The large-scale environment can have a significant impact on subtropical precipitating systems via the baroclinicity of the environment and the associated dynamical forcings. The degree of baroclinicity is examined using National Centers for Environmental Prediction (NCEP) reanalysis temperature and zonal wind fields over a two-year period for Southeast Texas, yielding classifications of barotropic, weakly baroclinic, and strongly baroclinic for the background environment. Weakly baroclinic environments accounted for half of the days throughout the two-year period. Barotropic environments occurred most frequently during summer and strongly baroclinic environments occurred most frequently in winter, although less often than weakly baroclinic environments. A climatology of storm types, based on dynamical forcing (i.e., weak forcing, drylines, cold fronts, warm fronts, stationary fronts and upper level disturbances) and precipitation structure (i.e., isolated, scattered, widespread, linear, unorganized and leading-line/trailing stratiform), was compiled and compared to the baroclinicity designations. Non-frontal storm types (i.e., weak forcing, drylines and upper level disturbances) are typical of barotropic environments, while frontal storm types (i.e.,warm, cold and stationary fronts) are typical of weakly and strongly baroclinic environments. Storm events and drop-size distributions (DSD) were identified from surface rainfall data collected by a Joss-Waldvogel disdrometer located in College Station, Texas. The DSDs were compared by baroclinicity and storm type. The barotropic DSD is weighted towards the largest drops because of the stronger convection and stratiform precipitation in the weak forcing and dryline storm types, while the strongly baroclinic DSD is weighted towards the smallest drops because of the weaker convection from the warm fronts and stationary fronts. The weakly baroclinic DSD is weighted more evenly towards small and large drops than the barotropic and strongly baroclinic DSDs because of the conflicting microphysical processes in the different storm types. The microphysical processes within the storms vary by storm type and baroclinicity regime, such that the large-scale environment modifies the precipitation characteristics of storms in SE Texas.

The large-scale environment can have a significant impact on subtropical precipitating systems via the baroclinicity of the environment and the associated dynamical forcings. The degree of baroclinicity is examined using National Centers for Environmental Prediction (NCEP) reanalysis temperature and zonal wind fields over a two-year period for Southeast Texas, yielding classifications of barotropic, weakly baroclinic, and strongly baroclinic for the background environment. Weakly baroclinic environments accounted for half of the days throughout the two-year period. Barotropic environments occurred most frequently during summer and strongly baroclinic environments occurred most frequently in winter, although less often than weakly baroclinic environments. A climatology of storm types, based on dynamical forcing (i.e., weak forcing, drylines, cold fronts, warm fronts, stationary fronts and upper level disturbances) and precipitation structure (i.e., isolated, scattered, widespread, linear, unorganized and leading-line/trailing stratiform), was compiled and compared to the baroclinicity designations. Non-frontal storm types (i.e., weak forcing, drylines and upper level disturbances) are typical of barotropic environments, while frontal storm types (i.e.,warm, cold and stationary fronts) are typical of weakly and strongly baroclinic environments. Storm events and drop-size distributions (DSD) were identified from surface rainfall data collected by a Joss-Waldvogel disdrometer located in College Station, Texas. The DSDs were compared by baroclinicity and storm type. The barotropic DSD is weighted towards the largest drops because of the stronger convection and stratiform precipitation in the weak forcing and dryline storm types, while the strongly baroclinic DSD is weighted towards the smallest drops because of the weaker convection from the warm fronts and stationary fronts. The weakly baroclinic DSD is weighted more evenly towards small and large drops than the barotropic and strongly baroclinic DSDs because of the conflicting microphysical processes in the different storm types. The microphysical processes within the storms vary by storm type and baroclinicity regime, such that the large-scale environment modifies the precipitation characteristics of storms in SE Texas.

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Nederbördsmätning är viktigt inom många områden och en relativt ny teknik är enoptisk distrometer som med hjälp av laserteknik mäter nederbördspartiklarnasdroppstorlek och fallhastighet. Syftet med detta arbete var att undersöka hur välThies distrometer stämmer överens med nederbördsmätning från ett vippkärl ochmanuella mätningar från institutionen för geovetenskaper vid Uppsala universitet.Institutionen för geovetenskaper överväger att gå över till denna teknik och därmedbehövdes distrometern utvärderas för olika faktorer som kan påverka instrumentet.Vid jämförelse mellan instrumenten visade det sig att distrometern totalt sett samladein mer nederbörd än de andra mätarna. Det är svårt att avgöra vad skillnaden mellaninstrumenten kan bero på men felkällor så som avdunstning och vätning hos vippkärletoch manuella mätningar kan ge mindre nederbörd. En annan orsak kan varafelkalibrering av datan från distrometern. Inga samband hittades för vindhastighet,vindriktning och typ av nederbörd mellan de tre instrumenten. En vidare undersökning gjordes för droppstorleksfördelningen för att ge exempelpå fördelar med en distrometer. Droppstorleksfördelningen från distrometernjämfördes med exponentialfördelningen framtagen av Marshall & Palmer (1948).Resultatet visade sig stämma överens med tidigare studier, fördelningen stämmerbra överens för stratiforma väder, men sämre för konvektiva och snö. / Measuring precipitation is important in many areas of research. A relatively newtechnology for measuring precipitation is the optical disdrometer, which measures thefalling velocity and drop size of particles by using lasers. The purpose of this workwas to compare data from a disdrometer with data from a tipping bucket and amanual measurement series from the Department of Earth Sciences at UppsalaUniversity. The comparison between the instruments showed that the disdrometermeasured more precipitation than the tipping bucket and the manual measurements.A reason for this can be due to evaporation and wetting from the tipping bucket andmanual measurement. Errors in calibration of data from the disdrometer may alsohave influence. Furthermore, an analysis of the drop size distribution was done in order todetermine areas of special use for the device. The drop size distribution calculatedfrom the distrometer was compared with the Marshall and Palmer (1948) distribution.The results showed that the MP-distribution was a good fit for stratiform weather;however, for convective clouds and snow the fit was not satisfactory and some otherrelationship should be used instead.

This article, emerged from a bachelor thesis, focuses on the classification of hydrometeors measured by the Laser Precipitation Monitor by the Adolf Thies GmbH & Co. KG. The optical disdrometer can classify measurements of hydrometeor size and fall velocity spectra concerning the precipitation type. The measurement principle of the disdrometer is explained, as well as the classifications. For reasons of calculation time, mostly six main precipitation types are considered (drizzle, rain, snow, ice grains, hail, mixed). It is the goal to understand the process of a reliable classification and to determine how these classifications are implemented. Therefore, the precipitation measurements from the measurement field of the Leipzig Institute for Meteorology from 2021 are used. An analysis of the spectrum consisting of hydrometeor diameter and fall speed is investigated. Afterwards, two machine learning methods are applied to the dataset. The classification of each sample through grouping similar samples using cluster analysis serves as an unsupervised approach and in particular examines the natural clusters present in the dataset. Contrasting that the purely statistical, nonphysical, supervised Random Forest method is applied as well. The comparison of the unsupervised and supervised approach shows that for the classification the supervised method is more promising. / Dieser Artikel konzentriert sich auf die Klassifizierung von Hydrometeoren, welche durch den Laser Niederschlags Monitor der Adolf Thies GmbH & Co. KG gemessen werden. Das optische Disdrometer kann die Messungen von Fallgeschwindigkeits- und Größenspektren der Niederschlagspartikel eigenständig in Gruppen der Niederschlagsart einsortieren. Das Messprinzip, sowie die Klassifizierungsmechanismen werden erklärt. Auf Grund der Rechenzeit werden im Rahmen der folgenden Untersuchungen hauptsächlich die 6 Hauptniederschlagsarten (Niesel, Regen, Schnee, Eiskörner, Hagel, Gemischt) unterschieden. Das Ziel der Analyse ist es, den Prozess einer zuverlässigen Klassifizierung zu verstehen und die Möglichkeiten der Anwendung abzuschätzen. Dafür werden die Niederschlagsdaten der Wetterwiese des Leipziger Instituts für Meteorologie aus dem Jahr 2021 verwendet. Nach erster grundlegender Betrachtung des Datensatzes werden zwei verschiedene Machine Learning Methoden angewendet. Als unüberwachte Methode dient der Ansatz der Clusteranalyse, welcher alle Samples über Ähnlichkeitskriterien gruppiert und dadurch die natürliche Gruppierbarkeit eines Datensatzes aufzeigt. Im Gegensatz dazu steht die rein statistische, unphysikalische Methode des Random Forest mit überwachtem Lernprozess. Im Vergleich beider Ansätze zeigt sich, dass ein überwachter Machine Learning Methode zufriedenstellendere Ergebisse erzeugt als unüberwachte Prozesse.

Vindtunneln som drivs av Sports Tech Research Centres   är en unik anläggning för att bedriva forskning på både atletiska utövare och   utrustning. Vindtunnelns avancerade system möjliggör för forskning och tester   på material och produkter kan utföras i en verklighetstrogen miljö. Det finns   även sedan byggnationen ett regnsystem installerat i vindtunneln. Detta   system är inte uppmätt efter viktiga faktorer och ingen vetskap om det   simulerade regnets egenskaper eller likhet med naturligt förekommande regn   finns. Syftet med arbetet var att utföra mätningar på det   befintliga regnsystemet med avseende på storlek och fallhastighet för   dropparna. Arbetets syfte var även att jämföra de uppmätta regn egenskaperna   mot vetenskapliga modeller som beskriver ett naturligt regn. Där målet med   arbetet var att ta fram ett underlag på det befintliga regnet i vindtunneln. Testerna utfördes med en optisk distrometer som   mätte de fallande vattendropparna med en laser. Distrometern användes för att   mäta storlek samt fallhastighet på vattendropparna. Distrometer placerades   vid tester på olika höjder i vindtunneln, regnet undersöktes även vid   varierande vattenflöde och vindhastigheter. Resultatet visade på att simulerade regnet hade en   lägre hastighet i förhållande till den uppmätta droppstorleken högt i   tunneln. Hastigheten på dropparna lågt i tunneln visade mer följa modellernas   beskrivning av en naturligfallhastighet. Droppstorleksfördelningen visades   inte överstämma mot naturligt regn utan visar på en högre mängd stora droppar   än vad som är naturligt förekommande. Intensiteten i vindtunneln var som   lägst 62 mm/h vilket väldigt högt sett från naturligt regn. Utifrån dessa   parametrar följer inte det simulerade regnet ett naturligt förekommande regn. / The wind tunnel operated by Sport Tech Research Centres,   are a unique facility to conduct research on athletic practitioners and their   equipment. The advanced systems in the wind tunnel allows for research and   testing of materials and product in a realistic environment. Since the   construction of the wind tunnel a rain system was fitted. This system is not   measured for important factors and no knowledge of the simulated rainfall   properties or similarities to naturally occurring rain exists. The aim of this work was to perform measurements of   the existing rainfall system with regards to size and falls speed of the   droplets. The purpose was also to compare the measure rain properties to   scientific models describing natural rainfall. The goal of the work was to   get a foundation of the existing rain in the wind tunnel. The tests were performed with an optic disdrometer   that measured the falling water particles with a laser. The disdrometer   measured size and fall speed of the droplets. The tests were carried out on   different heights in the wind tunnel, the rain was also investigated at   varying water pressure and wind speeds. The result shows that the simulated rainfall had   lower speed relative to the measured drop size high in the tunnel. Fall speed   of droplets low in the tunnel showed more according to the model’s   description of a natural rain fall speed. Drop size distribution was shown   not to be consistent with natural rainfall. The distribution shows a higher   amount of large drops than is naturally occurring. Rainfall intensity was   measured to 62 mm/h as lowest which is very high compared to natural rain.   Based on these parameters the simulated rain is not a naturally occurring   rainfall. / <p>Betyg: 180803</p>

<p>Storms in the SE-US often evolve in different environments than those in the central Plains. Many poorly understood aspects of these differing environments may impact the tornadic potential of SE-US storms. Among these differences are potential variations in the CCN concentration owing to differences in land cover, combustion, industrial and urban activity, and proximity to maritime environments. The relative influence of warm and cold rain processes is sensitive to CCN concentration, with higher CCN concentrations producing smaller cloud droplets and more efficient cold rain processes. Cold rain processes result in DSDs with relatively larger drops from melting ice compared to warm rain processes. Differences in DSDs impact cold pool and downdraft size and strength, that influence tornado potential. This study investigates the impact of CCN concentration on DSDs in the SE-US by comparing DSDs from ARPS-EnKF model analyses and forecasts to observed DSDs from portable disdrometer-equipped probes collected by a collaboration between Purdue University, the University of Oklahoma (OU), the National Severe Storms Laboratory (NSSL), and the University of Massachusetts in a tornadic QLCS on 30 April 2017 during VORTEX-SE.</p><p>The ARPS-EnKF configuration, which consists of 40 ensemble members, is used with the NSSL triple-moment microphysics scheme. Surface and radar observations are both assimilated. Data assimilation experiments with CCN concentrations ranging from 100 cm^-3 (maritime) to 2,000 cm^-3 (continental) are conducted to characterize the variability of DSDs and the model output DSDs are verified against the disdrometer observations. The sensitivity of the DSD variability to CCN concentrations is evaluated. Results indicate continental CCN concentrations (close to CCN 1,000 cm³) produce DSDs that align closest to the observed DSDs. Other thermodynamic variables also accord better to observations in intermediate CCN concentration environments.</p>

<div>Rain drop size distributions (DSDs) in severe convective storms are highly variable in time and space. DSDs can be derived from polarimetric radar observations at high spatiotemporal resolution but these observations are often lacking near the surface owing to radar horizon issues. Disdrometers provide “ground-truth” measurements and validation of radar-derived DSDs but are by nature limited point measurements. Moreover, substantial evolution of the DSD can occur between the lowest radar elevation angle and the surface. Recent studies have shown that hydrometeor size sorting (HSS) is an important and even dominant process contributing to DSD evolution in severe storms; many physical processes such as the strength of the updraft, transient effects, and storm-relative mean winds are contributing factors to continued size sorting. In this study, we focus on strong storm-relative mean winds that induce sustained size sorting owing to the different residence times of hydrometeors of different sizes as they fall in severe storms. The resulting differential advection leads to a distinct horizontal spread of hydrometeors of different sizes at the bottom of a given layer. The goal of this study is to evaluate the impact of size sorting on DSD evolution from the radar level to the surface. To accomplish this, we develop and apply a raindrop trajectory model to compute the evolution of DSDs between radar observations aloft and the surface. For simplicity and to isolate the effects of size sorting, we neglect processes such as breakup, collection, and evaporation, and assume a horizontally homogeneous wind profile. We use disdrometer and radar data, which measure DSDs at the surface and provide the observed quantities aloft, respectively. The disdrometer data was collected from portable disdrometers as a collaboration between Purdue University, University of Oklahoma, University of Massachusetts, and the National Severe Storms Laboratory during the VORTEX-SE 2017 field campaign. NEXRAD data from KHTX Huntsville, AL and KGWX Columbus Air Force Base, MS was retrieved from the National Centers for Environmental Information (NCEI).</div><div><br></div><div>We evaluate three separate cases, a tornadic QLCS on 30 April 2017, a cluster storm on 27 March 2017, and a squall line on 25 March 2017. After the radar data is pre-processed, we retrieve the DSDs from the radar by assuming a gamma distribution and discretize them into PARSIVEL bins to produce a gridded dataset of DSDs. We then apply the raindrop trajectory model to compute the DSDs at the surface which are then compared directly with disdrometer observations. Analysis and comparisons from all cases yield similar results in that-the sorted radar DSDs at the surface are overall closer to the disdrometer observations than the original radar DSDs aloft. Results also show that the spatial variation of DSDs is higher at the surface due to size sorting by the storm-relative mean winds.</div><div><br></div>

n fall 2022, disdrometer measurements were carried out at the MyDiv experiment in Bad Lauchstadt for six weeks. One optical Thies laser disdrometer was set up in the open field and a second one in a series of monoculture plots of tree communities. After several precipitation events, the disdrometer below canopy was moved to a different monoculture plot. The measurements aimed to investigate precipitation throughfall characteristics under different tree species compared to the disdrometer in open land. This paper first gives a brief overview about the measurement campaign and the instrumentation. Afterward, the data quality and filtering of the data are explained. This is followed by the data evaluation, in which both, the number of hydrometeors, and the amount and intensity of precipitation under the tree species are analyzed in comparison to the open field disdrometer. In addition, the precipitation amount is analyzed across tree species of different foliage density. / Im Herbst 2022 wurden auf dem Gelände des MyDiv Experiments in Bad Lauchstadt über sechs Wochen hinweg Distrometermessungen durchgeführt. Dabei wurde ein optisches Thies Laser Distrometer unter freiem Himmel und ein zweites in eine Reihe von Monokulturparzellen gestellt. Nach einigen Niederschlagsevents wurde das Distrometer unter dem Kronendach in eine andere Monokulturparzelle versetzt. Das Ziel der Messungen war dabei, die Niederschlagscharakteristika unter verschiedenen Baumarten im Vergleich zum Distrometer zu untersuchen. In dieser Arbeit wird zunachst ein kurzer Überblick über die Messkampagne und das Messgerät gegeben. Im Anschluss wird die Datenqualitat und Filterung der Daten erläutert. Daraufhin folgt die Datenauswertung, in der sowohl die Anzahl der Hydrometeore als auch die Menge und Intensität der Niederschlagsereignisse unter den Baumarten im Vergleich zum freistehenden Distrometer analysiert wird. Darüber hinaus wird weiterführend die Niederschlagsmenge auch zwischen Messungen unter Baumarten verschiedener Belaubungsdichte untersucht.

En cas de rejets de polluants ou de radionucléides dans l’atmosphère, l’estimation du lessivage des particules d’aérosol atmosphérique par les précipitations est une donnée essentielle pour évaluer la contamination de la biosphère. De nombreuses études se sont déjà intéressées à ce processus de dépôt humide, mais la plupart d’entre elles sont d’ordre théoriques ou ont été menées en laboratoire. Cette étude a donc pour objectif d’améliorer la connaissance du potentiel de lessivage des particules d’aérosol par les précipitations par une approche expérimentale en conditions in situ. Durant plusieurs mois, trois sites aux environnements distincts en termes de climatologie et d’empoussièrement ambiant ont été instrumentés pour disposer d’une palette de situations précipitations/empoussièrement la plus variée possible. Un disdromètre laser et un granulomètre (compteur électrique et/ou optique) ont mesurés respectivement les caractéristiques des précipitations et les concentrations de particules à une résolution temporelle élevée et sur une large gamme de diamètre. L’utilisation de ce couplage instrumental original a permis de déterminer les potentiels de lessivage pour des particules de la gamme nanométrique à supermicronique et pour différents types de précipitations (chutes de neige et pluies avec des hyétogrammes spécifiques). Dans un premier temps, le coefficient de lessivage ᴧ (paramètre décrivant la cinétique du processus) a été calculé en considérant l’effet global d’une précipitation. Cette approche « macroscopique » est limitée par l’influence de processus « concurrents », tels que l’advection ou les sources d’émissions de particules à proximité des sites de mesures. Pour minimiser l’impact de ces processus sur nos résultats, une seconde méthodologie basée sur la résolution temporelle élevée de l’instrumentation utilisée a été définie. Par cette approche « intra-évènementielle », les coefficients de lessivage ᴧ sont calculés sur de courtes périodes de temps, permettant ainsi d’étudier l’influence de la variabilité du diamètre des particules et des caractéristiques des précipitations sur ces coefficients. Les résultats obtenus par les deux types d’approches ont mis en évidence la nécessité de prendre en compte le diamètre des particules et les caractéristiques des précipitations pour modéliser fidèlement le lessivage des particules d’aérosol atmosphérique. En comparant les résultats des deux types de précipitations, la prédominance du lessivage par des chutes de neige par rapport au lessivage par la pluie a été illustrée. L’importance du diamètre des particules lessivées a été démontrée. Entre le mode « ultrafin » et le mode « grossiers », la variation du coefficient de lessivage est d’un ordre de grandeur (entre environ 2.10¯³et 2.10¯⁴ s¯¹). Le potentiel de lessivage minimum est obtenu pour des particules d’environ 100 nm, ce qui est cohérent avec la théorie du « Greenfield gap » (entre 0,1 et 1 µm). Pour les besoins de la modélisation, une paramétrisation robuste entre le coefficient de lessivage ᴧ et le diamètre des particules d’aérosol (de 10 nm à 10 µm) a été établie. Différentes relations entre le coefficient ᴧ et l’intensité pluviométrique sont proposées aussi pour différentes gammes de diamètre de particules et comparées notamment aux valeurs implémentées actuellement dans le modèle ldX utilisé à l’Institut de Radioprotection et de Sûreté Nucléaire. / In case of release of pollutant or radionuclides into the atmosphere, estimate of below-cloud scavenging of aerosol particles by precipitation (or washout) is an essential data to evaluate contamination of the biosphere. Many studies have already shown an interest to this wet deposition process, but most of them are theoretical or have been conducted in laboratories conditions. This study in situ conditions aims to improve knowledge of below-cloud scavenging of aerosol particles by precipitation. For several months, three sites with separate environments in terms of climate and ambient dust have been instrumented to have such a varied palette of precipitation/dust conditions as possible. A laser disdrometer and a granulomètre (electrical and/or optical counter) measure respectively precipitations characteristics and particles concentrations with a high temporal resolution (one minute). The use of this original instrumental coupling has allowed determining washout potentials for the nanometric size range of particles aerosol to the supermicronique size range and for different types of precipitation (snowfalls and rainfalls with specifics hyetograms).Initially, below-cloud scavenging coefficients ᴧ (parameter describing kinetic of this process) were calculated considering the gobal effet of a precipitation. This “macroscopic” approach is limited by the influence of “concurrent” processes, as advection or local emissions of aerosol particles close to the measurements sites. To minimise effect of these processes on our results, a second methodology based on the high temporal resolution of the instrumentation used was defined. With this “intra-event” approach, washout coefficients are calculated on short time scales, allowing study of impact of the variability of aerosol size and precipitations characteristics on these coefficients.Results obtained with the two approaches highlighted the need of considering particles diameter and characteristics of precipitation to model accurately below-cloud scavenging of aerosol particles. Comparing results for both type of precipitation, predomination of below-cloud scavenging by snowfalls compared with below-cloud scavenging by rainfalls was shown. The importance of the scavenged aerosol diameter was demonstrated. From the “ultrafine” size range to coarse mode of particles, below-cloud scavenging coefficient varies by an order of magnitude (from 2.10¯³ to 2.10¯⁴ s¯¹). Minimum potential is obtained for particles of about 100 nm, which is consistent with theory of “Greenfield gap” (from 0.1 to 1 µm). For modeling needs, a robust parametrization between washout coefficient ᴧ and aerosol particles diameter (from 10 nm to 10 µm) has been established. Also some relationships between coefficient ᴧ and rainfall intensity are proposed for different particles size range and compared in particular with values implemented in model ldX currently used at the French Institute of Radioprotection and Nuclear Safety.