RIKEN - Data Assimilation Research Team

Data Assimilation Seminar Series

Affiliation	University of the Ryukyus, MRI
Title	Advanced data assimilation techniques for predicting tropical cyclone intensities
Abstract	Abstract: Since tropical cyclones (TCs) are often highly destructive, their intensity prediction has been of particular importance for disaster prevention and mitigation. Considering the energy balance of a TC, it is presumably beneficial to diminish uncertainties in the values of air-sea exchange coefficients as well as initial condition through sophisticated data assimilation techniques. We will show the updated air-sea exchange coefficients yield persistent improvements in the TC intensity modelling with an idealized atmosphere-ocean model and JMA-NHM. We will also discuss predictions of four intense TCs approached to Japan by comparing 4D-Var-Bnmc, EnKF, and hybrid 4D-Var-Benkf, all of which are based on the JMA-NHM. Here, we consider two types of implementations for hybrid data assimilation system: spatial localization and neighboring ensemble approaches. Both hydrid systems and EnKF system are superior to 4D-Var-Bnmc in terms of TC track forecast, while hybrid systems are better than 4D-Var-Bnmc and EnKF in terms of TC intensity forecast.
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