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An Over-land Aerosol Optical Depth Data Set for Data Assimilation by Filtering, Correction, and Aggregation of Modis Collection 5 Optical Depth Retrievals : Volume 4, Issue 3 (01/03/2011)

By Hyer, E. J.

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Book Id: WPLBN0003975786
Format Type: PDF Article :
File Size: Pages 30
Reproduction Date: 2015

Title: An Over-land Aerosol Optical Depth Data Set for Data Assimilation by Filtering, Correction, and Aggregation of Modis Collection 5 Optical Depth Retrievals : Volume 4, Issue 3 (01/03/2011)  
Author: Hyer, E. J.
Volume: Vol. 4, Issue 3
Language: English
Subject: Science, Atmospheric, Measurement
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Zhang, J., Reid, J. S., & Hyer, E. J. (2011). An Over-land Aerosol Optical Depth Data Set for Data Assimilation by Filtering, Correction, and Aggregation of Modis Collection 5 Optical Depth Retrievals : Volume 4, Issue 3 (01/03/2011). Retrieved from

Description: Naval Research Laboratory, 7 Grace Hopper Avenue, Monterey, CA 93943, USA. MODIS Collection 5 retrieved aerosol optical depth (AOD) over land (MOD04/MYD04) was evaluated using 4 years of matching AERONET observations, to assess its suitability for aerosol data assimilation in numerical weather prediction models. Examination of errors revealed important sources of variation in random errors (e.g., atmospheric path length, scattering angle hot spot), and systematic biases (e.g., snow and cloud contamination, surface albedo bias). A set of quality assurance (QA) filters was developed to avoid conditions with potential for significant AOD error. An empirical correction for surface boundary condition using the MODIS 16-day albedo product captured 25% of the variability in the site mean bias at low AOD. A correction for regional microphysical bias using the AERONET fine/coarse partitioning information increased the global correlation between MODIS and AERONET from r2 = 0.62–0.65 to r2 = 0.71–0.73. Application of these filters and corrections improved the global fraction of MODIS AOD within (0.05 ± 20%) of AERONET to 77%, up from 67% using only built-in MODIS QA. The compliant fraction in individual regions was improved by as much as 20% (South America). An aggregated Level 3 product for use in a data assimilation system is described, along with a prognostic error model to estimate uncertainties on a per-observation basis. The new filtered and corrected Level 3 product has improved performance over built-in MODIS QA with less than a 15% reduction in overall data available for data assimilation.

An over-land aerosol optical depth data set for data assimilation by filtering, correction, and aggregation of MODIS Collection 5 optical depth retrievals

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