Predictability Limit of Monsoon Intraseasonal Precipitation: An Implication of Central Indian Ocean Mode

Jianhuang Qin,Ruiqiang Ding,Lei Zhou,Baosheng Li

doi:10.3389/fmars.2021.809798

Abstract

The prediction of monsoonal precipitation during Indian summer monsoon (ISM) remains difficult. Due to the high correlation between the Central Indian Ocean (CIO) mode index and the ISM precipitation variability, the predictability limit of the CIO mode index is investigated by the non-linear local Lyapunov exponent (NLLE) method in observations. Results show that the predictability limit of the CIO mode index can reach 38 days during boreal summer (from June to September), which is close to the upper predictability limit of intraseasonal precipitation (up to 40 days), and higher than the predictability limits of dynamical monsoon indices (under 3 weeks) and boreal summer intraseasonal oscillation (BSISO) indices (around 30 days). Such high predictability limit of the CIO mode index is mainly attributable to the long predictability limits from the intraseasonal sea surface temperature (SST) and intraseasonal zonal wind, which are the components of the CIO mode. As a result, the CIO mode is expected to extend the predictability of monsoonal precipitation, and benefits to improve the prediction skills of the ISM.

Highlights

Precipitation during Indian summer monsoon (ISM) is the lifeline of billions of people living on the rim of the Indian Ocean
It shows that the predictability limit of the CIO mode index can reach
that of well-known monsoon indices and BSISO indices based on the NLLE method

Summary

Introduction

Precipitation during Indian summer monsoon (ISM) is the lifeline of billions of people living on the rim of the Indian Ocean. MISO can account for above 60% of total precipitation variance over the Bay of Bengal (BoB, Goswami, 2005; Waliser, 2006) during the ISM. A better prediction of monsoonal precipitation requires a better prediction on the intraseasonal rainfall anomalies. For the dynamical forecast, the prediction skill for total rainfall ranges from 2 to 3 weeks among different models (e.g., Fu et al, 2007; Abhilash et al, 2014; Jie et al, 2017). The prediction skill for intraseasonal rainfall during ISM is a little higher, which is up to 3 weeks (e.g., Goswami and Xavier, 2003; Fu et al, 2013)

Methods

Results

Conclusion