Authors : DA Sachindra, Khandakar Ahmed, Md Mamunur Rashid, V Sehgal, S Shahid, BJC Perera
Publication date : 2019/10
Journal : Theoretical and Applied Climatology
Volume : 138
Issue : 1
Pages : 617-638
Publisher : Springer Vienna
Description : Among the regression techniques used in building statistical downscaling models, genetic programming (GP) which mimics Darwin’s theory of biological evolution possesses several pros such as it evolves explicit linear or non-linear relationships while identifying optimum predictors, and it discards irrelevant and redundant information in predictors. However, GP is known to simulate unphysically large outliers of predictands. In statistical downscaling, decomposition of predictand and predictor data into number of different time-frequency components with wavelet transform and modelling each component separately should better simulate the time-frequency properties of the predictand, in theory. Therefore, it is important to investigate pros and cons of using GP with wavelet transform in building downscaling models. In this study, wavelet and non-wavelet-based precipitation downscaling models were developed …
Total citations : Cited by 26
Scholar articles :
DA Sachindra, K Ahmed, MM Rashid, V Sehgal… – Theoretical and Applied Climatology, 2019