Markov chain analysis of southwest monsoon rainfall time-series data from 1951 to 2021 in areas with Type I Philippine climate

Authors

  • Gerard Anthony Delos Reyes Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
  • Nelio Altoveros Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
  • Renebeth Payod Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños

Abstract

Time-series rainfall data of the southwest monsoon were analyzed using the Markov chain to determine the tendencies of rainfall states in the areas with a Type I Philippine climate. We analyzed 71 years of rainfall data from June to September 1951 to 2021. Based on the computed stationary distribution, time-series rainfall data from Type I climate zones tend to lie in state R1 (0 mm to 5 mm) with long-term transition probability from any possible state to state R1 of πR1 = 0.551775 during the season. The long-term transition probability from any possible state to state R2 (6 mm to 25 mm) is πR2 = 0.28182, about half of the value for state R1. Classified rainfall states R3 to R6 have negligible long-term transition probabilities. These values correspond to the long-term tendencies of the rainfall state for the entire study period. Thus, daily rainfall from June to September mostly took place between the threshold of 0 mm to 5 mm for the past 71 years. This implies that the bulk of rainfall in Type I climate is concentrated on certain days, leaving the majority of remaining days to have dry to light rain weather.

Author Biographies

  • Nelio Altoveros, Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños

     

     

  • Renebeth Payod, Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños

     

     

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Published

2023-06-25

How to Cite

[1]
“Markov chain analysis of southwest monsoon rainfall time-series data from 1951 to 2021 in areas with Type I Philippine climate”, Proc. SPP, vol. 41, no. 1, pp. SPP–2023, Jun. 2023, Accessed: Mar. 24, 2026. [Online]. Available: https://proceedings.spp-online.org/article/view/SPP-2023-3D-04