10:45 AM - 11:00 AM
[MGI24-06] Comparison of the impact of all-sky and clear-sky infrared radiance assimilation for the global geostationary satellites in the JMA’s global NWP system
★Invited Papers
Keywords:Data assimilation, Numerical weather prediction, All-sky radiance
Infrared radiance data from imager sensors onboard geostationary (GEO) satellites give precious information about the atmosphere in the troposphere, with dense temporal and spatial resolution. Products derived from this data, including all-sky radiance (ASR), which represents the mean brightness temperature (BT) from certain pixels within a segment, and clear-sky radiance (CSR), which represents the mean BT from certain pixels under clear-sky conditions within a segment, are available in real-time. These products contain information about the atmosphere in the troposphere and are effective for improving the accuracy of analysis and forecasting in numerical weather prediction (NWP) systems through assimilation. Therefore, many weather prediction centers incorporate CSRs at water vapor (WV) bands, which provide information about temperature and WV content in the mid-to-upper troposphere. The Japan Meteorological Agency has also been assimilating these data into its operational global NWP system.
ASR assimilation is expected to provide greater benefits to NWP systems over CSR assimilation. Specifically, it will provide larger observation coverage and much information on cloud and its related variables. Furthermore, there is a merit in avoiding sampling bias, which is a significant issue in CSR assimilation. However, ASR assimilation presents several tougher challenges compared to CSR assimilation. For example, in the NWP system, achieving higher accuracy in cloud representation is necessary, along with the requirement to consider absorption and scattering processes in the radiative transfer model.
Okamoto et al. (2023) successfully addressed these challenges and achieved an impact on NWP surpassing CSR through the assimilation of Himawari-8 ASR data. We have extended this method to include GEO satellites in Europe, such as Meteosat Second Generation, and one in the United States, GOES-16. In the presentation, we'll compare the impacts of ASR and CSR assimilation and introduce the remaining challenges in achieving impacts surpassing CSR assimilation through ASR assimilation globally.
ASR assimilation is expected to provide greater benefits to NWP systems over CSR assimilation. Specifically, it will provide larger observation coverage and much information on cloud and its related variables. Furthermore, there is a merit in avoiding sampling bias, which is a significant issue in CSR assimilation. However, ASR assimilation presents several tougher challenges compared to CSR assimilation. For example, in the NWP system, achieving higher accuracy in cloud representation is necessary, along with the requirement to consider absorption and scattering processes in the radiative transfer model.
Okamoto et al. (2023) successfully addressed these challenges and achieved an impact on NWP surpassing CSR through the assimilation of Himawari-8 ASR data. We have extended this method to include GEO satellites in Europe, such as Meteosat Second Generation, and one in the United States, GOES-16. In the presentation, we'll compare the impacts of ASR and CSR assimilation and introduce the remaining challenges in achieving impacts surpassing CSR assimilation through ASR assimilation globally.