Validation of Water Vapor Vertical Distributions Retrieved from MAX-DOAS over Beijing, China

• Published in: Remote Sensing
• Main Authors: Hua Lin, Cheng Liu, Chengzhi Xing, Qihou Hu, Qianqian Hong, Haoran Liu, Qihua Li, Wei Tan, Xiangguang Ji, Zhuang Wang, Jianguo Liu
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2020
• Subjects: MAX-DOAS; water vapor; vertical profiles; HEIPRO; Science; Q; Aerosol Robotic Network
• Online Access: https://doi.org/10.3390/rs12193193; https://doaj.org/article/0da8f74be9004383a47684d923f0f375

Water vapor vertical profiles are important in numerical weather prediction, moisture transport, and vertical flux calculation. This study presents the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) retrieval algorithm for water vapor vertical profiles and the retrieved results are validated with corresponding independent datasets under clear sky. The retrieved Vertical Column Densities (VCDs) and surface concentrations are validated with the Aerosol Robotic Network (AERONET) and National Climatic Data Centre (NCDC) datasets, achieving good correlation coefficients (R) of 0.922 and 0.876, respectively. The retrieved vertical profiles agree well with weekly balloon-borne radiosonde measurements. Furthermore, the retrieved water vapor concentrations at different altitudes (100–2000 m) are validated with the corresponding European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim datasets, achieving a correlation coefficient (R) varying from 0.695 to 0.857. The total error budgets for the surface concentrations and VCDs are 31% and 38%, respectively. Finally, the retrieval performance of the MAX-DOAS algorithm under different aerosol loads is evaluated. High aerosol loads obstruct the retrieval of surface concentrations and VCDs, with surface concentrations more liable to severe interference from such aerosol loads. To summarize, the feasibility of detecting water vapor profiles using MAX-DOAS under clear sky is confirmed in this work.