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Short duration rainfall data are required for certain hydrological risk assessments. However, short timescale rainfall intensity records are still scarce due to the high cost and low reliability of the monitoring systems. One way to solve this problem is by disaggregating rainfall data using stochastic methods. This study used the Bartlett Lewis Rectangular Pulse model to disaggregate daily rainfall into hourly rainfall for ten stations in the central region of Peninsular Malaysia. The performance of the model was evaluated on its ability to reproduce statistical properties, namely the mean and standard deviation, derived from the historical records over the disaggregated rainfall. The disaggregation of daily to hourly rainfall produced daily and hourly means that closely matched the historical records. However, the standard deviations of the disaggregated daily rainfall were lower than the historical values. Despite the significant differences in the standard deviation, both data series exhibit similar patterns and the model adequately preserved the trends of all the statistical properties used in evaluating its performance. 相似文献
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Networks of rain gauges can provide a better insight into the spatial and temporal variability of rainfall, but they tend to be too widely spaced for accurate estimates. A way to estimate the spatial variability of rainfall between gauge points is to interpolate between them. This paper evaluates the spatial autocorrelation of rainfall data in some locations in Peninsular Malaysia using geostatistical technique. The results give an insight on the spatial variability of rainfall in the area, as such, two rain gauges were selected for an in-depth study of the temporal dependence of the rainfall data-generating process. It could be shown that rainfall data are affected by nonlinear characteristics of the variance often referred to as variance clustering or volatility, where large changes tend to follow large changes and small changes tend to follow small changes. The autocorrelation structure of the residuals and the squared residuals derived from autoregressive integrated moving average (ARIMA) models were inspected, the residuals are uncorrelated but the squared residuals show autocorrelation, and the Ljung–Box test confirmed the results. A test based on the Lagrange multiplier principle was applied to the squared residuals from the ARIMA models. The results of this auxiliary test show a clear evidence to reject the null hypothesis of no autoregressive conditional heteroskedasticity (ARCH) effect. Hence, it indicates that generalized ARCH (GARCH) modeling is necessary. An ARIMA error model is proposed to capture the mean behavior and a GARCH model for modeling heteroskedasticity (variance behavior) of the residuals from the ARIMA model. Therefore, the composite ARIMA–GARCH model captures the dynamics of daily rainfall in the study area. On the other hand, seasonal ARIMA model became a suitable model for the monthly average rainfall series of the same locations treated. 相似文献
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ABSTRACTThis study assesses the performance of Fourier series in representing seasonal variations of the tropical rainfall process in Malaysia. Fourier series are incorporated into a spatial-temporal stochastic model in an attempt to make the model parsimonious and, at the same time, capture the annual variation of rainfall distribution. In view of Malaysia’s main rainfall regime, the model is individually fitted for two regions with distinctive rainfall profiles: one being an urban area receiving rainfall from convective activities whilst the other receives rainfall from monsoonal activities. Since both regions are susceptible to floods, the study focuses on the rainfall process at fine resolution. Fourier series equations are developed to represent the model’s parameters to describe their annual periodicity. The number of significant harmonics for each parameter is determined by inspecting the cumulative fraction of total variance explained by the significant harmonics. Results reveal that the number of significant harmonics assigned for the parameters is slightly higher in the region with monsoonal rains. The overall simulation results show that the proposed model is capable of generating tropical rainfall series from convective and monsoonal activities.
Editor D. Koutsoyiannis Associate editor K. Hamed 相似文献
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Norzaida Abas Zalina M. Daud Fadhilah Yusof 《Theoretical and Applied Climatology》2014,118(3):597-607
A stochastic rainfall model is presented for the generation of hourly rainfall data in an urban area in Malaysia. In view of the high temporal and spatial variability of rainfall within the tropical rain belt, the Spatial–Temporal Neyman–Scott Rectangular Pulse model was used. The model, which is governed by the Neyman–Scott process, employs a reasonable number of parameters to represent the physical attributes of rainfall. A common approach is to attach each attribute to a mathematical distribution. With respect to rain cell intensity, this study proposes the use of a mixed exponential distribution. The performance of the proposed model was compared to a model that employs the Weibull distribution. Hourly and daily rainfall data from four stations in the Damansara River basin in Malaysia were used as input to the models, and simulations of hourly series were performed for an independent site within the basin. The performance of the models was assessed based on how closely the statistical characteristics of the simulated series resembled the statistics of the observed series. The findings obtained based on graphical representation revealed that the statistical characteristics of the simulated series for both models compared reasonably well with the observed series. However, a further assessment using the AIC, BIC and RMSE showed that the proposed model yields better results. The results of this study indicate that for tropical climates, the proposed model, using a mixed exponential distribution, is the best choice for generation of synthetic data for ungauged sites or for sites with insufficient data within the limit of the fitted region. 相似文献
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Tan Wei Lun Yusof Fadhilah Yusop Zulkifli 《Theoretical and Applied Climatology》2017,129(1-2):577-586
This study involves the modelling of a homogeneous hidden Markov model (HMM) on the northeast rainfall monsoon using 40 rainfall stations in Peninsular Malaysia for the period of 1975 to 2008. A six hidden states HMM was selected based on Bayesian information criterion (BIC), and every hidden state has distinct rainfall characteristics. Three of the states were found to correspond by wet conditions; while the remaining three states were found to correspond to dry conditions. The six hidden states were found to correspond with the associated atmospheric composites. The relationships between El Niño–Southern Oscillation (ENSO) and the sea surface temperatures (SST) in the Pacific Ocean are found regarding interannual variability. The wet (dry) states were found to be well correlated with a Niño 3.4 index which was used to characterize the intensity of an ENSO event. This model is able to assess the behaviour of the rainfall characteristics with the large scale atmospheric circulation; the monsoon rainfall is well correlated with the El Niño–Southern Oscillation in Peninsular Malaysia.
相似文献6.
Rainfall characterisation by application of standardised precipitation index (SPI) in Peninsular Malaysia 总被引：1，自引：1，他引：0
Fadhilah Yusof Foo Hui-Mean Jamaludin Suhaila Zulkifli Yusop Kong Ching-Yee 《Theoretical and Applied Climatology》2014,115(3-4):503-516
The interpretations of trend behaviour for dry and wet events are analysed in order to verify the dryness and wetness episodes. The fitting distribution of rainfall is computed to classify the dry and wet events by applying the standardised precipitation index (SPI). The rainfall amount for each station is categorised into seven categories, namely extremely wet, severely wet, moderately wet, near normal, moderately dry, severely dry and extremely dry. The computation of the SPI is based on the monsoon periods, which include the northeast monsoon, southwest monsoon and inter-monsoon. The trends of the dry and wet periods were then detected using the Mann–Kendall trend test and the results indicate that the major parts of Peninsular Malaysia are characterised by increasing droughts rather than wet events. The annual trends of drought and wet events of the randomly selected stations from each region also yield similar results. Hence, the northwest and southwest regions are predicted to have a higher probability of drought occurrence during a dry event and not much rain during the wet event. The east and west regions, on the other hand, are going through a significant upward trend that implies lower rainfall during the drought episodes and heavy rainfall during the wet events. 相似文献
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