All-Sky Assimilation of GOES-16 Water Vapor Channels in Consideration of Cloud-Dependent Interchannel Observation-Error Correlations

The Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-16 includes three water vapor channels (8, 9, 10). This study investigates an effective approach for assimilating the all-sky brightness temperatures (BTs) derived from these three water vapor channels while considering the characteristics of interchannel observation-error correlations (IOECs). The National Aeronautics and Space Administration (NASA) Unified Weather Research and Forecasting (NU-WRF) model, alongside the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI)-based three-dimensional ensemble-variational hybrid data assimilation (3DEnVAR) system, is utilized for this purpose. The IOECs with respect to the symmetric cloud proxy variable among these three channels are analyzed. The IOECs display sigmoid function characteristics, being lower and roughly invariant with respect to symmetric cloud proxy variables under clear sky conditions and higher in cloudy conditions. Different characteristics of IOECs in clear and cloudy skies can be understood by Jacobians. The eigenvalues and the conditional numbers of the observation error covariance matrix with IOECs will also be discussed. Given the unique properties of IOECs, sensitivity experiments with various configurations for assimilating the all-sky BTs from the three water vapor channels are conducted. Case studies of Hurricanes Laura (2020) and Ida (2021) are utilized. The results indicate that a strategy combining the assimilation of all-sky BTs from one of the GOES-16 channels, especially channel 10, with clear-sky BTs from the other water vapor channels yields superior analysis and forecasts in most scenarios, thereby highlighting the importance of appropriately estimating and accounting for cloud-dependent IOECs when assimilating all-sky BTs from the infrared channels in operational DA systems.