An Operational Cloud Masking Product for the NASA Multi-Angle Imager for Aerosols, MAIA
The NASA Multi-Angle Imager for Aerosols (MAIA) instrument is set to launch in 2022 with the mission of quantifying epidemiological relationships between aerosols and human health. The MAIA instrument's primary product is a level 4 aerosol particulate matter concentration measurement collected over cloud free pixels. To produce this product, an intermediate cloud screening product is required. In this project, we present a cloud screening algorithm, or cloud mask, for MAIA constrained to its hardware. It consists of 7 tests that are applied according to the scene type. The scene type is a unique combination of sun-view geometry, day of year and surface type, including a novel surface classification scheme derived from the Multi-Angle Implementation of Atmospheric Correction Bi-Directional Reflectance Distribution Function (MAIAC BRDF) data set. The cloud mask works by checking if an observation exceeds or falls short of a threshold for any of the 7 tests, resulting in a cloudy or clear classification. The thresholds are derived to match the performance of the Terra Moderate Resolution Imaging Spectro-Radiometer (MODIS) high-confidence-cloud cloud mask and are unique to a scene type. Although, they are tunable by the end user to reach a desired result using a confidence metric called distance to threshold. For the Los Angeles target area with 15 years of Terra MODIS data to derive the thresholds, over 70% of the scene types did better than 90% accurate using an independent 3 year test data set. Future work involves fine tuning issues in the threshold derivation that cause erroneous values due to data quality and extending the threshold dataset to the other 10 primary target areas. The cloud mask and all supporting datasets will be delivered to the NASA Jet Propulsion Laboratory by December 2020.
