Sahar Hadipour, Sobri Harun, Ali Arefnia, Mahiuddin Alamgir


Three transfer function based statistical downscaling namely, linear regression model (LM), generalized linear model (GLM), generalized additive model (GAM) have been developed to assess their performance in downscaling monthly rainfall. Previous studies reported that performance of downscaling model depends on climate region and characteristics of climatic variable being downscaled. This has motivated to assess the performance of these three statistical downscaling models to identify most suitable model for downscaling monthly rainfall in the East coast of Peninsular Malaysia. Assessment of model performance using standard statistical measures revealed that LM model performs best in downscaling monthly precipitation in the study area. The Nash–Sutcliffe efficiency (NSE) for LM was found always greater than 0.9 and 0.7 with predictor set selected using stepwise multiple regression method during model calibration and validation, respectively. The finding opposes the general conception of better performance of non-linear models compared to linear models in downscaling rainfall. The near normal distribution of monthly rainfall in the tropical region has made the LM model much stronger compared to other models which assume that distribution of dependent variable is not normal.


Statistical downscaling, transfer function model, multiple linear regression, generalized linear model, generalized additive model.

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Wang, X. J., Zhang, J., Shahid, S., Guan, E., Wu, Y., Gao, J. and He, R. 2016. Adaptation to Climate Change Impacts on Water Demand. Mitigation and Adaptation Strategies for Global Change. 21(1): 81-99.

Shahid, S., Harun, S. B. and Katimon, A. 2012. Changes in Diurnal Temperature Range in Bangladesh during the Time Period 1961–2008. Atmospheric Research. 118: 260-270.

Olaniya, O. M., Pour, S. H., Shahid, S., Mohsenipour, M., Harun, S. B., Heryansyah, A. and Ismail, T. 2015. Trends in Rainfall and Rainfall-Related Extremes in the East Coast of Peninsular Malaysia. Journal of Earth System Science. 124(8): 1609-1622.

Shahid, S. 2012. Vulnerability of the Power Sector of Bangladesh to Climate Change and Extreme Weather Events. Regional Environmental Change. 12(3): 595-606.

Ahmed, K., Shahid, S., Haroon, S. B. and Wang, X. J. 2015. Multilayer Perceptron Neural Network for Downscaling Rainfall in Arid Region: A Case Study of Baluchistan, Pakistan. Journal of Earth System Science. 124(6): 1325-1341.

Pour, S. H., Harun, S. B. and Shahid, S. 2014. Genetic Programming for the Downscaling of Extreme Rainfall Events on the East Coast of Peninsular Malaysia. Atmosphere. 5(4): 914-936.

Solman, S. A. 2013. Regional climate modeling over South America: a review. Advances in Meteorology, 2013: 1-13.

Goyal, M. K. And Ojha, C. S. P. 2012. Downscaling of Surface Temperature for Lake Catchment in an Arid Region in India Using Linear Multiple Regression and Neural Networks. International Journal of Climatology. 32(4): 552-566.

Ahmadi, A., Moridi, A., Lafdani, E. K. And Kianpisheh, G. 2014. Assessment of Climate Change Impacts on Rainfall Using Large Scale Climate Variables and Downscaling Models–A Case Study. Journal of Earth System Science. 123(7): 1603-1618.

Haylock, M. R., Peterson, T. C., Alves, L. M., Ambrizzi, T., Anunciação, Y. M. T., Baez, J. and Vincent, L. A. 2006. Trends in Total and Extreme South American Rainfall in 1960-2000 and Links with Sea Surface Temperature. Journal of Climate. 19(8): 1490-1512.

Harpham, C. and Dawson, C. W. 2006. The Effect of Different Basis Functions on a Radial Basis Function Network for Time Series Prediction: A Comparative Study. Neurocomputing. 69(16): 2161-2170.

Cannon, A. J. 2008. Probabilistic Multisite Precipitation Downscaling By an Expanded Bernoulli-Gamma Density Network. Journal of Hydrometeorology. 9(6): 1284-1300.

Hashmi, M. Z., Shamseldin, A. Y. and Melville, B. W. 2011. Statistical Downscaling of Watershed Precipitation Using Gene Expression Programming (GEP). Environmental Modelling & Software. 26(12): 1639-1646.

McCullagh, P. and Nelder, J. A. 1989. Generalized Linear Models. 37 In Monograph on Statistics and Applied Probability.

Hastie, T. J. and Tibshirani, R. J. 1990. Generalized Additive Models. 43 In Monograph on Statistics and Applied Probability.

Salameh, T., Drobinski, P., Vrac, M. And Naveau, P. 2009. Statistical Downscaling of Near-Surface Wind over Complex Terrain in Southern France. Meteorology and Atmospheric Physics. 103(1-4): 253-265.

Tisseuil, C., Vrac, M., Lek, S. and Wade, A. J. 2010. Statistical Downscaling of River Flows. Journal of Hydrology. 385(1): 279-291.

Hu, Y., Maskey, S. and Uhlenbrook, S. 2013. Downscaling Daily Precipitation over the Yellow River Source Region in China: A Comparison of Three Statistical Downscaling Methods. Theoretical and Applied Climatology. 112(3-4): 447-460.

Liu, Y. and Fan, K. 2013. A New Statistical Downscaling Model for Autumn Precipitation in China. International Journal of Climatology. 33(6): 1321-1336.

Kigobe, M., Wheater, H. and McIntyre, N. 2014. Statistical Downscaling of Precipitation in the Upper Nile: Use of Generalized Linear Models (GLMs) for the Kyoga Basin. In: Nile River Basin . Springer International Publishing. pp. 421-449.

Farajzadeh, M., Oji, R., Cannon, A. J., Ghavidel, Y. and Bavani, A. M. 2014. An Evaluation of Single-Site Statistical Downscaling Techniques in terms of Indices of Climate Extremes for the Midwest of Iran. Theoretical and Applied Climatology. 120(1-2): 377-390.

Hertig, E., Seubert, S., Paxian, A., Vogt, G., Paeth, H. and Jacobeit, J. 2014. Statistical Modelling of Extreme Precipitation Indices for the Mediterranean Area under Future Climate Change. International Journal of Climatology. 34(4): 1132-1156.

Lu, Y. and Qin, X. S. 2014. Multisite Rainfall Downscaling and Disaggregation in A Tropical Urban Area. Journal of Hydrology. 509: 55-65.

Beecham, S., Rashid, M. and Chowdhury, R. K. 2014. Statistical Downscaling of Multi‐Site Daily Rainfall in a South Australian Catchment Using a Generalized Linear Model. International Journal of Climatology. 34(14): 3654-3670.

Rashid, M., Beecham, S. and Chowdhury, R. K. 2015. Statistical Downscaling of Rainfall: A Non-Stationary and Multi-Resolution Approach. Theoretical and Applied Climatology. 1-15.

Qian, C., Zhou, W., Fong, S.K. and Leong, K.C., 2015. Two Approaches for Statistical Prediction of Non-Gaussian Climate Extremes: A Case Study of Macao Hot Extremes during 1912–2012. Journal of Climate, 28(2): 623-636.

Tukimat, N. N. A., Harun, S. and Shahid, S. 2012. Comparison of Different Methods in Estimating Potential Evapotranspiration at Muda Irrigation Scheme of Malaysia. Journal of Agriculture and Rural Development in the Tropics and Subtropics (JARTS). 113(1): 77–85

Hadipour, S., Shahid, S., Harun, S. B. and Wang, X. J. 2013. Genetic Programming for Downscaling Extreme Rainfall Events. Artificial 2013 1st International Conference on Intelligence, Modelling and Simulation (AIMS). 331-334, IEEE.



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