temporal variability
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Limnetica ◽  
2022 ◽  
Vol 41 (1) ◽  
pp. 43-60
J. J. Montes-Pérez ◽  
B. Obrador ◽  
T. Conejo-Orosa ◽  
V. Rodríguez ◽  
R. Marcé ◽  

2022 ◽  
Vol 22 (1) ◽  
Taline Zgheib ◽  
Florie Giacona ◽  
Anne-Marie Granet-Abisset ◽  
Samuel Morin ◽  
Aurore Lavigne ◽  

2022 ◽  
Samuel E. LeBlanc ◽  
Michal Segal-Rozenhaimer ◽  
Jens Redemann ◽  
Connor J. Flynn ◽  
Roy R. Johnson ◽  

Abstract. Aerosol particles can be emitted, transported, removed, or transformed, leading to aerosol variability at scales impacting the climate (days to years and over hundreds of kilometers) or the air quality (hours to days and from meters to hundreds of kilometers). We present the temporal and spatial scales of changes in AOD (Aerosol Optical Depth), and aerosol size (using Angstrom Exponent; AE, and Fine-Mode-Fraction; FMF) over Korea during the 2016 KORUS-AQ (KORea-US Air Quality) atmospheric experiment. We use measurements and retrievals of aerosol optical properties from airborne instruments for remote sensing (4STAR; Spectrometers for Sky-Scanning Sun Tracking Atmospheric Research) and in situ (LARGE; NASA Langley Aerosol Research Group Experiment) on board the NASA DC-8, geostationary satellite (GOCI; Geostationary Ocean Color Imager; Yonsei aerosol retrieval (YAER) version 2) and reanalysis (MERRA-2; Modern-Era Retrospective Analysis for Research and Applications, version 2). Measurements from 4STAR when flying below 500 m, show an average AOD at 501 nm of 0.43 and an average AE of 1.15 with large standard deviation (0.32 and 0.26 for AOD and AE respectively) likely due to mixing of different aerosol types (fine and coarse mode). The majority of AODs due to fine mode aerosol is observed at altitudes lower than 2 km. Even though there are large variations, for 18 out of the 20 flight days, the column AOD measurements by 4STAR along the NASA DC-8 flight trajectories matches the south-Korean regional average derived from GOCI. We also observed that, contrary to prevalent understanding, AE and FMF are more spatially variable than AOD during KORUS-AQ, even when accounting for potential sampling biases by using Monte Carlo resampling. Averaging between measurements and model for the entire KORUS-AQ period, a reduction in correlation by 15 % is 65.0 km for AOD and shorter at 22.7 km for AE. While there are observational and model differences, the predominant factor influencing spatial-temporal homogeneity is the meteorological period. High spatio-temporal variability occur during the dynamic period (25–31 May), and low spatio-temporal variability occur during blocking Rex pattern (01–07 June). The changes in spatial variability scales between AOD and FMF/AE, while inter-related, indicate that microphysical processes that impact mostly the dominant aerosol size, like aerosol particle formation, growth, and coagulation, vary at shorter scales than the aerosol concentration processes that mostly impact AOD, like aerosol emission, transport, and removal.

Jae Eun Lee ◽  
Muhammad Azam ◽  
Saif Ur Rehman ◽  
Muhammad Waseem ◽  
M. Naveed Anjum ◽  

2022 ◽  
Vol 208 ◽  
pp. 105739
G. Tarca ◽  
M. Guglielmin ◽  
P. Convey ◽  
M.R. Worland ◽  
N. Cannone

2022 ◽  
Vol 805 ◽  
pp. 150390
Laura Haak ◽  
Blaga Delic ◽  
Lin Li ◽  
Tatiana Guarin ◽  
Lauren Mazurowski ◽  

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