Merging is an estimation technique used to improve the accuracy of rainfall predictions by combining two rainfall predictions. In fact, the performance of remote sensing estimates varies in each place and time where the influence of the time has a relationship with the global weather phenomenon. The aim of this study is to investigate the influence of the two most influential phenomena on rainfall in the Indonesian maritime continent: the monsoon and Madden–Julian Oscillation. This assessment also analyzed the impact of rainfall intensity. While the change in correlation, root-mean-square-error (RMSE) and mean-absolute-error (MAE) will be used to assess the effectiveness of merging of monsoons and MJO. The result shows that the intensity of rainfall apparently affect the accuracy of merging, where the moderate-intensity has low RMSE and MAE and high correlation compared to heavy or very heavy rainfall. While comparing other phases and season found, the 5th phase of MJO and rainy seasons have the best performance. Moreover, among modification methods, the modification of conditional merging (CM) is the best merging technique for all seasons and MJO’s phases.

中文翻译：

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印度尼西亚海洋大陆降雨强度，季风和MJO对降雨合并的影响

合并是一种估计技术，用于通过组合两个降雨预测来提高降雨预测的准确性。实际上，在每个时间和地点的影响都与全球天气现象有关的地方，遥感估算的性能会有所不同。这项研究的目的是调查两个影响最大的现象对印度尼西亚海洋大陆的降雨的影响：季风和马登—朱利安涛动。该评估还分析了降雨强度的影响。虽然相关性发生了变化，但均方根误差（RMSE）和均值绝对误差（MAE）将用于评估季风和MJO合并的有效性。结果表明，降雨强度明显影响合并的准确性，与强降雨或强降雨相比，中强度的RMSE和MAE低，相关性高。在比较发现的其他阶段和季节时，MJO和雨季的第5阶段表现最佳。此外，在修改方法中，条件合并（CM）的修改是所有季节和MJO阶段的最佳合并技术。