Signs of a new geomagnetic jerk between 2019 and 2020 from Swarm and observatory data

Following the observed pattern of a new geomagnetic jerk every 3–4 years, certain predictions suggested that a new event should occur around 2020 after the one observed around 2017.5. In this work, we explore this scenario by analysing the secular variation of the East geomagnetic field component in both ground and satellite geomagnetic data. At ground, we use the available data from 2015 to 2021 in 10 observatories worldwide distributed. This analysis shows the occurrence of the mentioned jerk in mid-2017 at observatories located in the Pacific region, but also reveals a new jerk between mid-2019 and early 2020 with a clear global character. Swarm satellite data also corroborate these findings by means of the secular variation estimated using virtual observatories at 440 km altitude. In addition, a general view using the most recent CHAOS geomagnetic model confirms the global character of the 2020-jerk with V-shaped secular variation changes in meridional sectors covering the Eastern Pacific, America, Asia and the Indian Ocean; and Λ-shapes in Europe, Africa and Western Pacific. The radial geomagnetic field at the core–mantle boundary is investigated as the origin of the new jerk. Results show that the global-average secular acceleration of the radial field exhibits a new pulse at mid-2018, establishing the starting epoch of the 2020-jerk.

Geomagnetic Virtual Observatories: Global monitoring of geomagnetic secular variation with Swarm data

<p>The ESA Swarm DISC Geomagnetic Virtual Observatories (GVO) project aims to apply the virtual observatory concept to Swarm magnetic field measurements. The Virtual Observatory concept is a data processing method which mimics the behavior of magnetic monthly-mean time-series measured at ground observatories but at fixed locations on a uniform global grid at satellite altitude instead. Here we present several new GVO data products consisting of the average time-series of vector magnetic field values, regularly distributed in space and time which are suitable for monitoring the geomagnetic field. The GVO products consist of an equal-area grid with separation spacing of 300 km and cadence of either 1 month or 4 months. Various levels of processing are applied to remove the effects of altitude change and satellite local-time differences to produce a consistent time series. It is known that monthly time-series can have strong local-time artifacts which are removed with four-monthly averages, though with a loss of temporal resolution. The GVO products are designed to make Swarm magnetic data more accessible to researchers studying the physics of the core dynamo process, and related phenomenon such are secular variation, geomagnetic jerks and rapid core dynamics. In addition, the GVO data products also provide valuable information for investigating magnetospheric and ionospheric magnetic signals on timescales of months and longer.</p>

Denoising Swarm Geomagnetic Virtual Observatories using principal component analysis

<p>Geomagnetic Virtual Observatories (GVOs) use satellite measurements to provide estimates of the mean internally-generated magnetic field (MF) over a specified period (usually one or four months) at a fixed location in space, mimicking the mean values obtained at ground-based observatories (GOs). These permit secular variation (SV) estimates anywhere on the globe, thereby mitigating the effects of uneven GO coverage. Current GVO estimates suffer from two key contamination sources: first, local time sampling biases due to satellite orbital dynamics, and second, MFs generated in regions external to the Earth such as the magnetosphere and ionosphere. Current methods to alleviate this contamination have drawbacks:Averaging over four months removes the local time sampling bias at the cost of reduced temporal resolution</p><ol><li>Stringent data selection criteria such as night-time, quiet-time only data greatly reduce, but do not entirely remove, external MF contamination and result in a small subset (<5%) of the available data being used</li> <li>Removing model predictions for external MFs from the measurements also reduces noise, however such parameterisations cannot fully describe these physical systems and some of their signal remains in the data.</li> </ol><p>Here we present an alternative approach to denoising GVOs that uses principal component analysis (PCA). This method retains monthly resolution, uses all available vector satellite data and removes contamination from orbital effects and external MFs. We present an application of PCA, implemented in an open-source Python package called MagPySV, to new GVOs calculated as part of a Swarm DISC project.  The denoised data will be incorporated into a new GVO data set that will be available to the geomagnetism community as an official Swarm product.  </p>

Big Data in Astronomy: Surveys, Catalogs, Databases and Archives

We present the modern situation in astronomy, where Big Data coming from the Universe put new tasks for catalogizing, storage, archiving, analysis and usage of the scientific information. The two major characteristics of modern astronomy are multiwavelength (MW) studies (from γ-ray to radio, as well as multi-messenger studies, using also neutrinos, gravitational waves, etc.) and Big Data (including data acquisition, storage and analysis). Present astronomical databases and archives contain billions of objects observed in various wavelengths, both Galactic and extragalactic, and the vast amount of data on them allows new studies and discoveries. Astronomers deal with big numbers. Surveys are the main source for discovery of astronomical objects and accumulation of observational data for further analysis, interpretation, and achieving scientific results. We review the main characteristics of astronomical surveys, we compare photographic and digital eras of astronomical studies (including the development of wide-field observations), we give the present state of MW surveys, and we discuss the Big Data in astronomy and related topics of Virtual Observatories and Computational Astrophysics. The review includes many numbers and data that can be compared to have a possibly overall understanding on the studied Universe, cosmic numbers and their relationship to modern computational possibilities.

Solar survey at Pic du Midi: Calibrated data and improved images

Context. We carry out a solar survey with images of the photosphere, prominences, and corona at Pic du Midi observatory. This survey, named CLIMSO (for CLIchés Multiples du SOleil), is in the following spectral lines: Fe XIII corona (1.075 μm), Hα (656.3 nm), and He I (1.083 μm) prominences, and Hα and Ca II (393.4 nm) photosphere. All frames cover 1.3 times the diameter of the Sun with an angular resolution approaching one arcsecond. The frame rate is one per minute per channel (weather permitting) for the prominences and chromosphere, and one per hour for the Fe XIII corona. This survey started in 2007 for the disk and prominences and in 2015 for the corona. We have almost completed one solar cycle and hope to cover several more, keeping the same wavelengths or adding others. Aims. We seek to make the CLIMSO images easier to use and more profitable for the scientific community. Methods. At the beginning of the survey, the images that we sent to the CLIMSO database were not calibrated. We have implemented a photometric calibration for the present and future images, in order to provide “science-ready” data. The old images have been calibrated. We have also improved the contrast capabilities of our coronagraphs, which now provide images of the Fe XIII corona, in addition to previous spectral channels. We also implemented an autoguiding system based on a diffractive Fresnel array for precise positioning of the Sun behind coronagraphic masks. Results. The data, including the images and films, are publicly available and downloadable through virtual observatories and dedicated websites (use “CLIMSO” and “IRAP” keywords to find them). For the Hα and Ca II channels we calibrate the data into physical units, independent of atmospheric or instrumental conditions; we provide solar maps of spectral radiances in W m−2 sr−1 nm−1. The instrumental improvements and calibration process are presented in this paper.

Meteor Databases in Astronomy

There are specific problems of databases in meteor science such as making meteor databases into the modern research tools. Special institutes and virtual observatories exist for the meteor data storage where the data is online and in open access. However, there are also numerous databases without the open access, such as for example, three radar databases: Kharkiv database with 250,000 meteor orbits in Ukraine, New Zealand database with 500,000 meteor orbits, and Canadian database with more than 3 million meteor orbits. One of the reasons the open access is absent for these databases could be the complexity in the copyright compliance. In the framework of the creation of the modern effective research tool in the meteor science, we discuss here the case of the Kharkiv meteor database.