Abstract

The rapid changes of aerosol sources in eastern China during recent decades could bring considerable uncertainties for satellite retrieval algorithms that assume little spatiotemporal variation in aerosol single scattering properties (such as single scattering albedo (SSA) and the size distribution for fine-mode and coarse mode aerosols) in East Asia. Here, using ground-based observations in six AERONET sites, we characterize typical aerosol optical properties (including their spatiotemporal variation) in eastern China, and evaluate their impacts on Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol retrieval bias. Both the SSA and fine-mode particle sizes increase from northern to southern China in winter, reflecting the effect of relative humidity on particle size. The SSA is ~0.95 in summer regardless of the AEROENT stations in eastern China, but decreases to 0.85 in polluted winter in northern China. The dominance of larger and highly scattering fine-mode particles in summer also leads to the weakest phase function in the backscattering direction. By focusing on the analysis of high aerosol optical depth (AOD) (>0.4) conditions, we find that the overestimation of the AOD in Dark Target (DT) retrieval is prevalent throughout the whole year, with the bias decreasing from northern China, characterized by a mixture of fine and coarse (dust) particles, to southern China, which is dominated by fine particles. In contrast, Deep Blue (DB) retrieval tends to overestimate the AOD only in fall and winter, and underestimates it in spring and summer. While the retrievals from both the DT and DB algorithms show a reasonable estimation of the fine-mode fraction of AOD, the retrieval bias cannot be attributed to the bias in the prescribed SSA alone, and is more due to the bias in the prescribed scattering phase function (or aerosol size distribution) in both algorithms. In addition, a large yearly change in aerosol single scattering properties leads to correspondingly obvious variations in the time series of MODIS AOD bias. Our results reveal that the aerosol single scattering properties in the MODIS algorithm are insufficient to describe a large variation of aerosol properties in eastern China (especially change of particle size), and can be further improved by using newer AERONET data.

Highlights

  • Atmospheric aerosols play a vital role in regional climate by redistributing solar radiation in the Earth-atmosphere system and modifying cloud properties [1]

  • The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol algorithm only retrieves the aerosol optical depth (AOD) and the fraction between fine-mode and coarse mode AODs [10,11], while aerosol single scattering properties are fixed with only consideration of seasonal and continental-scale variation

  • Striking systematic deviation is found in both the MODIS Dark Target (DT) and Deep Blue (DB) retrievals, with distinct biases caused by their respective aerosol models

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Summary

Introduction

Atmospheric aerosols play a vital role in regional climate by redistributing solar radiation in the Earth-atmosphere system and modifying cloud properties [1]. Since satellite spectral radiances at the top of the atmosphere (TOA) are affected by the radiative interactions between surface reflectance and aerosol scattering, not all aerosol properties can be fully constrained and retrieved reliably from satellite measurements at the TOA. Aerosol single scattering properties (such as SSA and size distribution for fine or coarse particles that affect phase function) are often derived from a cluster analysis of ground observations, and are subsequently used in the algorithms for the satellite remote sensing of aerosols. The MODIS aerosol algorithm only retrieves the AOD and the fraction between fine-mode and coarse mode AODs [10,11], while aerosol single scattering properties are fixed with only consideration of seasonal and continental-scale variation

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