A new GEANT4 particle transport model -the Atmospheric Radiation Interaction Simulator (AtRIS, Banjac et al., 2018) -has been recently developed in order to model the interaction of radiation with planets. The upcoming instrumentational advancements in the exoplanetary science, in particular transit spectroscopy capabilities of missions like JWST and E-ELT, have motivated the development of a particle transport code with a focus on providing the necessary flexibility in planet specification (atmosphere and soil geometry and composition, tidal locking, oceans, clouds, etc.) for the modeling of radiation environment for exoplanets. Since there are no factors limiting the applicability of AtRIS to Mars and Venus, AtRIS' unique flexibility opens possibilities for new studies.Following the successful validation against Earth measurements (Banjac et al., 2018), this work applies AtRIS with a specific implementation of the Martian atmospheric and regolith structure to model the radiation environment at Mars. We benchmark these first modeling results based on different GEANT4 physics lists with the energetic particle spectra recently measured by the Radiation Assessment Detector (RAD) on the surface of Mars. The good agreement between AtRIS and the actual measurement provides one of the first and sound validations of AtRIS and the preferred physics list which could be recommended for predicting the radiation field of other conceivable (exo)planets with an atmospheric environment similar to Mars.

On July 25 2017 a multi-step Forbush decrease (FD) with the remarkable total amplitude of more than 15% was observed by MSL/RAD at Mars. We find that these particle signatures are related to very pronounced plasma and magnetic field signatures detected in situ by STEREO-A on July 24 2017, with a higher than average total magnetic field strength reaching more than 60 nT. In the observed time period STEREO-A was at a relatively small longitudinal separation (46 degrees) to Mars and both were located at the back side of the Sun as viewed from Earth. We analyse a number of multispacecraft and multi-instrument (both in situ and remote-sensing) observations, and employ modelling to understand these signatures. We find that the solar sources are two CMEs which erupted on July 23 2017 from the same source region on the back side of the Sun as viewed from Earth. Moreover, we find that the two CMEs interact non-uniformly, inhibiting the expansion of one of the CMEs in STEREO-A direction, whereas allowing it to expand more freely in the Mars direction. The interaction of the two CMEs with the ambient solar wind adds up to the complexity of the event, resulting in a long, sub-structured interplanetary disturbance at Mars, where different sub-structures correspond to different steps of the FD, adding-up to a globally large-amplitude FD.

The near-Earth cosmic ray flux has been monitored for more than 70 years by a network of ground-based neutron monitors (NMs). With the ever-increasing importance of quantifying the radiation risk and effects of cosmic rays for, e.g., air and space-travel, it is essential to continue operating the existing NM stations, while expanding this crucial network. In this paper, we discuss a smaller and cost-effective version of the traditional NM, the mini-NM. These monitors can be deployed with ease, even to extremely remote locations, where they operate in a semi-autonomous fashion. We believe that the mini-NM, therefore, offers the opportunity to increase the sensitivity and expand the coverage of the existing NM network, making this network more suitable to near-real-time monitoring for space weather applications. In this paper, we present the technical details of the mini-NM's design and operation, and present a summary of the initial tests and science results.

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Aims This paper presents a H2020 project aimed at developing the world’s most advanced space weather forecasting tool, combining the MagnetoHydroDynamic (MHD) solar wind and Coronal Mass Ejection (CME) evolution modelling with Solar Energetic Particle (SEP) transport and acceleration model(s). The EUHFORIA 2.0 project will address the geoeffectiveness of impacts and mitigation to avoid (part of the) damage, including that of extreme events, related to solar eruptions, solar wind streams, and SEPs, with particular emphasis on its application to forecast Geomagnetically Induced Currents (GICs) and radiation on geospace. Methods We will apply innovative methods and state-of-the-art numerical techniques to extend the recent heliospheric solar wind and CME propagation model EUHFORIA with two integrated key facilities that are crucial for improving its predictive power and reliability, namely 1) data-driven flux-rope CME models, and 2) physics-based, self-consistent SEP models for the acceleration and transport of particles along and across the magnetic field lines. This involves the novel coupling of advanced space weather models. In addition, after validating the upgraded EUHFORIA/SEP model, it will be coupled to existing models for GICs and atmospheric radiation transport models. This will result in a reliable prediction tool for radiation hazards from SEP events, affecting astronauts, passengers and crew in high-flying aircraft, and the impact of space weather events on power grid infrastructure, telecommunication, and navigation satellites. Finally, this innovative tool will be integrated into both the Virtual Space Weather Modeling Centre (VSWMC, ESA) and the space weather forecasting procedures at the ESA SSCC in Uccle (Belgium), so that it will be available to the space weather community and effectively used for improved predictions and forecasts of the evolution of CME magnetic structures and their impact on Earth. Results The results of the first six months of the EU H2020 project are presented here. These concern alternative coronal models, the application of adaptive mesh refinement techniques in the heliospheric part of EUHFORIA, alternative flux-rope CME models, evaluation of data-assimilation based on Karman filtering for the solar wind modelling, and a feasibility study of the integration of SEP models.