MAIAC Processing of OCI Over Land: High Resolution Aerosol Retrievals and Atmospheric CorrectionPI: Alexei Lyapustin - NASA Goddard Space Flight Center
Co-Is: Sujung Go (University of Maryland Baltimore County (UMBC)); Sergey Korkin (NASA Goddard Space Flight Center); Yujie Wang (UMBC)
The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in 2022, will carry three unique instruments which dramatically expand capabilities of the modern fleet of the polar-orbiting Earth observing satellites (MODIS, VIIRS). The Ocean Color Instrument (OCI), will, for the 1st time, provide well-calibrated, high signal-to- noise hyperspectral observations in 345-790nm interval with 5nm resolution and 5nm
(possibly 2.5nm) step. With additional seven discrete bands in the NIR-SWIR region with strong heritage of operational MODIS and VIIRS use, OCI offers a unique potential for the high accuracy global aerosol retrievals and atmospheric correction over land. The hyperspectral surface reflectance has being used for numerous applications such as forest management, precision farming, detecting invasive species, local to global land cover change detection etc. Through advanced characterization of vegetation, including Light Use Efficiency (LUE), plants' nutrients and pigments etc., it will help improve global modeling of vegetation and of terrestrial carbon. To unlock the unique potential of OCI for land vegetation analysis and other hyperspectral applications, we propose to adapt and prototype MAIAC algorithm for OCI processing. Specifically, we propose to:
1) Develop the global over-land processing of OCI data for land analysis, based on MAIAC algorithm. It will provide advanced cloud and snow detection, water vapor retrieval, high spatial resolution aerosol retrievals and atmospheric correction for OCI bands. 2) Develop retrieval algorithm for spectral aerosol absorption and height from OCI. 3) Prototype and test developed algorithm using TROPOMI data spectrally aggregated to OCI bands which will help achieve high pre-launch readiness. 4) Contribute to the HARP algorithm development for detailed aerosol characterization.