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Small Satellite Constellations for Data Driven Atmospheric Remote Sensing

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Dynamic Data-Driven Environmental Systems Science (DyDESS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8964))

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Abstract

Nanosatellite missions flying microwave radiometers for high-resolution microwave sounding are quickly proliferating, as microwave instrumentation is particularly well suited for implementation on a very small satellite, as the sensor requirements for power, pointing, and spatial resolution (aperture size) can be accommodated by a nanosatellite platform. The first mission, the Microsized Microwave Atmospheric Satellite (MicroMAS), will demonstrate temperature sounding in nine channels near 118 GHz. MicroMAS is currently onboard the International Space Station awaiting deployment for a 100-day mission. The Microwave Radiometer Technology Acceleration (MiRaTA) cubesat will demonstrate multi-band atmospheric sounding and co-located GPS radio occultation. MiRaTA will launch in early 2016, and will fly a tri-band sounder (60, 183, and 206 GHz) and a GPS radio occultation (GPS-RO) sensor. We present recent work to develop and demonstrate nanosatellite technologies for earth atmospheric remote sensing using microwave radiometry, and describe approaches for transitioning these new technologies into new research constellation missions to provide unprecedented measurement capabilities. Of particular interest is the potential of the constellation to provide data-driven sensing capabilities.

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References

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Acknowledgments

This work is sponsored by the National Oceanic and Atmospheric Administration under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions and recommendations are those of the authors and are not necessarily endorsed by the United States Government.

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Correspondence to W. Blackwell .

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Blackwell, W., Cahoy, K. (2015). Small Satellite Constellations for Data Driven Atmospheric Remote Sensing. In: Ravela, S., Sandu, A. (eds) Dynamic Data-Driven Environmental Systems Science. DyDESS 2014. Lecture Notes in Computer Science(), vol 8964. Springer, Cham. https://doi.org/10.1007/978-3-319-25138-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-25138-7_1

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  • Publisher Name: Springer, Cham

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