A probabilistic forecast of the Kuroshio current path variability using an 80-member ensemble simulation.

Kunihiro Aoki; Yasumasa Miyazawa; Tsutomu Hihara

Presentation information

[J] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-OS Ocean Sciences & Ocean Environment

[A-OS17] Kuroshio Large Meander

Tue. May 28, 2019 10:45 AM - 12:15 PM 106 (1F)

convener:Toru Miyama(Japan Agency for Marine-Earth Science and Technology, Application Laboratory), Norihisa Usui(Meteorological Research Institute), Takashi Setou(National Research Institute of Fisheries Science, Fisheries Research and Education Agency), Chairperson:Toru Miyama, Takashi Setou, Norihisa Usui

11:45 AM - 12:00 PM

[AOS17-05] A probabilistic forecast of the Kuroshio current path variability using an 80-member ensemble simulation.

*Kunihiro Aoki¹, Yasumasa Miyazawa¹, Tsutomu Hihara¹ (1.JAMSTEC)

Keywords:Ensemble forecast, Data assimilation, Clustering

This study aims to describe the probabilistic behavior of the Kuroshio current path variability using an 80-member ensemble simulation in a high-resolution numerical regional ocean model, JCOPE. This simulation provides the outputs for 4 months starting from the initial conditions optimized by the data assimilation (LETKF) for one months. All the members are found to predict the non-large meander path at first 2 months, but some members predict the large meander path after that. We propose a method of quantifying the occurrence/non-occurrence of the branch, the probabilities of each path, and a set of the mean and spread for each path by a machine learning method.