Skill of Indian summer monsoon rainfall prediction in multiple seasonal prediction systems
Skill of Indian summer monsoon rainfall prediction in multiple seasonal prediction systems
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DOI：
10.1007/s00382-018-4449-z
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发表时间：
2019-05-01
期刊：
影响因子：
4.6
通讯作者：
Mitra, Ashis K.
中科院分区：
文献类型：
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作者：
Jain, Shipra;Scaife, Adam A.;Mitra, Ashis K.
我们使用气候历史预测项目（CHFP）的季节性预测来研究多个气候模式在预测印度夏季风降水方面的技巧。从8个预测系统的季节性预测的多模式平均值显示出统计上显着的技能，预测印度季风降水在季节性提前期。快速收敛的热带降雨技能与合奏大小表明，季节性季风降雨预报的技能，提高只有轻微的多模式合奏（MME）的手段相比，单一的最熟练的系统。个别模特的技巧也有很大的差异。一些个体模型显示出高达0.6的相关性技能，这与MME平均值相似，而其他模型显示出低技能。我们还调查了空间平均预测季风降雨的技能的影响，并表明，预测平均在一个更大的面积比验证观测可以产生更高的技能，由于扩展的空间连贯性季风降雨的变化。我们还记录了当前季节性预测系统中的误差，并表明这些误差与厄尔尼诺南方涛动（ENSO）遥相关的误差比与平均降雨偏差的误差更密切相关。最后，我们研究了ENSO季风的关系，并确认这种关系可能是固定的，尽管在观测到的关系，这可以简单地解释为抽样变化的基本固定的遥相关ENSO和印度季风之间的波动。
We use seasonal forecasts from the Climate Historical Forecast Project (CHFP) to study the skill of multiple climate models in predicting Indian summer monsoon precipitation. The multi-model average of seasonal forecasts from eight prediction systems shows statistically significant skill for predicting Indian monsoon precipitation at seasonal lead times. Rapid convergence of tropical rainfall skill with ensemble size suggests that the skill of seasonal monsoon rainfall forecasts improves only marginally when using multi-model ensemble (MME) means as compared to the single most skillful system. There is also a large range in the skill of individual models. Some individual models show correlation skill as high as 0.6, which is similar to the MME mean, while others show low skill. We also investigate the effect of spatial averaging on the skill of predicting monsoon rainfall and show that the predictions averaged over a larger area than the verifying observations can yield higher skill due to the extended spatial coherence of monsoon rainfall variability. We also document current errors in seasonal prediction systems and show that these are more strongly related to the errors in El-Nino Southern Oscillation (ENSO) teleconnections than they are to mean rainfall biases. Finally, we examine the ENSO-monsoon relationship and confirm that this relationship is likely to be stationary, despite fluctuations in the observed relationship, which can simply be explained as sampling variability on an underlying stationary teleconnection between ENSO and the Indian monsoon.