Data Assimilation of AOD and Estimation of Surface Particulate Matters over the Arctic

Author:

Han Kyung M.ORCID,Jung Chang H.ORCID,Park Rae-SeolORCID,Park Soon-YoungORCID,Lee Sojin,Kulmala Markku,Petäjä Tuukka,Karasiński GrzegorzORCID,Sobolewski PiotrORCID,Yoon Young Jun,Lee Bang Young,Kim Kiyeon,Kim Hyun S.

Abstract

In this study, more accurate information on the levels of aerosol optical depth (AOD) was calculated from the assimilation of the modeled AOD based on the optimal interpolation method. Additionally, more realistic levels of surface particulate matters over the Arctic were estimated using the assimilated AOD based on the linear relationship between the particulate matters and AODs. In comparison to the MODIS observation, the assimilated AOD was much improved compared with the modeled AOD (e.g., increase in correlation coefficients from −0.15–0.26 to 0.17–0.76 over the Arctic). The newly inferred monthly averages of PM10 and PM2.5 for April–September 2008 were 2.18–3.70 μg m−3 and 0.85–1.68 μg m−3 over the Arctic, respectively. These corresponded to an increase of 140–180%, compared with the modeled PMs. In comparison to in-situ observation, the inferred PMs showed better performances than those from the simulations, particularly at Hyytiala station. Therefore, combining the model simulation and data assimilation provided more accurate concentrations of AOD, PM10, and PM2.5 than those only calculated from the model simulations.

Funder

National Research Foundation of Korea

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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