Magnetic holes (MHs) are pressure-balanced structures characterized by distinct decreases in the interplanetary magnetic field (IMF) strength in otherwise unperturbed solar wind. In this paper we present an analysis of MHs upstream of the Martian bow shock based on three months of observations by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft. Plasma properties within and around these structures as well as their shape characteristics are examined. We find an occurrence rate of around 2.1 events per day. About 48 percent of all events are of linear type with magnetic field rotation across the hole less than 10 degrees. We observe linear magnetic holes both as isolated events and as part of a train of magnetic holes. The proton temperature anisotropy inside MHs increases while alpha particles remain mostly isotropic. The average electron temperature inside MHs modestly increases with increasing hole depth. The duration of linear holes at 1.5 AU shows an increase compared to durations at smaller heliocentric distances, but the structures remain asymmetrical and ellipsoid. A case study of MHs accompanied by a population of heavy pickup ions is also discussed.

In this study, we try to explore the feasibility on whether or not the magnetospheric processes under northward Interplanetary Magnetic Field (IMF) conditions can be diagnosed using two different auroral phenomena; transpolar arc (TPA) and omega-band aurora. Both TPA and omega-band aurora can occur during the northward IMF intervals, and their appearances are closely related with the nightside magnetospheric processes. TPA can be formed and grown by the field-aligned currents induced by the plasma flow shear or the plasma vortex structures between the fast plasma flows generated by magnetotail magnetic reconnection and slower background magnetospheric flows, and the convection of the reconnection-formed closed magnetic fluxes, which cause in the nightside plasma sheet. On the other hand, the omega-band aurora can be attributed to the Kelvin-Helmholtz instabilities triggered by the flow shear between the plasma flows of the nightside magnetospheric boundary layer such as low-latitude boundary layer (LLBL) and background magnetospheric (plasma sheet) flows. If both auroral phenomena can simultaneously be observed, we might remotely investigate (diagnose) how the plasma and its energy are transported in the nightside magnetosphere and at the magnetospheric boundary region under northward IMF conditions. We will discuss the feasibility of this magnetospheric diagnosis, giving the observational example(s) of simultaneous observations of two different auroral phenomena, that is, TPA and omega-band aurora, and in-situ magnetospheric observation(s). Keyword: 1. Transpolar arc and omega band aurora 2. Solar wind-magnetotail-ionosphere coupling 3. Magnetospheric diagnosis 4. Magnetospheric dynamics under northward IMF conditions

Kepler-411 is a K2V-type star with an average rotation period of 10.52 days, radius of 0.79 Rsun and mass of 0.83 Msun. This active star has at least four planets, three of them eclipse the star, the three larger planets are mini Neptunes with radii of 2.2, 3.47 and 3.46 Earth radii, and periods of 3.0, 7.8 and 58.0 days, respectively. This star was observed by the Kepler satellite for about 600 days showing a total number of 195 transit for planet Kepler-411 b, 76 transits Kepler-411c and 10 transits for planet Kepler-411d. When a planet transits its host star, it may occult a spot causing a detectable signal in the light curve. In this work we apply the model described in Silva (2003), to characterize the starspots, which resulted in the detection of a total of 45 spots in Kepler-411b, 143 spots in Kepler-411c transits and 10 spots in Kepler-411d transits. Analysis of the spots detected on the different transit latitudes of these planets yields a differential shear of 0.050 rd/d or a relative differential rotation of 8.3%, assuming a solar like rotation profile. Also, a total of 66 flares and superflares were detected on the light curve. Here, we discuss the relationship between the size and temperature of the starspots with statistical data on flares and superflares.

The UCLA Planetarium hosts star shows and lectures on various astronomy topics, educating UCLA and the broader Los Angeles community about science and the wonders of the night sky. It serves over 4000 people per year, as UCLA Astronomy’s largest outreach effort. We host private shows for visiting school groups (30% of our attendees), shows for UCLA astronomy courses (20%), and weekly public shows for the community at large (50%). Our planetarium and its events are run exclusively by graduate students, who also maintain its historic projectors and dome. In the near future, we plan to improve and expand our outreach efforts in two specific ways. Our outreach efforts are free for educational groups, but we currently do not provide travel support for visiting schools. We plan to actively reach out to school groups from underserved communities and hope to raise funds to cover these schools’ field trip and travel expenses. We also plan to improve our science communication effectiveness, with strategies for improving volunteer recruitment, training volunteers on effective public speaking skills, and improving the quality of our existing repository of presentations. Of course, these in person events are on hold due to the ongoing pandemic; in the meantime, we are developing ways to serve our audience virtually. We recently hosted our first “virtual” planetarium show on YouTube Live, with over 1,700 viewers on the livestream and over 7,300 total viewers. We welcome any suggestions or ideas to help us improve our planetarium outreach efforts!

Predicting geomagnetic conditions based on in-situ solar wind observations allows us to evade disasters caused by large electromagnetic disturbances originating from the Sun to save lives and protect economic activity. In this study, we aimed to examine the relationship between the Kp index, representing global magnetospheric activity level, and solar wind conditions using an interpretable neural network known as potential learning (PL). Data analyses based on neural networks are difficult to interpret; however, PL learns by focusing on the “potentiality of input neurons” and can identify which inputs are significantly utilized by the network. Using the full advantage of PL, we extracted the influential solar wind parameters that disturb the magnetosphere under southward Interplanetary magnetic field (IMF) conditions. The input parameters of PL were the three components of the IMF (Bx, By, -Bz(Bs)), solar wind flow speed (Vx), and proton number density (Np) in geocentric solar ecliptic (GSE) coordinates obtained from the OMNI solar wind database between 1998 and 2019. Furthermore, we classified these input parameters into two groups (targets), depending on the Kp level: Kp = 6- to 9 (positive target) and Kp = 0 to 1+ (negative target). Negative target samples were randomly selected to ensure that numbers of positive and negative targets were equal. The PL results revealed that solar wind flow speed is an influential parameter for increasing Kp under southward IMF conditions, which was in good agreement with previous reports on the statistical relationship between the Kp index and solar wind velocity, and the Kp formulation based on the IMF and solar wind plasma parameters. Based on this new neural network, we aim to construct a more correct and parameter-dependent space weather forecasting model.

Science is fueled by data. Throughout history, scientists have operated sensors-from astronomical observatories to particle accelerators-that accumulate observations for analysis or to evaluate a hypothesis. However, as available technologies have increased both the volume of data and the efficiency of data storage and transmission, a new model of data access has emerged. The concept of a data buy is where an entity purchases access to a set of data or a data stream, instead of operating the sensors themselves. But why might a data consumer, whether a researcher or an end-user, prefer this kind of data access over the more traditional methods of running a network themselves? The simple answer, in some cases, is efficiency and, possibly, cost. Space weather forecasting and analysis has a growing private sector, and the extension to data gathering can be considered as a natural next step in the maturation of the field and the growing public-private partnerships. Operational applications require consistent, clean, and (in some cases) real-time data access that can be hard to support through the existing model of sensor deployment. Even in scientific applications, where access to raw information can be critical to discovery, there are benefits to the data buy model. Consistent access to a trusted data set allows more time to be spent on the scientific analysis, instead of maintaining machines that require consistent development, maintenance, and monitoring. The outsourcing of data infrastructure and pipelines can be particularly beneficial when the sensors are in distributed networks, spread over wide areas, and when there is a need to provide local data in observational gaps in existing networks. In the ideal case, a data buy can supplement the traditional observational networks in a beneficial and symbiotic way. It is important to note that data buys should not replace traditional observational networks, nor compete for funding with future observatories and infrastructure that the scientific community has deemed necessary (for example, through decadal survey processes).

This article has been moved to CERN platform >> 

Understanding the dynamical behavior of plasma and energetic particles in Earth’s inner magnetosphere requires carefully designed and calibrated instrumentation. The Van Allen Probes Mission included two instruments capable of measuring the proton distribution function in-situ. The Energetic Particle Composition and Thermal Plasma Suite (ECT) – Helium Oxygen, Proton, and Electron (HOPE) spectrometer (Spence et al., 2013; Funsten et al., 2013) used a top-hat detector designed to measure protons from the SC potential through 50 KeV in logarithmic energy steps. The Radiation Belt Storm Probes Ion Composition Detector (RBSPICE) instrument (Mitchell, 2013) used a time of flight and SSD detector design to measure protons from approximately 7 KeV through 650 KeV in logarithmic energy steps. Using the overlap of energy channels between the two instruments, the two instrument teams have worked diligently during the final Phase F of the mission to calibrate the observations so that a continuous distribution function can be resolved on nearly a spin-by-spin basis. During the life of these two instruments calibration changes have been required both on-board the spacecraft as well as within the final production datasets. Manweiler (2018) provided an early report on the intercalibration factors between HOPE and RBSPICE with a nominal factor of two difference between the proton data sets in the energy range between 7 and 50 KeV. With the final production of each of these data sets occurring in Fall 2021, both teams have been worked together to provide for an understanding of the required intercalibration factors to be used so that a full distribution function is available on a spin-by-spin basis. In this poster we report on the final efforts to provide this calibrated set of data products between the two instruments. Details of the intercalibration calculations are presented as well as year by year L by MLT maps of the factors required to match both datasets. Finally, we report on a supplementary data set that is to be made available which contains the spin-by-spin factors required to match the ECT/HOPE and RBSPICE/TOFxPH proton datasets. Funsten, H.O., et al. Space Sci Rev 179, 2013 Manweiler, J. W., et al., 2018 GEM Summer Workshop. Mitchell, D.G., et al., Space Sci. Rev., 179, 2013 Spence, H.E., et al. Space Sci Rev 179, 2013

Spacecraft equipped with magnetometers provide useful magnetic field data for a variety of applications such as monitoring the Earth’s magnetic field. However, spacecraft electrical systems generate magnetic noise that interfere with geomagnetic field data captured by magnetometers. Traditional solutions to this problem utilize mechanical booms to extend magnetometers away from noise sources. This solution can increase design complexity, cost, and introduce boom deployment risk. If a spacecraft is equipped with multiple magnetometers, signal processing algorithms can be used to compare magnetometer measurements and remove stray magnetic noise signals. We propose the use of density-based cluster analysis to identify spacecraft noise signals and compressive sensing to separate spacecraft noise from geomagnetic field data. This method assumes no prior knowledge of the number, location, or amplitude of noise signals, but assumes that they are independent and have minimal overlapping spectral properties. We demonstrate the validity of this algorithm by separating high latitude magnetic perturbations recorded by SWARM from noise signals in simulation and in a laboratory experiment using a mock CubeSat apparatus. In the case of more noise sources than magnetometers, this problem is an instance of Underdetermined Blind Source Separation (UBSS). This work presents a UBSS signal processing algorithm to remove spacecraft noise and eliminate the need for a mechanical boom.

A broad statistical study addresses for the first time an evolution of ultra-low frequency (ULF) waves/fluctuations in the terrestrial foreshock around the Moon generated through the interaction between the back-streaming particles reflected from the bow shock and the incoming solar wind. They propagate sunward but are convected by the solar wind flow back toward the bow shock and their amplitudes grow. However, our study shows that waves could be growing as well as decaying towards the bow shock under the quasi-radial interplanetary magnetic field. We demonstrate that the statistically determined growth rate is positive and larger for compressive variations of the density and magnetic field strength than for its components. We show that even if a possible influence of the Moon and its wake is excluded, the growth rate is decreased by non-linear effects leading to saturation of the wave amplitude.

The magnetosphere of the Earth presents a large scale plasma physics laboratory in which the complex interacting plasma phenomena are involved: global convecting plasma dynamics, wave–particle interactions in the bow shock and transmitted shock waves/impulses and magnetic field reconnection in the plasma current sheets. The NASA magnetospheric multiscale mission (MMS) provides unique observations of the thin structures and wave–particles interactions at the shock-like impulses while the spacecrafts were located at the dawn terminator (the time is 2016-03-07 20:00:00 UTC). It was assumed that these impulses may be created by the interaction between the background flow and plasma clouds. It was also assumed that those clouds were produced by either flux-transfer events or by coalescence/reconnection processes at the magnetopause current layer or by the mirror instabilities inside the low latitude boundary layer. 3-D hybrid kinetic code with separate description of the background and cloud ions was used for interpretation of the observed impulse structures. In this report we will discuss the effects of particle heating and acceleration inside the foreshock of the shock-like impulses, effects of the ion and electron non-Maxwellian velocity distributions, and particle finite gyroradius, and triggering the electromagnetic instability.

Atmospheric drag describes the main perturbing force of the atmosphere on the orbital trajectories of near-Earth orbiting satellites. The ability to accurately model atmospheric drag is critical for precise satellite orbit determination and collision avoidance. Assuming we know atmospheric winds and satellite velocity, area and mass, the primary sources of uncertainty in atmospheric drag include mass density of the space environment and the spacecraft drag coefficient, CD. Historically, much of the focus has been on physically or empirically estimating mass density, while CD is treated as a fitting parameter or fixed value. Presently, CD can be physically modeled through energy and momentum exchange processes between the atmospheric gas particles and the satellite surface. However, physical CD models rely on assumptions regarding the scattering and adsorption of atmospheric particles, and these responses are driven by atmospheric composition and temperature. Modifications to these assumptions can cause CD to change by up to ~40%. The nature and magnitude of these changes also depend on the shape of the spacecraft. We can check the consistency of the CD model assumptions by comparing densities derived from satellite drag measurements and computed CD values for satellites of different shapes orbiting in the same space environment. Since all of the satellites should see the same density, offsets in the derived densities should be attributable to inconsistencies in the CD model. Adjusting the CD model scattering assumptions can improve derived density consistency among the different satellites and inform the physics behind CD modeling. In turn, these efforts will help to reduce uncertainty in CD, leading to improved atmospheric drag estimates.

A key to understanding the evolution of the Martian climate over its history is the study of how the Martian atmosphere escapes to space. Studying the near-Mars space environment allows us to better understand atmospheric escape processes. One of these important processes is ion escape, in which atmospheric particles that are primarily ionized by the solar radiation above the exobase region can escape from the planet. Various model results, as well as MAVEN observations, have shown several important channels for ion escape in the Martian plasma environment. One of these channels forms when pickup ions are accelerated away from the planet by a motional electric field, creating a “plume” of escape organized by the upstream solar wind electric field. Although plasma models have predicted the existence of this plume before, only recently have we been able to regularly identify it in observations. Relatively little work has been done on how modeling choices influence the morphology of the plume. Here we present a comparison of two BATS-R-US multi-fluid MHD simulations, each with different spatial resolution, run using input conditions taken from a single MAVEN orbit in which the plume signature was clearly identified. Our analysis primarily focuses on differences seen in the location and morphology of the ion plume. While the two simulations match well at low altitudes, location differences in the ion plume become clear at high altitudes. We also analyze the effect of different spatial resolution on the simulated ion escape rates. Detailed investigation of the plume region in these simulations has also provided us with a better understanding of the underlying physics that shape and act on the ion plume. We have analyzed and identified regions where the v x B force accelerates ions while the J x B force confines them. This in turn allows us to identify the location of the plume. This study highlights the importance of choices in spatial resolution when modeling features in the Martian magnetosphere.

The Space Physics Data Facility (SPDF https://spdf.gsfc.nasa.gov) and Solar Data Analysis Center (SDAC https://umbra.nascom.nasa.gov/), as the NASA Heliophysics active final archives, will be preserving and distributing the data from Parker Solar Probe. Working in cooperation with current operating missions and the heliophysics community, SPDF ingests, preserves and serves a wide range of past and current public science-quality data from the ionosphere into the furthest reach of deep-space exploration. SPDF has been working with the Parker Solar Probe mission in preparation for archiving and serving its in-situ data starting 2019 Nov 12, and also has arrangements to serve in-situ data from Solar Orbiter when those data become public. SPDF will facilitate scientific analysis of multi-instrument and multi-mission datasets to enhance the science return of Parker Solar Probe mission. SPDF develops and maintains the Common Data Format (CDF) and the associated ISTP/SPDF metadata guidelines. SPDF services include CDAWeb, which supports both survey and burst mode data with graphics, listings and data superset/subset functions. All public data held by SPDF are also available for direct file download by HTTPS or FTPS links from the SPDF home page (https://spdf.gsfc.nasa.gov). SPDF is currently receiving and serving from missions including Helios, MMS, Van Allen Probes, THEMIS/ARTEMIS, GOLD, ACE, Cluster, Geotail, Polar, Wind and many others, and >120 Ground-Based investigations. SPDF recently added support for ARASE/ERG and MAVEN as supplementary access at the requests of those missions. SPDF also operates the multi-mission orbit displays and query services of SSCWeb and the Java-based 4D Orbit Viewer, as well as the Heliophysics Data Portal (HDP) discipline-wide data inventory and access service, and the OMNIweb near-Earth solar wind plasma and magnetic field database.

Key Points • NRLSSI2h solar irradiance variability model with 0.1-0.5 nm resolution captures larger UV. spectral line variability relative to continua. • At 300-400 nm, dominated by spectral features, NRLSSI2h estimates 2-5X smaller solar cycle variability than radiative transfer models. • Upper atmosphere solar radiation absorption can differ using NRLSSI2h (e.g., 34% decrease at 88 km for Lyman alpha).

Due to the high spectral resolution goals (R > 2x10^4) for the upcoming Full-sun Ultraviolet Rocket Spectrograph (FURST), instrument calibration will be particularly important. The Solar Physics groups at NASA MSFC and Montana State University (MSU) have been developing the tools necessary to achieve this goal. These include improved tracking of error propagation, in-situ monitoring of the camera gain with a radioactive Fe-55 source, and even better wavelength calibration. This presentation will focus on the latter. We will highlight the development of a calibration method which uses a two-dimensional second-order polynomial to map pixels to wavelength under a simulated noisy diagnostic lamp signal. Additionally, we have introduced a tilted CCD in order to overcome the Nyquist limit. With this as the background, we have been investigating an effect known well among ground-based imaging: geocoronal absorption. We have been looking into how much this effect will be present in the atmosphere at sounding-rocket altitudes (~100-200km). Many studies have found ways to correct for these so-called “Telluric” lines. However, it may be that these lines can in fact be a useful tool to further improve our calibration, rather than simply a nuisance to be corrected for!

The ionospheric numerical ionogram dataset on the Digisonde Ionogram Database (DIDBase) hosted by the Global Ionospheric Radio Observatory (GIRO) provides an important opportunity to study the bottomside ionospheric electron density profile. The study presents the description of software developed for digisonde numerical dataset that can be obtained from DIDBase. The developed DIDBase numerical data reader and cleaner named Digisonde Numeric Data (DINData) software can find missing data periods in the dataset and resequencing the date and time stamp on the dataset. The DINData software also allows users to apply settings to check the integrity of the scaled ionogram using the ionogram confidence score (CS) value. The DINData application is written in the Python programming language. The graphical user interface (GUI) of the software was developed using Kivy, a cross-platform Python GUI framework that is built on OpenGL. The Kivy framework allows the source code of the application to be packaged into various operating systems. The software currently runs on the Windows operating system and has a user-friendly graphical user interface to accept alphanumeric input entries.

The present paper demonstrates the first observations by the Magnetospheric Multiscale (MMS) mission of the counter-streaming energetic electrons and trapped energetic protons, localized in the magnetic field depressions between the mirror mode peaks, in the Earth’s dusk sector high-latitude magnetosphere. This region is characterized by high plasma beta, strong ion temperature anisotropy and intermediate plasma density between magnetospheric and magnetosheath plasma. We show that these plasma conditions are unstable for the drift mirror instability. The counter-streaming electron feature resembles those of the previously reported energetic electron microinjections, but without the energy-time dispersion signature. This suggests that MMS is passing through one of the potential microinjection source regions. The energetic ion data in the present study is mainly used to estimate the scale size of the mirror mode structures.

The in-situ magnetospheric exploration of the four large planets of our solar system had started with Pioneer 10’s flyby of Jupiter in Dec. 1973. The second collection of field, particle and radio data of the gas giant was carried out by Pioneer 11 in Dec. 1974, before this spacecraft made its closest approach to Saturn in Sep. 1979. Around the same period, Voyager 1 (2) flew by Jupiter in Mar. (Jul.) 1979 then Saturn in Nov. (Aug.) 1980 (1981). As of today, only Voyager 2 visited the magnetospheres of Uranus (Jan. 1986) and Neptune (Aug. 1989). Galileo had remained the only spacecraft to orbit an outer planet for several years (1995 - 2003) until the arrival of Juno at Jupiter in 2016. Between 2004 and 2017, the Cassini mission had provided a wealth of in-situ data pertinent to the study of magnetospheric particles at Saturn. In this paper, we present our current understanding of the processes that shape the spatial distributions of energetic electrons trapped in the magnetospheres of Jupiter (L < 6), Saturn (L < 15) and Uranus (L < 15) obtained by combining multi-instrument analyses of data from past missions (Pioneer, Voyager, Galileo, Cassini) and computational models of charged particle fluxes. To determine what controls the energy and spatial distributions throughout the different magnetospheres, we compute the time evolution of particle distributions with the help of a diffusion theory particle transport code that solves the governing 3-D Fokker-Planck equation. Particle, field and wave datasets are either used to provide model constraints, assist in modeling physical processes, or validate our simulation results. We first emphasize our latest results regarding the relative (or coupled) role of mechanisms at Saturn, including the radial transport and interactions of electrons with Saturn’s dust/neutral/plasma environments and waves, as well as particle sources from high-latitudes, interchange injections, and outer magnetospheric region. The lessons learned from our modeling of electron distributions at Saturn are used to identify the processes that may be missing in our modeling of Jupiter’s energetic electron environment or those in need to be implemented using new modeling concepts. Our first physics-based modeling of electron populations at Uranus is also assessed with our data-model comparison approach.

Ground-based amplitude measurements of GNSS signal during ionospheric scintillation are analyzed using prevalent data analysis tools developed in the fields of fluid and plasma turbulence. One such tool is the structure function of order $q$, with $q = 1$ to $q = 6$, which reduces to the computation of the second order difference in the GPS signal amplitude at various time lags, and allows for the exploration of dominant length scales in the propagation medium. We report the existence of a range where the structure function is linear with respect to time lag. This linear time-segment could be considered as an analog to the inertial range in the context of neutral and plasma turbulence theory. Below the linear range, the structure function increases nonlinearly with time lag, again in good concordance with the intermittent character of the signal, given that a parallel is drawn with turbulence theory. Quantitatively, the slope of the structure function in the linear range is in good agreement with the scaling exponent determined from in-situ measurements of the electrostatic potential at low altitude (E-region) and the electron density at the topside ionosphere (F-Region). This in turn suggests the conjecture that scintillation could be considered a proxy for ionospheric turbulence. Furthermore, we have found that the probability distribution function of the second order difference in the signal amplitude has non-Gaussian features at large time-lags; a result that seems inconsistent with equilibrium statistical physics which suggests a Gaussian distribution for the conventional random walk processes.

In this chapter we examine how our knowledge of present day Venus can inform terrestrial exoplanetary science and how exoplanetary science can inform our study of Venus. In a superficial way the contrasts in knowledge appear stark. We have been looking at Venus for millennia and studying it via telescopic observations for centuries. Spacecraft observations began with Mariner 2 in 1962 when we confirmed that Venus was a hothouse planet, rather than the tropical paradise science fiction pictured. As long as our level of exploration and understanding of Venus remains far below that of Mars, major questions will endure. On the other hand, exoplanetary science has grown leaps and bounds since the discovery of Pegasus 51b in 1995, not too long after the golden years of Venus spacecraft missions came to an end with the Magellan Mission in 1994. Multi-million to billion dollar/euro exoplanet focused spacecraft missions such as JWST, ARIEL and their successors will be flown in the coming decades. At the same time, excitement about Venus exploration is blooming again with a number of confirmed and proposed missions in the coming decades from India, Russia, Japan, the European Space Agency (ESA) and the National Aeronautics and Space Administration (NASA). In this chapter, we review what is known and what we may discover tomorrow in complementary studies of Venus and its exoplanetary cousins.

We examine the wave coupling efficiency of solar wind to magnetospheric fluctuations in the ULF frequency range using an advanced full-wave simulation code, Petra-M. Earth’s magnetic field is tilted to the ecliptic plane; thus, compressional wave sources can be incident over a wide range of magnetic latitudes. When compressional waves are incident at a low latitude, very little wave power can reach the inner magnetosphere. On the other hand, waves incident from a high latitude source can propagate efficiently into the inner magnetosphere and reach the ground near the cusp region. The mode-conversion and polarization reversal at the crossover plays a critical role in compressional wave propagation. The mode-converted linearly polarized electromagnetic ion cyclotron waves also occur at the Alfvén and ion-ion hybrid resonances. Therefore, the results suggest that solar wind compression can drive the linearly polarized EMIC waves, and the wave occurrence can have seasonal and diurnal dependence.

We present a new open-source tool for magnetospheric computations, that is modelling of cosmic ray propagation in the geomagnetosphere, named the “Oulu - Open-source geomagneToSphere prOpagation tool” (OTSO). A tool of this nature is required in order to interpret experiments and study phenomena within the cosmic ray research field. Within this work OTSO is applied to the investigation several ground level enhancement events. Here, we demonstrated several applications of OTSO, namely computation of asymptotic directions of selected cosmic ray stations, effective rigidity cut-off across the globe at various conditions within the design, general properties, including the magnetospheric models employed. A comparison and validation of OTSO with older widely used tools such as MAGNETOCOSMICS was performed and good agreement was achieved. An application of OTSO for providing the necessary background for analysis of two notable ground level enhancements is demonstrated and the their spectral and angular characteristics are presented.

Due to the potential risks that space weather (SW) events associated with solar-wind disturbances pose on modern technology and infrastructure, there has been increasing interest in physics-based forecasts of the solar wind and related phenomena, such as coronal mass ejections. Computational models of heliospheric space plasmas and space weather are generally based on the equations of ideal magnetohydrodynamics (MHD) that describe the conservation of plasma mass, momentum, and energy, as well as the time evolution of the magnetic field. Over the last few decades significant effort has been devoted to the development of efficient numerical schemes for solving the ideal MHD equations, especially in the context of space plasmas. More recently, there has been increasing interest in incorporating observational data within SW simulations via data assimilation (DA) to produce improved space weather forecasts. While the use of DA methods is a mature field that has proved to be vastly successful in meteorological applications, its use has seen limited application in heliospheric space weather forecasting, or MHD modeling in general. In this study, the results of the assimilation of synthetic plasma observations in one-dimensional ideal MHD initial value problems are considered. DA methods are generally divided into two families of approaches: variational and sequential methods. Both categories of approaches are examined here with assimilation results presented for the 4DVar and Ensemble Kalman Filter (EnKF) methods, respectively. Observing system simulation experiments are performed and the simulation errors obtained using the 4DVar and EnKF methods, as well as, without the use of DA are compared. The sensitivity of error reduction to temporal and spatial observation availability is explored, and the computational costs of each method are reported. Finally, the challenges associated with extensions to 3D models are discussed.