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An assessment of Indian monsoon seasonal forecasts and mechanisms underlying monsoon interannual variability in the Met Office GloSea5-GC2 system

机译：大都会办公室GloSea5-GC2系统对印度季风季节预报和季风年际变化潜在机制的评估

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摘要

We assess Indian summer monsoon seasonal forecasts in GloSea5-GC2, the Met Office fully coupled subseasonal to seasonal ensemble forecasting system. Using several metrics, GloSea5-GC2 shows similar skill to other state-of-the-art seasonal forecast systems. The prediction skill of the large-scale South Asian monsoon circulation is higher than that of Indian monsoon rainfall. Using multiple linear regression analysis we evaluate relationships between Indian monsoon rainfall and five possible drivers of monsoon interannual variability. Over the time period studied (1992-2011), the El Nio-Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD) are the most important of these drivers in both observations and GloSea5-GC2. Our analysis indicates that ENSO and its teleconnection with Indian rainfall are well represented in GloSea5-GC2. However, the relationship between the IOD and Indian rainfall anomalies is too weak in GloSea5-GC2, which may be limiting the prediction skill of the local monsoon circulation and Indian rainfall. We show that this weak relationship likely results from a coupled mean state bias that limits the impact of anomalous wind forcing on SST variability, resulting in erroneous IOD SST anomalies. Known difficulties in representing convective precipitation over India may also play a role. Since Indian rainfall responds weakly to the IOD, it responds more consistently to ENSO than in observations. Our assessment identifies specific coupled biases that are likely limiting GloSea5-GC2 Indian summer monsoon seasonal prediction skill, providing targets for model improvement.
机译：我们评估了大都会办公室GloSea5-GC2中印度夏季季风的季节预报，将亚季节与季节总体预报系统完全结合。 GloSea5-GC2使用多个指标，显示出与其他最新的季节性预报系统相似的技能。南亚大季风环流的预报技术要高于印度季风降雨的预报技术。使用多元线性回归分析，我们评估了印度季风降雨与季风年际变化的五个可能驱动因素之间的关系。在研究期间（1992年至2011年），在观测和GloSea5-GC2中，厄尔尼诺-南方涛动（ENSO）和印度洋偶极子（IOD）是这些驱动器中最重要的。我们的分析表明，在GloSea5-GC2中可以很好地表示ENSO及其与印度降雨的遥相关。但是，在GloSea5-GC2中，IOD与印度降水异常之间的关系太弱，这可能限制了当地季风环流和印度降水的预测能力。我们表明，这种弱关系可能是由于耦合的平均状态偏差所致，该偏差限制了异常风强迫对SST变异性的影响，从而导致IOD SST异常。代表印度对流降水的已知困难也可能起作用。由于印度降雨对IOD的响应较弱，因此它对ENSO的响应比在观测中更为一致。我们的评估确定了可能会限制GloSea5-GC2印度夏季风季风季节预报技能的特定耦合偏差，为模型改进提供了目标。

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  • 来源
    《Climate dynamics》 |2017年第6期|1447-1465|共19页
  • 作者

    Johnson Stephanie J.; Turner Andrew; Woolnough Steven; Martin Gill; MacLachlan Craig;

  • 作者单位

    Univ Reading, Dept Meteorol, Natl Ctr Atmospher Sci, Earley Gate, Reading RG6 6BB, Berks, England|ECMWF, Reading RG2 9AX, Berks, England;

    Univ Reading, Dept Meteorol, Natl Ctr Atmospher Sci, Earley Gate, Reading RG6 6BB, Berks, England;

    Univ Reading, Dept Meteorol, Natl Ctr Atmospher Sci, Earley Gate, Reading RG6 6BB, Berks, England;

    Met Off Hadley Ctr, FitzRoy Rd, Exeter EX1 3PB, Devon, England;

    Met Off Hadley Ctr, FitzRoy Rd, Exeter EX1 3PB, Devon, England;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Indian monsoon; Seasonal forecasting; Indian Ocean dipole;

    机译：印度季风;季节预报;印度洋偶极子;

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