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 - 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 - Schanner, Maximilian A1 - Korte, Monika A1 - Holschneider, Matthias T1 - ArchKalmag14k: A kalman-filter based global geomagnetic model for the holocene JF - Journal of geophysical research : Solid earth N2 - We propose a global geomagnetic field model for the last 14 thousand years, based on thermoremanent records. We call the model ArchKalmag14k. ArchKalmag14k is constructed by modifying recently proposed algorithms, based on space-time correlations. Due to the amount of data and complexity of the model, the full Bayesian posterior is numerically intractable. To tackle this, we sequentialize the inversion by implementing a Kalman-filter with a fixed time step. Every step consists of a prediction, based on a degree dependent temporal covariance, and a correction via Gaussian process regression. Dating errors are treated via a noisy input formulation. Cross correlations are reintroduced by a smoothing algorithm and model parameters are inferred from the data. Due to the specific statistical nature of the proposed algorithms, the model comes with space and time-dependent uncertainty estimates. The new model ArchKalmag14k shows less variation in the large-scale degrees than comparable models. Local predictions represent the underlying data and agree with comparable models, if the location is sampled well. Uncertainties are bigger for earlier times and in regions of sparse data coverage. We also use ArchKalmag14k to analyze the appearance and evolution of the South Atlantic anomaly together with reverse flux patches at the core-mantle boundary, considering the model uncertainties. While we find good agreement with earlier models for recent times, our model suggests a different evolution of intensity minima prior to 1650 CE. In general, our results suggest that prior to 6000 BCE the data is not sufficient to support global models. Y1 - 2022 U6 - https://doi.org/10.1029/2021JB023166 SN - 2169-9313 SN - 2169-9356 VL - 127 IS - 2 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Mauerberger, Stefan A1 - Schanner, Maximilian Arthus A1 - Korte, Monika A1 - Holschneider, Matthias T1 - Correlation based snapshot models of the archeomagnetic field JF - Geophysical journal international N2 - For the time stationary global geomagnetic field, a new modelling concept is presented. A Bayesian non-parametric approach provides realistic location dependent uncertainty estimates. Modelling related variabilities are dealt with systematically by making little subjective apriori assumptions. Rather than parametrizing the model by Gauss coefficients, a functional analytic approach is applied. The geomagnetic potential is assumed a Gaussian process to describe a distribution over functions. Apriori correlations are given by an explicit kernel function with non-informative dipole contribution. A refined modelling strategy is proposed that accommodates non-linearities of archeomagnetic observables: First, a rough field estimate is obtained considering only sites that provide full field vector records. Subsequently, this estimate supports the linearization that incorporates the remaining incomplete records. The comparison of results for the archeomagnetic field over the past 1000 yr is in general agreement with previous models while improved model uncertainty estimates are provided. KW - geopotential theory KW - archaeomagnetism KW - magnetic field variations through KW - time KW - palaeomagnetism KW - inverse theory KW - statistical methods Y1 - 2020 U6 - https://doi.org/10.1093/gji/ggaa336 SN - 0956-540X SN - 1365-246X VL - 223 IS - 1 SP - 648 EP - 665 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Schanner, Maximilian Arthus A1 - Mauerberger, Stefan A1 - Korte, Monika A1 - Holschneider, Matthias T1 - Correlation based time evolution of the archeomagnetic field JF - Journal of geophysical research : JGR ; an international quarterly. B, Solid earth N2 - In a previous study, a new snapshot modeling concept for the archeomagnetic field was introduced (Mauerberger et al., 2020, ). By assuming a Gaussian process for the geomagnetic potential, a correlation-based algorithm was presented, which incorporates a closed-form spatial correlation function. This work extends the suggested modeling strategy to the temporal domain. A space-time correlation kernel is constructed from the tensor product of the closed-form spatial correlation kernel with a squared exponential kernel in time. Dating uncertainties are incorporated into the modeling concept using a noisy input Gaussian process. All but one modeling hyperparameters are marginalized, to reduce their influence on the outcome and to translate their variability to the posterior variance. The resulting distribution incorporates uncertainties related to dating, measurement and modeling process. Results from application to archeomagnetic data show less variation in the dipole than comparable models, but are in general agreement with previous findings. Y1 - 2021 U6 - https://doi.org/10.1029/2020JB021548 SN - 2169-9313 SN - 2169-9356 VL - 126 IS - 7 PB - American Geophysical Union CY - Washington 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 - GEN A1 - Brown, Maxwell C. A1 - Donadini, Fabio A1 - Nilsson, Andreas A1 - Panovska, Sanja A1 - Frank, Ute A1 - Korhonen, Kimmo A1 - Schuberth, Maximilian A1 - Korte, Monika A1 - Constable, Catherine G. T1 - GEOMAGIA50.v3 BT - 2. A new paleomagnetic database for lake and marine sediments T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Background: GEOMAGIA50.v3 for sediments is a comprehensive online database providing access to published paleomagnetic, rock magnetic, and chronological data obtained from lake and marine sediments deposited over the past 50 ka. Its objective is to catalogue data that will improve our understanding of changes in the geomagnetic field, physical environments, and climate. Findings: GEOMAGIA50.v3 for sediments builds upon the structure of the pre-existing GEOMAGIA50 database for magnetic data from archeological and volcanic materials. A strong emphasis has been placed on the storage of geochronological data, and it is the first magnetic archive that includes comprehensive radiocarbon age data from sediments. The database will be updated as new sediment data become available. Conclusions: The web-based interface for the sediment database is located at http://geomagia.gfz-potsdam.de/geomagiav3/SDquery.php. This paper is a companion to Brown et al. (Earth Planets Space doi:10.1186/s40623-015-0232-0,2015) and describes the data types, structure, and functionality of the sediment database. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 875 KW - Geomagnetism KW - Paleomagnetism KW - Sediment magnetism KW - Rock magnetism KW - Environmental magnetism KW - Database KW - GEOMAGIA50 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-434768 SN - 1866-8372 IS - 875 ER - TY - JOUR A1 - Brown, Maxwell C. A1 - Donadini, Fabio A1 - Nilsson, Andreas A1 - Panovska, Sanja A1 - Frank, Ute A1 - Korhonen, Kimmo A1 - Schuberth, Maximilian A1 - Korte, Monika A1 - Constable, Catherine G. T1 - GEOMAGIA50.v3: 2. A new paleomagnetic database for lake and marine sediments JF - Earth, planets and space N2 - Background: GEOMAGIA50.v3 for sediments is a comprehensive online database providing access to published paleomagnetic, rock magnetic, and chronological data obtained from lake and marine sediments deposited over the past 50 ka. Its objective is to catalogue data that will improve our understanding of changes in the geomagnetic field, physical environments, and climate. Findings: GEOMAGIA50.v3 for sediments builds upon the structure of the pre-existing GEOMAGIA50 database for magnetic data from archeological and volcanic materials. A strong emphasis has been placed on the storage of geochronological data, and it is the first magnetic archive that includes comprehensive radiocarbon age data from sediments. The database will be updated as new sediment data become available. Conclusions: The web-based interface for the sediment database is located at http://geomagia.gfz-potsdam.de/geomagiav3/SDquery.php. This paper is a companion to Brown et al. (Earth Planets Space doi:10.1186/s40623-015-0232-0,2015) and describes the data types, structure, and functionality of the sediment database. KW - Geomagnetism KW - Paleomagnetism KW - Sediment magnetism KW - Rock magnetism KW - Environmental magnetism KW - Database KW - GEOMAGIA50 Y1 - 2015 U6 - https://doi.org/10.1186/s40623-015-0233-z SN - 1880-5981 VL - 67 PB - Springer CY - Heidelberg ER -