Validation of high‐resolution MAIAC aerosol product over South America

Abstract

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD550 was performed using ground‐truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground‐based measurements, with a correlation coefficient (R) close to unity (RTerra:0.956 and RAqua: 0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 (~66%) of retrievals are within the expected error (EE = ±(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset ~0.006). Additionally, MAIAC CWV presents quantitative information with R ~ 0.97 and more than 70% of retrievals within error (±15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Observations of the Interaction and Transport of Fine Mode Aerosols With Cloud and/or Fog in Northeast Asia From Aerosol Robotic Network and Satellite Remote Sensing

“…Several studies are currently conducting global evaluation of MAIAC AOD. Regional AERONET-based validation over North and South America is available from Superczynski et al (2017) and Martins et al (2017), respectively.…”

First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI

“…Since MCD19A1 is derived from the MAIAC algorithm, it is suitable to use in comparison with a MAIAC-derived Himawari-8 AHI SR product. Currently, validation at stage 2 has been achieved for MAIACTBRF and MAIACABRF [17][18][19][20][21]25]. MODIS landcover (MCD12Q1) was also used in this study to identify vegetation pixels.…”

“…The kernel combination of Equation (1) was applied in the operational MODIS Reflectance/AOD/BRDF/albedo and BRDF/albedo algorithms [28]. Since 2011, MAIAC-derived MODIS products have been extensively tested and validated by the land and air quality communities [17][18][19][20][21]. The operational MODIS Collection 6 MAIAC dataset (MCD19 suite of products) was publicly released in May of 2018.…”

“…The version of MAIAC is adapted from NASA's MODIS heritage-MAIAC for MCD19 products. MAIAC has been in development for more than 10 years [8][9][10][11][12][13][14][15][16] and has been highly evaluated by previous studies [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21].…”

Response to Reviewer 2

“…A high accuracy, high 1 km spatial resolution and high retrieval coverage made MAIAC aerosol optical depth (AOD) a focus of numerous air quality studies, e.g., Chudnovsky et al (2013), Kloog et al (2014), Just et al (2015), Di et al (2016), Stafoggia et al (2016), Tang et al (2017) and Xiao et al (2017) to name a few. Currently published validation studies (Martins et al, 2017;Superczynski et al, 2017) show a high MAIAC AOD accuracy over American continents and an improved accuracy and coverage over North America compared to the operational VIIRS algorithm (Superczynski et al, 2017). An emerging comparative aerosol validation analysis over North America (Jethva et al, 2018) and southern Asia (Mhawish et al, 2018) shows that MAIAC has a comparable or better accuracy than the DT algorithm over dark surfaces and generally improves accuracy over the Deep Blue (DB) algorithm over bright surfaces.…”