scholarly journals Statistical Modeling of RPCA-FCM in Spatiotemporal Rainfall Patterns Recognition

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 145
Siti Mariana Che Mat Nor ◽  
Shazlyn Milleana Shaharudin ◽  
Shuhaida Ismail ◽  
Sumayyah Aimi Mohd Najib ◽  
Mou Leong Tan ◽  

This study was conducted to identify the spatiotemporal torrential rainfall patterns of the East Coast of Peninsular Malaysia, as it is the region most affected by the torrential rainfall of the Northeast Monsoon season. Dimension reduction, such as the classical Principal Components Analysis (PCA) coupled with the clustering approach, is often applied to reduce the dimension of the data while simultaneously performing cluster partitions. However, the classical PCA is highly insensitive to outliers, as it assigns equal weights to each set of observations. Hence, applying the classical PCA could affect the cluster partitions of the rainfall patterns. Furthermore, traditional clustering algorithms only allow each element to exclusively belong to one cluster, thus observations within overlapping clusters of the torrential rainfall datasets might not be captured effectively. In this study, a statistical model of torrential rainfall pattern recognition was proposed to alleviate these issues. Here, a Robust PCA (RPCA) based on Tukey’s biweight correlation was introduced and the optimum breakdown point to extract the number of components was identified. A breakdown point of 0.4 at 85% cumulative variance percentage efficiently extracted the number of components to avoid low-frequency variations or insignificant clusters on a spatial scale. Based on the extracted components, the rainfall patterns were further characterized based on cluster solutions attained using Fuzzy C-means clustering (FCM) to allow data elements to belong to more than one cluster, as the rainfall data structure permits this. Lastly, data generated using a Monte Carlo simulation were used to evaluate the performance of the proposed statistical modeling. It was found that the proposed RPCA-FCM performed better using RPCA-FCM compared to the classical PCA coupled with FCM in identifying the torrential rainfall patterns of Peninsular Malaysia’s East Coast.

2018 ◽  
Vol 7 (4.35) ◽  
pp. 760
F. S. Buslima ◽  
R. C. Omar ◽  
Tajul Anuar Jamaluddin ◽  
Hairin Taha

Floods are natural phenomena of geo-hazards that usually happened when experiencing prolonged heavy rainfalls. Floods in Malaysia can be categorized into monsoon floods and flash floods. Monsoon floods is caused of Northeast Monsoon season commences in early November and ends in March that brings heavy rainfall, particularly to the east coast states of Peninsular Malaysia and western Sarawak. Flash floods usually occur in areas with rapid development by a rapid rise in water level, high velocity, and large amounts of debris. Flooding that occurred in December 2014 can be classified as worst floods that affected several states in Peninsular Malaysia, and the worst affected is Kelantan state. This disaster was recorded more than 200,000 people were affected with 21 people were killed and gives a massive impact on people, properties, agriculture, livestock, and infrastructure facilities. Following the worst floods that hit Malaysia in 2014, the opinions and views from various parties such as subject matter experts was needed to produce mitigations and prevents of the flood disaster at once to minimize vulnerability to hazard.

Shazlyn Milleana Shaharudin ◽  
Norhaiza Ahmad ◽  
Siti Mariana Che Mat Nor

This paper presents a modified correlation in principal component analysis (PCA) for selection number of clusters in identifying rainfall patterns. The approach of a clustering as guided by PCA is extensively employed in data with high dimension especially in identifying the spatial distribution patterns of daily torrential rainfall. Typically, a common method of identifying rainfall patterns for climatological investigation employed T mode-based Pearson correlation matrix to extract the relative variance retained. However, the data of rainfall in Peninsular Malaysia involved skewed observations in the direction of higher values with pure tendencies of values that are positive. Therefore, using Pearson correlation which was basing on PCA on rainfall set of data has the potentioal to influence the partitions of cluster as well as producing exceptionally clusters that are eneven in a space with high dimension. For current research, to resolve the unbalanced clusters challenge regarding the patterns of rainfall caused by the skewed character of the data, a robust dimension reduction method in PCA was employed. Thus, it led to the introduction of a robust measure in PCA with Tukey’s biweight correlation to downweigh observations along with the optimal breakdown point to obtain PCA’s quantity of components. Outcomes of this study displayed a highly substantial progress for the robust PCA, contrasting with the PCA-based Pearson correlation in respects to the average amount of acquired clusters and indicated 70% variance cumulative percentage at the breakdown point of 0.4.

2014 ◽  
Vol 71 (4) ◽  
Muhammad Faiz Pa'suya ◽  
Kamaludin Mohd Omar ◽  
Benny N. Peter ◽  
Ami Hassan Md Din ◽  
Mohd Fadzil Mohd Akhir

The sea surface circulation pattern over the coast of Peninsula Malaysia's East Coast during Northeast Monsoon (NE) and Southwest Monsoon (SW) are derived using the seasonally averaged sea level anomaly (SLA) data from altimetric data and 1992-2002 Mean Dynamic Ocean Topography. This altimetric data has been derived from multi-mission satellite altimeter TOPEX, ERS-1, ERS-2, JASON-1, and ENVISAT for the period of nineteen years (1993 to 2011) using the Radar Altimeter Database System (RADS). The estimated sea level anomaly (SLA) have shown similarity in the pattern of sea level variations observed by four tide gauges. Overall, the sea surface circulations during the NE and SW monsoons shows opposite patterns, northward and southward respectively. During the SW monsoon, an anti-cyclonic circulation has been detected around the Terengganu coastal area centred at (about 5.5° N 103.5° E) and nearly consistent with previous study using numerical modelling. The estimated geostrophic current field from the altimeter is consistent with the trajectories of Argos-tracked Drifting Buoys provided by the Marine Environmental Data Services (MEDS) in Canada.

2009 ◽  
Vol 6 (4) ◽  
pp. 5471-5503 ◽  
C. L. Wong ◽  
R. Venneker ◽  
S. Uhlenbrook ◽  
A. B. M. Jamil ◽  
Y. Zhou

Abstract. This study analyzed and quantified the spatial patterns and time-variability of rainfall in Peninsular Malaysia on monthly, yearly and monsoon temporal scales. We first obtained an overview of rainfall patterns through the analysis of 16 point data sources. The results led to choosing three distinct regions, i.e.~the east coast, inland and west coast regions. For detailed analysis, Shepard's interpolation scheme was applied to the station data to produce daily rainfall fields on a 0.05 degree resolution grids for the period 1971–2006. The rainfall characteristics in time and space derived from a frequency analysis were found to be distinctly different in these three regions. In the east coast region, monthly rainfall shows a significant periodicity dominated by an annual cycle, followed by a half-year cycle. The inland and west coast regions show that the dominant periodic fluctuations in the monthly rainfall are dominated by a half-year cycle, followed by an annual cycle. The long-term rainfall variability analysis shows that the dry and wet conditions in Peninsular Malaysia are not primarily governed by the ENSO events. The results from the individual regions suggest that although the relative variability is influenced by ENSO, local and regional conditions have an effect on the interannual rainfall variability, which is superimposed on the large-scale weather conditions. A significant increasing trends in annual rainfall (9.3 mm/year) and northeast monsoon rainfall (6.2 mm/monsoon) were only detected in the west coast region. No trend was found in the monthly rainfall, except for November in the west coast region. The spatial variation analysis shows that the east coast region, which received substantially higher amounts of rainfall during the northeast monsoon, has lower spatial rainfall variability and a more uniform rainfall distribution than other regions. A larger range for the monthly spatial variation was observed in the west coast region.

S.M. Shaharudin ◽  
N. Ahmad ◽  
N.H. Zainuddin ◽  
N.S. Mohamed

A robust dimension reduction method in Principal Component Analysis (PCA) was used to rectify the issue of unbalanced clusters in rainfall patterns due to the skewed nature of rainfall data. A robust measure in PCA using Tukey’s biweight correlation to downweigh observations was introduced and the optimum breakdown point to extract the number of components in PCA using this approach is proposed. A set of simulated data matrix that mimicked the real data set was used to determine an appropriate breakdown point for robust PCA and  compare the performance of the both approaches. The simulated data indicated a breakdown point of 70% cumulative percentage of variance gave a good balance in extracting the number of components .The results showed a  more significant and substantial improvement with the robust PCA than the PCA based Pearson correlation in terms of the average number of clusters obtained and its cluster quality.

2012 ◽  
Omar Yaakob ◽  
Peng Chau Quah

Kertas kerja ini membentangkan hasil kajian mengenai kesan cuaca ke atas industri perikanan di Semenanjung Malaysia. Kajian ini dilakukan dengan tujuan untuk menentukan perhubungan yang jelas antara operasi menangkap ikan dan cuaca terutama di musim tengkujuh. Kertas kerja ini difokuskan kepada corak ombak dan angin dan kesannya ke atas kebolehoperasian bot perikanan, tangkapan, kesediaadaan dan harga ikan. Kesan ke atas aktiviti nelayan dan pendapatan akibat cuaca buruk juga dibincangkan. Keputusan yang diperolehi menunjukkan pertalian rapat antara cuaca dan operasi menangkap ikan dan seterusnya pendapatan nelayan. Kajian ini juga menyimpulkan bahawa kesan cuaca lebih ketara bagi nelayan Pantai Timur berbanding nelayan Pantai Barat. Kata kunci: Kesan cuaca, bot perikanan, operasi perikanan, tengkujuh This paper presents the results of a study of the effect of weather downtime on the fishing industry in Peninsular Malaysia. The study was carried out with the aim of establishing a clearer relationship between weather and fishing operation, especially during monsoon season. This paper focused on the wind and wave pattern and their effects on fishing boat operability, fish landing, fish availability, and price. The effect on the fishermen activity and income as a result of the weather down time was also discussed. The result of the study has indicated that there is a close relationship between weather and fishing operation as well as fishermen’s income. The study also concluded that weather has been significantly affecting the East Coast fishermen compared with their West Coast counterparts. Key words: Weather downtime, fishing boats, fishing operation, monsoon

2015 ◽  
Vol 802 ◽  
pp. 89-94 ◽  
Mohd Khairul Azuan Muhammad ◽  
T.A. Majid ◽  
Noram I. Ramli ◽  
S.N.C. Deraman ◽  
Farah Alwani Wan Chik

Strong wind is an annual natural hazard in Malaysia due to the geographical location. The northeast monsoon season usually commences in early November and ends in March. During this season, steady easterly or northeasterly winds of 10 to 20 knots prevail. The strong wind events such as hurricane and storms often caused severe damage to the large number of low rise building especially at the roofing system. At end of year 2014, the series of thunderstorm hit the Northern area of Peninsular Malaysia and caused million ringgit losses. This paper is focused on the roofing system failure of the low rise houses at the rural area that constitute the great majority of the infrastructure in less affluent communities. These non-engineered structures are typically built with very little, or no technical engineering input, and are often the product of varied building traditions and cultures.

2013 ◽  
Vol 63 (2) ◽  
Wei Lun Tan ◽  
Fadhilah Yusof ◽  
Zulkifli Yusop

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 quantile-quantile 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.

2021 ◽  
Vol 11 (1) ◽  
Nurul Diana Dzaraly ◽  
Mohd Nasir Mohd Desa ◽  
AbdulRahman Muthanna ◽  
Siti Norbaya Masri ◽  
Niazlin Mohd Taib ◽  

AbstractPilus has been recently associated with pneumococcal pathogenesis in humans. The information regarding piliated isolates in Malaysia is scarce, especially in the less developed states on the east coast of Peninsular Malaysia. Therefore, we studied the characteristics of pneumococci, including the piliated isolates, in relation to antimicrobial susceptibility, serotypes, and genotypes at a major tertiary hospital on the east coast of Peninsular Malaysia. A total of 100 clinical isolates collected between September 2017 and December 2019 were subjected to serotyping, antimicrobial susceptibility test, and detection of pneumococcal virulence and pilus genes. Multilocus sequence typing (MLST) and phylogenetic analysis were performed only for piliated strains. The most frequent serotypes were 14 (17%), 6A/B (16%), 23F (12%), 19A (11%), and 19F (11%). The majority of isolates were resistant to erythromycin (42%), tetracycline (37%), and trimethoprim-sulfamethoxazole (24%). Piliated isolates occurred in a proportion of 19%; 47.3% of them were multidrug-resistant (MDR) and a majority had serotype 19F. This study showed ST236 was the most predominant sequence type (ST) among piliated isolates, which was related to PMEN clone Taiwan19F-14 (CC271). In the phylogenetic analysis, the piliated isolates were grouped into three major clades supported with 100% bootstrap values. Most piliated isolates belonged to internationally disseminated clones of S. pneumoniae, but pneumococcal conjugate vaccines (PCVs) have the potential to control them.

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