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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Here we explore a key difference between statistical techniques for estimating electric fields in chaotic, overmoded cavities.
The 10-min wind statistics from ground-based Doppler lidar at site H were calculated using the Sathe et al., 2015, paper in the references.
The 10-min wind statistics from ground-based Doppler lidar at the BLOC site were calculated using the Sathe et al., 2015, paper in the references. This lidar was Halo XR #216 through February 24, 2025, Halo XR #217 from February 24, 2025 through April 17, 2025, and again Halo XR #216 after that.
The 10-min wind statistics from ground-based Doppler lidar at site H were calculated using the Sathe et al., 2015, paper in the references.
The 10-min wind statistics from ground-based Doppler lidar at site A1 were calculated using a modified version of the Sathe et al., 2015 paper in the references.
The 10-minute wind statistics from the ground-based Doppler lidar at site A1 were calculated using a modified version of the Sathe et al., 2015 paper in the references.
The 10-min wind statistics from ground-based Galion lidar at the RHOD site were calculated using the Sathe et al., 2015, paper in the references.
The 10-min wind statistics from ground-based Doppler lidar at site A1 were calculated using a modified version of the Sathe et al., 2015 paper in the references.
This dataset contains 10-minute wind statistics from the ground-based NLR profiling lidar (Windcube v2.1) deployed at FC Site 4.0.
This dataset contains 10-minute wind statistics from ground-based NLR Halo XR+235 performing six-beam scans.
This dataset contains statistics (mean and standard deviation) calculated from quality-control lidar radial wind speed data through the LiSBOA method. This is an intermediate product for the synthesis of dual-Doppler wind maps.
This dataset contains statistics (mean and standard deviation) calculated from quality-control lidar radial wind speed data through the LiSBOA method. This is an intermediate product for the synthesis of dual-Doppler wind maps.
This dataset contains statistics (mean and standard deviation) calculated from quality-control lidar radial wind speed data through the LiSBOA method. This is an intermediate product for the synthesis of dual-Doppler wind maps.
This dataset contains statistics (mean and standard deviation) calculated from quality-control lidar radial wind speed data through the LiSBOA method. This is an intermediate product for the synthesis of dual-Doppler wind maps.
Abstract Space scientists often face the question of whether data collected by different instruments are measurements of the same source population. This paper proposes a statistical validation method for evaluating the agreement between such related data sets. It offers a detailed case study focused on validating a new data set from the Interstellar Boundary Explorer (IBEX) mission, which serves as a practical how-to guide for similar analyses. Since 2008, the IBEX satellite has been gathering data on heliospheric energetic neutral atoms (ENAs) while being exposed to various sources of background noise, such as cosmic rays and solar energetic particles. The IBEX mission initially released only a qualified triple-coincidence (qABC) data product, which was designed to provide observations of ENAs free of background contamination. Further measurements revealed that the qABC data were in fact susceptible to contamination, having relatively low ENA counts and high background rates. To mitigate this issue, the mission team recently considered releasing a certain qualified double-coincidence (qBC) data product, which has roughly twice the detection rate of the qABC data product. This paper presents a simulation-based validation of the new qBC data product against the already-released qABC data product. The results show that the qBCs can plausibly be said to be measuring the same source population as the qABCs up to an average absolute deviation of 3.6%. Visual diagnostics provide additional confirmation of source rate coherence across data products. The framework introduced here is general and can be applied to other validation problems both within and outside the field of space physics.
We build on the simplified spectral deferred corrections (SDC) coupling of hydrodynamics and reactions to handle the case of nuclear statistical equilibrium (NSE) and electron/positron captures/decays in the cores of massive stars. Our approach blends a traditional reaction network on the grid with a tabulated NSE state from a very large, ${\mathcal O }(100)$ nuclei network. We demonstrate how to achieve second-order accuracy in the simplified-SDC framework when coupling NSE to hydrodynamics, with the ability to evolve the star on the hydrodynamics time step. We discuss the application of this method to convection in massive stars leading up to core collapse. We also show how to initialize the initial convective state from a 1D model in a self-consistent fashion. All of these developments are done in the publicly available Castro simulation code and the entire simulation methodology is fully GPU-accelerated.
We present a comprehensive statistical analysis of ion-scale waves including dual-band ion-scale waves (DBIWs) observed by the Parker Solar Probe in the solar wind. DBIWs are characterized by the simultaneous occurrence of distinct left- and right-handed polarized wave packets at higher and lower frequencies, respectively, in the spacecraft frame, implying the presence of bidirectionally propagating L-mode waves. We identify and compare DBIWs to single-band ion-scale waves (SBIWs) and investigate their spatial distributions, background magnetic field conditions, and associated inertial range turbulence characteristics. We find that DBIWs exhibit a strong preferential occurrence at heliocentric distances between 0.2 and 0.25 au (equivalently 43 and 54 R S ) in contrast to SBIWs, the occurrence rate of which peaks closer to the Sun and decreases with the heliocentric distance. DBIWs are also preferentially observed under conditions of strong Alfvénic turbulence, characterized by low magnetic compressibility and perpendicular-dominant fluctuations. These findings support a scenario in which stochastic ion heating via sufficiently large perpendicular Alfvénic fluctuation generates the ion temperature anisotropies required to excite bidirectional ion cyclotron waves. This work advances our understanding of kinetic wave generation in the solar wind and its connection to large-scale turbulence.
Magnetospheric sawtooth events are characterized by periodic particle injections and magnetic dipolarizations spread quasi-simultaneously across a wide range of magnetic local times. We present a comprehensive statistical study of magnetospheric sawtooth events (STEs) during solar cycle 24 (2008–2016), extending previous catalogs and enabling solar cycle comparisons. Our results confirm that STEs predominantly occur during the rising and declining phases of the solar cycle, and are strongly associated with geomagnetic storms. Superposed epoch analysis reveals near-simultaneous particle injections across all magnetic local time sectors, but magnetic field dipolarization confined to the midnight region. These results support a scenario in which nightside tail reconnection and enhanced convection are the primary drivers of sawtooth oscillations. The localization of magnetic dipolarizations during STEs challenges global instability interpretations and suggests that STEs represent a stormtime substorm mode triggered under specific solar wind and magnetotail conditions. Superposed epoch analyses also show enhanced oxygen content in the magnetosphere during sawtooth events, but do not show a significant difference from geomagnetic storms that do not exhibit periodic behavior.