Statistical investigations of flow structures in different regimes of the stable boundary layer

A combination of methods originating from non-stationary timeseries analysis is applied to two datasets of near surface turbulence in order to gain insights on the non-stationary enhancement mechanism of intermittent turbulence in the stable atmospheric boundary layer (SBL). We identify regimes of SBL turbulence for which the range of timescales of turbulence and submeso motions, and hence their scale separation (or lack of separation) differs. Ubiquitous flow structures, or events, are extracted from the turbulence data in each flow regime. We relate flow regimes characterised by very stable stratification but different scales activity to a signature of flow structures thought to be submeso motions.Comment: Accepted for publication in Boundary Layer Meteorolog

Towards continuous-wave regime teleportation for light matter quantum relay stations

We report a teleportation experiment involving narrowband entangled photons at 1560 nm and qubit photons at 795 nm emulated by faint laser pulses. A nonlinear difference frequency generation stage converts the 795 nm photons to 1560 nm in order to enable interference with one photon out of the pairs, i.e., at the same wavelength. The spectral bandwidth of all involved photons is of about 25 MHz, which is close to the emission bandwidth of emissive quantum memory devices, notably those based on ensembles of cold atoms and rare earth ions. This opens the route towards the realization of hybrid quantum nodes, i.e., combining quantum memories and entanglement-based quantum relays exploiting either a synchronized (pulsed) or asynchronous (continuous- wave) scenario

A versatile source of polarisation entangled photons for quantum network applications

We report a versatile and practical approach for generating high-quality polarization entanglement in a fully guided-wave fashion. Our setup relies on a high-brilliance type-0 waveguide generator producing paired photon at a telecom wavelength associated with an advanced energy-time to polarisation transcriber. The latter is capable of creating any pure polarization entangled state, and allows manipulating single photon bandwidths that can be chosen at will over five orders of magnitude, ranging from tens of MHz to several THz. We achieve excellent entanglement fidelities for particular spectral bandwidths, i.e. 25 MHz, 540 MHz and 100 GHz, proving the relevance of our approach. Our scheme stands as an ideal candidate for a wide range of network applications, ranging from dense division multiplexing quantum key distribution to heralded optical quantum memories and repeaters.Comment: 5 figure

A short guide to increase FAIRness of atmospheric model data

The generation, processing and analysis of atmospheric model data are expensive, as atmospheric model runs are often computationally intensive and the costs of ‘fast’ disk space are rising. Moreover, atmospheric models are mostly developed by groups of scientists over many years and therefore only few appropriate models exist for specific analyses, e.g. for urban climate. Hence, atmospheric model data should be made available for reuse by scientists, the public sector, companies and other stakeholders. Thereby, this leads to an increasing need for swift, user-friendly adaptation of standards.The FAIR data principles (Findable, Accessible, Interoperable, Reusable) were established to foster the reuse of data. Research data become findable and accessible if they are published in public repositories with general metadata and Persistent Identifiers (PIDs), e.g. DataCite DOIs. The use of PIDs should ensure that describing metadata is persistently available. Nevertheless, PIDs and basic metadata do not guarantee that the data are indeed interoperable and reusable without project-specific knowledge. Additionally, the lack of standardised machine-readable metadata reduces the FAIRness of data. Unfortunately, there are no common standards for non-climate models, e.g. for mesoscale models, available. This paper proposes a concept to improve the FAIRness of archived atmospheric model data. This concept was developed within the AtMoDat project (Atmospheric Model Data). The approach consists of several aspects, each of which is easy to implement: requirements for rich metadata with controlled vocabulary, the landing pages, file formats (netCDF) and the structure within the files. The landing pages are a core element of this concept as they should be human- and machine readable, hold discipline-specific metadata and present metadata on simulation and variable level. This guide is meant to help data producers and curators to prepare data for publication. Furthermore, this guide provides information for the choice of keywords, which supports data reusers in their search for data with search engines. © 2020 The author

The ATMODAT Standard enhances FAIRness of Atmospheric Model data

Within the AtMoDat project (Atmospheric Model Data, www.atmodat.de), a standard has been developed which is meant for improving the FAIRness of atmospheric model data published in repositories. Atmospheric model data form the basis to understand and predict natural events, including atmospheric circulation, local air quality patterns, and the planetary energy budget. Such data should be made available for evaluation and reuse by scientists, the public sector, and relevant stakeholders. Atmospheric modeling is ahead of other fields in many regards towards FAIR (Findable, Accessible, Interoperable, Reusable, see e.g. Wilkinson et al. (2016, doi:10.1101/418376)) data: many models write their output directly into netCDF or file formats that can be converted into netCDF. NetCDF is a non-proprietary, binary, and self-describing format, ensuring interoperability and facilitating reusability. Nevertheless, consistent human- and machine-readable standards for discipline-specific metadata are also necessary. While standardisation of file structure and metadata (e.g. the Climate and Forecast Conventions) is well established for some subdomains of the earth system modeling community (e.g. the Coupled Model Intercomparison Project, Juckes et al. (2020, https:doi.org/10.5194/gmd-13-201-2020)), other subdomains are still lacking such standardisation. For example, standardisation is not well advanced for obstacle-resolving atmospheric models (e.g. for urban-scale modeling). The ATMODAT standard, which will be presented here, includes concrete recommendations related to the maturity, publication, and enhanced FAIRness of atmospheric model data. The suggestions include requirements for rich metadata with controlled vocabularies, structured landing pages, file formats (netCDF), and the structure within files. Human- and machine-readable landing pages are a core element of this standard and should hold and present discipline-specific metadata on simulation and variable level

Warum und wie Sie Klimamodelldaten veröffentlichen sollten

Vorhersage und ProjektionBei Klimasimulationen werden große Mengen an Daten erzeugt. Aus diesem Grund können in der Regel nicht alle Ergebnisse einer Simulation eines Klimamodells von einer Forschungsgruppe alleine ausgewertet werden. Beim Coupled Model Intercomparison Projekt (CMIP) wird daher ein Fokus darauf gelegt, dass auch andere Forschungsgruppen die Daten auswerten können. Deshalb gibt es genaue Vorgaben, wie diese Daten zu beschreiben und zu formatieren sind. Zudem werden viele dieser Datensätze mit einem DOI (Digital Object Identifier) versehen. Dies alles erleichtert die Suche und Weiterverarbeitung der Daten. Allerdings gibt es weitaus mehr als CMIP Daten, die für die Klimaforschung wichtig sind. Viele Ergebnisse von z.B. regionalen Klimamodellen oder Stadtklimamodellen werden nicht veröffentlicht, obwohl von den Datenerzeugern nur ein Bruchteil der Ergebnisse ausgewertet werden kann. Deshalb drängen viele Förderer auf eine Veröffentlichung der Daten in einem Repositorium. Aber auch in diesem Fall können sie oft nicht weiterverwendet werden. Die Gründe sind vielfältig: Unzureichende Metadaten Mangelnde Auffindbarkeit, z.B. durch Suchmaschinen Fehlende Rechte zur Weiterverarbeitung Fehlende Qualitätskontrolle Das BMBF geförderte Projekt AtMoDat (https://www.ATMODAT.de) wurde 2019 gestartet, um die Veröffentlichung von Atmosphärischen Modelldaten zu stärken und zu verbessern. Eine Methode ist dabei die Einhaltung der FAIR-Prinzipien - Findable, Accessible, Interoperable, Reusable (siehe Wilkinson et al., 2016). Zudem sollten alle Daten mit einem DataCite DOI veröffentlicht werden, um die Auffindbarkeit und Zitierbarkeit zu verbessern. Eine Anleitung, wie man dabei vorgehen sollte, findet sich in dem Standard, der im AtMoDat-Projekt entwickelt wurde. Der ATMODAT-Standard ist leicht umzusetzen und beinhaltet genaue Vorgaben für die Metadaten des DOI, die Landing Page und die Header der netCDF-Dateien. Daten, die diesem Standard genügen und dessen Einhaltung vom jeweiligen Repositorium geprüft wurde, können mit dem Earth System Data Branding (EASYDAB) versehen werden. Durch dieses Branding kann eine angemessene Qualitätssicherung der Daten durch die Nutzer sehr leicht nachvollzogen werden. Im Vortrag werden der Standard und EASYDAB vorgestellt

ATMODAT Standard v3.0

Within the AtMoDat project (Atmospheric Model Data), a standard has been developed which is meant for improving the FAIRness of atmospheric model data published in repositories. The ATMODAT standard includes concrete recommendations related to the maturity, publication and enhanced FAIRness of atmospheric model data. The suggestions include requirements for rich metadata with controlled vocabularies, structured landing pages, file formats (netCDF) and the structure within files. Human- and machine readable landing pages are a core element of this standard, and should hold and present discipline-specific metadata on simulation and variable level. This standard is an updated and translated version of "Bericht über initialen Kernstandard und Kurationskriterien des AtMoDat Projektes (v2.4

Epilepsy in Onchocerciasis Endemic Areas: Systematic Review and Meta-analysis of Population-Based Surveys

Epilepsy is particularly common in tropical areas. One main reason is that many endemic infections have neurological consequences. In addition, the medical, social and demographic burden of epilepsy remains substantial in these countries where it is often seen as a contagious condition and where the aetiology is often undetermined. For several decades, field researchers had reported some overlapping between the geographical distributions of epilepsy and onchocerciasis, a parasitic disease caused by the filarial worm Onchocerca volvulus which afflicts some 40 million persons worldwide. Here, we conducted a statistical analysis of all the data available on the relationship between the two conditions to determine whether the proportion of people suffering from epilepsy in a community could be related to the frequency of onchocerciasis. The combined results of the eight studies carried out in west, central and east Africa indicate a close epidemiological association between the two diseases. Should a causative relationship be demonstrated, onchocerciasis, which is known as “river blindness” because of its most serious sequela and the distribution of its vectors, could thus also be called “river epilepsy”. More research is needed to determine the mechanisms explaining this association and to assess the burden of onchocerciasis-associated epilepsy