DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations.
For further information please refer to:
[in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ]
[in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]
This dataset contains supplementary materials to the manuscripts “Interpreting inverse magnetic fabric in Miocene dikes from Eastern Iceland” by Trippanera et al., (submitted to JGR) and “Anatomy of an extinct magmatic system along a divergent plate boundary: Alftafjordur, Iceland” by Urbani et al. 2015. These works present an extensive multi-scale and multi-disciplinary study focused on the magnetic fabric of dikes belonging to the Alftafjordur volcanic system in Eastern Iceland. Eastern Iceland is one of the most suitable places to analyze the roots of the volcanic systems that are composed of central volcanoes and fissure swarms. We sampled 19 NNE-SSW oriented dikes (for a total of 383 samples) belonging to the exhumed fissure swarm portion of Alftafjordur volcanic system, aiming at understanding the direction of magma propagation in the swarm by using Anisotropy of Magnetic Susceptibility (AMS) analysis. However, most of the samples (80% out of the measured cores) show an inverse geometric magnetic fabric (kmax is perpendicular to the dike margins and sub-horizontal)- therefore the study of the flow direction is complicated. Nevertheless, this result poses the problem of why the geometrically inverse fabric is present and widespread in the whole dike swarm. In order to understand the origin of this inverse fabric, besides standard AMS measurements, we also performed additional analysis such as different field and temperature AMS, Anisotropy of Anhystheretic Remanent Magnetization (AARM), Hysteresis loops and First-order reversal curves (FORC), Scanning Electron Microscope (SEM) and Optic microscope images analysis.
This dataset includes the following materials: • Location of the sampled sites (.kml) • AMS measurements at room temperature by using H=300 A/m for all samples (.ran) • AMS measurements at room temperature by using H=200 A/m and H=600 A/m for selected samples (.ran) • AMS measurements at different temperature (from 20 to 580 ℃) for selected samples (.ran) • AARM measurements for selected samples (.ran) • DayPlots data for selected samples (.xls or .csv) • SEM and Optical microscope images of thin sections of selected samples.
AMS and AARM data can be opened through Anisoft open-source software provided by Agico (Chadima and Jelinek, 2009; https://www.agico.com/text/software/anisoft/anisoft.php). Data have been acquired at: Roma Tre University (Rome, Italy), Istuto di Geofisica e Vulcanologia (INGV, Rome, Italy) and Laboratoire des Sciences du Climat et de l'Environnement, CEA, CNRS, UVSQ (Gif-sur-Yvette Cedex, France).
For the interpretation of the data refer to Urbani et al., 2015 and Trippanera et al., (submitted). The description of each dataset is provided in the description file.
Objective: There is a need for better measurement instruments for analysis of airborne particles, in particular nanoparticles. Use of powders, nanomaterials/ceramics, and nanoparticles is rising fast. Occupational health problems are present at a wide range of different work places due to airborne particulates. Toxic particles such as asbestos and silica are responsible for the majority of particle related illnesses. The overall impacts of the NanoAir project are to reduce number of deaths and illnesses caused by workplace related exposure to particles. The air pollution detection market is growing fast, as new concerns are identified especially for indoor air pollution. The market is under pressure from USA from many new high-tech solutions, and progression regarding air pollution legislation and NP industries. Thus the concept of the project is to develop a new method to analyse airborne particles, onsite, real-time and with a high quality readout. The method can identify the particle types together with the size distribution. In the project we have a new idea for the development of an improved particle sampling system, which will allow collecting particles with a high efficiency and a wide range of particle sizes, including the nano-size regime. This will allow much improved analysis results and sensitivity for a wide range of particle types and sizes. This sampling system together with a mobile X-ray diffraction analysis technique opens up for new possibilities within air quality detection, especially within the capability to analyse nanoparticles. Detection and analysis of nanoparticles may be a very crucial field in the future air quality analysis, due to a rapidly increase in use of nanomaterials and nanoparticles in building materials, paintings, cleaning products, cosmetics, etc. At the same time, new research have indicated very large potential risks for man-made nanoparticles, due to a very deep deposition in the lungs and high chemical reactivity.