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Very low frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, this dataset, called the ‘maw’ product, covers a very low frequency range of infrasound (0.02-0.07 Hz). The temporal resolution (time step and window length) is 30 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022.

Higher frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, within the CTBT-relevant infrasound range (around 0.01-4 Hz), this dataset covers higher frequencies (1-3 Hz) and is therefore called the ‘hf’ product. The temporal resolution (time step and window length) is 5 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022

Microbarom low-frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, this dataset covers the dominant frequency range of microbaroms (0.15-0.35 Hz) and is therefore called the ‘mb_lf’ product. The temporal resolution (time step and window length) is 15 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022

Microbarom high-frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, this dataset covers, among other phenomena, the upper frequency range of microbaroms (0.45-0.65 Hz) and is therefore called the ‘mb_hf’ product. The temporal resolution (time step and window length) is 15 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022

Very low frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, this dataset, called the ‘maw’ product, covers a very low frequency range of infrasound (0.02-0.07 Hz). The temporal resolution (time step and window length) is 30 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022.

Higher frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, within the CTBT-relevant infrasound range (around 0.01-4 Hz), this dataset covers higher frequencies (1-3 Hz) and is therefore called the ‘hf’ product. The temporal resolution (time step and window length) is 5 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022

Microbarom low-frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, this dataset covers the dominant frequency range of microbaroms (0.15-0.35 Hz) and is therefore called the ‘mb_lf’ product. The temporal resolution (time step and window length) is 15 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022

Microbarom high-frequency data products of the International Monitoring System’s infrasound stations

This dataset consists of data products derived from broadband signal detection lists that have been processed for the certified infrasound stations of the International Monitoring System. More specifically, this dataset covers, among other phenomena, the upper frequency range of microbaroms (0.45-0.65 Hz) and is therefore called the ‘mb_hf’ product. The temporal resolution (time step and window length) is 15 min. For processing the infrasound data, the Progressive Multi-Channel Correlation (PMCC) array processing algorithm with a one-third octave frequency band configuration between 0.01 and 4 Hz has been used. The detected signals from the most dominant directions in terms of number of arrivals within a time window and the product-specific frequency range are summarized at predefined time steps. Along with several detection parameters such as the back azimuth, apparent velocity, or mean frequency, additional quantities for assessing the relative quality of the detection parameters are provided. The dataset is available as a compressed .zip file containing the yearly data products (.nc files, NetCDF format) of all certified stations (since 2003). Further information on the processing and details about the open-access data products can be found in: Hupe et al. (2022), IMS infrasound data products for atmospheric studies and civilian applications, Earth System Science Data, doi:10.5194/essd-14-4201-2022

Labor für Künstliche Intelligenz und Big Data am Umweltbundesamt gestartet

Gemeinsame Pressemitteilung von Umweltbundesamt und Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz Bundesumweltministerin Lemke und UBA-Präsident Messner geben Startschuss für neuen Experimentierraum zur Analyse von Umweltdaten Bundesumwelt- und -verbraucherschutzministerin Steffi Lemke und der Präsident des Umweltbundesamts (UBA) Prof. Dr. Dirk Messner haben heute das Anwendungslabor für Künstliche Intelligenz und Big Data (KI-Lab) am UBA eröffnet. Das KI-Lab soll Grundlagen schaffen, um mit Künstlicher Intelligenz (KI) die Analyse großer Mengen von Umweltdaten (Big Data) stärker zu vereinfachen. Alle Behörden im Umweltressort werden das KI-Lab für ihre Arbeit nutzen, das heute seine Arbeit aufnimmt. Steffi Lemke, Bundesumwelt- und -verbraucherschutzministerin: „Die Potentiale von KI und Big Data sind immens – auch für den Schutz von Umwelt, ⁠ Klima ⁠ und Natur. Sie auf nachhaltige Weise zu heben, ist eine wichtige Gemeinschaftsaufgabe und gehört zu verantwortungsvoller Digitalisierung. Das neue KI-Lab ist innovativ und ermöglicht den Behörden des Umweltressorts, passgenaue Anwendungen für Herausforderungen zu entwickeln – zum Beispiel für die effizientere Auswertung von Satellitendaten, um den Ausbau von Wind- und Sonnenstrom besser planen zu können. Diese Anwendungen sollen die Arbeit der Behörden unterstützen und das Verständnis von Problemen, Lösungen und Zusammenhängen im Umweltbereich sowohl bei den Behörden selbst als auch in der Öffentlichkeit verbessern. Das hat Modellcharakter.“ ⁠ UBA ⁠-Präsident Prof. Dr. Dirk Messner: „Digitale Transformation und künstliche Intelligenz sind ein Paradigmenwechsel auch im Umweltschutz. Wir werden Umweltdaten künftig völlig anders und auch besser analysieren können. Dazu müssen wir neue datenwissenschaftliche Methoden für die Umwelt- und Nachhaltigkeitsforschung nutzen und Kompetenzen im gesamten Umweltressort aufbauen. Sonst werden wir nicht Schritt halten bei der so wichtigen Verwaltungsdigitalisierung. Unser Anwendungslabor ist dafür ein einmaliger Experimentier- und Gestaltungsraum für die Analyse von Umweltdaten.“ Das KI-Lab nutzt datenwissenschaftliche Methoden und Technologien, um die heterogenen, komplexen und bisher oft schwer zugänglichen Datenbestände in der Umweltverwaltung besser zu verwerten. Das umfasst Erdbeobachtungs- und Messdaten, Prozessdaten für eine Verwaltungs- und Vollzugsoptimierung und viele andere weitere Umwelt-, Natur- und Strahlenschutzdaten. Erste Beispiele für die mögliche Anwendung von KI sind etwa das Identifizieren von Wind- und Photovoltaik-Anlagen in Satellitendaten für eine bessere Planung. Auch lassen sich illegal in Online-Handelsplattformen angebotene und geschützte Tier- und Pflanzenarten besser aufspüren. Mit dem KI-Lab können alle Behörden des Umweltressorts KI-Anwendungen auf Basis von Umweltdaten entwickeln – neben dem UBA sind dies das Bundesamt für Naturschutz, das Bundesamt für Strahlenschutz und das Bundesamt für die Sicherheit der nuklearen Entsorgung. Das KI-Lab ist eine Initiative im Rahmen der Umweltpolitischen Digitalagenda des ⁠ BMUV ⁠ und Teil des BMUV 5-Punkte-Programms „Künstliche Intelligenz für Umwelt und Klima“. Hierfür stehen aus Mitteln des Konjunktur- und Zukunftspaketes der Bundesregierung (2021) 26,4 Millionen Euro zur Verfügung. Es werden rund 30 Mitarbeitende, zunächst befristet bis 2025, an den Standorten Leipzig, Berlin und Dessau-Roßlau beschäftigt. Das KI-Lab legt besonderen Wert auf den verantwortungsvollen Umgang mit Daten und entwickelt Lösungen zur ressourcenschonenden Nutzung von KI und Big Data (Responsible & Green AI). Dabei stehen verschiedene Aspekte nachhaltiger Software im Raum: Vom möglichst energieeffizienten Einsatz der Hardware über passgenaue und ethische Auswahl der Daten und Algorithmen, bis zur Verwertbarkeit durch dritte im Rahmen von Open-Source. Das KI-Lab arbeitet aktuell daran, wirkungsvolle nationale und internationale Netzwerke und Kollaborationen zum Thema KI und deren Nutzung im Umweltressort zu etablieren. Ziel ist es, im gesamten Umweltressort methodisch und technisch relevante Kompetenzen aufzubauen. Die Behörden wollen voneinander lernen und so der digitalen Transformation in der Umweltverwaltung Anschub geben.  „Wir arbeiten bei der Umsetzung von Beispielanwendungen (Use Cases) mit ganz unterschiedlichen Expertinnen und Experten aus dem Umweltressort eng zusammen: von der Meeresforschung, über Strahlenschutz bis hin zur Atmosphärenphysik im urbanen Raum. Es ist uns ein Anliegen, dass das KI-Lab sowohl eine Wirkung nach außen entfacht, als auch ins eigene Haus wirkt.“  so Robert Wagner, Leiter des KI-Lab am UBA.

NOAA Auswertung: Erwärmungspause gab es nicht

Einer von US-Behörde National Oceanic and Atmospheric Administration (NOAA) erstellte Studie, die am 4. Juni 2015 in der Fachzeitschrift Science veröffentlicht wurde, kommt zu dem Schluss, dass es in den letzten Jahren keine Verlangsamung bzw. in der Erderwärmung gegeben hat. Aus der aktuellen Analyse der globalen Oberflächentemperatur der Wissenschafter des National Climatic Data Center(NCEI) der NOAA in Asheville geht hervor, dass sich die Temperatur seit 1998 in gleichem Ausmaß erhöht hat wie davor. Die vermeintliche Erwärmungspause ist eine Illusion. Zustande gekommen nur durch systematische Fehler, die sich bei den langjährigen Temperaturmessungen im Ozean eingeschlichen haben.

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