Diagnosing SST Error Growth during ENSO Developing Phase in the BCC_CSM1.1(m) Prediction System

Abstract

In this study, the predictability of the El Niño-South Oscillation (ENSO) in an operational prediction model from the perspective of initial errors is diagnosed using the seasonal hindcasts of the Beijing Climate Center System Model, BCC_CSM1.1(m). Forecast skills during the different ENSO phases are analyzed and it is shown that the ENSO forecasts appear to be more challenging during the developing phase, compared to the decay phase. During ENSO development, the SST prediction errors are significantly negative and cover a large area in the central and eastern tropical Pacific, thus limiting the model skill in predicting the intensity of El Niño. The large-scale SST errors, at their early stage, are generated gradually in terms of negative anomalies in the subsurface ocean temperature over the central-western equatorial Pacific, featuring an error evolutionary process similar to that of El Niño decay and the transition to the La Niña growth phase. Meanwhile, for short lead-time ENSO predictions, the initial wind errors begin to play an increasing role, particularly in linking with the subsurface heat content errors in the central-western Pacific. By comparing the multiple samples of initial fields in the model, it is clearly found that poor SST predictions of the Niño-3.4 region are largely due to contributions of the initial errors in certain specific locations in the tropical Pacific. This demonstrates that those sensitive areas for initial fields in ENSO prediction are fairly consistent in both previous ideal experiments and our operational predictions, indicating the need for targeted observations to further improve operational forecasts of ENSO.

摘要

本文基于国家气候中心气候预测模式BCC_CSM1.1(m),从初始误差增长的角度探讨了厄尔尼诺-南方涛动(ENSO)的可预测性问题。考察了ENSO发展和衰减位相的预测表现,结果指出相比于ENSO衰减位相,模式对ENSO发展位相的预测技巧更低,此时赤道中东太平洋海表温度呈现大范围的“冷”预报偏差。误差诊断表明上述“冷”偏差源于初始时刻赤道中西太平洋次表层的海温负异常,其误差演变类似于一次厄尔尼诺衰减、随后拉尼娜发展的过程。同时,对于超前6个月及以下的ENSO预测,风场的初始误差影响出现,并与赤道中西太平洋的次表层热含量误差紧密相连。通过对模式多初始样本的比较分析,进一步揭示了Niño-3.4海区海温预测较差的主要原因是热带太平洋特定位置存在的初始误差。无论是前人的理想模型,还是本文的业务模式,ENSO预测对应的初始敏感区基本一致,因此,本文可为通过优化目标观测来进一步改善ENSO的业务预测提供科学指导。