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

Authors :
Zhu, Songyan
Xu, Jian
Zeng, Jingya
Yu, Chao
Wang, Yapeng
Wang, Haolin
Shi, Jiancheng
Source :
Scientific Data; 11/20/2023, Vol. 10 Issue 1, p1-12, 12p
Publication Year :
2023

Abstract

This study presents a novel ensemble of surface ozone (O<subscript>3</subscript>) generated by the LEarning Surface Ozone (LESO) framework. The aim of this study is to investigate the spatial and temporal variation of surface O<subscript>3</subscript>. The LESO ensemble provides unique and accurate hourly (daily/monthly/yearly as needed) O<subscript>3</subscript> 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<subscript>3</subscript> and satellite-derived O<subscript>3</subscript> total columns together with high-resolution meteorological reanalysis data. This breakthrough overcomes the challenge of retrieving O<subscript>3</subscript> in the lower atmosphere from satellite signals. A comprehensive validation indicated that the LESO datasets explained approximately 80% of the hourly variability of O<subscript>3</subscript>, with a root mean squared error of 19.63 μg/m<superscript>3</superscript>. 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20524463
Volume :
10
Issue :
1
Database :
Complementary Index
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
173761410
Full Text :
https://doi.org/10.1038/s41597-023-02656-4