Contemplating synergistic algorithms for the NASA ACE Mission

Gerald G. Mace; David O.'C. Starr; Roger Marchand; Steven A. Ackerman; Steven E. Platnick; Ann Fridlind; Steven Cooper; Deborah G. Vane; Graeme L. Stephens

doi:10.1117/12.2030206

25 October 2013 Contemplating synergistic algorithms for the NASA ACE Mission

Gerald G. Mace, David O.'C. Starr, Roger Marchand, Steven A. Ackerman, Steven E. Platnick, Ann Fridlind, Steven Cooper, Deborah G. Vane, Graeme L. Stephens

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Proceedings Volume 8890, Remote Sensing of Clouds and the Atmosphere XVIII; and Optics in Atmospheric Propagation and Adaptive Systems XVI; 88900I (2013) https://doi.org/10.1117/12.2030206
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

ACE is a proposed Tier 2 NASA Decadal Survey mission that will focus on clouds, aerosols, and precipitation as well as ocean ecosystems. The primary objective of the clouds component of this mission is to advance our ability to predict changes to the Earth’s hydrological cycle and energy balance in response to climate forcings by generating observational constraints on future science questions, especially those associated with the effects of aerosol on clouds and precipitation. ACE will continue and extend the measurement heritage that began with the A-Train and that will continue through Earthcare. ACE planning efforts have identified several data streams that can contribute significantly to characterizing the properties of clouds and precipitation and the physical processes that force these properties. These include dual frequency Doppler radar, high spectral resolution lidar, polarimetric visible imagers, passive microwave and submillimeter wave radiometry. While all these data streams are technologically feasible, their total cost is substantial and likely prohibitive. It is, therefore, necessary to critically evaluate their contributions to the ACE science goals. We have begun developing algorithms to explore this trade space. Specifically, we will describe our early exploratory algorithms that take as input the set of potential ACE-like data streams and evaluate critically to what extent each data stream influences the error in a specific cloud quantity retrieval.

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Gerald G. Mace, David O.'C. Starr, Roger Marchand, Steven A. Ackerman, Steven E. Platnick, Ann Fridlind, Steven Cooper, Deborah G. Vane, and Graeme L. Stephens "Contemplating synergistic algorithms for the NASA ACE Mission", Proc. SPIE 8890, Remote Sensing of Clouds and the Atmosphere XVIII; and Optics in Atmospheric Propagation and Adaptive Systems XVI, 88900I (25 October 2013); https://doi.org/10.1117/12.2030206

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KEYWORDS

Clouds

Aerosols

Atmospheric particles

Climatology

Particles

Atmospheric modeling

Radar

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