The nonthermal continuum radiation (NTC) beaming angle is computed over the entire Van Allen Probes A mission when the spacecraft was in the dawn sector. The conditions in the dawn sector are favorable for the wave vector to lie near/in the spacecraft’s spin plan allowing a favorable estimate of the beaming angle, and the dawn sector is also advantageous in that previous studies show NTC occurrence to peak in this sector. We found that scatter plots, over the entire mission, of beaming angle versus magnetic latitude form a distinct inverted V pattern, with the apex at/near the magnetic equator. This pattern was sharpest for frequencies (f) ≲ 100 kHz. Using the NTC beaming formula from LMCT, we show that such an inverted V pattern is expected due to the large variation in the plasmapause location over the entire mission. The theoretical derived pattern qualitatively reproduces the observed pattern but not quantitatively. The lack of quantitative agreement is discussed and is attributed to several factors, one factor is off centered emissions from the radio window. The qualitative agreement strongly supports LMCT as being the dominant mechanism generating NTC for f ≲ 100 kHz. For f ≳ 100 kHz the inverted V pattern becomes less distinct, and strong near equatorial beaming is observed. After considering contamination of our selections by left-handed polarized AKR, our study suggests that besides LMCT another unidentified NTC generation mechanism becomes important for f ≳ 100 kHz.

Two-dimensional hybrid particle-in-cell (PIC) simulations are carried out on a constant L-shell (or drift shell) surface of the dipole magnetic field to investigate the generation process of near-equatorial fast magnetosonic waves (a.k.a equatorial noise; MSWs hereafter) in the inner magnetosphere. The simulation domain on a constant L-shell surface adopted here allows wave propagation and growth in the azimuthal direction (as well as along the field line) and is motivated by the observations that MSWs propagate preferentially in the azimuthal direction in the source region. Furthermore, the equatorial ring-like proton distribution used to drive MSWs in the present study is (realistically) weakly anisotropic. Consequently, the ring-like velocity distribution projected along the field line by Liouville’s theorem extends to rather high latitude, and linear instability analysis using the local plasma conditions predicts substantial MSW growth up to +- 27deg latitude. In the simulations, however, the MSW intensity maximizes near the equator and decreases quasi-exponentially with latitude. Further analysis reveals that the stronger equatorward refraction at higher latitude due to the larger gradient of the dipole magnetic field strength prevents off-equatorial MSWs from growing continuously, whereas MSWs of equatorial origin experience little refraction and can fully grow. Furthermore, the simulated MSWs exhibit a rather complex wave field structure varying with latitude, and the scattering of energetic ring-like protons in response to MSW excitation occurs faster than the bounce period of those protons so that they do not necessarily follow Liouville’s theorem during MSW excitation.

Heliophysics 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 inter-comparison 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.

We report observations of the ion dynamics inside an Alfven branch wave that propagates near the reconnecting dayside magnetopause. The measured frequency, wave normal angle and polarization are within 1% with the predictions of a dispersion solver, and indicate that the wave is an electromagnetic ion cyclotron wave with very oblique wave vector. The magnetospheric plasma contains hot protons (keV), cold protons (eV), plus some heavy ions. The cold protons follow the magnetic field fluctuations and remain frozen-in, while the hot protons are at the limit of magnetization. The cold proton velocity fluctuations contribute to balance the Hall term in Ohm’s law, allowing the wave polarization to be highly-elliptical and right-handed, a necessary condition for propagation at oblique wave normal angles. The dispersion solver indicates that increasing the cold proton density facilitates generation and propagation of these waves at oblique angles, as it occurs for the observed wave.

The Heliophysics Application Programmer’s Interface (HAPI) is a standard mechanism for accessing time series data. Because of its adoption at multiple Heliophysics (HP) and Space Weather (SW) data centers, it is now a useful way to reach many different resources within the community. It is also a COSPAR standard. The use of HAPI so far has been as a standard layer on top of a traditional mission or instrument archive, where HAPI lives alongside an existing, custom web-based computer interface. We will give highlights of recent additions to the specification which is now at version 3.0, with 3.1 around the corner. We also will present explorations into two new ways in which HAPI can be utilized. 1) HAPI as a way to access output from model runs, which can generate large volumes of data at various time cadences and spatial distributions. 2) HAPI as an interface over cloud-based data resources. In the cloud, HAPI can connect large volumes of data to scientist-friendly front-end analysis capabilities, such as a JupyterHub or potentially a Pangeo-like environment. The evolution of HAPI and its uses is expected to keep enhancing interoperability among Heliophysics and Space Weather resources.

Interoperability between datasets in Heliophysics and Planetary archives is increasingly important to address complex science questions about space weather and planetary plasma environments. Yet for cross-disciplinary studies, data ingestion is often a tedious, time-consuming process. We have developed the Heliophysics Application Programmer’s Interface (HAPI), a standard specification that captures a lowest common denominator method for accessing time series data. HAPI offers the ability to request data from multiple sources using a single interface, coupled with the ability to get identically formatted data from each source. HAPI has been recognized as a standard by the Committee on Space Research (COSPAR) and has gained adoption at multiple institutions in the US, including Goddard Space Flight Center’s Coordinated Data Analysis Web (GSFC/CDAWeb), the Planetary Data System Planetary Plasma Interactions Node (PDS/PPI), and the Laboratory for Atmospheric and Space Physics (LASP) Interactive Solar Irradiance Data Center (LISIRD). European plasma data centers such as the French Plasma Physics Data Centre (CDPP) and European Space Astronomy Centre (ESAC) are also in the process of adopting HAPI. We present an overview of the HAPI specification and describe how data centers can add HAPI access to their content. We also present how scientists can plot or download HAPI data using Python or using existing analysis tools such as Autoplot (Faden, 2010) and Space Physics Environment Data Analysis Software (SPEDAS) (Angelopoulos, 2019). Faden, J.B., Weigel, R.S., Merka, J. et al. Autoplot: a browser for scientific data on the web. Earth Sci Inform 3, 41–49 (2010). https://doi.org/10.1007/s12145-010-0049-0 Angelopoulos V, Cruce P, Drozdov A, et al. The Space Physics Environment Data Analysis System (SPEDAS). Space Sci Rev. 2019;215(1):9. doi:10.1007/s11214-018-0576-4

The Heliophysics Application Programmer’s Interface (HAPI) represents a grass-roots effort to develop a common interface that data providers can use to offer time series data for computer-to-computer data access. Multiple data centers with Heliophysics and Planetary data are adopting this emerging standard. Several scientific analysis packages (Autoplot, SPEDAS) seamlessly pull from HAPI servers, and we have created and are enhancing Python libraries that can be used to read HAPI data into useful data structures within personalized analysis code. The HAPI specification and supporting software are available on GitHub. We will discuss the latest developments of the HAPI specification, current server and client implementations, all in the context of the push for increased interoperability within Heliophysics and Planetary data analysis. https://hapi-server.github.io/

High-quality measurements of electromagnetic fields and electron velocity distributions by the Magnetospheric Multiscale (MMS) mission in Earth’s magnetosheath present a unique opportunity to characterize heliospheric plasma turbulence and to determine the mechanisms responsible for its dissipation. We apply the field-particle correlation technique to the MMS measurements to identify the dissipation mechanism and quantify the dissipation rate. It is found that 95% of the intervals have velocity-space signatures of electron Landau damping that are quantitatively consistent with linear kinetic theory for the collisionless damping of kinetic Alfvén waves. About 75% of the intervals have asymmetric signatures, implying that often the collisionless damping is stronger for waves propagating one direction along the magnetic field than the other. Nearly half of the samples have the same electron energization rates as order-of-magnitude estimates of the turbulent energy cascade rate, suggesting that electron Landau damping is frequently responsible for the dissipation of magnetosheath turbulent energy.

The ability to access time series data with one API would significantly enhance science data interoperability. The Heliophysics Application Programmers Interface (HAPI) is a simple, standardized mechanism for exposing time series data through a service. HAPI is being adopted by data centers within the Planetary and Heliophysics communities, especially for plasma, particle and field datasets. At the recent COSPAR meeting, the Panel on Space Weather passed a resolution encouraging data providers to have at minimum a HAPI server to deliver time series data. The COSPAR is now considering the resolution for full organizational endorsement. HAPI standardizes the two key parts of a data service: the request interface and the result format. The request interface is very simple and captures the common features of many existing data access services. For result formats, the HAPI specification allows several options, all of them streaming. Servers must provide a Comma Separated Value (CSV) result format, but may optionally provide a JSON or binary stream as well. The details of the request and result formats are described in the current version of the specification document, which is available at GitHub: https://github.com/hapi-server/data-specification. Several institutions have recently added HAPI-compliant access. These include the large Heliophysics archive at Goddard’s Coordinated Data Analysis Web (CDAWeb), as well as the Planetary Plasma Interactions node of the Planetary Data System, the Laboratory for Atmospheric and Space Physics at CU Boulder, the University of Iowa, George Mason University, and the Johns Hopkins University Applied Physics Lab. Multiple client options are available for accessing HAPI data from the growing number of servers. Autoplot (Faden, et al, 2010) and SPEDAS (http://spedas.org/wiki) both read HAPI data, and other clients (Java, Python, Matlab, IDL) can be downloaded from the HAPI Github project. The ease with which various providers have adapted existing servers to create a HAPI-compliant capability shows that it does capture a useful way to represent time series data. Because clients for reading HAPI data are also easy to create, we anticipate significant growth and interest in this emerging standard. Faden, et al, Earth Sci Inform (2010) 3:41–49, DOI 10.1007/s12145-010-0049-0