NSF Award
2429346
Aerosol and ocean properties have important impacts on ecosystems by influencing the climate, photosynthesis, and evapotranspiration. Understanding of global aerosol optical and microphysical properties largely relies on passive satellite remote sensing measurement. New polarimeter instruments that can measure the polarization of light in addition to the intensity can provide significantly increased information content about aerosol, cloud, and ocean properties. Nevertheless, an aerosol retrieval algorithm is needed to convert the observed passive measurement into the desired aerosols properties such as aerosol absorption. The recently launched Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), a NASA Earth-observing satellite, is designed to provide the state-of-the-art observations. These observations include polarization measurement to improve understanding of aerosol, cloud and ocean properties. To exploit the full range of PACE polarimeter measurement, an advanced aerosol retrieval algorithm is critical. This work will ultimately improve the research capacity of the home institution and benefit the State of Louisiana, which manages rich coastal resources and the restoration and balance of its wetlands. This fellowship will further bring partnership between a minority-serving and primarily undergraduate institution with NASA.<br/><br/>This Research Infrastructure Improvement EPSCoR Research Fellows project will provide a fellowship to an Associate Professor at the Southern University New Orleans. This work would be conducted in collaboration with researchers at the NASA Langley Research Center (LaRC). This project will enable the development and application of an aerosol retrieval algorithm to retrieve aerosol and ocean properties over the Gulf of Mexico using Hyper-Angular Rainbow Polarimeter #2 (HARP2) measurement. The main objectives of this study are to apply the neural network models in the PACE Microphysical Aerosol Properties from Polarimetry (PACE-MAPP) aerosol retrieval algorithm. The project is expected to improve the retrieval accuracy of aerosol and ocean properties over the Gulf of Mexico using the wide 2,400 km HARP2 swath. The project will further expand the capability of the PACE-MAPP aerosol retrieval algorithm to cope with spectrally dependent aerosol refractive indices in order to exploit the full spectral range of PACE data. The expertise gained during this fellowship will enable the PI to train and educate students at the Southern University New Orleans in cutting-edge remote sensing data analysis and machine learning-based retrieval algorithms.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
