Non-Homogeneous Hidden Markov Model for Daily Rainfall Amount in Peninsular Malaysia | Zendy

Wei Tan | Zendy; Fadhilah Yusof | Zendy; Zulkifli Yusop | Zendy

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Non-Homogeneous Hidden Markov Model for Daily Rainfall Amount in Peninsular Malaysia

Author(s) -

Wei Tan,

Fadhilah Yusof,

Zulkifli Yusop

Publication year - 2013

Publication title -

jurnal teknologi

Language(s) - English

Resource type - Journals

eISSN - 2180-3722

pISSN - 0127-9696

DOI - 10.11113/jt.v63.1916

Subject(s) - quantile , environmental science , climatology , homogeneous , principal component analysis , monsoon , flood myth , downscaling , meteorology , geography , precipitation , statistics , mathematics , geology , archaeology , combinatorics

The non-homogeneous hidden Markov model (NHMM) generates the rainfall observation depends on few weather states which serve as a link between the large scale atmospheric measures. The daily rainfall at 20 stations from Peninsular Malaysia for 33 years sequences is analyzed using NHMM during the northeast monsoon season. A NHMM with six hidden states are identified. The atmospheric variable was obtained from NCEP Reanalysis Data as predictor. The gridded atmospheric fields are summarized through the principle component analysis (PCA) technique. PCA is applied to sea level pressure (SLP) to identify their principal spatial patterns co-varying with rainfall. The NHMM can accurately simulate the observed daily mean rainfall, correlations between stations for daily rainfall amounts and the quantilequantile plots. It can be concluded that the NHMM is a useful method to simulate the daily rainfall amounts that may be used to prepare strategies and planning for the unpredicted disaster such as flood and drought.

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