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The continuously expanding toolbox of nonlinear time series analysis techniques has recently highlighted the importance of dynamical complexity to understand the behavior of the complex solar wind–magnetosphere–ionosphere–thermosphere coupling system and its components. Here, we apply new such approaches, mainly a series of entropy methods to the time series of the Earth's magnetic field measured by the Swarm constellation. We show successful applications of methods, originated from information theory, to quantitatively study complexity in the dynamical response of the topside ionosphere, at Swarm altitudes, focusing on the most intense magnetic storm of solar cycle 24, that is, the St. Patrick's Day storm, which occurred in March 2015. These entropy measures are utilized for the first time to analyze data from a low-Earth orbit (LEO) satellite mission flying in the topside ionosphere. These approaches may hold great potential for improved space weather nowcasts and forecasts. [ABSTRACT FROM AUTHOR]

Space radiation exposure from omnipresent Galactic Cosmic Rays (GCRs) in interplanetary space poses a serious carcinogenic risk to astronauts due to the-limited or absent-protective effect of the Earth's magnetosphere and, in particular, the terrestrial atmosphere. The radiation risk is directly influenced by the quality of the radiation, i.e., its pattern of energy deposition at the micron/DNA scale. For stochastic biological effects, radiation quality is described by the quality factor, [Formula: see text], which can be defined as a function of Linear Energy Transfer (LET) or the microdosimetric lineal energy ([Formula: see text]). In the present work, the average [Formula: see text] of GCR for different mission scenarios was calculated using a modified version of the microdosimetric Theory of Dual Radiation Action (TDRA). NASA's OLTARIS platform was utilized to generate the radiation environment behind different aluminum shielding (0-30 g/cm 2 ) for a typical mission scenario in low-earth orbit (LEO) and in deep space. The microdosimetric lineal energy spectra of ions ([Formula: see text]) in 1 μm liquid water spheres were calculated by a generalized analytical model which considers energy-loss fluctuations and δ-ray transport inside the irradiated medium. The present TDRA-based [Formula: see text]-values for the LEO and deep space missions were found to differ by up to 10% and 14% from the corresponding ICRP-based [Formula: see text]-values and up to 3% and 6% from NASA's [Formula: see text]-model. In addition, they were found to be in good agreement with the [Formula: see text]-values measured in the International Space Station (ISS) and by the Mars Science Laboratory (MSL) Radiation Assessment Detector (RAD) which represent, respectively, a LEO and deep space orbit., (© 2023. The Author(s).)

In order to advance our understanding of the dynamic interactions between coronal mass ejections (CMEs) and the magnetized solar wind, we investigate the impact of magnetic erosion on the well-known aerodynamic drag force acting on CMEs traveling faster than the ambient solar wind. In particular, we start by generating empirical relationships for the basic physical parameters of CMEs that conserve their mass and magnetic flux. Furthermore, we examine the impact of the virtual mass on the equation of motion by studying a variable-mass system. We next implement magnetic reconnection into CME propagation, which erodes part of the CME magnetic flux and outer-shell mass, on the drag acting on CMEs, and we determine its impact on their time and speed of arrival at 1 AU. Depending on the strength of the magnetic erosion, the leading edge of the magnetic structure can reach near-Earth space up to ≈ three hours later, compared to the non-eroded case. Therefore, magnetic erosion may have a significant impact on the propagation of fast CMEs and on predictions of their arrivals at 1 AU. Finally, the modeling indicates that eroded CMEs may experience a significant mass decrease. Since such a decrease is not observed in the corona, the initiation distance of erosion may lie beyond the field-of-view of coronagraphs (i.e. 30 R ⊙ )., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2023.)

Electrons in the outer Van Allen (radiation) belt occasionally reach relativistic energies, turning them into a potential hazard for spacecraft operating in geospace. Such electrons have secured the reputation of satellite killers and play a prominent role in space weather. The flux of these electrons can vary over time scales of years (related to the solar cycle) to minutes (related to sudden storm commencements). Electric fields and plasma waves are the main factors regulating the electron transport, acceleration and loss. Both the fields and the plasma waves are driven directly or indirectly by disturbances originating in the Sun, propagating through interplanetary space and impacting the Earth. This paper reviews our current understanding of the response of outer Van Allen belt electrons to solar eruptions and their interplanetary extensions, i.e. interplanetary coronal mass ejections and high-speed solar wind streams and the associated stream interaction regions. This article is part of the theme issue 'Solar eruptions and their space weather impact'.

The average summer temperatures as well as the frequency and intensity of hot days and heat waves are expected to increase due to climate change. Motivated by this consequence, we propose a methodology to evaluate the monthly heat wave hazard and risk and its spatial distribution within large cities. A simple urban climate model with assimilated satellite-derived land surface temperature images was used to generate a historic database of urban air temperature fields. Heat wave hazard was then estimated from the analysis of these hourly air temperatures distributed at a 1-km grid over Athens, Greece, by identifying the areas that are more likely to suffer higher temperatures in the case of a heat wave event. Innovation lies in the artificial intelligence fuzzy logic model that was used to classify the heat waves from mild to extreme by taking into consideration their duration, intensity and time of occurrence. The monthly hazard was subsequently estimated as the cumulative effect from the individual heat waves that occurred at each grid cell during a month. Finally, monthly heat wave risk maps were produced integrating geospatial information on the population vulnerability to heat waves calculated from socio-economic variables.