In this regard, investigating brain physiology of stress response underlying the remarkable individual variability in terms of behavioral outcome may uncover stress-vulnerability pathways as a source of candidate targets for conceptually new antidepressant treatments. Serum response factor (SRF) has been addressed as a stress transducer via promoting inherent experience-induced Immediate Early Genes (IEGs) expression in neurons. However, in resting conditions, SRF also represents a transcriptional repressor able to assemble the core LSD1/CoREST/HDAC2 corepressor complex, including demethylase and deacetylase activities. We here show that dominant negative SRF splicing isoform lacking most part of the transactivation domain, namely SRFΔ5, owes its transcriptional repressive behavior to the ability of assembling LSD1/CoREST/HDAC2 corepressor complex meanwhile losing its affinity for transcription-permissive cofactor ELK1. SRFΔ5 is highly expressed in the brain and developmentally regulated. In the light of its activity as negative modulator of dendritic spine density, SRFΔ5 increase along with brain maturation suggests a role in synaptic pruning. Upon acute psychosocial stress, SRFΔ5 isoform transiently increases its levels. Remarkably, when stress is chronically repeated, a different picture occurs where SRF protein becomes stably upregulated in vulnerable mice but not in resilient animals. These data suggest a role for SRFΔ5 that is restricted to acute stress response, while positive modulation of SRF during chronic stress matches the criteria for stress-vulnerability hallmark

Invited perspectives: Thunderstorm Intensification from Mountains to Plains

Severe thunderstorms are among the most damaging and impactful weather phenomena. In Europe, notable clusters occur in the vicinity of complex terrain. These areas not only experience frequent thunderstorms but also show a strong climate change signal with an increasing storm frequency. Despite the relevance of the subject, our understanding of severe convection in complex terrain, particularly in a changing climate, remains incomplete. This review presents the current state of the research on thunderstorms in complex orography, covering storm severity, modification of pre-storm environments, convection initiation, storm-scale interactions with complex terrain, impactful hazards, numerical modeling and forecasting, climatologies and climate change signals, as well as innovative storm observations. Highlighting the gaps in our understanding, this review underscores the need for a coordinated European field campaign on Thunderstorm Intensification from Mountains to Plains (TIM). Initial plans for the TIM campaign built by participating authors and institutions of this article are briefly outlined. Obtaining coordinated and dense data on orographically driven storms is a key step toward improving warnings, forecasts, future climate projections, and adaptation measures

Acute Stress-Induced Epigenetic Modulations and Their Potential Protective Role Toward Depression

Psychiatric disorders entail maladaptive processes impairing individuals’ ability to appropriately interface with environment. Among them, depression is characterized by diverse debilitating symptoms including hopelessness and anhedonia, dramatically impacting the propensity to live a social and active life and seriously affecting working capability. Relevantly, besides genetic predisposition, foremost risk factors are stress-related, such as experiencing chronic psychosocial stress—including bullying, mobbing and abuse—, and undergoing economic crisis or chronic illnesses. In the last few years the field of epigenetics promised to understand core mechanisms of gene-environment crosstalk, contributing to get into pathogenic processes of many disorders highly influenced by stressful life conditions. However, still very little is known about mechanisms that tune gene expression to adapt to the external milieu. In this Perspective article, we discuss a set of protective, functionally convergent epigenetic processes induced by acute stress in the rodent hippocampus and devoted to the negative modulation of stress-induced immediate early genes (IEGs) transcription, hindering stress-driven morphostructural modifications of corticolimbic circuitry. We also suggest that chronic stress damaging protective epigenetic mechanisms, could bias the functional trajectory of stress-induced neuronal morphostructural modification from adaptive to maladaptive, contributing to the onset of depression in vulnerable individuals. A better understanding of the epigenetic response to stress will be pivotal to new avenues of therapeutic intervention to treat depression, especially in light of limited efficacy of available antidepressant drugs

Acute Stress-Induced Epigenetic Modulations and Their Potential Protective Role Toward Depression

Psychiatric disorders entail maladaptive processes impairing individuals’ ability to appropriately interface with environment. Among them, depression is characterized by diverse debilitating symptoms including hopelessness and anhedonia, dramatically impacting the propensity to live a social and active life and seriously affecting working capability. Relevantly, besides genetic predisposition, foremost risk factors are stress-related, such as experiencing chronic psychosocial stress—including bullying, mobbing and abuse—, and undergoing economic crisis or chronic illnesses. In the last few years the field of epigenetics promised to understand core mechanisms of gene-environment crosstalk, contributing to get into pathogenic processes of many disorders highly influenced by stressful life conditions. However, still very little is known about mechanisms that tune gene expression to adapt to the external milieu. In this Perspective article, we discuss a set of protective, functionally convergent epigenetic processes induced by acute stress in the rodent hippocampus and devoted to the negative modulation of stress-induced immediate early genes (IEGs) transcription, hindering stress-driven morphostructural modifications of corticolimbic circuitry. We also suggest that chronic stress damaging protective epigenetic mechanisms, could bias the functional trajectory of stress-induced neuronal morphostructural modification from adaptive to maladaptive, contributing to the onset of depression in vulnerable individuals. A better understanding of the epigenetic response to stress will be pivotal to new avenues of therapeutic intervention to treat depression, especially in light of limited efficacy of available antidepressant drugs

Endocannabinoid-Epigenetic Cross-Talk: A Bridge toward Stress Coping

There is no argument with regard to the physical and psychological stress-related nature of neuropsychiatric disorders. Yet, the mechanisms that facilitate disease onset starting from molecular stress responses are elusive. Environmental stress challenges individuals’ equilibrium, enhancing homeostatic request in the attempt to steer down arousal-instrumental molecular pathways that underlie hypervigilance and anxiety. A relevant homeostatic pathway is the endocannabinoid system (ECS). In this review, we summarize recent discoveries unambiguously listing ECS as a stress coping mechanism. As stress evokes huge excitatory responses in emotional-relevant limbic areas, the ECS limits glutamate release via 2-arachydonilglycerol (2-AG) stress-induced synthesis and retrograde cannabinoid 1 (CB1)-receptor activation at the synapse. However, ECS shows intrinsic vulnerability as 2-AG overstimulation by chronic stress rapidly leads to CB1-receptor desensitization. In this review, we emphasize the protective role of 2-AG in stress-response termination and stress resiliency. Interestingly, we discuss ECS regulation with a further nuclear homeostatic system whose nature is exquisitely epigenetic, orchestrated by Lysine Specific Demethylase 1. We here emphasize a remarkable example of stress-coping network where transcriptional homeostasis subserves synaptic and behavioral adaptation, aiming at reducing psychiatric effects of traumatic experiences.</jats:p

Stormforecast.eu: real-time automated forecasts for hail and lightning based on post-processed NWP

&amp;lt;p&amp;gt;The European Severe Storms Laboratory (ESSL) has developed logistic models (AR-CHaMo) for the occurrence of lightning and (very) large hail based on the ERA5 reanalysis, with the primary purpose of investigating long-term chance in severe weather occurrence. These models can, however, also be used in a forecasting context.&amp;amp;#160;&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;We have set up a routine that uses AR-CHaMo models to post-process the output of three different NWP models, the ECMWF IFS HRES, DWD&amp;#039;s ICON-EU, and NCEP&amp;#039;s GFS to obtain probabilities of hail and lightning occurrence. The results were evaluated as a part of the ESSL Testbeds in 2022.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;Forecast maps showing the calculated probabilities for the current and following day are calculated from the average of the three models and are made available on a website. The website interface allows overlaying reports from the European Severe Weather Database, which give an impression of the quality of the forecasts and help to identify existing weaknesses. Work is underway to include ensemble forecasts, and quantitative real-time verification, and to extend the forecast horizon as part of projects supported by the Austrian Science Fund and ECMWF. We show several AR-CHaMo lightning and large hail forecasts that resulted in no hail, large hail, and very large hail and discuss their performance.&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;</jats:p

Psychiatric Disorders and lncRNAs: A Synaptic Match

Psychiatric disorders represent a heterogeneous class of multifactorial mental diseases whose origin entails a pathogenic integration of genetic and environmental influences. Incidence of these pathologies is dangerously high, as more than 20% of the Western population is affected. Despite the diverse origins of specific molecular dysfunctions, these pathologies entail disruption of fine synaptic regulation, which is fundamental to behavioral adaptation to the environment. The synapses, as functional units of cognition, represent major evolutionary targets. Consistently, fine synaptic tuning occurs at several levels, involving a novel class of molecular regulators known as long non-coding RNAs (lncRNAs). Non-coding RNAs operate mainly in mammals as epigenetic modifiers and enhancers of proteome diversity. The prominent evolutionary expansion of the gene number of lncRNAs in mammals, particularly in primates and humans, and their preferential neuronal expression does represent a driving force that enhanced the layering of synaptic control mechanisms. In the last few years, remarkable alterations of the expression of lncRNAs have been reported in psychiatric conditions such as schizophrenia, autism, and depression, suggesting unprecedented mechanistic insights into disruption of fine synaptic tuning underlying severe behavioral manifestations of psychosis. In this review, we integrate literature data from rodent pathological models and human evidence that proposes the biology of lncRNAs as a promising field of neuropsychiatric investigation.</jats:p

Forecasting Large Hail Using Logistic Models and the ECMWF Ensemble Prediction System

&amp;lt;p&amp;gt;An additive logistic regression model for large hail was developed based on convective parameters from ERA5 reanalysis, severe weather reports from the European Severe Weather Database (ESWD), and lightning observations from the Met Office Arrival Time Difference network (ATDnet). This model was shown to accurately reproduce the spatial distribution and the seasonal cycle of observed hail events in Europe. A spatial map of the modelled mean distribution for hail &amp;gt;&amp;amp;#160;2 cm will be presented.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To explore the value of this approach to medium-range forecasting, a similar statistical model was developed using four predictor parameters available from the ECMWF Ensemble Prediction System (EPS) reforecasts: Mixed Layer CAPE, Deep Layer Shear, Mixed Layer Mixing Ratio and the Wet Bulb Zero Height. Probabilistic large hail predictions were created for all available 11-member ensemble forecasts (2008 to 2019), for lead times from 12 to 228 hours.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;First, we evaluated the model&amp;amp;#8217;s predictive skill depending on the forecast lead time using the Area Under the ROC Curve (AUC) as a validation score. For forecasts up to two to three days, the model highlights a very high predictive skill (AUC &amp;gt; 0.95). Furthermore, the model retains a high predictive skill even for extended forecasts (AUC = 0.85 at 180 hours lead time) showing that it can identify regions with hail potential well in advance. Second, we compared the forecast spatial probabilities at various lead times with observed hail occurrence focusing on a few recent hail outbreaks. Finally, our four-dimensional model was compared with logistic models based on composite parameters such as the Significant Hail Parameter (SHP) and the product of CAPE and Deep Layer Shear (CAPESHEAR). The four-dimensional model outperformed these composite-based ones at lead times up to four days. The high AUC scores show that this model could improve short-medium range hail forecasts. Preliminary application of this approach to other convective hazards such as convective wind gusts will be presented as well.&amp;lt;/p&amp;gt;</jats:p