Adding CO2 channel 16 to AHI data assimilation over land further improves short-range rainfall forecasts

• Main Author: Zhengkun Qin
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2020-01-01
• Series: Tellus: Series A, Dynamic Meteorology and Oceanography
• Subjects: data assimilation; geostationary satellite; ahi; land
• Online Access: http://dx.doi.org/10.1080/16000870.2020.1840210

The new generation of geostationary environmental operational satellite imager, the Himawari-8 Advanced Himawari Imager (AHI), adds two more water vapour channels and four more other channels than its predecessor, MTSAT-2. But except for the three water vapour channels, AHI channels are often not assimilated over land due to large uncertainty in surface parameters. Using the relative adjoint sensitivity analysis method, we show that the brightness temperature of AHI channel 16 is much more sensitive to the low-tropospheric atmosphere than to the surface emissivity, similar to those high-level water vapour channels. We thus assimilated AHI channel 16 brightness temperature observations together with AHI water vapour channels over land, and assessed the added benefits on short-range quantitative precipitation forecasts for several convection-induced rainfall cases. Results show that adding channel 16 over land to AHI data assimilation further improves short-range rainfall forecasts. Assimilation of AHI channel 16 improves the upstream near surface atmospheric temperature analysis and influences the development of downstream precipitating weather systems.