Classification of Cassini’s Orbit Regions as Magnetosphere, Magnetosheath, and Solar Wind via Machine Learning

Several machine learning algorithms and feature subsets from a variety of particle and magnetic field instruments on-board the Cassini spacecraft were explored for their utility in classifying orbit segments as magnetosphere, magnetosheath or solar wind. Using a list of manually detected magnetopause and bow shock crossings from mission scientists, random forest (RF), support vector machine (SVM), logistic regression (LR) and recurrent neural network long short-term memory (RNN LSTM) classification algorithms were trained and tested. A detailed error analysis revealed a RNN LSTM model provided the best overall performance with a 93.1% accuracy on the unseen test set and MCC score of 0.88 when utilizing 60 min of magnetometer data (|B|, Bθ, Bϕ and BR) to predict the region at the final time step. RF models using a combination of magnetometer and particle data, spanning H+, He+, He++ and electrons at a single time step, provided a nearly equivalent performance with a test set accuracy of 91.4% and MCC score of 0.84. Derived boundary crossings from each model’s region predictions revealed that the RNN model was able to successfully detect 82.1% of labeled magnetopause crossings and 91.2% of labeled bow shock crossings, while the RF model using magnetometer and particle data detected 82.4 and 74.3%, respectively

MESSENGER observations of suprathermal electrons in Mercury's magnetosphere

The X‐Ray Spectrometer (XRS) on the MErcury Surface, Space ENvironment, GEochemistry, and Ranging spacecraft regularly detected fluorescent X‐rays near Mercury induced by low‐energy (1–10 keV) or suprathermal electrons. We devised an algorithm to select these events from XRS records between April 2011 and March 2015 on the basis of their duration, location, and spectral slope. We identified 3102 events during 3900 orbits around Mercury, sampling all Mercury longitudes multiple times over the 4 year period. These suprathermal electrons were present near the planet at all local times, but the majority were on the nightside of the planet, and a dawn‐dusk asymmetry is seen in the data. When the event locations are plotted in a coordinate system based on a simplified magnetic field model, several distinct clusters of events are evident. We infer that all are signatures of accelerated electrons that were injected from Mercury's tail region to form a quasi‐trapped electron population at Mercury

Comprehensive survey of energetic electron events in Mercury's magnetosphere with data from the MESSENGER Gamma‐Ray and Neutron Spectrometer

Data from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) Gamma‐Ray and Neutron Spectrometer have been used to detect and characterize energetic electron (EE) events in Mercury's magnetosphere. This instrument detects EE events indirectly via bremsstrahlung photons that are emitted when instrument and spacecraft materials stop electrons having energies of tens to hundreds of keV. From Neutron Spectrometer data taken between 18 March 2011 and 31 December 2013 we have identified 2711 EE events. EE event amplitudes versus energy are distributed as a power law and have a dynamic range of a factor of 400. The duration of the EE events ranges from tens of seconds to nearly 20 min. EE events may be classified as bursty (large variation with time over an event) or smooth (small variation). Almost all EE events are detected inside Mercury's magnetosphere on closed field lines. The precise occurrence times of EE events are stochastic, but the events are located in well‐defined regions with clear boundaries that persist in time and form what we call “quasi‐permanent structures.” Bursty events occur closer to dawn and at higher latitudes than smooth events, which are seen near noon‐to‐dusk local times at lower latitudes. A subset of EE events shows strong periodicities that range from hundreds of seconds to tens of milliseconds. The few‐minute periodicities are consistent with the Dungey cycle timescale for the magnetosphere and the occurrence of substorm events in Mercury's magnetotail region. Shorter periods may be related to phenomena such as north‐south bounce processes for the energetic electrons

HAPI - A Standard Time Series Data Access API for Heliophysics and Planetary Data

Inter- and Intra-operability between Heliophysics and Planetary datasets are needed to address new problems in space weather and planetary science. Although there are a few standard file formats commonly in these communities, no standard has been developed for an Application Programmer's Interface (API) for time series data. HAPI (Heliophysics API) is a specification that captures the lowest common denominator method for accessing time-series data in Heliophysics and Planetary science. HAPI has been recognized as a standard by the Committee on Space Research (COSPAR) and has gained adoption at multiple institutions in the US and Europe, including Goddard Space Flight Center’s Coordinated Data Analysis Web (CDAWeb) and Satellite Situation Center Web (SSCWeb); the Planetary Data System Planetary Plasma Interactions Node (PDS/PPI); European Space Agency ViRES/Swarm mission data server, International Real-time Magnetic Observatory Network (INTERMAGNET), and the Laboratory for Atmospheric and Space Physics Interactive Solar Irradiance Data Center (LiSIRD). Several additional plasma data centers, such as the French Plasma Physics Data Centre (CDPP) and the European Space Astronomy Centre (ESAC), are also adopting HAPI. In this presentation, we provide an overview of the HAPI specification and the many software tools developed for accessing data from a HAPI-enabled server

SPASE metadata as a building block of a heliophysics science-enabling framework

International audienceHeliophysics and space weather research encompass the effects of solar output on practically the entire Solar System and are fundamentally cross-disciplinary. Cross-domain science investigations, such as in Sun-heliosphere interactions, solar wind-magnetosphere interactions, or magnetosphere-ionosphere coupling, often require the use of data, models, and other digital resources pertaining to different heliophysical domains: the Sun, the solar wind, the magnetosphere, the ionosphere, the thermosphere and the mesosphere. Due to differences in measurement platforms, techniques and instruments, heliophysics data obtained from different domains are diverse and complex, making the resource landscape difficult for untrained users to navigate. Without proper and adequate guidance from domain experts, it is often difficult for early-career scientists and non-domain experts to discover useful datasets and to know from where and how to obtain and understand the data they need to support their research. This paper describes the roles of metadata in providing the identification, location, access protocol, and detailed content description of a digital resource. More specifically, we point out that metadata written according to the Space Physics Archive Search and Extract (SPASE) metadata model are fully compatible with the FAIR principles so that digital resources described using the SPASE model can be uniformly Findable, Accessible, Interoperable, and Reusable. SPASE metadata can thus be the key element, the lingua franca so to speak, that enables unfettered information flow between data systems and services throughout the heliophysics data environment and lowers the understandability barrier of the resources to ensure their independent usability. After describing various components of the heliophysics data environment, their metadata requirements for effective operations, and some essential features of the SPASE metadata model, we then illustrate how metadata in SPASE can enable or facilitate the performance of different science tasks. The current status and future outlook of SPASE are also presented

HAPI: An API Standard for Accessing Heliophysics Time Series Data

International audienceHeliophysics data analysis often involves combining diverse science measurements, many of them captured as time series. Although there are now only a few commonly used data file formats, the diversity in mechanisms for automated access to and aggregation of such data holdings can make analysis that requires intercomparison of data from multiple data providers difficult. The Heliophysics Application Programmer's Interface (HAPI) is a recently developed standard for accessing distributed time series data to increase interoperability. The HAPI specification is based on the common elements of existing data services, and it standardizes the two main parts of a data service: the request interface and the response data structures. The interface is based on the REpresentational State Transfer (REST) or RESTful architecture style, and the HAPI specification defines five required REST endpoints. Data are returned via a streaming format that hides file boundaries; the metadata is detailed enough for the content to be scientifically useful, e.g., plotted with appropriate axes layout, units, and labels. Multiple mature HAPI-related open-source projects offer server-side implementation tools and client-side libraries for reading HAPI data in multiple languages (IDL, Java, MATLAB, and Python). Multiple data providers in the US and Europe have added HAPI access alongside their existing interfaces. Based on this experience, data can be served via HAPI with little or no information loss compared to similar existing web interfaces. Finally, HAPI has been recommended as a COSPAR standard for time series data delivery