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Heliophysics Science Division
Operational

Living With a Star Program (LWS)

The Living With a Star program emphasizes the science necessary to improve our understanding of how and why the sun varies; how Earth and the solar system respond; and how the variability and response affect humanity in space and on Earth. One of the program's key goals is to improve our ability to forecast geomagnetic storms and other forms of stormy "space weather." Such events can interrupt or damage satellite communications systems, trigger surges in power grid systems, and increase radiation hazards to orbiting astronauts and spacecraft.

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The Living With a Star program emphasizes the science necessary to improve our understanding of how and why the sun varies; how Earth and the solar system respond; and how the variability and response affect humanity in space and on Earth. One of the program's key goals is to improve our ability to forecast geomagnetic storms and other forms of stormy "space weather." Such events can interrupt or damage satellite communications systems, trigger surges in power grid systems, and increase radiation hazards to orbiting astronauts and spacecraft.

Related Publications

2024. "Global Empirical Model of Sporadic-E Occurrence Rates.", Frontiers in Astronomy and Space Sciences, 11 [10.3389/fspas.2024.1434367] [Journal Article/Letter]

2022. "Global GNSS-RO Electron Density in the Lower Ionosphere.", Remote Sensing, 14 (7): 1577 [10.3390/rs14071577] [Journal Article/Letter]

2016. "On the reduced geoeffectiveness of solar cycle 24: A moderate storm perspective.", Journal of Geophysical Research: Space Physics, 121 (9): 8188-8202 [10.1002/2016ja022885] [Journal Article/Letter]

2023. "Comparison of a Bottom-Up GNSS Radio Occultation Method to Measure D- and E-Region Electron Densities with Ionosondes and FIRI.", Remote Sensing, 15 (18): 4363 [10.3390/rs15184363] [Journal Article/Letter]

2023. "Optimal Estimation Inversion of Ionospheric Electron Density from GNSS-POD Limb Measurements: Part I-Algorithm and Morphology.", Remote Sensing, [https://doi.org/10.3390/rs15133245] [Journal Article/Letter]