How much of the solar irradiance variations is caused by the magnetic field at the solar surface?

The contribution to total solar irradiance variations by the magnetic field at the solar surface is estimated. Detailed models of the irradiance changes on the basis of magnetograms show that magnetic features at the solar surface account for over 90% of the irradiance variations on a solar rotation time scale and at least 70% on a solar cycle time scale. If the correction to the VIRGO record proposed by Fröhlich & Finsterle (2001) is accepted, then magnetic features at the solar surface are responsible for over 90% of the solar cycle irradiance variations as well.     

Chromosome aberrations as biomarkers of radiation exposure: modelling basic mechanisms.

The space radiation environment is a mixed field consisting of different particles having different energies, including high charge and energy (HZE) ions. Conventional measurements of absorbed doses may not be sufficient to completely characterise the radiation field and perform reliable estimates of health risks. Biological dosimetry, based on the observation of specific radiation-induced endpoints (typically chromosome aberrations), can be a helpful approach in case of monitored exposure to space radiation or other mixed fields, as well as in case of accidental exposure. Furthermore, various ratios of aberrations (e.g. dicentric chromosomes to centric rings and complex exchanges to simple exchanges) have been suggested as possible fingerprints of radiation quality, although all of them have been subjected to some criticisms. In this context a mechanistic model and a Monte Carlo code for the simulation of chromosome aberration induction were developed. The model, able to provide dose-responses for different aberrations (e.g. dicentrics, rings, fragments, translocations, insertions and other complex exchanges), was further developed to assess the dependence of various ratios of aberrations on radiation quality. The predictions of the model were compared with available data, whose experimental conditions were faithfully reproduced. Particular attention was devoted to the scoring criteria adopted in different laboratories and to possible biases introduced by interphase death and mitotic delay. This latter aspect was investigated by taking into account both metaphase data and data obtained with Premature Chromosome Condensation (PCC).     

Fast Probabilistic Particle Identification algorithm using silicon strip detectors

Active detectors used as radiation monitors in space are not usually able to perform Particle Identification (PID). Common techniques need energy loss spectra with high statistics to estimate ion abundances. The ALTEA-space detector system is a set of silicon strip particle telescopes monitoring the radiation environment on board the International Space Station since July 2006 with real-time telemetry capabilities. Its large geometrical factor due to the concurrent use of six detectors permits the acquisition of good energy loss spectra even in a short period of observation. In this paper we present a novel Fast Probabilistic Particle Identification (FPPI) algorithm developed for the ALTEA data analysis in order to perform nuclear identification with low statistics and, with some limitations, also in real time.     

Correction to: Determining the Relative Cratering Ages of Regions of Psyche’s Surface

Space Science Reviews - Analysis of Homestake, Gallex and GNO measurements reveals evidence of variability of presumed solar-neutrino-flux measurements. Analysis of Super-Kamiokande neutrino...     

Determination of characteristic frequencies of elastic oscillations of the <Emphasis Type=Italic>International Space Station</Emphasis> construction

The results of investigating free oscillations of the International Space Station construction appearing during spacecraft docking and undocking are described. The study is carried out using the measurement data of the low-frequency MAMS accelerometer. Several intervals of measurements performed in 2005 and 2006 were chosen to be studied. For chosen intervals, only the data intervals corresponding to the process of free attenuation of the oscillations construction elements were analyzed. Characteristic frequencies of elastic oscillations of the station construction and attenuation coefficients corresponding to them are found. The comparative analysis of the results obtained for various docking ports (nodes) is carried out. The described study is performed as a part of the technical experiment “The ISS Environment” carried out onboard the station in accordance with the Russian program of scientific and engineering experiments.     

Doppler characteristics of HF spread Doppler clutter recorded at Alice Springs,Australia

Mean night-time peak power, Doppler shift and Doppler width of spread Doppler clutter (SDC) received by a high frequency backscatter radar located at Alice Springs, Australia from 2000 to 2018 is presented as a function of azimuth, sunspot number, time of year and frequency. The sampled region covers 90 degrees from West to North and includes the northern and southern equatorial anomalies.SDC peak power diminished across all azimuths during the winter solstice from around May to August (local winter) coinciding with the global decrease in F layer density due to the annual non-seasonal F2 anomaly but was generally constant during the equinoxes. In contrast, SDC Doppler width and inbound Doppler shift both increased during the equinoxes and exhibited azimuthal dependence related to the eastward equatorial plasma drift.SDC peak power increased with increasing sunspot number with frequency dependence during winter but not summer. Inbound Doppler shift and Doppler width increased with increasing sunspot number during equinox but not solstice with a strong dependence on azimuth and a weak dependence on frequency.     

Robust Kalman filter design for predictive wind shear detection

Severe low-altitude wind shear is a threat to aviation safety. Newly developed airborne sensors measure the radial component of wind along a line directly in front of an aircraft. The authors use optimal estimation theory to define a detection algorithm to warn of hazardous wind shear from these sensors. To achieve robustness, a wind shear detection algorithm must distinguish threatening wind shear from less hazardous gustiness, despite variations in wind shear structure. Statistical analysis methods to refine wind shear detection algorithm robustness are presented. Computational methods predict the ability to warn of severe wind shear and avoid false warning. Comparative capability of the detection algorithm as a function of its design parameters is determined, identifying designs that provide robust detection of severe wind shear