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LESO: A ten-year ensemble of satellite-derived intercontinental hourly surface ozone concentrations.

Songyan ZhuJian XuJingya ZengChao YuYapeng WangHaolin WangJiancheng Shi
Published in: Scientific data (2023)
This study presents a novel ensemble of surface ozone (O 3 ) generated by the LEarning Surface Ozone (LESO) framework. The aim of this study is to investigate the spatial and temporal variation of surface O 3 . The LESO ensemble provides unique and accurate hourly (daily/monthly/yearly as needed) O 3 surface concentrations on a fine spatial resolution of 0.1◦ × 0.1◦ across China, Europe, and the United States over a period of 10 years (2012-2021). The LESO ensemble was generated by establishing the relationship between surface O 3 and satellite-derived O 3 total columns together with high-resolution meteorological reanalysis data. This breakthrough overcomes the challenge of retrieving O 3 in the lower atmosphere from satellite signals. A comprehensive validation indicated that the LESO datasets explained approximately 80% of the hourly variability of O 3 , with a root mean squared error of 19.63 μg/m 3 . The datasets convincingly captured the diurnal cycles, weekend effects, seasonality, and interannual variability, which can be valuable for research and applications related to atmospheric and climate sciences.
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