Archive | 2021
Evaluation of FIO-ESM v1.0 Seasonal Prediction Skills Over the North Pacific
Abstract
<p>Accurate prediction over the North Pacific, especially for the key parameter of sea<br>surface temperature (SST), remains a challenge for short-term climate prediction. In<br>this study, seasonal predicted skills of the First Institute of Oceanography Earth System<br>Model version 1.0 (FIO-ESM v1.0) over the North Pacific were assessed. Ensemble<br>adjustment Kalman filter (EAKF) and Projection Optimal Interpolation (Projection-OI) data<br>assimilation schemes were used to provide initial conditions for FIO-ESM v1.0 hindcasts<br>that were started from the first day of each month between 1993 and 2017. Evolution<br>and spacial distribution of SST anomalies over the North Pacific were reasonably<br>reproduced in EAKF and Projection-OI assimilation output. Two hindcast experiments<br>show that the skill of FIO-ESM v1.0 with the EAKF data assimilation scheme to predict<br>SST over the North Pacific is considerably higher than that with Projection-OI data<br>assimilation for all lead times of 1–6 months, especially in the central North Pacific where<br>the subsurface ocean temperature in the initial conditions is significantly improved by<br>EAKF data assimilation. For the Kuroshio–Oyashio extension (KOE) region, the errors<br>in the initial conditions have more rapid propagation resulting in large discrepancies<br>between simulated and observed values, which are reduced by inducing surface<br>waves into the climate model. Incorporation of realistic initial conditions and reasonable<br>physical processes into the coupled model is essential to improving seasonal prediction<br>skill. These results provide a solid basis for the development of operational seasonal<br>prediction systems for the North Pacific.</p>