A208-07
Simulated Proxy Data for PACE OCI Pre-Launch Inversion Algorithm Development

Wednesday, 16 December 2020: 04:44
Virtual
Amir Ibrahim1, Patricia Castellanos1, Andrew M Sayer2, Bryan A Franz1, Cecile S Rousseaux1, Watson W Gregg1, Brian Cairns3, Arlindo daSilva1, Peter M Norris4, Robert J D Spurr5 and Jeremy Werdell1, (1)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (2)Universities Space Research Association (USRA), Columbia, MD, United States, (3)NASA Goddard Institute for Space Studies, New York, NY, United States, (4)Goddard Earth Sciences Technology and Research, Greenbelt, MD, United States, (5)Rt Solutions Inc., Cambridge, MA, United States
Abstract:
The NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will host a state-of-the-art Ocean Color Instrument (OCI) as well as two advanced multi-angular polarimeters. OCI will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 2.5 nm spacing (5 nm bandwidth) and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038, 1250, 1378, 1615, 2130, and 2260 nm. A simulated dataset has been created utilizing NASA’s Goddard Global Modeling and Assimilation Office (GMAO) Nature Run (NR) geophysical model for the atmosphere, coupled with a global ocean water-leaving radiance model to simulate top-of-atmosphere (TOA) radiance for OCI granules from multiple expected PACE orbits. The TOA radiance was simulated using the vector radiative transfer code VLIDORT. The model accounts for different aerosol types, clouds, and fully couples absorbing gases, such as ozone, water vapor, and oxygen. The ocean radiance, as a bottom-of-atmosphere boundary layer in VLIDORT, was simulated using the Ocean-Atmosphere Spectral Irradiance Model (OASIM) that produces global assimilated distributions of ocean optical constituents. Although not the focus here, land surfaces are also included in the simulation, drawing on MODIS retrieval climatologies. The synthetic data provide a realistic global distribution of expected TOA radiance that OCI can observe, which will facilitate development and testing of OCI pre-launch inversion algorithms across atmosphere, ocean, and land disciplines.