Abstract
Detailed knowledge of the complex refractive indices (m) of fine- and coarse-mode aerosols is important for enhancing understanding of the effect of atmospheric aerosol on climate. However, studies on obtaining aerosol modal m values are particularly scarce. This study proposes a method for inferring m values of fine- and coarse-mode aerosol using the inversion products from the AERONET ground-based aerosol robotic network. By identifying the aerosol type, modal m values are constrained and then inferred based on a maximum likelihood method. Numerical tests showed that compared with the reference values, our method slightly overestimates the real parts of the refractive indices (n), but underestimates the imaginary parts (k) by 2.11% ± 11.59% and 8.4% ± 26.42% for fine and coarse modes, respectively. We applied this method to 21 AERONET sites around China, which yielded annual mean m values of (1.45 ± 0.04) + (0.0109 ± 0.0046)i and (1.53 ± 0.01) + (0.0039 ± 0.0011)i for fine- and coarse-mode aerosols, respectively. It is observed that the fine mode n decreased from 1.53 to 1.39 with increasing latitude, while fine mode k values were generally larger than 0.008 over most of China. The coarse-mode n and k ranged from 1.52 to 1.56 and from 0.002 to 0.006, respectively.
Highlights
Atmospheric aerosol plays an important role in the Earth-Ocean-Atmosphere system because it changes the radiance balance of the system via both direct effects, such as absorption and scattering of shortwave solar radiation and longwave earth radiation, and indirect effects, such as acting as cloud condensation nuclei [1,2]
The widespread ground-based aerosol robotic network (AERONET), as well as the sky radiometer network mainly located in eastern Asia (SKYNET), realize real-time monitoring of atmospheric aerosols by measuring the direct sun and diffuse sky radiance and provide related parameters including aerosol optical depth (AOD), single scattering albedo (SSA), m, and volume size distribution (VSD) [28,29,30]
Both aerosol relative optical depth (AROD) and AOD0.44 values can be used to distinguish maritime (MA), continental (CO), desert dust (DD), sub-continental (SC), urban industry (UI), and biomass burning (BB) aerosols [35], which has been applied to the data from the AERONET MAPS-Seoul Campaign to investigate regional variations in aerosol type [36]
Summary
Atmospheric aerosol plays an important role in the Earth-Ocean-Atmosphere system because it changes the radiance balance of the system via both direct effects, such as absorption and scattering of shortwave solar radiation and longwave earth radiation, and indirect effects, such as acting as cloud condensation nuclei [1,2]. The widespread ground-based aerosol robotic network (AERONET), as well as the sky radiometer network mainly located in eastern Asia (SKYNET), realize real-time monitoring of atmospheric aerosols by measuring the direct sun and diffuse sky radiance and provide related parameters including aerosol optical depth (AOD), single scattering albedo (SSA), m, and volume size distribution (VSD) [28,29,30] Both of the AERONET and SKYNET algorithms use the internal mixing hypothesis that assumes that fineand coarse-mode aerosol particles have the same m values [23,24], which is not correct as the different particle modes have different compositions and different m values [3]. The arrangement of this paper is as follows: Section 2 introduces the AERONET data and related methods; Section 3 presents the numerical tests; Section 4 discusses application of the estimation method over China; and Section 5 gives a brief conclusion of this study
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