Atmospheric composition data assimilation using multiple chemical transport models

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K05296
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Meteorology/Physical oceanography/Hydrology
• Research Institution: Japan Agency for Marine-Earth Science and Technology
• Principal Investigator: MIYAZAKI Kazuyuki 国立研究開発法人海洋研究開発機構, 地球環境観測研究開発センター, 主任研究員 (30435838)
• Co-Investigator(Kenkyū-buntansha): 弓本 桂也 九州大学, 応用力学研究所, 准教授 (50607786)
• Co-Investigator(Renkei-kenkyūsha): WATANABE Shingo 国立研究開発法人海洋研究開発機構, シームレス環境予測研究分野, 分野長 (50371745) ; KANAYA Yugo 国立研究開発法人海洋研究開発機構, 地球環境観測研究開発センター, センター長代理 (60344305) ; SUDO Kengo 名古屋大学, 環境学研究科, 准教授 (40371744)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: データ同化 / オゾン / 窒素酸化物 / 大気汚染 / 対流圏 / 大気化学

Outline of Final Research Achievements

We conducted tropospheric chemistry reanalysis calculations by assimilating multiple data sets from multiple satellite sensors. The reanalysis calculations were conducted using three different global chemical transport model and an ensemble Kalman filter technique that simultaneously optimises the chemical concentrations of various species and emissions of several precursors. The optimisation of both the concentration and the emission fields is an efficient method to correct the entire tropospheric profile and its year-to-year variations, and to adjust various tracers chemically linked to the species assimilated. Using the multiple chemical transport models, we demonstrated the importance of forecast model performance on tropospheric chemistry data assimilation.

Free Research Field

大気科学