Long time-series of geophysical observations



Long term observations are of vital importance in the Earth Sciences, yet often difficult to pursue and fund. The distinction of a fluctuation from a long-term change in Earth processes is a key question to better understand processes within the Earth and in the Earth system. Likewise, it is a prerequisite for the assessment of the Earth's climate change as well as risk assessment. In order to distinguish fluctuations from a steady change, knowledge on the time variability of the signal itself and long term observations are required. Exemplarily, due to the decadal variability of sea level, reliable sea level trends can only be obtained after about sixty years of continuous observations. Reliable strain rates of deformation require a minimum of a decade of continuous data, due to ambient and anthropogenic factors leading to fluctuations. This session invites contributions demonstrating the importance of long term geophysical, geodynamic, oceanographic, geodetic, and climate observatories. Advances in sensors, instrumentation, monitoring techniques, analyses, and interpretations of data, or the comparison of approaches are welcome, with the aim to stimulate a multidisciplinary discussion among those dedicated to the accumulation, preservation and dissemination of data over decadal time scales or beyond. Studies utilizing novel approaches such as AI for analysis of long time series are very welcome. Likewise, studies that show the mutual transfer of knowledge of terrestrial and satellite observations are a topic of interest. With this session, we also would like to provide an opportunity to gather and exchange experiences for representatives from observatories both in Europe and worldwide.

Co-organized by CL5.2/EMRP2/G3/GI2
Convener: Nina Kukowski | Co-conveners: Dorothee Rebscher, Valentin KasburgECSECS, Carla Braitenberg, Hans-Peter Bunge
| Wed, 25 May, 17:00–18:30 (CEST)
Room -2.91

Presentations: Wed, 25 May | Room -2.91

Chairpersons: Nina Kukowski, Valentin Kasburg
Virtual presentation
Roman Leonhardt

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,, 2022.

Virtual presentation
Kalevi Mursula

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,, 2022.

Virtual presentation
Dorothee Rebscher, Senecio Schefer, Finnegan Reichertz, Yves Guglielmi, William Foxall, Inma Gutiérrez, and Edi Meier

The Mont Terri rock laboratory, located in the Swiss Jura Mountains, is dedicated to research on argillaceous rocks. Since its founding in 1996, the objective is the hydrogeological, geochemical, and geotechnical characterisation of Opalinus Clay in the context of nuclear waste repositories. More recently, the work has broadened to additional fields, covering potential uses of the deep geological subsurface such as geological storage of carbon dioxide and geothermal energy. With the excellent infrastructure, a comprehensive database, and the broad scientific and technological expertise, knowledge is enhanced e.g. through the advancement and comparison of approaches as well as the development and testing of novel investigation methods. These, as well as studies on feasibility and risk assessment, are of benefit also for underground laboratories in general and in situ explorations in different rock types worldwide. Due to the long-term commitment and the available gallery space of the research facility, elaborate as well as decade-long experiments can be implemented.

In order to detect, quantify, and understand short- and long-term deformations in the Mont Terri rock laboratory, quasi continuous time series are established employing various monitoring techniques. The latter complement each other in regard to their spatial dimensions, operational frequency optima, and their point or integral information. The approach combines

  • a 50 m long uniaxial hydrostatic levelling system (HLS, Type “PSI”, positioned along a gallery wall, measuring principle: electrical plate capacitors),
  • four mini-arrays of very-broad-band triaxial seismometers, installed in the rock laboratory (one under the HLS) as well as outside the rock laboratory at the surface,
  • and an array of high resolution, biaxial platform tiltmeters, with instruments situated close to the HLS and in various parts of the rock laboratory, integrated in other in situ experiments.

The observed signals and their analysis differ in space and time. They range from the detection of local nanoseismic as well as large tele seismic events, to the determination of earth tides, and to the identification of seasonal trends versus other long term geodetic movements. Besides the mutual comparison of the three deformation measurements, the time series provide valuable input for numerous scientific questions such as the stability of the rock laboratory as a whole or in its parts, the influence of excavation, ventilation, or fluid injection on rock matrix and faults. Long data series of ambient parameters, essential for interpretation of the deformation records, such as temperature, pressure, and humidity, are recorded by sensors integrated in the above listed instruments and are also of interest in further experiments performed by the Mont Terri Consortium.

How to cite: Rebscher, D., Schefer, S., Reichertz, F., Guglielmi, Y., Foxall, W., Gutiérrez, I., and Meier, E.: Long term deformation and seismic observations at the Mont Terri rock laboratory, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6814,, 2022.

Presentation form not yet defined
Valentin Kasburg, Alexander Breuer, Martin Bücker, and Nina Kukowski

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,, 2022.

Presentation form not yet defined
Nina Kukowski, Valentin Kasburg, Andreas Goepel, Cornelius Schwarze, Thomas Jahr, and Ronny Stolz

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,, 2022.

Virtual presentation
José M. Vaquero, María C. Gallego, Nieves Bravo-Paredes, Víctor M.S. Carrasco, and Irene Tovar

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.


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.

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,, 2022.

Presentation form not yet defined
Amos Winter, Davide Zanchettin, Malcolm McCulloch, Manuel Rigo, Clark Sherman, and Angelo Rubino

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,, 2022.

Virtual presentation
Mosisa Tujuba Wakjira, Nadav Peleg, and Peter Molnar

Climate information from in-situ observation networks can be used to significantly improve the accuracy of gridded climate datasets, even in data-scarce regions. We applied a bias correction and spatial disaggregation method on daily maximum and minimum ERA5-Land (ERA5L) 2-m air temperature dataset covering Ethiopia. Due to large gaps in the observed temperature data, the bias correction is based on the statistics rather than the complete time series. First, long-term daily, monthly and annual temperature statistics (mean and variance) were summarized for the time series obtained from 155 stations covering the period 1981-2010. Second, the temperature statistics were interpolated onto a 0.05° x 0.05° grid using an inverse non-Euclidean distance weighting approach. This method accounts for the effects of elevation, thus enabling downscaling of the temperature to a higher spatial resolution. Next, the ERA5L maximum and minimum temperature were bias-corrected using quantile mapping assuming a Gaussian distribution transfer function. The quantile mapping was performed at daily, monthly and annual time steps to reproduce the climatology, seasonality, and interannual variability of the data. The performance of the bias correction was evaluated using the leave-out-one cross-validation method. The cross-validation shows that the bias-corrected maximum (minimum) daily temperature has an improved mean absolute error value of 68% (52%) in comparison to the original ERA5L reanalysis air temperature bias. The bias-corrected dataset is therefore suggested as an alternative for the ERA5L and can be used in a wide range of applications in Ethiopia.

How to cite: Wakjira, M. T., Peleg, N., and Molnar, P.: Downscaling to high-resolution and correcting air temperature from the ERA5-Land over Ethiopia, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11916,, 2022.