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Atmospheric Composition

One of the primary objectives of NASA's Glory mission is quantify the direct and indirect effects of aerosols on the Earth's climate through accurate measurements of the global distribution of aerosol and cloud properties from the Aerosol Polarimetery Sensor (APS). Partial cloud contamination of the APS instrument footprints will have an unknown influence on the accuracy of the APS aerosol retrievals, however. Two strategies have been identified for addressing this issue: 1) cloud screening using the two high-spatial resolution cloud cameras (CCs) on Glory, and 2) the simultaneous retrieval of aerosol and cloud component properties within partially cloudy APS footprints. As we demonstrate here, complete cloud screening will likely eliminate a significant fraction of the available APS footprints, so the second approach appears to be the more acceptable strategy, provided that methods exist for developing and assessing algorithms for "unmixing" the radiative contribution of unresolved clouds and aerosol. One-dimensional (1D) polarized radiative transfer (RT) calculations suggest that the distinctive angular and polarimetric signatures of clouds and aerosols can be exploited to isolate and retrieve the important properties of both components. However, numerous studies have also shown that unresolved three-dimensional (3D) RT effects can lead to significant errors in satellite retrievals based on 1D approaches, which ignore the radiative interactions between aerosols and clouds that are present in commonly occurring, broken cloud scenes. In order to assess the performance of potential aerosol-cloud unmixing algorithms, as well as the potential impact of unresolved 3D effects on aerosol and cloud retrievals, we will combine observations from both APS and the CCs on Glory with information from other A-Train instruments within a state-of-the-art 3D, polarized, computational RT modeling framework. Within this framework realistic clouds and aerosols can be simulated based on geophysical information derived from actual data. The RT model will simultaneously provide the flexibility and fidelity required to simulate and assess the highly accurate radiopolarimetric data that will be provided by APS, and this capability will complement validation data acquired from suborbital platforms including ground sites and aircraft. The proposing team has extensive experience in both 3D radiative transfer modeling and cloud and aerosol satellite remote sensing, which will facilitate the development of the modeling testbed within the limited timeframe and budget of this Glory Science Team program. A simple linearly mixed aerosol-cloud model will be tested against both simulated and actual APS and CC data for specific cases to determine its utility in a straightforward unmixing algorithm suitable for 1D operational APS retrievals. Information from MODIS, and possibly CloudSat-CALIPSO, will be used to supplement the observational data when appropriate to assess the impact of unresolved 3D effects within the APS footprint. An extended 18-month timeline will allow assessment of more sophisticated (independently developed) unmixing algorithms, either for operational APS data processing or for research, using the full 3D polarized RT framework that incorporates realistic clouds and aerosols. Furthermore, the extended timeframe will allow for the design of mitigation strategies to restore APS aerosol characterization accuracy in the presence of unresolved clouds. This work is proposed to be conducted as Fundamental Research.

Project PI: Anthony Davis/Jet Propulsion Laboratory

Jet Propulsion Laboratory M/S 169-237 4800 Oak Grove Drive Pasadena, CA 9110

Phone: (818)354-0450

Email: Anthony.B.Davis@jpl.nasa.gov

http://science.jpl.nasa.gov/people/ADavis/

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Started: Sep 27, 2010

Last Activity: Jan 04, 2011

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