Publications

Mishra, MK; Misra, A; Kumar, R (2023). Operational AOD Retrieval at Subkilometer Resolution Using OceanSat-2 OCM Over Land: SAER Algorithm, Uncertainties, Validation & Inter-Sensor Comparison. EARTH AND SPACE SCIENCE, 10(7), e2023EA002896.

Abstract
The ocean color monitor (OCM) sensor onboard OceanSat-2 is providing data in visible and near Infrared (NIR) bands. Due to the limited spectral coverage of OCM, the widely used dark-target and deep-blue aerosol algorithms cannot be adapted. Here, a new aerosol optical depth (AOD) retrieval algorithm for OCM (or similar sensors) over land, termed Space Applications Center AErosol Retrieval (SAER) is described. It utilizes two blue bands for the AOD inversion and, Red and NIR band to characterize the surface in visible bands without assuming red and NIR bands transparent to aerosols. Unlike the dark-target algorithm, the SAER algorithm can retrieve AOD over bright arid and urban areas too. The uncertainty analysis of SAER suggests a theoretically expected error (EE) envelope of +/-(0.06 + 0.26 x AOD) for typical retrieval conditions. OCM AOD over land is retrieved operationally for the first time over Indian and neighboring countries' landmass at the finest spatial resolution of 0.007 degrees. The SAER algorithm is validated against in-situ AOD measurements during the years 2016-2018 at 21 Aerosol Robotic Network stations located in south-Asia. Overall validation using 1900 match-up points shows correlations exceeding 0.8 with 74% of retrievals within EE. The retrievals over cropland, grassland, and mixed land cover types show high (low) correlation (bias), while over bright urban areas somewhat low (high) correlation (bias) is observed. Excluding monsoon season, OCM AOD retrievals show good performance over the year. The performance of MODerate Resolution Imaging Spectroradiometer dark-target and OCM AOD, against common in-situ, is close to each other. The study shows that OCM AOD can be used for air quality monitoring/modeling at high spatial resolution.

DOI:
10.1029/2023EA002896

ISSN:
2333-5084