Stochastic Modeling of Rainfall Series in Kelantan Using an Advanced Weather Generator

A. H. Syafrina, A. Norzaida, O. Noor Shazwani

Abstract


Weather generator is a numerical tool that uses existing meteorological records to generate series of synthetic weather data. The AWE-GEN (Advanced Weather Generator) model has been successful in producing a broad range of temporal scale weather variables, ranging from the high-frequency hourly values to the low-frequency inter-annual variability. In Malaysia, AWE-GEN has produced reliable projections of extreme rainfall events for some parts of Peninsular Malaysia. This study focuses on the use of AWE-GEN model to assess rainfall distribution in Kelantan. Kelantan is situated on the north east of the Peninsular, a region which is highly susceptible to flood. Embedded within the AWE-GEN model is the Neyman Scott process which employs parameters to represent physical rainfall characteristics. The use of correct probability distributions to represent the parameters is imperative to allow reliable results to be produced. This study compares the performance of two probability distributions, Weibull and Gamma to represent rainfall intensity and the better distribution found was used subsequently to simulate hourly scaled rainfall series. Thirty years of hourly scaled meteorological data from two stations in Kelantan were used in model construction. Results indicate that both probability distributions are capable of replicating the rainfall series at both stations very well, however numerical evaluations suggested that Gamma performs better. Despite Gamma not being a heavy tailed distribution, it is able to replicate the key characteristics of rainfall series and particularly extreme values. The overall simulation results showed that the AWE-GEN model is capable of generating tropical rainfall series which could be beneficial in flood preparedness studies in areas vulnerable to flood.


Keywords


weather generator; flood; rainfall intensity; probability distribution; northeastern monsoon

Full Text:

PDF

References


References

D. S. Wilks, R. L. Wilby, “The Weather Generation Game: A Review of Stochastic Weather Models”, Progress in Physical Geography, Vol. 23, No. 3, pp. 329-357, 1999

M. Kevin, R. Ramesh, O. John, A. Imran, G. Bahram, “Evaluation of weather generator ClimGen for southern Ontario”, Canadian Water Resources Journal, Vol. 30, No. 4, pp. 315-330, 2005

C. W. Richardson, “Stochastic simulation of daily precipitation, temperature, and solar radiation”, Water Resources Research, Vol. 17, No. 1, pp. 182–190, 1981

C. W. Richardson, D. A. Wright, WGEN: A model for generating daily weather variables, US Department of Agriculture, Agricultural Research Service, ARS-8, 1984

A. D. Nicks, L. J. Lane, G. A. Gander, “Weather generator”, in: USDA_Water Erosion Prediction Project: Hillslope Profile and Watershed Model Documentation, NSERL Report No. 10, Chapter 2, West Lafayette, 1995

M. A. Semenov, E. M. Barrow, “LARS-WG, A Stochastic Weather Generator for Use in Climate Impact Studies, User Manual”, Available at: http://resources.rothamsted.ac.uk/sites/default/files/groups/mas-

models/download/LARS-WG-Manual.pdf, 2002

C. G. Kilsby, P. Jones, A. Burton, A. Ford, H. Fowler, C. Harpham, P. James, A. Smith, R. L. Wilby, “A Daily Weather Generator for Use in Climate Change Studies”, Environmental Modelling and Software, Vol. 22, No. 12, pp. 1705–1719, 2007

M. Dubrovsky, J. Buchteke, Z. Zalud, “High-frequency and low-frequency variability in stochastic daily weather generator and its effect on agricultural and hydrologic modeling”, Climatic Change, Vol. 63, No. 145-179, pp. 1123-1130, 2004

Q. J. Wang, R. J. Nathan, “A method for coupling daily and monthly time scales in stochastic generation of rainfall series”, Journal of Hydrology, Vol. 346, No. 3-4, pp. 122–130, 2007

D. E. Keller, A weather generator for current and future climate conditions, PhD Thesis, ETH-Zurich 2015

E. M. Furrer, R. W. Katz, “Improving the simulation of extreme precipitation events by stochastic weather generators”, Water Resources Research, Vol. 44, No. 12, 2008

J. Chen, F. P. Brissette, R. Leconte, “Uncertainty of Downscaling Method in Quantifying the Impact of Climate Change on Hydrology”, Journal of Hydrology, Vol. 401, No. 3-4, pp. 190-202, 2011

M. A. Semenov, “Simulation of Extreme Weather Events by a Stochastic Weather Generator”, Climate Research, Vol. 35, pp. 203-212, 2008

S. Mehan, T. Guo, M. W. Gitau, D. C. Flanagan, “Comparative study of different stochastic weather generators for long-term climate data simulation”, Climate, Vol. 5, No. 26, 2017

S. Fatichi, V. Y. Ivanov, E. Caporali, “Simulation of Future Climate Scenarios with a Weather Generator”, Advances in Water Resources, Vol. 34, No. 4, pp. 448-467, 2011

A. H. Syafrina, M. D. Zalina L. Juneng, “Historical trend of hourly extreme rainfall in Peninsular Malaysia”, Theoretical & Applied Climatology, Vol. 120, No. 1, pp. 259–285, 2015

I. Rodriguez-Iturbe, P. S. Eagleson, “Mathematical Models of Rainstorm Events in Space and Time”, Water Resources Research, Vol. 23 No.1, pp. 181-190, 1987

S. Dan'azumi, S. Shamsudin, A. Aris, “Modeling the distribution of rainfall intensity using hourly data”, American Journal of Environmental Sciences, Vol. 6, No. 3, pp. 238-243, 2010

Y. Fadhilah, M. D. Zalina, V. T. V. Nguyen, Y. Zulkifli, “Performance of Mixed Exponential and Exponential Distribution Representing Rain Cell Intensity in Neyman-Scott Rectangular Pulse (NSRP) Model”, Malaysian Journal of Civil Engineering, Vol. 10, No. 1, pp. 55-72, 2007

A. Norzaida, M. D. Zalina, Y. Fadhilah, “A comparative study of Mixed Exponential and Weibull distributions in a stochastic model replicating a tropical rainfall process”, Theoretical & Applied Climatology, Vol. 118, pp. 597-607, 2014

A. Norzaida, M. D. Zalina, Y. Fadhilah, “Application of Fourier series in managing the seasonality of convective and monsoon rainfall”, Hydrological Sciences Journal, Vol. 61, No. 10, pp. 1967-1980, 2016

O. Zolina, A. Kapala, C. Simmer, S. K. Gulev, “Analysis of extreme precipitation over Europe from different reanalyses: A comparative assessment”, Global and Planetary Change, Vol. 44, No. 1-4, pp. 129–161, 2004




eISSN: 1792-8036     pISSN: 2241-4487