bluuebunny/crossref_metadata_2025 huggingface dataset:
Will hail be severe? Elusive Environmental Predictors Generating Large Hail
Authors: Allen John , Nixon Cameron , Kumjian Matthew , Taszarek Mateusz
Published: March 2023

Expected hail size is frequently poorly forecast. Hail predictions have been explored on a variety of timescales through both modeling and statistical approaches, though relatively few skillful predictors have been identified. The lack of applicable predictors has led to challenges in understanding why a given parameter may inform the expected occurrence of hail, or its absolute diameter. Previous approaches have focused around bulk metrics or coarse parameterizations of storm processes. However, these efforts have been hampered by a failure to focus on the underlying quality control of the data, including lack of  consideration of the representativeness of hail size observations, inappropriate use of nulls, and failure to look beyond existing parameters. This presentation will focus on new insights and parameters identified through modeling, discriminant analyses, self-organising maps and clustering, and leverages a data-informed approach to better characterise the relationship between the ambient storm environment and hail characteristics. We find that key to addressing this problem is the addition of consideration of synoptic regime, regional differences, seasonality and storm mode.

 

Parameter importance is tested through ERA-5 pseudo-proximity soundings to hail profiles from multiple datasets, including the Storm Prediction Center (SPC) Storm Data, the SPC Storm Mode Dataset, Community Collaborative Rain, Hail and Snow Network (CoCoRAHS) and Meteorological Phenomena Identification Near the Ground (MPING). Through use of buddy-checking, and a KD-tree approach for spatial independence, these sources in combination yield 80,000 reliable and independent cases over the past 25 years. Using these data allows assessment of the relationship between hail and its environment for a variety of sizes ranging from 6.4mm to >100.2 mm in maximum diameter. Results show that the null dataset being used to predict hail is important, and prior approaches have likely failed due to strong parameter overlaps for existing parameters. Through this analysis, we find that predictability exists for whether hail will be severe (>2.5 cm) or not, but with existing parameters the predictability becomes more challenging for discriminating larger categories. These results also highlight that many common associations between parameters (e.g. CAPE and hail size) are improperly-posed, as hail production exhibits multiple environmental pathways or requires different parameters, or can be driven by storm dynamics. These suggest that a multi-model and profile-aware approach is necessary to obtain reliable environmental-based predictions of hail size.  

 
Toward a dedicated warning system of severe storms in Italy: the PRETEMP project
Authors: De Martin Francesco , Carlon Nicola , Pavan Federico , Carpentari Sebastiano , Giazzi Marco , Peressutti Gianandrea , Miglietta Mario Marcello , Davolio Silvio
Published: March 2023

A dedicated warning system can significantly reduce economic and human losses during severe storm events. While in the USA a well-tested warning system exists since many years, a corresponding institutional warning system has not been established so far in Europe. ESTOFEX has been the first attempt of a severe weather forecasting system at a European-scale, very appreciated by the meteorological community, but on a voluntary basis. 

PRETEMP is an initiative carried on by a group of students and young meteorologists who aim to replicate the ESTOFEX initiative at a national scale: it has been publishing a severe weather outlook specific for Italy every day since 2015. Italy is a country with very complex orography mostly surrounded by the sea. Therefore, a national dedicated warning system may allow to capture local mesoscale features, important for severe storm development, better than an outlook on a continental scale. Like ESTOFEX, PRETEMP is a volunteer group, but it has informal collaboration with local weather agencies: hopefully, in the near future it can be an example for an institutional warning system. The PRETEMP forecast is based on four levels of severity, ranging from level 0 (generic thunderstorms) to level 3 (extremely severe storms).

Furthermore, PRETEMP has been collecting severe storm reports from Italy since 2018, exploiting the Storm Report Database created by Meteonetwork, an Italian amateur association. These reports, collected by many volunteers and local meteorological associations, ensure a capillary network of storm spotters: it represents an effective example of citizen science applied to severe weather. They have been automatically submitted to the ESWD (European Severe Weather Database) since 2019 representing the main source of storm reports from Italy. In addition, in case of tornado events, PRETEMP contribute to the path damage reconstruction and tornado classification, in collaboration with ESSL. 

More recently PRETEMP is testing some forecast verification techniques to increase the reliability of the forecast product and to assess and improve the forecaster performance. Initially the forecast verification was qualitative, based on a simple overlay of storm report locations on the outlook map. PRETEMP is now moving toward a more quantitative approach, testing both dichotomous (to create performance diagrams) and probabilistic approaches (using the Brier Skill Score index), to find the most suitable method to assess the outlooks.
Comparing probabilistic and dichotomous forecasts of hazardous events on a consistent basis: Toy statistical models applied to tornado forecasting
Authors: Brooks Harold
Published: March 2023

In 1963, Fred Sanders wrote “it is urged the probability be acknowledged as the proper internal language of forecasters.” As such, we can consider all forecasts to be based on probabilities. Nevertheless, as Sanders discussed, issuance of probabilistic forecasts to users is not completely clear. In many cases, users may prefer a categorical forecast and, as such, the internal language of probabilities must be translated into an external language of categorical forecasts. Although there are simple ways to threshold probabilities of a dichotomous (yes/no) event into a yes/no forecast, doing so in a way that is consistent between the two expressions is not always easy. This becomes even more complex when not all users have the same decision threshold and, as a result, may have different preferences for where the optimal threshold is set.

A typical example of this problem is the area of tornado forecasting, especially for short range (<1 hour) forecasts of events, such as is the case for tornado warnings in the United States. Here, I develop and explore some simple (“toy”) models of probability distributions for the forecast and occurrence of tornadoes, as well as the user decision problems. Since each of the three models have one (occurrence given a forecast) or two (forecast probability and distribution of user decisions) parameters, it is relatively easy to construct probabilistic models that can be thresholded to mimic tornado warning performance over time in the United States. In addition, the apparent global benefits (or losses) can be estimated for different probabilistic forecast distributions related to different user decisions compared to dichotomous forecasts.

Although this methodology could not directly produce tornado warnings in an operational setting, it provides some limits on how a future system based on probabilities could be constrained. The process allows for the development of thresholded forecasts that are consistent with the underlying probabilistic information.
SALAMA: A Machine Learning approach for lightning forecasting through post-processing of simulation data
Authors: Vahid Yousefnia Kianusch , Bölle Tobias , Zöbisch Isabella
Published: March 2023

Thunderstorms constitute a major hazard to society and economy. Especially in light of the expected increase of extreme weather events due to climate change, reliable thunderstorm warnings become ever more important. However, as lightning is not directly computed in numerical weather prediction (NWP) simulations, the appearance of thunderstorms in forecast output remains elusive. In this work, we introduce SALAMA, a tool to identify signatures of lightning activity in NWP simulations using a feedforward artificial neural network (ANN). It infers in a reliably calibrated manner the probability of lightning occurrence at some point in space and time, given only a set of local input parameters that are extracted from NWP simulations and related to thunderstorm development. We train the neural network with ensemble forecasts from ICON-D2-EPS during the summer period of 2021. The skill of SALAMA is measured through established scores from meteorology and machine learning. We study in detail how the forecast skill depends on the lead time of the forecast as well as the spatial scale of the forecast objects and put particular emphasis on a careful estimation of model uncertainty. Even with a relatively simple ANN architecture and local input parameters, we find a forecast skill superior to traditional approaches in the literature. SALAMA is ready for operational use.
Implementing physical assumptions about nonspherical hailstone shapes
Authors: Lin Yuzhu , Kumjian Matthew R.
Published: March 2023

Numerical modeling is valuable in hail research and forecasting. Physical assumptions regarding hailstones’ shape, tumbling behavior, fall speed, and thermal energy transfer are applied in this process, be it explicit or inexplicit. However, many of these physical assumptions are uncertain. In this study, we investigate the effect of applying different physical assumptions in hail modeling using Cloud Model 1 to simulate supercell storms, coupled with the detailed 3D hail growth trajectory model by Kumjian & Lombardo (2020; hereafter KL20). We then examine the reason behind the variability in hail statistics produced with these assumptions. 

Most microphysics schemes and hail models assume hailstones are spherical (e.g., Morrison et al. 2005; Adams-Selin & Ziegler 2016; KL20). Using hailstone shape data from Heymsfield et al. (2020) and Shedd et al. (2021), we establish a relationship between the hailstones’ mass or equivalent spherical diameter and the largest, smallest, and intermediate dimensions with reasonable degrees of randomness in consideration of hailstones’ shape variability, capturing the observed distribution of tri-axial ellipsoidal shapes. We also incorporated explicit, random 3D tumbling of individual hailstones during each timestep of their growth to simulate the behavior of free-falling, non-spherical particles (Bagheri & Bonadonna 2016) and the resultant changes in cross-sectional area (which affects collection of cloud droplets). These physical attributes are then incorporated in calculating the hailstone’s terminal velocity, using either empirical relationships such as that derived in Heymsfield et al. (2020), or analytical relationships from Bagheri & Bonadonna (2016) based on each hailstone’s Best number and Reynolds number. Options for drag coefficient modification are added to characterize the hailstone’s rough surface with varying degrees of “lobiness.” The hailstone’s shape and “lobiness,” in turn, modify its thermal energy transfer coefficient (Macklin 1963; Bailey & Macklin 1968). We find the choice of hailstone diameter-mass relation, and terminal velocity scheme to have the strongest influence on final hail size. Using non-spherical, tumbling hailstones tends to reduce the number of large hail produced in our simulated supercell storms; applying shape-specific thermal energy transfer coefficients tends to increase final hail size by a small amount; the effect of lobes varies depending on the terminal velocity scheme used. We show that many of these physical assumptions, albeit adding complexity to hailstone growth modeling, can be parameterized efficiently and potentially used in bulk microphysics schemes.
Marginal Tornado Environments: Tipping the Balance
Authors: Anderson-Frey Alexandra
Published: March 2023

Tornado warnings for more extreme near-storm environments generally have higher skill, with better probability of detection and false alarm ratio both associated with tornadic environments featuring higher CAPE, shear, storm-relative helicity, and lower LCL heights. Tornadoes do, however, often occur in association with more marginal near-storm environments, suggesting several possibilities that may occur in combination, including: (1) the proximity sounding used to define the environment may not be representative of the environment in which the tornadic storm actually developed (e.g., via convective contamination or positioning of the sounding to the wrong side of an environmental gradient), (2) the presence or absence of a tornado may display an extreme sensitivity to minor fluctuations in the environment (e.g., if CAPE is limited in an environment, a very small amount of CAPE may tip the balance), or (3) the presence or absence of a tornado may display an extreme lack of sensitivity to environmental parameters (e.g., the driving force for a given tornado is described by small-scale stochastic processes rather than any bulk features of the near-storm environment).

In order to gauge the appropriateness and limitations of traditional near-storm environmental parameters in the cases for which near-storm environments are marginal, this work digs into US tornado events that are clustered via self-organizing maps around a node in which the 480 km x 480 km squares of significant tornado parameter (STP) surrounding the recorded tornado events are characterized by universally low values (the examination of a broad area surrounding the tornado helps ensure that representativeness does not hinge on a single proximity sounding). This marginal cluster is then further split via a nested SOM to tease out any subtle variations and patterns in the environment that may be present. Discussion focuses on regional, seasonal, and diurnal variability of these patterns across tornado events, with an eye to establishing some of the situations in which tornadogenesis occurs in spite of marginal-to-unfavorable conditions in the near-storm environment, opening the door to idealized numerical modeling studies.
Analysis of severe weather detection in the metropolitan area of Korea using X-Band weather radar
Authors: Park Jin-woo , Mo Sun-Jin , Gu Ji-Young , Lee Seungwoo
Published: March 2023

It is very important  to detect hazardous small scale weather phenomena occurred in highly populated areas because of its catastrophic damages. In order to monitor these local events and provide appropriate information about high impact weather, the Weather Radar Center of the Korea Meteorological Administration has installed the X-band radar netwGork consisting of three dual-polarization radars with the solid state power amplifier (SSPA) over the metropolitan area in October 2018. These radars are operating with three elevation angles per 1 minute and 150m gate size. 

In this study, we investigated severe weather cases that occurred in the Seoul metropolitan area by the analysis of data from the X-band weather radar observation network. The first case is  a strong convective event that led flash flood and many casualties over the central area of Seoul city within a 6-hour period in August 2022.  The second one is the tornado case that occurred in September 2020. Although it is a rare event on the Korean Peninsula, the high spatial and temporal resolution data of the X-band weather radar observation network can provide detailed characteristics of hazardous weather.  In particular, the X-Band network yielded better results compared with the S-Band weather radar observation network through the high spatio-temporal resolution.

In this study, we have found out some benefits of the X-band radar network when we explore the rapid developing small scale convective events. Since the X-band frequency has more attenuation for heavy precipitation and lose signals in wet radom condition, quality control and correction are essential to the performance of the products. Therefore, QC and quantitative estimation of heavy rainfall will be the main objectives of our future study.  

 

Acknowledgements:

This research was supported by the "Development of radar based severe weather monitoring technology (KMA2021-03221)" of "Development of analysis technologies for local-scale weather radar network and next generation radar" project funded by the Weather Radar Center, Korea Meteorological Administration.
Assessment of extremes hazards during thunderstorm in France 2000-2019
Authors: Bertrand Nathalie , Gaonac'h Adrien
Published: March 2023

The estimation of natural hazard levels must be considered for the protection of industrial sites for important safety issues. Our study estimates the occurrence, the spatial extension and the concomitance of natural hazards (rain, wind, hail and lighting) during thunderstorm over France during the period 2000-2019.

A thunderstorm is an atmospheric convective instability. In general, a thunderstorm needs a warm and humid air mass to rise in an unstable atmosphere under the effect of some kind of forcing initiating a more or less deep humid convection leading to the formation of cumulonimbus. Depending on the characteristics of the air mass and the wind regimes at different altitude levels, thunderstorms will be of different natures and will produce different types of hazards with a certain intensity: heavy rain, lightning discharges, hail, strong wind gusts and sometimes tornadoes. A severe thunderstorm is defined by the occurrence of at least one of the following conditions: heavy rain, hail with a diameter of more than 2 cm, wind gusts above 25 m/s and tornadoes.

Hence, the study considers all the available data and project them on the same grid (Meteorage lightning grid with 25 km resolution). A thunderstorm event is defined when more than ten lightning are observed on the same day. Then, the probabilities and conditional probabilities knowing the occurrence of a thunderstorm were derived for each hazard over the period and by seasons. It emerges that the regions particularly affected by thunderstorms and their hazards are in a diagonal going from south-west to north-east France, the mountains areas during the warm seasons and the Mediterranean region, the Cevennes during hot and cold seasons especially in autumn with the Mediterranean event which brings heavy rainfall due to the influence of the sea and the proximity with the mountain. However, although it seems that thunderstorms are more frequent over the decade 2010-2019 than in the years 2000-2009, it is difficult to draw a conclusion on the evolution and intensity of these events over such a short period with the inter-annual variability.

To go further, the study explores the potential of the so-called "self-organising" map to describe the different synoptic scenarios leading to these extreme events and their combinations.
Deep Learning for Hail Size Estimation Using Polarimetric Radar Data
Authors: Forcadell Vincent , Augros Clotilde , Dedieu Kevin , Caumont Olivier
Published: March 2023

In 2022, convective storms producing large hailstones were responsible of significant damages in Europe, particularly in France, where the insurance sector was severely hit. As a result, prices for 2023 might rise significantly compared to 2022, leaving a lot of pressure on the sector. Thus, the need to correctly assess and measure hail damage in real time has become crucial to assist communities in Europe and help them recover from such events.

The potential of radar data, when it comes to the detection of hail, is not to be challenged anymore: radar remains since decades the best remote sensing tool to detect such hazard. As a result, a lot of computational methods using radar data were developed to detect hail and estimate its size in real-time. Probability of hail based algorithms, hydrometeor classification using fuzzy logic or new methods using machine learning were explored to locally quantify the presence of hail in storms. Recent studies even suggest that studying the structure of the parent storm when there is hail could be of interest. Deep Learning algorithms built to analyze images and detect features in multi-dimensional data appear to be a good lead for estimating the occurrence and the size of hail in storms and on the ground. Applied to radar data, such techniques could detect signatures specific to hail and enhance our understanding on why one storm can produce 2cm hailstones and another 10cm hailstones.

This work aims to present a novel approach using Convolutional Neural Networks (CNNs) on radar images to detect hail occurrence and estimate its size. Based on multiple hail cases in France from 2017 to 2022 and hail reports on the ground, a CNN is trained and tested. Comparisons are made with existing sizing algorithms such as Fuzzy-Logic Hydrometeor Classification or Maximum Estimated Size of Hail (MESH). First results show great perspectives, even with really simple network architectures.
Enhance object-based thunderstorm nowcasting with the use of next-generation satellite data at DWD
Authors: Strube Cornelia , Müller Richard , Werner Manuel
Published: March 2023

The first satellite of the European next-generation meteorological satellite series Meteosat Third Generation was launched in December 2022 and is expected to deliver data operationally by the end of 2023. The new Flexible Combined Imager (FCI) instrument provides an image repeat rate of 10 minutes and higher spatial resolution of the up to 500m at the sub-satellite point. In addition, new datasets from channels that have not been available from the predecessor instrument SEVIRI on Meteosat Second Generation as well as the new Lightning Imager instrument will offer improved opportunities for the thunderstorm nowcasting over Europe and Africa.

At Deutscher Wetterdienst (DWD; english: German Meteorological Service), we strive to include these new datasets into our nowcasting pipelines. Here, we want to present work on the definition and incorporation of satellite-based storm features to enhance the object-based thunderstorm nowcasting tool KONRAD3D. So far, satellite data was not part of the process. We define storm objects in satellite images using a region-growing approach seeded on the radar-based KONRAD3D feature centroids in particular in early-convection environments. These storm objects are then used to calculate properties of the developing storm from satellite data, like relevant convective (initiation) characteristics, e.g. glaciation, updraft, and cloud-top cooling properties from infrared brightness temperatures, as well as structural features in the visible reflectance. By design, these additional storm characteristics from the satellite can be easily assigned to the corresponding KONRAD3D object and used in decisions like the determination of the storm severity. In addition, we plan to use the statistical analysis of the properties and tracking of the radar and satellite objects alongside each other to develop a data-driven classification model to connect early detection of cumulus clouds from the satellite to the later severity of the developed storm. Since the commissioning phase data from FCI will only become available in the course of this year, the development still builds on equivalent channels in SEVIRI data for now prepared to switch to FCI as soon as the data becomes available.
CHMI Forecasters Supported by a Team of Convective Experts
Authors: Valachová Michaela , Adamovský Martin , Tomšů Radek , Piskala Gvoždíková Blanka
Published: March 2023

A special team of forecasters – the Convective Group (CG), largely trained by ESSL Testbeds, was appointed at CHMI to improve the prediction and nowcasting of convective storms. We bring the experience and lessons learned from the first, pilot season of the CG operation. A decision-making process, data availability, and communication was the most demanding part of our supporting shifts, which we will show in a few case studies from 2022. The CG has established new criteria for different levels of severe storm warnings, including the expected storm structure. CHMI issues thunderstorm warnings one or two days in advance for a larger area, where is a higher chance for severe storms. Later, tens of minutes before the severe storm occurrence, a warning is issued (manually) with 100% probability that the given area will be affected. The CG works as an advisory body for the forecasters on duty, who issue the actual warnings. The scope of other activities is wide, the CG trains forecasters before the summer, also proposed the use of drones for damage surveys (e.g. downburst, tornado, or flash flood). During the season, we were in close contact with the forecasters on duty during days when storms were expected. Concurrently, we were immediately in contact with the public/media and informed about imminent danger, uncertainty, or summary of recent events through the CHMI social networks. We received a lot of positive feedback, which was very encouraging. Inspiration from other national weather services is very welcome.
Recent developments in convection forecasting at ECMWF
Authors: Tsonevsky Ivan , Groenemeijer Pieter , Battaglioli Francesco , Púčik Tomáš
Published: March 2023

The representation of convection in ECMWF’s forecasting system has been improved in recent years by advances in computing, substantial upgrades of both horizontal and vertical resolutions, and by major changes in the moist processes in the model. These developments have also opened up the opportunity for improvements of existing convective products and the development of new ones, such as lightning density diagnostics. As part of this ongoing initiative ECMWF is partnering with the European Severe Storms Laboratory (ESSL) on a number of projects. The computation of Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN) parameters from the model has been revised and more versions of CAPE and CIN have been implemented and are made available to the forecasting community. CAPE and composite CAPE-shear parameters have been included in ECMWF’s Extreme Forecast Index (EFI) to help forecasting outbreaks of severe convection in the medium range. Alongside objective statistical verification, the convective EFI has been evaluated at ESSL’s Testbed recently. ECMWF has implemented ensemble vertical profiles to facilitate forecasting convection among other applications. ECMWF is working with ESSL on providing more parameters and products for forecasting deep, moist convection and its attendant severe weather. These include Storm Relative Helicity (SRH) and post-processed probabilities of various convective hazards such as large hail and severe wind gusts. Following its open data policy, ECMWF has also provided more probabilistic and deterministic graphical convective products on its website. This presentation will provide a brief overview of all these recent developments.
Climatological aspects of quasi-linear convective systems across Europe
Authors: Surowiecki Artur , Pilguj Natalia , Taszarek Mateusz , Piasecki Krzysztof , Pucik Tomas
Published: March 2023

In this work, we use 8 years of OPERA radar data, ESWD severe weather reports, and ATDnet lightning detection data to create a climatology of quasi-linear convective systems (QLCS) across Europe. In the first step, 15-minute composite animations of radar reflectivity and lightning data were used to manually identify 2201 QLCS polygons in the period of 2014 to 2021. Severe weather reports, lightning data, and morphological properties (such as the presence of bowing segments) allowed classifying QLCSs according to their intensity into 1844 marginal, 304 moderate, and 53 derecho cases. The manual evaluation also allowed us to identify: the basic archetype of the system, the location of stratiform precipitation relative to the active convective part, propagation with respect to the mean wind, areal coverage, width, length, accompanying hazards, and social impacts associated with each QLCS. Results indicate that QLCSs are the most frequent during summer in Central Europe, while in southern Europe the season of their occurrence is extended to late autumn. QLCSs are the least frequent during winter when they appear mostly in northwestern Europe in the form of narrow cold frontal rainbands (NCFR). In spring they are most common across western Europe. The vast majority of systems move from southwest and west. 22% of the systems were associated with a bow echo signature and 6% produced a mesoscale convective vortex. Among precipitation modes, trailing (53%) and embedded (45%) stratiform types were the most common. The longest classified QLCS had a length of 2200 km (9 Aug 2018), while the widest reached 1635 km (10 Jan 2015). The most frequent hazard accompanying QLCSs was lightning (produced during 95% of the total QLCSs lifetime), followed by severe winds gusts (7.7%), excessive precipitation (5.3%), large hail (2.7%), and tornadoes (0.4%). Derechos had the largest coverage of severe wind reports with respect to their path area (49%), while back-building QLCS had the largest coverage of excessive precipitation events (12%). Large hail was most common with bow-echo complexes (6.5%).
Tornadoes in France since 1900: A chronology and spatial analysis.
Authors: Lacroix Matthieu , Gunnell Yanni , Kermadi Saïda
Published: March 2023

Since 1900, France has recorded annually 22 tornadoes of low to moderate intensity. Here we investigate the spatial distribution and seasonal patterns of these tornadoes, and document some of the meteorological situations in which they have occurred. We further produce (i) a synthesis of the areas where thunderstorms are formed, with the aim of better understanding the environments favourable to thunderstorm development in France; and (ii) a national tornado risk map emphasising areas exposed to tornadoes in relation to population density. The results of this study are based on data from the Météo-France major events repository (BDEM), the European Severe Storm Laboratory (ESSL/ESWD), and the Keraunos database. This combination results in a complete inventory covering the period 1900-2022. The events selected for the study were analysed in a Geographic Information System, and data from different meteorological reanalyses, such as the GPM IMERG (NOAA NCEP/NCP) and ERA 5, were used for defining the formation zones of a selection of tornado events in the highly affected region.

The spatial distribution of tornadoes in France highlights three vulnerable areas: the north (Normandy, Flanders), the Atlantic west (Poitou, Charentes) and the Mediterranean coastal belt (Languedoc, Provence, NE Corsica). Whereas monthly results highlight a systematic concentration of tornadoes during the warmer season, their spatial distribution appears to be a function of topography- and land-cover-related factors. Specific zones of tornadic storm formation over the Bay of Biscay and the Mediterranean Sea also feature prominently, and these are expected to continue generating tornadoes in the future. The high-risk areas include densely populated urban regions, especially in northern France and near the Mediterranean.

 
What is a Mesocyclone?
Authors: Kumjian Matthew , Lombardo Kelly , Coffer Brice , Dahl Johannes
Published: March 2023

A defining feature of supercells is the mesocyclone, which has been implicated in facilitating updraft maintenance and strength, as well as tornado and hail production. But what, exactly, is a mesocyclone?

Popular textbooks define the mesocyclone as a “region of vertical vorticity with a characteristic width of 3-8 km and magnitude O(10-2 s-1)” (Markowski and Richardson 2010), or a “cyclonically rotating vertical vortex with typical diameters ~5 to 6 km” with tangential windspeeds of “several 10s of m s-1,” and typical vertical vorticity of 0.01 s-1 (Trapp 2013). The American Meteorological Society’s Glossary defines the mesocyclone as a “cyclonically rotating vortex, around 2-10 km in diameter, in a convective storm,” with a vertical vorticity threshold of >0.01 s-1. These definitions also indicate persistence and depth through a significant fraction of the updraft as important factors (e.g., Doswell and Burgess 1993). Using these definitions, however, many high-resolution supercell simulations would fail to generate a “mesocyclone.” Often, only a “vortex segment” – and not a closed vortex – is present (e.g., Dahl 2017). Further, such simulations often reveal noisy vertical vorticity fields lacking broad, coherent regions meeting the thresholds above.

In practice, mesocyclones are detected using Doppler radar. In particular, mesocyclones are identified when cyclonic azimuthal shear thresholds are met (often with temporal and depth criteria, too). However, such measurements are incapable of unambiguously determining the presence of a vortex, and provide only a proxy for vertical vorticity. Further, a single Doppler radar generally offers no information on the updraft’s boundaries. Thus, many of the defining characteristics mesocyclones are not actually detectable operationally.

In this presentation, we seek discussion from the community of whether an improved, dynamical definition for a mesocyclone is needed, how to reconcile such a definition to make it applicable to both simulations and radar observations, and to solidify ambiguities in the terminology of "low-" and "midlevel" mesocyclones.

We also offer an interactive activity: go to the link below and identify the coordinates (x, y) of the mesocyclone center and its diameter for the two images provided on that webpage. We will report on the results at the conference. 

https://forms.gle/FEKNWZe6mkcLcWpS6

 
Using dual-polarimetric radar moments to improve the precipitation estimate over Germany 
Authors: Gottschalk Matthias , Hengstebeck Thomas
Published: March 2023

Deep summertime convection associated with heavy rain and flooding endangers life and property. Radar derived quantitative precipitation estimates (QPE) play an important role as input for hydrological models and flash flood warnings. QPE is also one of the key inputs for nowcasting applications and seamless forecasting products as developed by the SINFONY (Seamless INtegrated FOrecastiNg sYstem)-project of Deutscher Wetterdienst (DWD).

Currently, the QPE at the DWD follows a hydrometeor-based approach, where reflectivity-rainfall rate relationships are selected depending on the results of a hydrometeor classification scheme. Each solid hydrometeor, such as hail, graupel or snow, has its own reflectivity-rainfall rate relationship, while the liquid phase also includes a proxy for convective or stratiform rain depending on the gradient in the reflectivity field.

According to literature, dual-polarimetric radar moments can directly be used to derive QPE. Gorgucci et al., 1994 showed an improvement in rain rate by combining the radar reflectivity and the differential reflectivity (ZDR) to derive the QPE. Chen et al., 2021 favored a combination of reflectivity and the specific differential phase (KDP) to estimate rain rates for the German C-Band radars. While heavy precipitation attenuates the reflectivity and thus leads to an underestimation of QPE, KDP is immune to attenuation. 

We compare these two methods to the current operational algorithm and perform a verification with ground stations (ombrometer) based on hourly precipitation accumulations. The analysis will focus on a case study of the flooding event in Germany in July 2021 and might extent to a full convective season. First results show an improvement in QPE when KDP is used for stronger liquid precipitation. 

References
•    Chen et al., 2021: Assessing the benefits of specific attenuation for quantitative precipitation estimation with a C-band radar network, Journal of Hydrometeorology, 22, 2617–2631.
•    Gorgucci et al., 1994: A robust estimator of rainfall rate using differential reflectivity, Journal of Atmospheric & Oceanic Technology, 11, 586-592
Performance of the flood warning system in Germany in July 2021 – insights from affected residents
Authors: Thieken Annegret H. , Bubeck Philip , Heidenreich Anna , von Keyserlingk Jennifer , Dillenardt Lisa , Otto Antje
Published: March 2023

Abstract. In July 2021 intense rainfall caused devastating floods
in western Europe and 184 fatalities in the German federal states of North
Rhine-Westphalia (NW) and Rhineland-Palatinate (RP), calling into question their flood
forecasting, warning and response system (FFWRS). Data from an online survey
(n=1315) reveal that 35 % of the respondents from NW and 29 % from
RP did not receive any warning. Of those who were warned, 85 % did not
expect very severe flooding and 46 % reported a lack of situational
knowledge on protective behaviour. Regression analysis reveals that this
knowledge is influenced not only by gender and flood experience but also by the
content and the source of the warning message. The results are complemented
by analyses of media reports and official warnings that show shortcomings in
providing adequate recommendations to people at risk. Still, the share of
people who did not report any emergency response is low and comparable to
other flood events. However, the perceived effectiveness of the protective behaviour was low and mainly compromised by high water levels and the perceived level of surprise about the flood magnitude. Good situational knowledge and a higher number of previously experienced floods were linked to performing more effective loss-reducing action. Dissemination of warnings,
clearer communication of the expected flood magnitude and recommendations on
adequate responses to a severe flood, particularly with regard to flash and
pluvial floods, are seen as major entry points for improving the FFWRS in
Germany.
Tourist Information Center (TIC) Application for Department of Tourism – East Kalimantan
Authors: Almira Dhanita , Maria Eny , Franz Annafi
Published: March 2023

- The activities of tourism information centers in Department of Tourism of East Kalimantan have not been exposed, which are still manually using brochure sheets, YouTube or Instagram to develop tourism in various fields in order to boost regional income from various potentials they have. Information systems are needed in order to produce the right and clear information in order to help tourists or tourists in their trips. The Tourist Information Center application in East Kalimantan Province is an idea that is expected to provide solutions to solve these problems. By using two methods of data collection, namely the interview and observation methods at agencies. The construction of the system used in this study uses the System Development Life Cycle (SDLC) with a waterfall model or called a waterfall, which is started by the stage of literature study, problem analysis, design (design), system implementation and testing. With the Tourist Information Center application, it can be used as a reference for tourists to vacation in East Kalimantan and provide information about tourism or lodging in East Kalimantan.
Race Analysis and Determination of Stroke Frequency – Stroke Length Combinations during the 50-M Freestyle Event
Authors: Morais Jorge E. , Barbosa Tiago M. , Bragada José A. , Nevill Alan M. , Marinho Daniel A.
Published: March 2023

The aims of this study were to: (1) analyze and compare the stroke kinematics between junior and senior elite male swimmers in every section of the race during the 50-m freestyle event, and; (2) identify stroke frequency (SF)–stroke length (SL) combinations on swim speed independently for junior and senior swimmers in each section of the 50-m freestyle event. Eighty-six junior swimmers (2019) and 95 seniors (2021) competing in the 50-m long course meter LEN Championships were analyzed. The t-test independent samples (p ≤ 0.05) were used to compare juniors and seniors. The SF and SL combinations on swim speed were explored using three-way ANOVAs. Senior swimmers were significantly faster in the 50-m race than juniors (p < 0.001). Speed presented the largest significant difference (p < 0.001) in section S0-15 m (start until the 15th meter mark) being seniors fastest. Both junior and senior swimmers revealed a significant categorization (p < 0.001) by stroke length and stroke frequency in each race section. It was possible to model several SF–SL combinations for seniors and juniors in each section. The fastest swim speed in each section, for seniors and juniors independently, was achieved by a SF–SL combination that may not be the fastest SF or the longest SL. Coaches and swimmers must be aware that despite the 50-m event being an all-out bout, several SF–SL combinations were observed (independently for juniors and seniors), and they differ between race sections.
The Nexus of Learning Organization Practices and Subjective Performance of Employees: A Moderating Role of Employees’ Engagement in the Energy Sector of Pakistan
Authors: Bano Meher , Ali Asad , Asif Muhammad , Tufail Muhammad Sajid
Published: March 2023

This research aims to investigate the moderating effect of employee engagement on the association between learning organization practices and employees' subjective performance in Pakistan's energy sector. Seven elements of Learning organization practices and employee perceptions of their success in developing financial markets are the focus of this research. We have selected a sample of 550 professionals through questionnaires. The snowball sampling technique was used to reach the maximum number of employees, because it assumed that the creativity of an economy depends upon the innovativeness of an organization’s employees. Out of 550, we received only 330 useable questionnaires for data analysis with a response rate of 78% in person and online resources. There are also utilized Pearson correlation and direct regression analysis to measure the relationship among variables. The impact of learning organizations on the subjective performance of employees is found positive and highly significant in the energy sector of Pakistan. Likewise, the moderating role of employees’ engagement is also noted as remarkable in the above relationship. The study recommends that all seven dimensions of learning organization practices should be considered by the management of financial firms to enhance the subjective performance of the employees in the energy sector of Pakistan. Employees’ engagement can accelerate the development of the energy sector. The above-mentioned aspect of financial firms and institutions of the developed countries, whereas the developing countries are relatively less explored on the topic. It is worthwhile to explore this relationship for the energy sector of Pakistan.
Vertebral sarcoidosis: diagnosis to management
Authors: Ferjani Hanene Lassoued , Rahmouni Safa , Nessib Dorra Ben , Triki Wafa , Maatallah Kaouther , Kaffel Dhia , Hamdi Wafa
Published: March 2023

Sarcoidosis is a systemic inflammatory granulomatous disease that can develop in almost any organ system. Rheumatologists may encounter sarcoidosis in different situations varying from arthralgia to bone involvement. While the peripheral skeleton was a frequent location, data regarding axial involvement is scarce.

Most patients with vertebral involvement have a known diagnosis of intrathoracic sarcoidosis. They tend to report mechanical pain or tenderness over the involved area.

Imaging modalities, particularly Magnetic Resonance Imaging (MRI), are a mainstay of axial screening. It helps exclude differential diagnoses and delineate the extent of bone involvement. Histological confirmation combined with the ap- propriate clinical and radiological presentation is the key of diagnosis.

Corticosteroids remain the cornerstone of treatment. In refractory cases, methotrexate is the steroid- sparing agent of choice. Biologic therapies may be used, although the evidence base for their efficacy is bone sarcoidosis controversial.
BIODIVERSITY – A new space mission to monitor Earth ecosystems at fine scale
Authors: BRIOTTET Xavier , BAJJOUK Touria , CHAMI Malik , DELACOURT Christophe , FERET Jean-Baptiste , JACQUEMOUD Stephane , MINGHELLI Audrey , SHEEREN David , WEBER Christiane , FABRE Sophie , ADELINE Karine , VAUDOUR Emmanuelle , LUQUE Sandra , DEVILLE Yannick , SOUDANI Kamel , VERPOOTER Charles
Published: March 2023

Imaging spectroscopy has demonstrated its interest in characterizing the biochemical, biophysical and structural properties of vegetation, natural and agricultural soils, as well as artificial surfaces. Following the Hyperion mission, new space missions have emerged (PRISMA, EnMap), or are under study (CHIME, SBG). However, one of their main limitations lies in their spatial resolution that induces a large number of mixed pixels reducing their potential for discrimination for very heterogeneous areas. The BIODIVERSITY mission aims to complement these space missions with better GSD acquisitions (typically 8-10 m) with a 5-day revisit on targeted reference sites with identified and well-located characteristics. It will thus make it possible, in particular, to answer two scientific issues that will design the instrument. The first issue concerns the spatial and temporal distribution of vegetation traits in species assemblages; these traits are associated with the resilience of terrestrial ecosystems, anthropogenic influences, and the biodiversity of ecosystems in terms of species composition and assemblages. The second issue relates to improving our knowledge of coastal areas and inland waters in terms of biodiversity, water quality and bathymetry, in order to assess the impact of human activity on their ecosytems. The scientific challenges as well as the user requirements for such a mission are presented for each application.
Imagerie Hyperspectrale Et Zones Urbaines: Résultats Du Projet HYEP
Authors: WEBER Christiane , BRIOTTET Xavier , HOUET Thomas , GADAL Sébastien , AGUEJDAD Rahim , DEVILLE Yannick , DALLA-MURA Mauro , MALLET Clément , LE BRIS Arnaud , KAROUI Moussa , BENHALOUCHE Fatima , DJERRIRI Khelifa , FABRE Sophie , AVAL Jocelyn
Published: March 2023

Le projet HYEP (ANR HYEP 14-CE22-0016-01 HYperspectral imagery for Environmental urban Planning - Programme Mobilité et systèmes urbains - 2014) a permis de confirmer l’intérêt d’une approche globale du milieu urbain par télédétection et notamment en utilisant l’imagerie hyperspectrale (IH). L’intérêt des images hyperspectrales réside dans la gamme d’informations fournies sur des longueurs d’onde de 0,4 à 4 μm ; elles fournissent ainsi un accès aux grandeurs spectrales d'intérêt et aux paramètres chimiques ou biophysiques de la surface. HYEP avait pour objectif de préciser ceci et de proposer un panel de méthodes et de traitements en tenant compte des caractéristiques des autres capteurs existants afin d’en comparer les performances. Les développements réalisés ont été appliqués et évalués sur des images aéroportées hyperspectrales acquises sur Toulouse (France) et Kaunas (Lituania), utilisées également pour synthétiser des systèmes spatiaux : Sentinel-2, Hypxim/Biodiversity et Pleiades. Parmi les verrous identifiés, ceux liés à l'amélioration des capacités spatiales des capteurs et aux changements d’échelle spatiale ont été en partie levés par des approches de fusion, qui se sont avérées concluantes. Des méthodes d’extraction, de fusion ou de classification ont été appliquées à différentes résolutions spatiales afin de qualifier les gains et la complémentarité de l’IH par rapport à d’autres capteurs. Ces évaluations ont ainsi porté sur des « objets » d’intérêt pour les gestionnaires et aménageurs du milieu urbain : les surfaces imperméables, la végétation ou encore la détection de panneaux solaires.