GD9.2

The geomagnetic field, the Earth’s primary barrier against charged particles from the sun, varies on time scales from million years to sub-second fluctuations. In the past decades significant advances in measurement techniques, both ground and space based, paleo- and rock magnetic methods, as well as numerical and analytical simulations, improved our understanding of underlying processes and their consequences on our planet and on our society. Geomagnetic storms, often related to coronal mass ejections on the sun and their interaction with the Earth‘s magnetic field, pose a threat to our modern society as they affect satellites, disturb radio communication, and, in particular, damage power grids and cause electrical blackouts on a massive scale. Ground based measurements, which are used together with satellite data to investigate these events, point towards the occurrence of global scale major storms once every 100 years. When further looking at such observatory data, which is existing for the last few hundred years, it is also striking that the global Earth‘s magnetic field is gradually weakening, by more the 10% in the past 200 years. Paleo- and archeomagnetic investigations are used to extend our observational range into the past in order to clarify the significance and reasons of this field reduction. When looking even further into the past, complete flips of the geomagnetic field are recorded in geological archives like volcanic rocks and sediments. These geomagnetic field reversals, the last one happening about 770kyrs ago, are accompanied by strong reductions of the geomagnetic field strength and complex field behavior on the Earths surface, effects which are sometimes brought into connection with our modern observation of field reduction. This presentation will provide a comprehensive overview about geomagnetic field variations, and the necessity of using long timeseries for interpretation of its current state and future evolution.

How to cite: Leonhardt, R.: Variations of the Earth magnetic field: From geomagnetic storms to field reversal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8343, https://doi.org/10.5194/egusphere-egu22-8343, 2022.

Geomagnetic activity is a measure aimed to quantify the effect of solar wind upon the Earth's magnetic environment. The main structures in solar wind driving geomagnetic activity are the coronal mass ejections (CME) and the high-speed solar wind streams together with related co-rotating interaction regions (HSS/CIR). While CMEs are closely related to sunspots and other active regions on solar surface, the HSSs are related to solar coronal holes, forming a proxy of solar polar magnetic fields. This gives an interesting possibility to obtain versatile information on solar activity and solar magnetic fields from geomagnetic activity.

Various indices have been developed to quantify and monitor global geomagnetic activity. The most often used indices of overall geomagnetic activity are the aa index, developed by P. Mayaud and running already since 1868, and the Kp/Ap index, developed by J. Bartels and running since 1932. Both aa and Kp/Ap depict the increase of geomagnetic activity during the first half of the 20th century, and a steep decline in the 2000s. However, although the two indices are constructed from midlatitude observations using roughly the same recipe, they depict notable differences during the 90-year overlapping interval. While the Kp/Ap index reaches a centennial maximum in the late 1950s, at the same time as sunspots, the aa index has its maximum only in 2003. Also, the Kp/Ap is systematically relatively more active in the first decades until 1960s, while aa is more active thereafter. The Dst index was developed to monitor geomagnetic storms and the ring current since 1957. We have corrected some early errors in the Dst index and extended its time interval to 1932. This extended storm index is called the Dxt index. Here we study these long-term geomagnetic indices and their differences. We also use their different dependences on the main solar wind drivers in order to obtain new information on the centennial evolution of solar activity and solar magnetic fields.

How to cite: Mursula, K.: Long-term geomagnetic activity: Comparison and analysis of geomagnetic activity indices during the last 90 years, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12745, https://doi.org/10.5194/egusphere-egu22-12745, 2022.

Geophysical observatories around the world collect data on various natural phenomena within the Earth and on its surface. Many of these measurements are made automatically, sometimes at high sampling rates, so that enormous amounts of data accumulate over the years. Continuous analysis is important to classify current phenomena and decide which data are important and which can be downsampled later.

At Moxa Geodynamic Observatory, located in central Germany, several laser strainmeters have been installed in subsurface galleries in order to measure strain of the Earth's crust. These instruments run in north-south, east-west, and northwest-southeast directions. Nano-strain rates are determined with a sampling rate of 0.1 Hz almost continuously over distances of 26 and 38 m, respectively, since summer 2011.

Signals of tectonically induced crustal deformation are superimposed by other signals of greater amplitude, e.g., tides, changes in atmospheric pressure, hydrologic events such as heavy rainfall, and earthquakes. Classification of these events is important to better associate jumps in the temporal vicinity and to distinguish anomalies from instrument failures. To avoid time-consuming pattern recognition by hand, algorithms are required to do most of the work automatically. Due to recent advances in the field of artificial intelligence, it is possible to implement time series algorithms that are capable of unifying and automating many steps of data analysis. Although artificial intelligence applications are increasingly used to support data analysis, their use for time series of geophysical origin so far is not widespread outside of seismology.

In this contribution, an approach to automatically detect earthquakes in the strain data using 1D Convolutional Neural Networks is presented, including the generation of artificial training data with time series data augmentation. Also the training process and generation of new training data, based on classification by hand and false predictions of the trained model is described. The 1D Convolutional Neural Networks are able to identify almost all earthquakes in the strain data and have F1 values > 0.99, showing that their application has the potential to significantly reduce the time required in signal classification of observatory time series data.

How to cite: Kasburg, V., Breuer, A., Bücker, M., and Kukowski, N.: Earthquake detection in time-series of laser strainmeter measurements as a first step towards automatic signal classification., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3906, https://doi.org/10.5194/egusphere-egu22-3906, 2022.

To achieve very low ambient noise and thus very good conditions for long-term geophysical observations at a high level of instrumental accuracy in order to decipher also faint signals from Earth and environmental processes, sensors often are installed in the subsurface in galleries or in boreholes. This however, makes it necessary to consider the potential influence of the geological setting and properties of the surrounding rock formations and overburden.
Moxa Geodynamic observatory, located in a remote part of the Thuringian slate mountains, approximately 30 km south of Jena, provides an ideal setting to address this topic as it comprises two galleries, which are running perpendicular to each other. As the observatory is built at the toe of a relatively steep slope, coverage of the galleries varies along them. Further, the tectonic structure and hydrological settings of the overburden is rather complex.
Instruments sensitive to deformation, which include three laser strain meters measuring nano-strain, borehole tiltmeters and a superconducting gravimeter CD-034, together with other instruments, e.g. a node for the Global Network of Optical Magnetometers for Exotic physics (GNOME), are installed in various positions in the building of the observatory, close to the building, and in the galleries. The laser strainmeters record along three galleries in north-south, east-west and NW-SE directions. Further, information on fluid flow is gained from downhole temperature measurements employing an optical fiber and several groundwater level indicators, some of them installed in shallow boreholes. Additionally, information on environmental parameters is coming from a climate station and on the subsurface tectonic structure from various near surface geophysical data sets. 
Here, we present first results of an ongoing project which combines actual deformation recordings, structural and drillhole information to decipher how the tectonic structure of the and groundwater movement within the overlying slope on top of the observatory’s galleries may impact on the various instrumental recordings.

How to cite: Kukowski, N., Kasburg, V., Goepel, A., Schwarze, C., Jahr, T., and Stolz, R.: Impact of the geological setting of the overburden on long-time series recorded at underground geophysical observatories: case study from the FSU Jena Geodynamic Observatory Moxa (Thuringia, central Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11079, https://doi.org/10.5194/egusphere-egu22-11079, 2022.

In recent years, our research group has tried to improve the knowledge of the historical climate of the Extremadura region, located in the interior of the southwest of the Iberian Peninsula. Some results can be highlighted:

• Temperature and precipitation indices were constructed for the period 1750-1840 from the correspondence of the Duke of Feria (Fernández-Fernández et al., 2014, 2015, 2017).
• We have recovered many “pro pluvia” rogation dates (Domínguez-Castro et al., 2021) and we have seen their relationship with the North Atlantic Oscillation (Bravo-Paredes et al., 2020).
• We have studied the catastrophic floods of the Guadiana River since AD1500 (Bravo-Paredes et al., 2021).
• We have recovered more than 700,000 meteorological data from the Extremadura region taken in the 19th and early 20th centuries (Vaquero et al., 2022), including some uncommon series (Bravo-Paredes et al., 2019).

In recent months, we have started a study of the meteorological information published by the regional press of Extremadura in the last 150 years and here we will present some preliminary results.

References

Bravo-Paredes, N. et al. (2019) Tellus B 71, 1663597.

Bravo-Paredes, N. et al. (2020) Atmosphere 11(3), 282.

Bravo-Paredes, N. et al. (2021) Science of the Total Environment 797, 149141.

Domínguez-Castro, F. et al. (2021) Scientific Data 8, 186.

Fernández-Fernández, M.I. et al. (2014) Climatic Change 126, 107.

Fernández-Fernández, M.I. et al. (2015) Climatic Change 129, 267.

Fernández-Fernández, M.I. et al. (2017) Climatic Change 141, 671.

Vaquero, J.M. et al. (2022) Geoscience Data Journal. https://doi.org/10.1002/gdj3.131

How to cite: Vaquero, J. M., Gallego, M. C., Bravo-Paredes, N., Carrasco, V. M. S., and Tovar, I.: Reconstructing the climate of the Extremadura region (SW Spain) from documentary sources, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3134, https://doi.org/10.5194/egusphere-egu22-3134, 2022.

The Caribbean Sea in the tropical Atlantic is one of the major heat engines of the Earth and a sensitive area for monitoring climate variability. Salinity changes in the Caribbean Sea record changes in ocean currents and can provide information about variations in ocean heat transport. Seawater salinity in the Caribbean Sea has been monitored in recent decades, nevertheless, of all oceanographic environmental parameters salinity information before the instrumental period remains limited, due to the difficulty of reconstructing salinity, arguably the most difficult natural archives to recreate. We were able to reconstruct salinity changes in the Caribbean Sea from 1700 to the present from southwest Puerto Rico using slowly growing and long-lived scelerosponges from southwest Puerto Rico. These well-dated sponges are known to precipitate their skeletons in isotopic equilibrium (i.e., their record is not affected much by vital effects) and were retrieved from various depths in the mixed layer, from the surface to 90 m depth. We were able to establish salinity changes by deconvoluting stable isotopes (d¹⁸O) and trace element (Sr/Ca) proxies taken from the sponges at regular intervals. In this contribution, we will present the salinity record and illustrate the process for salinity reconstruction. We will also discuss how we determine how salinity changes in our record relate to radiative forcing as well as connect them with dominant mechanisms operating in the region, including changes in the position of the InterTtropical Convergence Zone and intensity of the Atlantic meridional Overturning Circulation over time.

How to cite: Winter, A., Zanchettin, D., McCulloch, M., Rigo, M., Sherman, C., and Rubino, A.: A high-resolution record of vertically-resolved seawater salinity in the Caribbean Sea mixed layer since 1700 AD., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1388, https://doi.org/10.5194/egusphere-egu22-1388, 2022.