A Statistical Analysis of Plasma Bubbles Observed by Swarm Constellation during Different Types of Geomagnetic Storms

Based on the observations of Ionospheric Bubble Index (IBI) data from the Swarm mission, the characteristics of plasma bubbles are investigated during different types of geomagnetic storms recorded from 2014 to 2020. The geometrical constellation of the Swarm mission enabled us to investigate the altitudinal profile of the IBIs during different activity levels in a statistical mean. Results show that the majority of IBIs associated with moderate storms are observed at low altitudes and the probability of observing IBIs at high altitudes (Swarm-B) increases with the increase in storm level. This is confirmed by observing the F2 layer peak height (hmF2) during super storm events at larger altitudes using COSMIC data. The maximum number of IBIs is recorded within the South Atlantic Anomaly (SAA) region with a long duration time and tends to increase only during dusk time. Both the large duration time and number of IBIs over the South Atlantic Anomaly (SAA) suggest that the gradient in the electron density and the depression in the magnetic field are the main factors controlling IBI events. Also, the IBIs at high altitudes are larger at sunset and at low altitudes pre-midnight. In addition, the occurrence of IBIs is always larger in the northern hemisphere than in the southern hemisphere irrespective of the type of storm, as well as during the summer months. Moreover, there is no correlation between the duration time of IBIs and both the altitudinal observation of the IBIs and the storm type. Seasonal occurrence of IBIs is larger during equinoxes and vice versa during solstices irrespective of both the type of storm and the altitude of the satellite. The large number of IBIs during equinoxes agrees with the previous studies, which expect that the large electron density is a developer of steeper . Large occurrences of super storm IBIs observed within the pre-midnight during summer and at sunset during equinoxes are a novel observation that needs further investigation. Also, the majority of IBIs are observed a few hours after geomagnetic substorms, which reflects the role of the Disturbance Dynamo Electric Field (DDEF) as a main driver of IBIs.

Quasi real-time monitoring of the ionosphere plasma irregularities by the records of the Swarm mission

<p>The magnetic and plasma observations of Low-Earth orbit (LEO) space missions represent not only the dynamical state of the ionosphere but also the physical variations of its electromagnetically connected surroundings, i.e. of the plasmasphere and magnetosphere, as well as of their driver, the solar wind. The monitoring of the ionosphere plasma variables is therefore a big asset for the study of our space environment in broad spatial region. Within the framework of the EPHEMERIS project supported by ESA, we aim at investigating two ionosphere phenomena that exhibit close relationship to global physical processes and space weather activity. We use the magnetic and plasma records of the LEO Swarm mission. First, we investigate the temporal and spatial occurrences of the mid-latitude ionosphere trough (MIT), a typical feature of the topside sub-auroral ionosphere appearing as a few degree wide depleted zone, where electron density (Ne) drops by orders of magnitude. It is shown that the locations of MITs are excellent proxies for the detection of the plasmapause position as well as of the equatorward edge of the auroral oval. Secondly, we monitor the irregular fluctuations of the magnetic field along the Swarm orbits via their intermittent behaviour. A new index called intermittency index (IMI) is introduced for the quantitative exemplification of the spatial and temporal distribution of irregular variations at the Swarm spacecraft altitudes. The paper focuses on the introduction of the methodology of IMI time-series compilation. Since IMIs are deduced via a statistical approach, we use the 50 Hz sampling frequency magnetic field records of the mission. We show that most frequently, the ionosphere magnetic field irregularities occur at low-latitudes, about the dip equator and at high latitudes, around the auroral region. It is conjectured that the equatorial events are the results of equatorial spread F (ESF) or equatorial plasma bubble (EPB) phenomena, while the auroral irregularities are related to field-aligned currents (FAC). The ionosphere plasma irregularities may result in the distortion or loss of GPS signals. Therefore our analysis also concerns the investigation of the correlation between observed intermittent events in the ionosphere and contemporary GPS signal loss events and scintillations detected both by on-board Swarm GPS receivers and ground GNSS stations.</p>

The impact of severe storms on forecasting the Ionosphere-Thermosphere system through the assimilation of SWARM-derived neutral mass density into physics-based models

<p>The response of the Ionosphere - Thermosphere (IT) system to severe storm conditions is of great importance to fully understand its coupling mechanisms. The challenge to represent the governing processes of the upper atmosphere depends, to a large extent, on an accurate representation of the true state of the IT system, that we obtain by assimilating relevant measurements into physics-based models. Thermospheric Mass Density (TMD) is the summation of total neutral mass within the atmosphere that is derived from accelerometer measurements of satellite missions such as CHAMP, GOCE, GRACE(-FO) and Swarm. TMD estimates can be assimilated into physics-based models to modify the state of the processes within the IT system. Previous studies have shown that this modification can potentially improve the simulations and predictions of the ionospheric electron density. These differences could also be interpreted as an indicator of the ionosphere-thermosphere interaction. The research presented here, aims to quantify the impact of data satellite based TMD assimilation on numerical model results.</p><p>Subject of this study is the Coupled Thermosphere-Ionosphere-Plasmasphere electrodynamics (CTIPe) physics-based model in combination with the recently developed Thermosphere-Ionosphere Data Assimilation (TIDA) scheme. TMD estimates from the ESA’s Swarm mission are assimilated in CTIPe-TIDA during the 16 to the 20 of March 2015. This period was characterized by a strong geomagnetic storm that triggered significant changes in the IT system, the so-called St. Patrick day storm 2015. To assess the changes in the IT system during storm conditions due to data assimilation, the model results from assimilating SWARM mass density normalized to the altitude of 400 km are compared to independent thermospheric estimates like GRACE-TMDS. In order to evaluate the impact of the data assimilation on the ionosphere, the corresponding output of electron density is compared to high-quality electron density estimates derived from data-driven model of the DGFI-TUM.</p>

Swarm Mission: instruments performance, data availability, quality and future evolutions

<p>The European Space Agency (ESA) Swarm mission, launched on November 2013, continue to provide very accurate measurements of the strength, direction and variation of the Earth’s magnetic field. These data together with precise navigation, accelerometer, electric field, plasma density and temperature measurements, are crucial for a better understanding of the Earth’s interior and its environment. This paper will provide a status update of the Swarm Instrument performance after seven years of operations. Moreover, we will provide full details on the new Swarm Level 1b product baseline of Magnet and Plasma data which will be generated and distributed soon to the whole Swarm Community.  Please note that the main evolutions to be introduced in the Swarm L1B Algorithm are: i) computation of the Sun induced magnetic disturbance (dB_Sun) on the Absolute Scalar Magnetometer (ASM) and Vector Field Magnetometer (VFM) data; ii) computation of systematic offset between Langmuir Probes (LP) measurements ad ground observations derived from Incoherent Scatter Radars (IRS) located at middle, low, and equatorial latitudes. These and further improvements are planned to be included in the upcoming versions of the Swarm Level 1b products, aiming at achieving the best data quality for scientific applications.</p>

Indices of geomagnetic activity derived from space-born magnetic data from the Swarm mission

<p>Ground based indices, such as the Dst and AE, have been used for decades to describe the interplay of the terrestrial magnetosphere with the solar wind and provide quantifiable indications of the state of geomagnetic activity in general. These indices have been traditionally derived from ground based observations from magnetometer stations all around the Earth. In the last 7 years though, the highly successful satellite mission Swarm has provided the scientific community with an abundance of high quality magnetic measurements at Low Earth Orbit, which can be used to produce the space-based counterparts of these indices, such the Swarm-Dst and Swarm-AE Indices. In this work, we present the first results from this endeavour, with comparisons against traditionally used parameters, and postulate on the possible usefulness of these Swarm based products for space weather monitoring and forecasting.</p>

UAV Swarms Behavior Modeling Using Tracking Bigraphical Reactive Systems

Recently, there has been a fairly rapid increase in interest in the use of UAV swarms both in civilian and military operations. This is mainly due to relatively low cost, greater flexibility, and increasing efficiency of swarms themselves. However, in order to efficiently operate a swarm of UAVs, it is necessary to address the various autonomous behaviors of its constituent elements, to achieve cooperation and suitability to complex scenarios. In order to do so, a novel method for modeling UAV swarm missions and determining behavior for the swarm elements was developed. The proposed method is based on bigraphs with tracking for modeling different tasks and agents activities related to the UAV swarm mission. The key finding of the study is the algorithm for determining all possible behavior policies for swarm elements achieving the objective of the mission within certain assumptions. The design method is scalable, highly automated, and problem-agnostic, which allows to incorporate it in solving different kinds of swarm tasks. Additionally, it separates the mission modeling stage from behavior determining thus allowing new algorithms to be used in the future. Two simulation case studies are presented to demonstrate how the design process deals with typical aspects of a UAV swarm mission.

Comparative Study of the Energetic Electrons Registered Together with the Broad Band Emissions in Different Regions of the Ionosphere

ELF/VLF waves have been registered in the outer polar cusps simultaneously with high energy electrons fluxes by the satellites Magion 4 (subsatellite to Interball 1), Polar and CLUSTER. Further, we discuss similar observations in the different regions of the ionosphere, where DEMETER registered energetic electrons. The DEMETER satellite operating on the nearly polar orbit at the altitude 650 km crossed different regions in the ionosphere. Registrations of ELF/VLF/HF waves together with the energetic electrons in the polar cusp, in the ionospheric trough and over thunderstorm areas are presented in this paper. The three satellites of ESA’s Swarm mission provide additional information on the ELF waves in the mentioned areas together with electron density and temperature. A brief discussion of the generation of these emissions by the so-called “fan instability” (FI) and beam instability is presented.

Marine Robots for Underwater Surveillance

Purpose of Review The paper reviews the role of marine robots, in particular unmanned vehicles, in underwater surveillance, i.e. the control and monitoring of an area of competence aimed at identifying potential threats in support of homeland defence, antiterrorism, force protection and Explosive Ordnance Disposal (EOD). Recent Findings The paper explores separately robotic missions for identification and classification of threats lying on the seabed (e.g. EOD) and anti-intrusion robotic systems. The current main scientific challenge is identified in terms of enhancing autonomy and team/swarm mission capabilities by improving interoperability among robotic vehicles and providing communication networking capabilities, a non-trivial task, giving the severe limitations in bandwidth and latency of acoustic underwater messaging. Summary The work is intended to be a critical guide to the recent prolific bibliography on the topic, providing pointers to the main recent advancements in the field, and to give also a set of references in terms of mission and stakeholders’ requirements (port authorities, coastal guards, navies).

Improving Motion Safety and Efficiency of Intelligent Autonomous Swarm of Drones

Interest is growing in the use of autonomous swarms of drones in various mission-physical applications such as surveillance, intelligent monitoring, and rescue operations. Swarm systems should fulfill safety and efficiency constraints in order to guarantee dependable operations. To maximize motion safety, we should design the swarm system in such a way that drones do not collide with each other and/or other objects in the operating environment. On other hand, to ensure that the drones have sufficient resources to complete the required task reliably, we should also achieve efficiency while implementing the mission, by minimizing the travelling distance of the drones. In this paper, we propose a novel integrated approach that maximizes motion safety and efficiency while planning and controlling the operation of the swarm of drones. To achieve this goal, we propose a novel parallel evolutionary-based swarm mission planning algorithm. The evolutionary computing allows us to plan and optimize the routes of the drones at the run-time to maximize safety while minimizing travelling distance as the efficiency objective. In order to fulfill the defined constraints efficiently, our solution promotes a holistic approach that considers the whole design process from the definition of formal requirements through the software development. The results of benchmarking demonstrate that our approach improves the route efficiency by up to 10% route efficiency without any crashes in controlling swarms compared to state-of-the-art solutions.