Einfluss atmosphärischer Umgebungsbedingungen auf den Lebenszyklus konvektiver Zellen in der Echtzeit-Vorhersage

Die vorliegende Dissertation beschäftigt sich mit der Analyse der Lebenszyklen konvektiver Zellen im Zusammenhang mit den vorherrschenden Umgebungsbedingungen in Deutschland. Darüber hinaus werden verschiedene statistische Vorhersagemodelle zur Abschätzung der Lebensdauer und der Größe konvektiver Zellen entwickelt und untersucht. Das Ziel dabei ist es herauszufinden, welche Methode für eine Verbesserung von Verfahren zur Echtzeit-Vorhersage (Nowcasting) am besten geeignet ist. Die Grundlage für diese Untersuchungen bilden Daten des radarbasierten Zellverfolgungsalgorithmus KONRAD, anhand derer zusammenhängende Lebenszyklen von isolierter Konvektion (Einzel- und Superzellen) für die Sommerhalbjahre 2011-2016 erstellt werden. Zusätzlich wird eine Vielzahl konvektionsrelevanter Umgebungsvariablen unter Verwendung von hochaufgelösten Assimilationsanalysen des numerischen Wettervorhersagemodells COSMO-EU berechnet und mit den Lebenszyklen zusammengeführt. Auf Basis dieses kombinierten Datensatzes werden statistische Zusammenhänge zwischen verschiedenen Zellattributen und Umgebungsvariablen untersucht. Wie die Analysen zeigen, sind insbesondere Maße der vertikalen Windscherung aufgrund ihres Einflusses auf die Organisationsform der Konvektion geeignet, zwischen Zellen mit kurzer und langer Lebensdauer zu unterscheiden. Eine erhöhte thermische Instabilität der Atmosphäre geht mit einem schnelleren anfänglichen Wachstum der Zellen einher, welches wiederum eine größere horizontale Zellausdehnung (Zellfläche) während des Lebenszyklus und damit indirekt eine längere Lebensdauer begünstigt. Drei unterschiedliche multivariate Methoden (logistische Regression, Random Forest, nicht-linearer Polynomansatz) werden als Modelle für die Abschätzung der Lebensdauer und der maximalen Zellfläche der konvektiven Zellen mit Hilfe eines Ensembleansatzes untersucht. Die Vorhersagegüte der Modelle wird evaluiert und die Bedeutung der anfänglichen Zellentwicklung und der Umgebungsvariablen analysiert. Dabei werden Potentiale und Grenzen der Methoden aufgezeigt, die verdeutlichen, dass die Wahl eines geeigneten Verfahrens von der genauen Fragestellung bzw. Anforderung des Nowcastings abhängt. Die Untersuchungen legen dar, dass sich die maximale Zellfläche der konvektiven Zellen insgesamt besser abschätzen lässt als ihre Lebensdauer. Umgebungsvariablen, die den dynamischen und thermodynamischen Zustand der Atmosphäre charakterisieren, sind insbesondere zu Beginn der Zellentwicklung für die Abschätzung der zukünftig zu erwartenden Entwicklung der Zellen bedeutsam, während mit zunehmendem Zellalter die vergangene Zellhistorie immer wichtiger wird

Evaluating Bunkers\u27 storm motion of hail-producing supercells and their storm-relative helicity in Germany

This paper presents a statistical analysis of the motion of hail-producing supercells in Germany based on data from a radar-based cell detection and tracking algorithm and a mesocyclone detection algorithm. The parameterization of supercell motion by Bunkers et al. (2000), originally developed using storm data from the United States, is evaluated regarding its applicability in Central Europe, where storm environments have other dynamic and thermodynamic characteristics owing to different geographical features. As a first step, the motion of 354 observed supercells in the warm season (April to September) 2013–2016 is compared to the motion obtained with the original parameterization. The cells are classified as right-moving or left-moving supercells due to their motion direction with regard to the vertical wind shear of the environment, which is calculated using high-resolution model analyses. Afterwards, the accuracy of the parameterization is checked for both motion classes, as well as for classifications according to the lifetime, track length, and severity proxies of the cells. Clear differences between observed and parameterized motion are obtained for all categories, calling for an adjustment of the parameterization in a second step. This adjusted parameterization improves the storm motion estimation for most of the storm categories. A better storm motion estimation improves the calculation of storm-relative helicity, enabling a more reliable nowcasting and forecasting of supercell potential

An Approach for Integration of Transport Drones Into Offshore Wind Farms

Costs of offshore wind farms (OWF) are largely driven by the service costs of the required maintenance. Current maintenance is either conducted via sea using special ships or helicopters. Both transport methods involve costly and thus limited available assets as well as specially trained personnel to operate them. This not only drives costs up but also limits the planning horizon of maintenance operations. Transport drones could be a complementing alternative to the traditional use of vessels and helicopters for the transport of servicing items and replacement parts to wind farms. For efficient and safe operations, drones must be properly integrated into the maritime domain and the OWF. The integration requires modifications of the drone and wind turbines as well as developing and evaluating operational concepts. The Upcoming Drone Windfarms (UDW) project between the German Aerospace Center (DLR) and the energy provider Energie Baden-Württemberg (EnBW) targets several aspects of these central challenges. This paper presents the main concept for the fictitious drone transport mission to OWF EnBW Hohe See which acts as exemplary scenario to develop the integration and operation concept. Special emphasis is on the automated interaction between the drone and the wind farm infrastructure for which according concepts for communication must be developed and implemented. The contributions to this topic are the identification of necessary infrastructure extensions to enable a reliable communication, the interaction between the drone and the wind farm, and a summary of necessary information which needs to be exchanged between both entities to ensure safe operation of the drone. The ongoing work will eventually result in flight tests with a drone in an onshore wind farm to demonstrate the concept and its technical feasibility. The development of the technical setup for these tests is presented

Severe thunderstorms with large hail across Germany in June 2019

From 10 to 12 June 2019, severe thunderstorms affected large parts of Germany. Hail larger than golf ball size caused considerable damage, especially in the Munich area where losses amount to EUR 1 billion. This event thus ranks among the ten most expensive hail events in Europe in the last 40 years. Atmospheric blocking in combination with a moist, unstably stratified air mass provided an excellent setting for the development of severe, hail‐producing thunderstorms across the country. imageGerman Research Foundation http://dx.doi.org/10.13039/50110000165

Swabian MOSES 2021: An interdisciplinary field campaign for investigating convective storms and their event chains

The Neckar Valley and the Swabian Jura in southwest Germany comprise a hotspot for severe convective storms, causing tens of millions of euros in damage each year. Possible reasons for the high frequency of thunderstorms and the associated event chain across compartments were investigated in detail during the hydro-meteorological field campaign Swabian MOSES carried out between May and September 2021. Researchers from various disciplines established more than 25 temporary ground-based stations equipped with state-of-the-art in situ and remote sensing observation systems, such as lidars, dual-polarization X- and C-band Doppler weather radars, radiosondes including stratospheric balloons, an aerosol cloud chamber, masts to measure vertical fluxes, autosamplers for water probes in rivers, and networks of disdrometers, soil moisture, and hail sensors. These fixed-site observations were supplemented by mobile observation systems, such as a research aircraft with scanning Doppler lidar, a cosmic ray neutron sensing rover, and a storm chasing team launching swarmsondes in the vicinity of hailstorms. Seven Intensive Observation Periods (IOPs) were conducted on a total of 21 operating days. An exceptionally high number of convective events, including both unorganized and organized thunderstorms such as multicells or supercells, occurred during the study period. This paper gives an overview of the Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign, briefly describes the observation strategy, and presents observational highlights for two IOPs

Einfluss atmosphärischer Umgebungsbedingungen auf den Lebenszyklus konvektiver Zellen in der Echtzeit-Vorhersage

Precise warnings of the accompanying effects of thunderstorms are essential for preventive measures. The dynamic development of thunderstorm cells often leads to a large discrepancy between the real-time forecasts (nowcasts) of weather services and the observed weather conditions. Data from a cell tracking algorithm are combined with model analyses to investigate the life cycle of thunderstorms in Germany and to develop and evaluate procedures useful for thunderstorm nowcasting

Evaluating Bunkers' storm motion of hail-producing supercells and their storm-relative helicity in Germany

This paper presents a statistical analysis of the motion of hail-producing supercells in Germany based on data from a radar-based cell detection and tracking algorithm and a mesocyclone detection algorithm. The parameterization of supercell motion by Bunkers et al. (2000), originally developed using storm data from the United States, is evaluated regarding its applicability in Central Europe, where storm environments have other dynamic and thermodynamic characteristics owing to different geographical features. As a first step, the motion of 354 observed supercells in the warm season (April to September) 2013–2016 is compared to the motion obtained with the original parameterization. The cells are classified as right-moving or left-moving supercells due to their motion direction with regard to the vertical wind shear of the environment, which is calculated using high-resolution model analyses. Afterwards, the accuracy of the parameterization is checked for both motion classes, as well as for classifications according to the lifetime, track length, and severity proxies of the cells. Clear differences between observed and parameterized motion are obtained for all categories, calling for an adjustment of the parameterization in a second step. This adjusted parameterization improves the storm motion estimation for most of the storm categories. A better storm motion estimation improves the calculation of storm-relative helicity, enabling a more reliable nowcasting and forecasting of supercell potential

Statistical relevance of meteorological ambient conditions and cell attributes for nowcasting the life cycle of convective storms

AbstractThe usually short lifetime of convective storms and their rapid development during unstable weather conditions makes forecasting these storms challenging. It is necessary, therefore, to improve the procedures for estimating the storms' expected life cycles, including the storms' lifetime, size, and intensity development. We present an analysis of the life cycles of convective cells in Germany, focusing on the relevance of the prevailing atmospheric conditions. Using data from the radar‐based cell detection and tracking algorithm KONRAD of the German Weather Service, the life cycles of isolated convective storms are analysed for the summer half‐years from 2011 to 2016. In addition, numerous convection‐relevant atmospheric ambient variables (e.g., deep‐layer shear, convective available potential energy, lifted index), which were calculated using high‐resolution COSMO‐EU assimilation analyses (0.0625°), are combined with the life cycles. The statistical analyses of the life cycles reveal that rapid initial area growth supports wider horizontal expansion of a cell in the subsequent development and, indirectly, a longer lifetime. Specifically, the information about the initial horizontal cell area is the most important predictor for the lifetime and expected maximum cell area during the life cycle. However, its predictive skill turns out to be moderate at most, but still considerably higher than the skill of any ambient variable is. Of the latter, measures of midtropospheric mean wind and vertical wind shear are most suitable for distinguishing between convective cells with short lifetime and those with long lifetime. Higher thermal instability is associated with faster initial growth, thus favouring larger and longer living cells. A detailed objective correlation analysis between ambient variables, coupled with analyses discriminating groups of different lifetime and maximum cell area, makes it possible to gain new insights into their statistical connections. The results of this study provide guidance for predictor selection and advancements of nowcasting applications.Based on a combination of data of the cell tracking algorithm KONRAD of the German Weather Service and COSMO‐EU model analyses for the summer half‐years from 2011 to 2016, statistical relationships between storm attributes (lifetime and maximum horizontal area), and ambient variables as well as the storms' history are quantified. The initial growth of the cell area is a better indicator of the lifetime and maximum area than ambient variables are. Of the latter, measures of the midtropospheric wind and vertical wind shear, in particular, are most suitable for distinguishing between convective cells with short and long lifetimes, whereas higher convective instability favours larger cells. Bundesministerium für Digitales und Verkehr http://dx.doi.org/10.13039/10000838