Effect of Various Propagation Types of Madden-Julian Oscillation (MJO) on 95th Extreme Probability Change in Indonesia
Dendi Setiabudi1*, Juni Tika Simanjuntak1,2, Banu Wijaya Yonas1,2, Dr. Rusmawan Suwarman, S.Si., M.T.1, Dr. Muhammad Rais Abdillah, S.Si., M.Sc.1

1 Faculty of Earth Sciences and Technology, Institut Teknologi Bandung, Bandung, Indonesia
*whitemailnew[at]gmail.com
2 Badan Meteorologi Klimatologi dan Geofisika (BMKG), Indonesia

Abstract

The Madden-Julian Oscillation (MJO) is the eastward propagation of cloud clusters and precipitation from the Indian Ocean to the Pacific Ocean [2]. Intraseasonal variability of rainfall in Indonesia region is dominated by the Madden-Julian Oscillation (MJO) [4]. Each MJO phase has different characteristics and influences from one another in Indonesia [1].

The impact of the MJO on extreme daily rainfall (x_MJO greater than equals x_c), namely the 95th extreme, is known by quantifying the difference in the probability of extreme daily rainfall during the MJO phases against the November-April (NDJFMA) (delta_P_MJO) in the equation from Xavier et al. [5]:

delta_P_MJO = ((P_MJO(x_MJO greater than equals x_c) - P_NDJFMA(x_NDJFMA greater than equals x_c))/P_NDJFMA(x_NDJFMA greater than equals x_c)*100% (1)

Recent research conducted by Wang et al. [3] regarding MJO propagation found that MJO has four propagation characteristics (stand, jump, fast, and slow). In this study, the difference in the 95th extreme probability is the impact of the characteristics of the four types of MJO propagation which differ from each other according to recent research by Wang et al. [3]. Quantification of the 95th extreme probability difference with seasonal time scales makes preparation in weather forecasting better. Increasing understanding of phenomena associated with extreme weather can improve the potential for extreme weather forecasting.

MJO identification according to Wang et al. [3], namely by using a band-pass filter frequency of 20-70 days against the daily average Outgoing Longwave Radiation (OLR) and certain criteria. Fast Forier Transform is applied to daily average OLR. The MJOs were identified according to certain criteria and grouped based on the similarity of propagation types using the k-mean clustering method. The Indonesia region is divided into 3 to create a matrix of regional opportunities from the 95th extreme probability difference and has 3 categories, areas from the 95th extreme probability difference >15% (positive chance), <15% (negative chance), and between >- 15% to <15% (normal chance). Slow and fast during active phases 2-4 in the Indian Ocean and Indonesian region (inactive phases 6-8 in the Pacific Ocean) are followed by an increase (decrease) in daily rainfall of 6 mm (-6 mm) and the probability of 95th extremes is 67-100% (-67 to -100%). Jump and stand do not propagate through Indonesian territory, but their active phase (inactive phases) approaches Indonesian territory and causes an increase in daily rainfall of 4 mm (-4 mm) and a probability of the 95th extreme of 33-67% (-67 to -100%). The regional probability of the 95th extreme probability difference has the same pattern as the four MJO types according to the criteria of Wang et al. [3], namely following propagation during the active and inactive phases.

References
Hidayat, R. and Kizu, S. (2010). Influence of the Madden-Julian Oscillation on Indonesian Rainfall Variability in Austral Summer. International Journal of Climatology.
Madden, R. A. and dan Julian, P. R. (1972a). Description of Global-Scale Circulation Cells in the Tropics with a 40-50 Day Period. Journal of the Atmospheric Sciences. 29(6). 1109-1123.
and Julian, P. R. (1972b). Description of Global-Scale Circulation Cells in the Tropics with a 40-50 Day Period. Journal of the Atmospheric Sciences. 29(6). 1109-1123.
Wang, B. G. Chen, and Liu, F. (2019). Diversity of the Madden-Julian Oscillation. Science Advance: Research Article.
Wheeler, M. C. and Hendon, H. H. (2004). An All-Season Real-Time Multivariate MJO Index: Development of an Index for Monitoring and Prediction. Monthly Weather Review. 132(8). 1917-1932.
Xavier, P., Rahmat, R., Cheong, W. K., and Wallace, E. (2014). Influence of Madden-Julian Oscillation on Southeast Asia Rainfall Extremes: Observations and Predictability. Geophysical Research Letter.

Keywords: Madden-Julian Oscillation, MJO phases, 95th extreme, 95th extreme probability difference, MJO types (stand, jump, fast, slow), band-pass filter, fast forier transform, k-mean clustering, probability matrix.

Topic: Probability and Stochastic Analysis