OMI UV aerosol index data analysis over the Arctic region for future data assimilation and climate forcing applications

Blake T. Sorenson,Jianglong Zhang, Jeffrey S. Reid,Peng Xian, Shawn Jaker

crossref(2022)

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摘要
Abstract. Due to a lack of high latitude ground-based and satellite-based data from traditional passive- and active-based measurements, the impact of aerosol particles on the Arctic region is one of the least understood factors contributing to recent Arctic sea ice changes. In this study, we investigated the feasibility of using the UV Aerosol Index (AI) parameter from the Ozone Monitoring Instrument (OMI), a semi-quantitative aerosol parameter, for quantifying spatiotemporal changes in UV-absorbing aerosols over the Arctic region. We found that OMI AI data are affected by additional row anomaly that is unflagged by the OMI quality control flag and are systematically biased as functions of observing conditions, such as azimuth angle, and certain surface types over the Arctic region. Two methods were developed in this study for quality assuring the Arctic AI data. Using quality-controlled OMI AI data from 2005 through 2020, we found decreases in UV-absorbing aerosols in the spring months (April and May) over much of the Arctic region and increases in UV-absorbing aerosols in the summer months (June, July, and August) over northern Russia and northern Canada. Additionally, we found significant increases in the frequency and size of UV-absorbing aerosol events across the Arctic and high Arctic (north of 80° N) regions for the latter half of the study period (2014–2020), driven primarily by a significant increase in boreal biomass-burning plume coverage.
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