Decadal Variation of Predictability of the Indian Ocean Dipole during 1880–2017 Using an Ensemble Prediction System

Author:

Song Xunshu12,Tang Youmin342,Li Xiaojing12,Liu Ting12

Affiliation:

1. a State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China

2. b Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

3. c University of Northern British Columbia, Prince George, British Columbia, Canada

4. d College of Oceanography, Hohai University, Nanjing, China

Abstract

Abstract In this study, we investigate both the decadal variation of the Indian Ocean dipole (IOD) prediction skill and possible sources of this decadal variation. We use an ensemble long-term retrospective forecast experiment covering 1880–2017 that utilizes the Community Earth System Model (CESM). We find that the decadal variation of the IOD prediction skill is significant and that it varies with the lead time. We also find that the decadal variation of the IOD prediction skill for the target season of boreal autumn determines that for all initial conditions, regardless of the lead months. For short lead times, the decadal variations of the IOD strength and of the IOD precursor in the initial month of July are the major factors influencing the IOD prediction skill. This occurs because the IOD events are in the developmental phase, and the stronger IOD signal in the initial conditions leads to better predictions. For long lead times, the decadal variation of remote forcing by El Niño–Southern Oscillation (ENSO) and the ENSO precursor signal in the IOD influence the IOD prediction skill more significantly than do the strengths of the ENSO or the IOD. In addition, the analysis also indicated that the period with a low ENSO–IOD relationship has low predictability, not only because the ENSO little influence on IOD but also because the model biasedly overestimates the ENSO–IOD relationship. Significance Statement The Indian Ocean dipole (IOD) has strong climatic effects, both around the Indian Ocean and globally, which have strong impacts on human life and economic development. It is important to be able to predict IOD events accurately to mitigate those impacts. Here, we conducted a 138-yr prediction experiment using a state-of-the-art climate model to confirm the existence of a decadal variation in IOD predictability and to identify factors that influence the IOD prediction skill. The most important factors that influence the decadal variation of IOD prediction skill differ for 3-month and 6-month lead times, and additional studies will be necessary to clarify the specific factors responsible for these differences.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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