An analysis of the Collection 5 MODIS over-ocean aerosol optical depth product for its implication in aerosol assimilation

Abstract

As an update to our previous use of the Collection 4 Moderate Resolution Imaging Spectroradiometer (MODIS) over-water aerosol optical depth (AOD, symbol as τ data, we examined ten years of Terra and eight years of Aqua data Collection 5 data for its potential usage in aerosol data assimilation. Uncertainties in the over-water MODIS AOD were studied as functions of observing conditions, such as surface characteristics, aerosol optical properties, and cloud artifacts. Empirical corrections and quality assurance procedures were developed and compared to Collection 4 data. After applying quality assurance and empirical correction procedures, the Root-Mean-Square-Error (RMSE) in the MODIS Terra and Aqua AOD are reduced by 30% and 10–20%, respectively. Ten years of Terra and eight years of Aqua quality-assured level 3 MODIS over-water aerosol products were produced. The newly developed MODIS over-water aerosol products will be used in operational aerosol data assimilation and aerosol climatology studies, and will also be useful to other researchers who are using the MODIS satellite products in their projects

A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water MODIS and Level 2 MISR aerosol products

“…However, a few studies have shown that uncertainties still exist in current satellite aerosol products attributable to the complex surface, cloud contamination, and aerosol models used in the retrieving process (e.g. Zhang and Reid, 2006;Zhang et al, 2005;Kahn et al, , 2009Shi et al, 2010;. Those studies also suggested one must be wary of mistakenly interpreting noises and biases in satellite aerosol products as legitimate signals, particularly in demanding application such as data assimilation and long term trend analyses.…”

“…The DA quality MODIS data were created after extensive quality assurance procedures for removing possible cloud contamination, empirical corrections for wind to minimize the uncertainties from surface conditions, and aerosol micro-physical corrections based on derived fine mode fraction. Originally developed for MOD04 data collection 4, minor alterations to the correction coefficients have been made for data collection 5 (Shi et al, 2010). Currently the total global data loss through screening is 24-26%, with a reduction of absolute errors of 10-30% (e.g.…”

“…Six datasets are included in this study: the NASA operational over ocean collection 5 Terra MODIS level-2 aerosol product (MOD04, since 2000), the subsequent NRL data assimilation quality level-3 Terra MODIS aerosol product (Zhang and Reid, 2006;Shi et al, 2010), a similar pair of data products from Aqua MODIS (MYD, since 2003), Terra MISR version 22 level 2 product, and Aerosol Robotic Network (AERONET) sun photometer data (Holben et al, 1998).…”

“…IPCC) the decadal variations of atmospheric aerosol loadings are gaining increased interest from both the scientific and policy community (e.g. Kishcha et al, 2007;Mishchenko et al, 2007aMishchenko et al, , 2009Remer et al, 2008;Zhao et al, 2008;Li et al, 2009a;Herman et al, 2009;Li et al, 2009b;Streets et al, 2009;Yu et al, 2009;Cermak et al, 2010). Such studies are plagued by calibration issues (both within and between multiple sensors), signal to noise issues, and the aforementioned retrieval biases (e.g., Zhang and Reid, 2006;Li et al, 2009b).…”

“…Because many biases are removed, we also employ the adapted data assimilation (DA) grade level-three product of Zhang and Reid (2006) with updated coefficients for data collect 5 by Shi et al (2010). Limited comparisons to AERONET, Aqua MODIS and MISR are provided to display the range of possible outcomes.…”