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Impact of rainfall intensity, monsoon and MJO to rainfall merging in the Indonesian maritime continent

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Abstract

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.

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Acknowledgements

Data for this research was supported by the Indonesian Meteorological Agency (BMKG). The authors especially appreciate the Maros Climatology Station. R and python, especially wradlib an open source for radar library has been used for this study.

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Authors and Affiliations

  1. Department of Geography, Gadjah Mada University, Yogyakarta, 55281, Indonesia

    Giarno, Muhammad Pramono Hadi, Slamet Suprayogi & Sigit Herumurti

  2. Paotere Maritime Station, Meteorology Climatology and Geophysical Agency, Makassar, 90165, Indonesia

    Giarno

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Correspondence to Giarno.

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Communicated by Kavirajan Rajendran

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Giarno, Hadi, M.P., Suprayogi, S. et al. Impact of rainfall intensity, monsoon and MJO to rainfall merging in the Indonesian maritime continent. J Earth Syst Sci 129, 164 (2020). https://doi.org/10.1007/s12040-020-01427-8

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