TY - JOUR A1 - Pick, Leonie A1 - Korte, Monika T1 - An annual proxy for the geomagnetic signal of magnetospheric currents on Earth based on observatory data from 1900–2010 JF - Geophysical Journal International N2 - We introduce the Annual Magnetospheric Currents index as long-term proxy for the geomagnetic signal of magnetospheric currents on Earth valid within the time span 1900–2010. Similar to the widely used disturbance storm time and ‘Ring Current’ indices, it is based on geomagnetic observatory data, but provides a realistic absolute level and uncertainty estimates. Crucial aspects to this end are the revision of observatory crustal biases as well as the implementation of a Bayesian inversion accounting for uncertainties in the main field estimate, both required for the index derivation. The observatory choice is based on a minimization of index variance during a reference period spanning 1960–2010. The new index is capable of correcting observatory time series from large-scale external signals in a user-friendly manner. At present the index is only available as annual mean values. An extension to hourly values for the same time span is in progress. KW - Magnetic field variations through time KW - Satellite magnetics KW - Inverse theory KW - Statistical methods KW - Time-series analysis Y1 - 2017 U6 - https://doi.org/10.1093/gji/ggx367 SN - 1365-246X SN - 0956-540X VL - 211 IS - 2 SP - 1223 EP - 1236 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Pick, Leonie A1 - Korte, Monika A1 - Thomas, Yannik A1 - Krivova, Natalie A1 - Wu, Chi-Ju T1 - Evolution of Large-Scale Magnetic Fields From Near-Earth Space During the Last 11 Solar Cycles JF - Journal of Geophysical Research: Space Physics N2 - We use hourly mean magnetic field measurements from 34 midlatitude geomagnetic observatories between 1900 and 2015 to investigate the long-term evolution and driving mechanism of the large-scale external magnetic field at ground. The Hourly Magnetospheric Currents index (HMC) is derived as a refinement of the Annual Magnetospheric Currents index (HMC, Pick & Korte, 2017, https://doi.org/10.1093/gji/ggx367). HMC requires an extensive revision of the observatory hourly means. It depends on three third party geomagnetic field models used to eliminate the core, the crustal, and the ionospheric solar-quiet field contributions. We mitigate the dependency of HMC on the core field model by subtracting only nondipolar components of the model from the data. The separation of the residual (dipolar) signal into internal and external (HMC) parts is the main methodological challenge. Observatory crustal biases are updated with respect to AMC, and the solar-quiet field estimation is extended to the past based on a reconstruction of solar radio flux (F10.7). We find that HMC has more power at low frequencies (periods = 1 year) than the Dcx index, especially at periods relevant to the solar cycle. Most of the slow variations in HMC can be explained by the open solar magnetic flux. There is a weakly decreasing linear trend in absolute HMC from 1900 to present, which depends sensitively on the data rejection criteria at early years. HMC is well suited for studying long-term variations of the geomagnetic field. KW - geomagnetic indices KW - geomagnetic observatories Y1 - 2019 U6 - https://doi.org/10.1029/2018JA026185 SN - 2169-9402 SN - 0148-0227 SP - 2527 EP - 2540 PB - Union CY - Washington, DC ER - TY - THES A1 - Pick, Leonie Johanna Lisa T1 - The centennial evolution of geomagnetic activity and its driving mechanisms N2 - This cumulative thesis is concerned with the evolution of geomagnetic activity since the beginning of the 20th century, that is, the time-dependent response of the geomagnetic field to solar forcing. The focus lies on the description of the magnetospheric response field at ground level, which is particularly sensitive to the ring current system, and an interpretation of its variability in terms of the solar wind driving. Thereby, this work contributes to a comprehensive understanding of long-term solar-terrestrial interactions. The common basis of the presented publications is formed by a reanalysis of vector magnetic field measurements from geomagnetic observatories located at low and middle geomagnetic latitudes. In the first two studies, new ring current targeting geomagnetic activity indices are derived, the Annual and Hourly Magnetospheric Currents indices (A/HMC). Compared to existing indices (e.g., the Dst index), they do not only extend the covered period by at least three solar cycles but also constitute a qualitative improvement concerning the absolute index level and the ~11-year solar cycle variability. The analysis of A/HMC shows that (a) the annual geomagnetic activity experiences an interval-dependent trend with an overall linear decline during 1900–2010 of ~5 % (b) the average trend-free activity level amounts to ~28 nT (c) the solar cycle related variability shows amplitudes of ~15–45 nT (d) the activity level for geomagnetically quiet conditions (Kp<2) lies slightly below 20 nT. The plausibility of the last three points is ensured by comparison to independent estimations either based on magnetic field measurements from LEO satellite missions (since the 1990s) or the modeling of geomagnetic activity from solar wind input (since the 1960s). An independent validation of the longterm trend is problematic mainly because the sensitivity of the locally measured geomagnetic activity depends on geomagnetic latitude. Consequently, A/HMC is neither directly comparable to global geomagnetic activity indices (e.g., the aa index) nor to the partly reconstructed open solar magnetic flux, which requires a homogeneous response of the ground-based measurements to the interplanetary magnetic field and the solar wind speed. The last study combines a consistent, HMC-based identification of geomagnetic storms from 1930–2015 with an analysis of the corresponding spatial (magnetic local time-dependent) disturbance patterns. Amongst others, the disturbances at dawn and dusk, particularly their evolution during the storm recovery phases, are shown to be indicative of the solar wind driving structure (Interplanetary Coronal Mass Ejections vs. Stream or Co-rotating Interaction Regions), which enables a backward-prediction of the storm driver classes. The results indicate that ICME-driven geomagnetic storms have decreased since 1930 which is consistent with the concurrent decrease of HMC. Out of the collection of compiled follow-up studies the inclusion of measurements from high-latitude geomagnetic observatories into the third study’s framework seems most promising at this point. N2 - Diese kumulative Arbeit behandelt die Entwicklung der geomagnetischen Aktivität seit Beginn des 20. Jahrhunderts, also die zeitabhängige Antwort des Erdmagnetfeldes auf das Einwirken der Sonne. Der Fokus liegt auf einer Beschreibung des in der Magnetosphäre begründeten, magnetischen Störfeldes auf der Erdoberfläche. Die Variabilität dieses Störfeldes reagiert besonders sensibel auf das Ringstromsystem und wird hinsichtlich des Sonnenantriebs interpretiert. Damit trägt diese Arbeit dazu bei, die langfristige solar-terrestrische Interaktion umfassend zu verstehen. Die gemeinsame Basis der vorgestellen Publikationen ist eine Reanalyse der vektoriellen Magnetfeldmessungen von geomagnetischen Observatorien, die auf niedrigen und mittleren geomagnetischen Breitengraden liegen. In den beiden ersten Studien werden neue, auf den Ringstrom spezialisierte, geomagntische Aktivitätsindizes hergeleitet, die „Annual/Hourly Magnetopsheric Currents“ (A/HMC) Indizes. Verglichen mit existierenden Indizes (z.B. dem Dst Index) verlängern sie nicht nur die abgedeckte Zeitspanne, sondern sie stellen auch eine qualitative Verbesserung bezüglich des absoluten Niveaus und der mit dem ca. 11-jährigen Sonnenzyklus einhergehenden Variabilität dar. Die Auswertung des A/HMC zeigt, dass (a) die jährliche geomagnetiche Aktivität einem intervallabhängigen Trend unterliegt mit einer linearen Abnahme von ca. 5 % im Zeitraum 1900-2010 (b) das durchschnittliche, Trend-befreite Aktivitätsniveau bei ca. 28 Nanotesla (nT) liegt (c) die mit dem Sonnenzyklus zusammenhängende Variabilität eine Amplitude zwischen 15 und 45 nT aufweist (d) das Aktivitätsniveau für geomagnetisch ruhige Konditionen (Kp < 2 nT) bei knapp unter 20 nT liegt. Die Plausibilität der letztgenannten drei Punkte lässt sich über einen Vergleich mit unabhängigen Abschätzungen sicherstellen. Entweder zieht man hierzu Magnetfeldmessungen von „Low-Earth-Orbit“ Satellitenmissionen (seit den 1990er-Jahren), oder eine Modellierung der geomagnetischen Aktivität mittels der Parameter des Sonnenwindes (seit den 1960er-Jahren) heran. Eine unabhängige Validierung des langfristigen Trends ist jedoch problematisch, hauptsächlich, weil die Sensitivität der lokalen geomagnetischen Aktivität vom Breitengrad abhängt. Folglich ist A/HMC weder mit globalen, geomagnetischen Aktivitätindizes (z.B. mit dem aa Index), noch mit dem teils rekonstruierten, „offenen“ solaren Magnetfluss direkt vergleichbar. Die dritte Studie kombiniert eine konsistente, HMC-basierte Identifikation geomagnetischer Stürme aus dem Zeitraum 1930-2015 mit einer Analyse der entsprechenden räumlichen Störungsmuster. Die Studie zeigt, dass insbesondere die Entwicklung der Magnetfeldstörungen zu Sonnenauf- und Sonnenuntergang während der Erholungsphase der Stürme statistisch unterschiedlich auf die Art des Sonnenwindantriebs (Koronale Massenauswürfe (KM) oder korotierende Wechselwirkungsregionen) reagieren. Dies ermöglicht eine Bestimmung der Antriebsklassen von historischen geomagnetischen Stürmen. Die Ergebnisse zeigen, dass KM-getriebene Stürme seit 1930 abgenommen haben, was mit der einhergehenden Verringerung von HMC zusammenpasst. Aus der Sammlung möglicher Folgestudien erscheint es zum jetzigen Zeitpunkt am vielversprechendsten, Observatoriumsmessungen aus hohen Breiten im Rahmen der dritten Studie einzubeziehen. T2 - Die hundertjährige Entwicklung der geomagnetischen Aktivität und ihre Antriebsmechanismen KW - Geomagnetic activity KW - Geomagnetic index KW - Geomagnetic observatory KW - Space climate KW - Space weather KW - Geomagnetische Aktivität KW - Geomagnetischer Index KW - Geomagnetisches Observatorium KW - Weltraumklima KW - Weltraumwetter Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-472754 ER - TY - JOUR A1 - Pick, Leonie A1 - Effenberger, Frederic A1 - Zhelavskaya, Irina A1 - Korte, Monika T1 - A Statistical Classifier for Historical Geomagnetic Storm Drivers Derived Solely From Ground-Based Magnetic Field Measurements JF - Earth and Space Science N2 - Solar wind observations show that geomagnetic storms are mainly driven by interplanetary coronal mass ejections (ICMEs) and corotating or stream interaction regions (C/SIRs). We present a binary classifier that assigns one of these drivers to 7,546 storms between 1930 and 2015 using ground‐based geomagnetic field observations only. The input data consists of the long‐term stable Hourly Magnetospheric Currents index alongside the corresponding midlatitude geomagnetic observatory time series. This data set provides comprehensive information on the global storm time magnetic disturbance field, particularly its spatial variability, over eight solar cycles. For the first time, we use this information statistically with regard to an automated storm driver identification. Our supervised classification model significantly outperforms unskilled baseline models (78% accuracy with 26[19]% misidentified interplanetary coronal mass ejections [corotating or stream interaction regions]) and delivers plausible driver occurrences with regard to storm intensity and solar cycle phase. Our results can readily be used to advance related studies fundamental to space weather research, for example, studies connecting galactic cosmic ray modulation and geomagnetic disturbances. They are fully reproducible by means of the underlying open‐source software (Pick, 2019, http://doi.org/10.5880/GFZ.2.3.2019.003) KW - geomagnetic observatory data KW - geomagnetic storm drivers KW - historical geomagnetic storms KW - supervised machine learning Y1 - 2019 U6 - https://doi.org/10.1029/2019EA000726 SN - 2333-5084 VL - 6 SP - 2000 EP - 2015 PB - American Geophysical Union CY - Malden, Mass. ER - TY - GEN A1 - Pick, Leonie A1 - Effenberger, Frederic A1 - Zhelavskaya, Irina A1 - Korte, Monika T1 - A Statistical Classifier for Historical Geomagnetic Storm Drivers Derived Solely From Ground-Based Magnetic Field Measurements T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Solar wind observations show that geomagnetic storms are mainly driven by interplanetary coronal mass ejections (ICMEs) and corotating or stream interaction regions (C/SIRs). We present a binary classifier that assigns one of these drivers to 7,546 storms between 1930 and 2015 using ground‐based geomagnetic field observations only. The input data consists of the long‐term stable Hourly Magnetospheric Currents index alongside the corresponding midlatitude geomagnetic observatory time series. This data set provides comprehensive information on the global storm time magnetic disturbance field, particularly its spatial variability, over eight solar cycles. For the first time, we use this information statistically with regard to an automated storm driver identification. Our supervised classification model significantly outperforms unskilled baseline models (78% accuracy with 26[19]% misidentified interplanetary coronal mass ejections [corotating or stream interaction regions]) and delivers plausible driver occurrences with regard to storm intensity and solar cycle phase. Our results can readily be used to advance related studies fundamental to space weather research, for example, studies connecting galactic cosmic ray modulation and geomagnetic disturbances. They are fully reproducible by means of the underlying open‐source software (Pick, 2019, http://doi.org/10.5880/GFZ.2.3.2019.003) T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 982 KW - geomagnetic observatory data KW - geomagnetic storm drivers KW - historical geomagnetic storms KW - supervised machine learning Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-474996 SN - 1866-8372 IS - 982 SP - 2000 EP - 2015 ER -