[Postponed] The 242nd R-CCS Cafe - part 3

Weather forecasting and simulation are complex at different temporal-spatial scales, one of the reasons is that a broad range of physical parameterization is required. Recently, a novel method of parameter estimation using an ensemble-based data assimilation (DA) technique has been established and practiced in the physical schemes in the climatological simulation (e.g., Kotsuki et al., 2018, 2020; Sueki et al., 2022). In this talk, I would like to briefly introduce the DA-based parameter estimation method (e.g., by Extended Kalman filter) and a weather-DA system (SCALE-LETKF), produced by the Data assimilation Research Team and the Computational Climate Science Research Team. Finally, three main research topics using this weather-DA system now I am working on would like to be shared: estimating parameters of microphysics scheme in an ideal 2-dimension squall-line experiment, parameters of cumulus scheme in a real tropical-cyclone-induced precipitation, and parameters of dust scheme in a real dust emission simulation.