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Comparisons of Spectral Aerosol Single Scattering Albedo in Seoul, South Korea

Quantifying aerosol absorption at ultraviolet (UV) wavelengths is important for monitoring air pollution and aerosol amounts using current (e.g., Aura/OMI (Ozone Monitoring Instrument)) and future (e.g., TROPOMI (TROPOspheric Monitoring Instrument), TEMPO (Tropospheric Emissions: Monitoring of POllution), GEMS (Geostationary Environment Monitoring Spectrometer) and Sentinel-4) satellite measurements. Measurements of column average atmospheric aerosol single scattering albedo (SSA) are performed on the ground by the NASA AERONET (AEROsol robotic NETwork) in the visible (VIS) and near-infrared (NIR) wavelengths and in the UV-VIS-NIR by the SKYNET (SKY radiometer NETwork) networks. Previous comparison studies have focused on VIS and NIR wavelengths due to the lack of co-incident measurements of aerosol and gaseous absorption properties in the UV. This study compares the SKYNET-retrieved SSA in the UV with the SSA derived from a combination of AERONET, MFRSR (MultiFilter Rotating Shadowband Radiometer), and Pandora (AMP) retrievals in Seoul, South Korea, in spring and summer 2016. The results show that the spectrally invariant surface albedo assumed in the SKYNET SSA retrievals leads to underestimated SSA compared to AMP values at near UV wavelengths. Re-processed SKYNET inversions using spectrally varying surface albedo, consistent with the AERONET retrieval improve agreement with AMP SSA. The combined AMP inversions allow for separating aerosol and gaseous (NO2 and O3) absorption and provide aerosol retrievals from the shortest UVB (305 nanometers) through VIS to NIR wavelengths (870 nanometers).

aerosol and gaseous absorption properties↗

Aerosol analysis techniques and results from micro pulse lidar

The effect of clouds and aerosol on the atmospheric energy balance is a key global change problem. Full knowledge of aerosol distributions is difficult to obtain by passive sensing alone. Aerosol and cloud retrievals in several important areas can be significantly improved with active remote sensing by lidar. Micro Pulse Lidar (MPL) is an aerosol and cloud profilometer that provides a detailed picture of the vertical structure of boundary layer and elevated dust or smoke plume aerosols. MPL is a compact, fully eyesafe, ground-based, zenith pointing instrument capable of full-time, long-term unattended operation at 523 nm. In October of 1993, MPL began taking full-time measurements for the Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) site and has since expanded to ARM sites in the Tropical West Pacific (TWP) and the North Slope of Alaska (NSA). Other MPL's are moving out to some of the 60 world-wide Aerosol Robotic Network (AERONET) sites which are already equipped with automatic sun-sky scanning spectral radiometers providing total column optical depth measurements. Twelve additional MPL's have been purchased by NASA to add to the aerosol and cloud database of the EOS ground validation network. The original MPL vertical resolution was 300 meters but the newer versions have a vertical resolution of 30 meters. These expanding data sets offer a significant new resource for atmospheric radiation analysis. Under the direction of Jim Spinhirne, the MPL analysis team at NASA/GSFC has developed instrument correction and backscatter analysis techniques for ARM to detect cloud boundaries and analyze vertical aerosol structures. A summary of MPL applications is found in Hlavka (1997). With the aid of independent total column optical depth instruments such as the Multifilter Rotating Shadowband Radiometer (MFRSR) at the ARM sites or sun photometers at the AERONET sites, the MPL data can be calibrated, and time-resolved vertical profiles of aerosol optical depth as well as aerosol extinction can be calculated. The techniques used to calibrate the lidar, calculate the aerosol extinction-to-backscatter ratio, and produce profiles of aerosol extinction and aerosol optical depths, will be described. Results using these techniques will be presented for case studies at the ARM site in the Tropical West Pacific and later in the Southern Great Plains.

Hlavka, Dennis L.↗

Ground-based retrievals of aerosol column absorption in the UV spectral region and their implications for GEMS measurements

Quantifying the spectral variation of column aerosol absorption in the ultraviolet (UV) and visible (Vis) wavelengths is required for accurate satellite-based aerosol and trace-gas retrievals. Retrievals of the column-averaged imaginary part of refractive index and single scattering albedo (SSA) in the UV–Vis range have been performed at Yonsei University, Seoul, Korea, since 2016 by combining co-located measurements from the NASA Aerosol Robotic Network (AERONET) Cimel sun-sky photometer, the Ultraviolet Multifilter Rotating Shadowband Radiometer (UV-MFRSR), the SKYNET Prede sky radiometer, and the NASA Pandora sun spectrometer. We investigated the spectral variation of column-averaged imaginary part of refractive index for UV–Vis wavelengths to refine models used in our aerosol retrieval algorithm to process measurements from the upcoming Geostationary Environment Monitoring Satellite (GEMS). The retrieved imaginary part of refractive index for highly absorbing fine pollution particles (BC), dust (DS), and non-absorbing (NA) particles in the selected UV–Vis range (380–440 nm) showed 0–20%, 30%, and 0–40% of spectral dependence, respectively. Retrievals of Ozone Monitoring Instrument (OMI) measurement data using the improved aerosol model showed improved correlation with AERONET data compared to the old algorithm that did not properly account for aerosol absorption effects. These results corroborate the advantage of using local climatology derived from ground-based UV–Vis spectral aerosol absorption measurements for satellite GEMS aerosol retrievals over East Asia. Moreover, this study reveals that spectral variations in the UV column aerosol absorption in East Asia differ from those in other regions.

ultraviolet (UV) and visible (Vis) wavelengths↗