AUTOMATIC HAZARD DETECTION FOR SPACE WEATHER

OVERVIEW: 

Severe space weather unleashed by the Sun may disrupt/disable satellites, ground stations and the electricity grid causing knock-on disasters in power, navigation, timing, transport, sanitation, hospitals, water-delivery, and food distribution, etc. Severe space weather will also adversely affect future astronauts on the Moon, outside Earth’s protective mangetosphere.  Current early-warning satellites at the “L1” point between the Earth and the Sun (e.g. ACE, SOHO and DSCOVR), only give us about a 40 min lead time of impending Earth-directed severe solar storms. In-situ data is needed both to confirm the particle count excursion for any Earth-directed coronal mass ejections (CME) as well as the orientation of the embedded plasma magnetic field.  Satellites closer to the sun than L1 could provide such in-situ data and increase the lead-time of the warnings. However this poses challenges in terms of architecting the system because the satellites closer to sun begin to drift off the Earth-Sun line. How can developments in autonomy either improve detection of space weather phenomena or address issues of cubesat constellations to improve early-warning systems? 

Solutions from the private sector that could solve these problems, either by addressing this “station-keeping” problem (e.g. solar sails, novel thrusters, etc.), or by designing a multi-cubesat early-warning constellation, or through autonomy are solicited. The solutions should detail communication, power, propulsion, size, weight and cost issues as, for example, outlined in Chapter 6 of the UNCLASS JASON report.

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