Data Assimilation Seminar
Dr. Jing-Shan Hong (Oct. 25, 2018, 15:30-)
|Affiliation||Central Weather Bureau (CWB), Taiwan|
|Title||Re-Center algorithm on the Continuous Cycling Radar Data Assimilation: Multi-scale Blending Scheme|
The torrential rains result from the short duration extreme rainfall system is of most critical for the disaster prevention. However, the limited predictability is the essence of the short duration extreme rainfall system due to the multi-scale interaction, fast evolution and strong nonlinearity. The assimilation of the radar observation with rapid, continuous update cycle is a key to level up the predictability of such a system.
The continuous rapid update cycle is able to capture and keep convective-scale structure and avoid the model spin-up problems. However, many challenges were faced in the continuous update cycle data assimilation. For example, the limited-area model systems in general suffer a deﬁciency to effectively represent the large-scale features and are unavoidable to experience the obvious large-scale forecast errors. In particular, the domain size is restricted due to the compromise of increasing model resolution and limited computer resources. Furthermore, the model errors are ease to accumulate over the sparse observation area, especially as the data assimilation system configured as a continuous cycle mode.
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