A spatio‐temporal approach for global validation and analysis of MODIS aerosol products

TLDR

The launch of MODIS on Terra has produced global aerosol datasets that require validation and analysis. This paper presents the methodology for generating and analyzing the datasets used in two MODIS aerosol validation studies. The authors compute spatial statistics—mean, standard deviation, direction and rate of spatial variation, and spatial correlation—for MODIS aerosol parameters at over 100 global sites, compare these with temporally subset AERONET data, and use the spatial variation metrics to examine aerosol distribution locally and comparatively. While the mean values of MODIS and AERONET agree, the standard deviations indicate surface effects on MODIS aerosol retrievals over land, particularly at low aerosol loading.

Abstract

With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET‐derived aerosol data. The means and standard deviations of identical parameters from MODIS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.