Data Assimilation Seminar
Prof. Shu-Chih Yang (October 1, 2020, 13:00-14:00)
|Affiliation||National Central University, Taiwan|
|Title||Recent improvements of the NCU convective-scale ensemble data assimilation system and their impact on short-term precipitation prediction in Taiwan.|
Radar data assimilation has been an essential component in convective-scale data assimilation in Taiwan. The observation error correlation is included recently for assimilating radial velocity to optimize the advantage of high-resolution radar data. Results with a heavy rainfall event show that the inclusion of observation error correlation provides more small-scale corrections, enhancing the local convergence for convection development. Compared with the experiment using independent observation error, the precipitation prediction, especially the probability, is improved with the inclusion of observation error correlation. Given that the radar measurement cannot directly observe the moisture variable improving the moisture analysis accuracy is relatively restrictive with radar data assimilation. The ground-based GNSS ZTD data provides fast moisture information that can fill in the gaps between radiosondes and satellites. The assimilation of the ground-based GNSS ZTD data with rapid update cycles can complement radar data in convective-scale data assimilation. In this talk, I will also discuss the added value from assimilating the ZTD data on precipitation prediction and the optimization of ZTD data assimilation.