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ROSES Proposals

Unified Algorithm for Aerosol Characterization from OCI on PACE 19-PACESAT19-0014

PI: Lorraine Remer - University of Maryland Baltimore County
Co-Is: N. Christina Hsu (NASA Goddard Space Flight Center (GSFC)); Robert C. Levy (NASA GSFC); Omar Torres (NASA GSFC)
For decades, NASA has flown a fleet of single-view radiometers that have been used for characterizing the global aerosol system. These have included the Total Ozone Mapping Spectrometer (TOMS), the MODerate resolution Imaging Spectroradiometer (MODIS) on both Terra and Aqua satellites, the Ozone Monitoring Instrument (OMI) on Aura, the Ozone Mapping Profiler Suite (OMPS) and the VIsible InfraRed Sensor (VIIRS) on Suomi-National Polar orbiting Partnership (S-NPP) satellite.

During this era, multiple algorithms have been developed to extract the specific information offered by each sensor and retrieve properties of global aerosol. Algorithms derived for TOMS, OMI and OMPS make use the ultraviolet (UV) portion of the reflected solar spectrum. Algorithms developed for MODIS and VIIRS rely on the visible (VIS) through the shortwave infrared (SWIR). Each spectral range provides information that has been exploited for aerosol characterization, some of which is unique to the specific spectral range and some of which overlaps between ranges. For example, the UV is particularly sensitive to aerosol absorption characteristics, the SWIR sensitive to size distribution and all wavelengths useful to derive aerosol loading in the form of aerosol optical depth (AOD).

With the Ocean Color Instrument (OCI) on PACE, there is opportunity to exploit the full reflected shortwave spectrum for retrieving global aerosol properties. Although we expect there will be at-launch algorithms applied to OCI, these will be based on the heritage set, which was tuned to either UV or VIS/NIR/SWIR. Although these products would include AOD in the UV and VIS over land and ocean, and the fine mode fraction of the AOD over oceans, they would NOT include any information on aerosol absorption, aerosol layer height, nor aerosol above clouds. To retrieve these important characteristics, and narrow uncertainties in estimating aerosol effects on climate change and air quality, we must mine PACE-OCI's full potential. Using OCI's broad spectrum from the UV to the SWIR we can bring home spectral AOD, size parameter, absorption, layer height over ocean and land, and aerosol above clouds. Furthermore, we can use OCI's hyperspectral capability through the oxygen absorption bands to provide an independent measure of aerosol layer height.

We propose a comprehensive aerosol characterization algorithm for OCI-alone, rooted in heritage, but yet completely innovative. By joining forces, we are cutting out the redundancies (and inconsistencies) of multiple aerosol algorithm groups working on separate algorithms on separate UV and VIS/NIR/SWIR sensors. We are not ignoring the added benefit that polarimeters can bring to aerosol characterization, but will not rely on this information for real-time aerosol retrievals.

We intend to provide a unified aerosol algorithm for OCI-unified in its spectral approach from UV to SWIR and unified in bringing multiple heritage groups together into one team. Together spectrally and together in experience, we can produce the best aerosol characterization possible in an operational environment.