Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation

ZHAO Yiding; YIN Xunqiang; SONG Yajuan; QIAO Fangli

doi:10.1007/s13131-019-1366-x

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Article Navigation > Acta Oceanologica Sinica > 2019 > 38(1): 5-12

ZHAO Yiding, YIN Xunqiang, SONG Yajuan, QIAO Fangli. Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation[J]. Acta Oceanologica Sinica, 2019, 38(1): 5-12. doi: 10.1007/s13131-019-1366-x

Citation:

ZHAO Yiding, YIN Xunqiang, SONG Yajuan, QIAO Fangli. Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation[J]. Acta Oceanologica Sinica, 2019, 38(1): 5-12. doi: 10.1007/s13131-019-1366-x

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Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation

doi: 10.1007/s13131-019-1366-x

1.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China;First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
2.
First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266071, China;Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China

Received Date: 2017-09-10

Abstract

Abstract

The seasonal prediction of sea surface temperature (SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model (FIO-ESM) is assessed in this study. The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993-2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for mid-latitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions. The average skill of the North Pacific variability (NPV) index from 1 to 6 months lead is as high as 0.72 (0.55) when El Niño-Southern Oscillation and NPV are in phase (out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6% (23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction.
- seasonal prediction,
- North Pacific,
- sea surface temperature,
- precipitation,
- FIO-ESM climate model

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References(51)

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