TY - GEN A1 - Heidenreich, Sebastian A1 - Bär, Markus A1 - Klauenberg, Katy A1 - Elster, Clemens A1 - Harris, Peter A1 - Lines, Keith A1 - Hippolyte, Jean-Laurent A1 - George, Indhu A1 - Wright, Louise A1 - Cox, Maurice A1 - Rhodes, Susan A1 - Zilberti, Luca A1 - Manzin, Alessandra A1 - Pennecchi, Francesca A1 - Kok, Gertjan A1 - van der Veen, Adriaan A1 - Fischer, Nicolas A1 - Sousa, Joao Alves A1 - Vogel, Kristin A1 - Bosnjakovic, Alen A1 - Ellison, Stephen T1 - Strategic Agenda, European Metrology Network for Mathematics and Statistics N2 - This document constitutes the Strategic Research Agenda (SRA) for the European Metrology Network for Mathematics and Statistics in Metrology (EMN Mathmet). The EMN Mathmet is an alliance of European National Metrology Institutes (NMIs), Designated Institutes (DIs) and an EMN Partner that aims to strengthen research and cooperation in the field. The SRA has been developed within a European project (EMPIR 18NET05 MATHMET) to promote and support the network. The SRA was developed based on a consultation process with stakeholders and the strategies of individual NMIs and DIs, and in alignment with the EURAMET 2030 strategy. As a key result, the SRA defines a long-term research goal: the EMN Mathmet will coordinate research to strengthen the trust in algorithms, software tools and data to underpin digital transformation. For this purpose, new emerging research topics where algorithms, software tools and data play a significant role were identified: (i) Artificial Intelligence and Machine Learning, and (ii) Computational Modelling and Virtual Metrology. The foundation for the development of these new topics is given by the traditional focus on (iii) Data Analysis and Uncertainty Evaluation. The SRA characterises the future needs and challenges in the field of mathematics and statistics in metrology and provides an outline of how the EMN Mathmet can meet these new emerging requirements. KW - Research Agenda KW - Metrology KW - Mathematics and Statistics PY - 2023 UR - https://www.euramet.org/european-metrology-networks/mathmet/strategy/strategic-research-agenda SN - 978-3-942992-78-7 SP - 1 EP - 68 PB - EURAMET e.V. CY - Braunschweig AN - OPUS4-59526 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Veh, G. A1 - Lützow, N. A1 - Tamm, J. A1 - Luna, L. V. A1 - Hugonnet, R. A1 - Vogel, Kristin A1 - Geertsema, M. A1 - Clague, J. J. A1 - Korup, O. T1 - Less extreme and earlier outbursts of ice-dammed lakes since 1900 N2 - Episodic failures of ice-dammed lakes have produced some of the largest floods in history, with disastrous consequences for communities in high mountains. Yet, estimating changes in the activity of ice-dam failures through time remains controversial because of inconsistent regional flood databases. Here, by collating 1,569 ice-dam failures in six major mountain regions, we systematically assess trends in peak discharge, volume, annual timing and source elevation between 1900 and 2021. We show that extreme peak flows and volumes (10 per cent highest) have declined by about an order of magnitude over this period in five of the six regions, whereas median flood discharges have fallen less or have remained unchanged. Ice-dam floods worldwide today originate at higher elevations and happen about six weeks earlier in the year than in 1900. Individual ice-dammed lakes with repeated outbursts show similar negative trends in magnitude and earlier occurrence, although with only moderate correlation to glacier thinning8. We anticipate that ice dams will continue to fail in the near future, even as glaciers thin and recede. Yet widespread deglaciation, projected for nearly all regions by the end of the twenty-first century9, may bring most outburst activity to a halt. KW - Outburst floods KW - Bayesian hierachical modelling KW - Trends in extreme events PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-570529 DO - https://doi.org/10.1038/s41586-022-05642-9 VL - 614 IS - 7949 SP - 701 EP - 707 AN - OPUS4-57052 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Vogel, Kristin A1 - Sieg, T. A1 - Veh, G. A1 - Fiedler, B. A1 - Moran, T. A1 - Peter, M. A1 - Rottler, E. A1 - Bronstert, A. T1 - Natural Hazards in a Changing World: Methods for Analyzing Trends and Non‐Linear Changes N2 - Estimating the frequency and magnitude of natural hazards largely hinges on stationary models, which do not account for changes in the climatological, hydrological, and geophysical baseline conditions. Using five diverse case studies encompassing various natural hazard types, we present advanced statistical and machine learning methods to analyze and model transient states from long‐term inventory data. A novel storminess metric reveals increasing European winter windstorm severity from 1950 to 2010. Non‐stationary extreme value models quantify trends, seasonal shifts, and regional differences in extreme precipitation for Germany between 1941 and 2021. Utilizing quantile sampling and empirical mode decomposition on 148 years of daily weather and discharge data in the European Alps, we assess the impacts of changing snow cover, precipitation, and anthropogenic river network modifications on river runoff. Moreover, a probabilistic framework estimates return periods of glacier lake outburst floods in the Himalayas, demonstrating large differences in 100‐year flood levels. Utilizing a Bayesian change point algorithm, we track the onset of increased seismicity in the southern central United States and find correlation with wastewater injections into deep wells. In conclusion, data science reveals transient states for very different natural hazard types, characterized by diverse forms of change, ranging from gradual trends to sudden change points and from altered seasonality to overall intensity variations. In synergy with the physical understanding of Earth science, we gain important new insights into the dynamics of the studied hazards and their possible mechanisms. KW - Natural hazards KW - Time dependent modeling KW - Transient state KW - Data science KW - Climate change PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-601540 DO - https://doi.org/10.1029/2023EF003553 VL - 12 IS - 5 SP - 1 EP - 29 PB - American Geophysical Union (AGU) AN - OPUS4-60154 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Veh, Georg A1 - Wang, Björn G. A1 - Zirzow, Anika A1 - Schmidt, Christoph A1 - Lützow, Natalie A1 - Steppat, Frederic A1 - Zhang, Guoqing A1 - Vogel, Kristin A1 - Geertsema, Marten A1 - Clague, John J. A1 - Korup, Oliver T1 - Progressively smaller glacier lake outburst floods despite worldwide growth in lake area N2 - Glacier lake outburst floods (GLOFs) may originate from larger lakes as these continue to grow with ongoing glacier retreat; however, this perception remains poorly supported in available GLOF databases. Here we mapped the areas of 1,686 glacier lakes, just before they drained, across 13 glaciated mountain regions outside polar regions and examined the trends in pre-GLOF lake areas between 1990 and 2023. We found that pre-GLOF lake areas barely changed, or even decreased, regionally through time, even as the total lake area, and thus hazard potential, grew overall. This counterintuitive finding reflects limits to growing GLOF magnitudes, such as the decoupling of lakes and parent glaciers, the development of wide, low-gradient outlets or human management. Across all regions, pre-GLOF lake areas depend on a few ice-dammed lakes, which have produced ten times more reported outbursts and ten times larger outbursts than moraineand bedrock-dammed lakes. The latter two dam types will continue to impound growing amounts of meltwater, thereby accounting for most of the overall GLOF hazard potential, while ice-dammed lakes will shrink with deglaciation. As these lake types will evolve differently in the twenty-first century, we call for customized simulations of GLOF outflows and impacts, given the growing exposure of critical infrastructure. KW - Climate change KW - Bayesian hierachical modelling KW - Outbursts flood PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-625709 DO - https://doi.org/10.1038/s44221-025-00388-w SN - 2731-6084 SP - 1 EP - 25 AN - OPUS4-62570 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Paul, Andrea A1 - Liestmann, Zoe A1 - Zaenker, Steffen A1 - Vogel, Kristin A1 - Broszies, Tanja A1 - Ostermann, Markus T1 - How reliable is the X‐ray fluorescence‐based differentiation between glass wool and rock wool and the age classification of rock wool? N2 - AbstractA prerequisite for the recycling of mineral wool is information about the type of material, that is, whether it is glass wool or rock wool. As mineral wool produced before the year 2000 can be potentially carcinogenic, it is furthermore important to distinguish between “old” and “new” wool when handling the material. Based on VDI 3492, it is possible to determine the material and, in the case of rock wool, the age by analyzing the mass fractions of eight oxides, which are the main components of mineral wool. This study presents the X‐ray fluorescence (XRF) analyses of 141 man‐made mineral fibers collected in Germany. Only in a few cases it was not possible to clearly assign the material type. In contrast, the identification of “old” and “new” rock wool posed a challenge as there were many borderline samples. Based on the available data, a chemometric model was developed that can classify “old” and “new” RW with a sensitivity of 93% and 89% and with a specificity of 100% in both cases. However, care must be taken when oxide contents are close to the specification limits. The reason for this mainly lies in the overlapping intervals of key oxides as suggested by VDI 3492, and, to a lesser extent, in the uncertainties typically occurring in the XRF‐based analysis of oxides. With this study, a comprehensive collection and evaluation of XRF data on mineral wool is made available, which can serve as a reference database for future users. KW - Mineral wool KW - RFA KW - Multivariate data analysis KW - VDI 3492 PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-610285 DO - https://doi.org/10.1002/xrs.3451 SN - 1097-4539 SP - 1 EP - 11 PB - Wiley CY - New York, NY AN - OPUS4-61028 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Recknagel, Sebastian A1 - Vogel, Kristin T1 - Berechnung und Nutzung von Unsicherheiten zertifizierter Werte von Referenzmaterialien N2 - Referenzmaterialien sind entscheidend für die Qualitätssicherung von Laboratorien. Diese nutzen Referenzmaterialien unter anderem zur Validierung von Messverfahren und zur Kalibrierung von Geräten. Dabei ist zu beachten, dass zertifizierte Merkmalswerte stets eine gewisse Unsicherheit aufweisen. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Artikels. Des Weiteren wird ein Vorgehen beschrieben, wie die Unsicherheit von Messverfahren mit Hilfe eines Referenzmaterials bestimmt werden kann. KW - Referenzmaterial KW - Messunsicherheit KW - Qualitätskontrolle PY - 2024 DO - https://doi.org/10.1515/teme-2024-0025 SN - 0171-8096 SP - 1 EP - 7 PB - De Gruyter AN - OPUS4-60564 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Recknagel, Sebastian A1 - Vogel, Kristin T1 - Berechnung und Nutzung von Unsicherheiten zertifizierter Werte von Referenzmaterialien N2 - Referenzmaterialien sind unter anderem ein wichtiges Werkzeug zur Qualitätskontrolle von Messungen bestimmter Merkmalswerte. Dabei ist zu berücksichtigen, dass zertifizierte Merkmalswerte immer eine gewisse Unsicherheit haben. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Vortrags. Referenzmaterialien sind gleichzeitig ein wertvolles Werkzeug zur Ermittlung der Unsicherheit von Messverfahren und -Analysen unbekannter Proben. Die Vorgehensweise bei der Ermittlung der Messunsicherheit mit Hilfe eines Referenzmaterials wird beschrieben. T2 - 11. VDI-Fachtagung Messunsicherheit und Prüfprozesse CY - Erfurt, Germany DA - 14.11.2023 KW - Referenzmaterial KW - Messunsicherheit KW - ISO Guide 35 PY - 2023 AN - OPUS4-58946 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Recknagel, Sebastian A1 - Vogel, Kristin T1 - Berechnung und Nutzung von Unsicherheiten zertifizierter Werte von Referenzmaterialien N2 - Referenzmaterialien sind unter anderem ein wichtiges Werkzeug zur Qualitätskontrolle von Messungen bestimmter Merkmalswerte. Dabei ist zu berücksichtigen, dass zertifizierte Merkmalswerte immer eine gewisse Unsicherheit haben. Die Ermittlung dieser Unsicherheitsbeiträge ist Gegenstand des Vortrags. Referenzmaterialien sind gleichzeitig ein wertvolles Werkzeug zur Ermittlung der Unsicherheit von Messverfahren und -Analysen unbekannter Proben. Die Vorgehensweise bei der Ermittlung der Messunsicherheit mit Hilfe eines Referenzmaterials wird beschrieben. T2 - Jahrestagung des GDMB-Chemiker-Ausschusses CY - Kassel, Germany DA - 07.11.2023 KW - Referenzmaterial KW - Messunsicherheit KW - ISO Guide 35 PY - 2023 AN - OPUS4-58929 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Vogel, Kristin T1 - Die Berechnung von Unsicherheiten zertifizierter Werte von Referenzmaterialien und deren Nutzung zur Berechnung von Verfahrensmessunsicherheiten N2 - Die Angabe von Unsicherheiten bei zertifizierten Werten von Referenzmaterialien ist von entscheidender Bedeutung. Die korrekte Einbindung der Unsicherheiten zur Berechnung von Verfahrensmessunsicherheiten ist wesentlich für die Gewährleistung der Genauigkeit und Zuverlässigkeit von Messungen. In diesem Vortrag werden die verschiedenen Einflussfaktoren auf die Unsicherheit zertifizierter Werte gemäß ISO Guide 35 dargestellt. Dabei werden insbesondere die Charakterisierung, Homogenität und Stabilität als entscheidende Faktoren für die Bestimmung der Unsicherheit eines Referenzmaterials betrachtet. Abschließend wird das Konzept anhand eines konkreten Beispiels veranschaulicht, um die praktische Anwendung und die Auswirkungen auf die Berechnung von Verfahrensmessunsicherheiten zu verdeutlichen. T2 - 324. PTB-Seminar Berechnung der Messunsicherheit – Empfehlungen für die Praxis CY - Berlin, Germany DA - 22.05.2023 KW - Referenzmaterialien KW - Unsicherheit PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-598418 UR - https://www.ptb.de/cms/fileadmin/internet/fachabteilungen/abteilung_8/8.4_mathematische_modellierung/324_PTB_Seminar/Vortraege/324-PTB-Seminar_Unsicherheiten_zertifizierter_Werte.pdf UR - https://www.ptb.de/cms/ptb/fachabteilungen/abt8/fb-84/ag-842/seminare/324-ptb-seminar-berechnung-der-messunsicherheit-empfehlungen-fuer-die-praxis.html AN - OPUS4-59841 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lisec, Jan A1 - Recknagel, Sebastian A1 - Prinz, Carsten A1 - Vogel, Kristin A1 - Koch, Matthias A1 - Becker, Roland T1 - eCerto—versatile software for interlaboratory data evaluation and documentation during reference material production N2 - The statistical tool eCerto was developed for the evaluation of measurement data to assign property values and associated uncertainties of reference materials. The analysis is based on collaborative studies of expert laboratories and was implemented using the R software environment. Emphasis was put on comparability of eCerto with SoftCRM, a statistical tool based on the certification strategy of the former Community Bureau of Reference. Additionally, special attention was directed towards easy usability from data collection through processing, archiving, and reporting. While the effects of outlier removal can be flexibly explored, eCerto always retains the original data set and any manipulation such as outlier removal is (graphically and tabularly) documented adequately in the report. As a major reference materials producer, the Bundesanstalt für Materialforschung und -prüfung (BAM) developed and will maintain a tool to meet the needs of modern data processing, documentation requirements, and emerging fields of RM activity. The main features of eCerto are discussed using previously certified reference materials. KW - Reference material KW - Statistics KW - Software KW - Collaborative trial PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-591851 DO - https://doi.org/10.1007/s00216-023-05099-3 SP - 1 EP - 9 PB - Springer Science and Business Media LLC AN - OPUS4-59185 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Müller, Simon A1 - Hofmann-Böllinghaus, Anja A1 - Chen, Zhimin A1 - Vogel, Kristin A1 - Benner, Philipp T1 - A high-resolution spatiotemporal wildfire propagation dataset for the Mediterranean and Europe N2 - Wildfires are becoming more frequent and severe under the influence of climate change, posing increasing risks to ecosystems, human health, and infrastructure. Accurate spatiotemporal data on wildfire propagation is essential for advancing fire behavior modeling, improving management strategies, and mitigating future impacts. However, existing datasets with both high spatial and temporal resolution are rare, costly, and time-consuming to produce. To address this gap, we present FireSpread_MedEU, a dataset comprising 320 consecutive burned area maps from 103 wildfire events across the Mediterranean and Europe between 2017 and 2023. Burned areas were derived from high-resolution Planet optical satellite imagery (~3 m spatial, mostly daily temporal resolution) using a semi-automated workflow, followed by manual refinement to ensure highest accuracy. Each dataset entry is enriched with detailed metadata and a subjective quality assessment. With its high level of spatiotemporal precision, FireSpread_MedEU provides essential data for the development and validation of machine learning models or wildfire simulation models. It opens new research opportunities in wildfire behavior analysis, risk assessment, and predictive modeling. KW - Wildfire KW - Remote Sensing KW - Data PY - 2026 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-657294 DO - https://doi.org/10.1038/s41597-026-06965-2 SN - 2052-4463 VL - 13 IS - 1 SP - 1 EP - 7 PB - Springer Science and Business Media LLC AN - OPUS4-65729 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -