Study of long‐term trend in aerosol optical thickness observed from operational AVHRR satellite instrument

Abstract

[1] The long-term trend of aerosol optical thickness (AOT) over the global oceans has been studied by using a nearly 25-year aerosol record from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere extended (PATMOS-x) data set. Both global and regional analyses have been performed to derive the AOT tendencies for monthly, seasonal, and annual mean AOT values at AVHRR 0.63 mm channel (or Channel-1). A linear decadal change of À0.01 is obtained for globally and monthly averaged aerosol optical thickness, t 1 , of AVHRR Channel-1. This negative tendency is even more evident for globally and annually averaged t 1 and the magnitude can be up to À0.03/decade. Seasonal patterns in the AOT regional long-term trend are evident. In general, negative tendencies are observed for seasonally averaged t 1 in regions influenced by emissions from industrialized countries and the magnitude can be up to À0.10/decade. Positive tendencies are observed in regions influenced by emissions from fast developing countries and the magnitude can be up to +0.04/decade. For regions heavily influenced by Saharan desert particles, a negative trend with a maximum magnitude of À0.03/decade is detected. However, over regions influenced by smoke from biomass burning, positive tendencies with a maximum magnitude of +0.04/decade are observed. Sensitivity analyses have also been performed to study the effects of radiance calibration, aerosol retrieval algorithm, and spatial resolution of input retrieval radiances on the global aerosol long-term tendencies.

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

“…Kishcha et al, 2007;Mishchenko et al, 2007a and b;Remer et al, 2008;Zhao et al, 2008;Herman et al, 2009;Li et al, 2009b;Streets et al, 2009;Yu et al, 2009), unlike previous research efforts, using decade of over water MODIS and MISR aerosol products, we carefully examine biases in satellite AOD trend analysis due to radiometric calibration, cloud contamination, and sampling biases ). The statistical significance of the AOD trends estimated from this study, both in regional and global scale, were also evaluated for the data assimilation quality over water Terra MODIS aerosol product.…”

“…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).…”

Analysis of linear long-term trend of aerosol optical thickness derived from SeaWiFS using BAER over Europe and South China

“…Even though this linear model may not be the real, it allows a simple approximation of direction and magnitude of the changes in the data for many practical purposes (Weatherhead et al, 1998). Many previous studies also have adopted the simple model for AOT trend analysis Zhao et al, 2008;Papadimas et al, 2008;Yu et al, 2009;Xie and Xia, 2008;Kishcha et al, 2009;Karnieli et al, 2009;de Meij et al, 2010;Kaskaoutis et al, 2011). This study used the simple linear model for AOT trend comparisons.…”

“…First, a simple linear model, which is used to minimize chi-square error statistics, was adopted for the estimation of both trends. In order to analyze accurate trends, the simple model needs to be analyzed with respect to AOT variability, which is usually autocorrelated (Zhao et al, 2008). Even though this linear model may not be the real, it allows a simple approximation of direction and magnitude of the changes in the data for many practical purposes (Weatherhead et al, 1998).…”

“…Therefore, the increase of surface sunlight more evidently proved that the climate was getting warmer during the past decade. Zhao et al (2008) provided a more elaborate analysis for global and regional AOT trends using the AVHRR Pathfinder Atmosphere (PATMOS) climate data set. They added uncertainty tests (i.e.…”