A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Assimilating Himawari-8 AHI aerosol observations with a rapid-update data assimilation system
Abstract Himawari-8, a next-generation geostationary meteorological satellite, is equipped with the Advanced Himawari Imager (AHI) that provides full-disk images of Earth every 10 min for 16 observation bands from visible to infrared. In this study, the capability to assimilate AHI Aerosol optical depth (AOD) has been developed within the Gridpoint Statistical Interpolation (GSI) system with an hourly cycling configuration and application to a dust storm over East Asia during 5–7 May 2017. Analyses were produced hourly, and 24 h forecasts were produced every 6 h within the Weather Research and Forecasting with Chemistry model. It was found that the mean bias and root-mean-square error (RMSE) after data assimilation is obviously reduced (by about 30%) when compared to the control experiment which didn't assimilate any observations during the dust storm period, which verified the positive effects of AOD data assimilation systems. In addition, aerosol analyses and forecasts with AOD data assimilation were substantially improved when compared to independent AOD observations from AERONET sites. Therefore, the AOD data assimilation system developed here could be used as a tool to generate better dust storm forecasts.
Highlights It is the first attempt to assimilate AHI AOD with a rapid-update DA system. It was investigated for the dust storm occurred over East Asia on 5–7 May 2017. General positive impacts were achieved from assimilating high-frequency data.
Assimilating Himawari-8 AHI aerosol observations with a rapid-update data assimilation system
Abstract Himawari-8, a next-generation geostationary meteorological satellite, is equipped with the Advanced Himawari Imager (AHI) that provides full-disk images of Earth every 10 min for 16 observation bands from visible to infrared. In this study, the capability to assimilate AHI Aerosol optical depth (AOD) has been developed within the Gridpoint Statistical Interpolation (GSI) system with an hourly cycling configuration and application to a dust storm over East Asia during 5–7 May 2017. Analyses were produced hourly, and 24 h forecasts were produced every 6 h within the Weather Research and Forecasting with Chemistry model. It was found that the mean bias and root-mean-square error (RMSE) after data assimilation is obviously reduced (by about 30%) when compared to the control experiment which didn't assimilate any observations during the dust storm period, which verified the positive effects of AOD data assimilation systems. In addition, aerosol analyses and forecasts with AOD data assimilation were substantially improved when compared to independent AOD observations from AERONET sites. Therefore, the AOD data assimilation system developed here could be used as a tool to generate better dust storm forecasts.
Highlights It is the first attempt to assimilate AHI AOD with a rapid-update DA system. It was investigated for the dust storm occurred over East Asia on 5–7 May 2017. General positive impacts were achieved from assimilating high-frequency data.
Assimilating Himawari-8 AHI aerosol observations with a rapid-update data assimilation system
Xia, Xiaoli (author) / Min, Jinzhong (author) / Wang, Yuanbing (author) / Shen, Feifei (author) / Yang, Chun (author) / Sun, Zhandong (author)
Atmospheric Environment ; 215
2019-07-25
Article (Journal)
Electronic Resource
English
Assimilating observations to simulate marine layer stratocumulus for solar forecasting
| British Library Online Contents | 2018
Assimilating observations to simulate marine layer stratocumulus for solar forecasting
| British Library Online Contents | 2018