Examination of Various Feature Selection Approaches for Daily Precipitation Downscaling in Different Climates

Ahmad Jafarzadeh (), Mohsen Pourreza-Bilondi (), Abbas Khashei Siuki () and Javad Ramezani Moghadam ()
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Ahmad Jafarzadeh: University of Birjand
Mohsen Pourreza-Bilondi: University of Birjand
Abbas Khashei Siuki: University of Birjand
Javad Ramezani Moghadam: University of Mohaghegh Ardabili

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2021, vol. 35, issue 2, No 1, 407-427

Abstract: Abstract To turn General Circulation Models (GCMs) projection toward better assessment, it is crucial to employ a downscaling process to get more reliability of their outputs. The data-driven based downscaling techniques recently have been used widely, and predictor selection is usually considered as the main challenge in these methods. Hence, this study aims to examine the most common approaches of feature selection in the downscaling of daily rainfall in two different climates in Iran. So, the measured daily rainfall and National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) predictors were collected, and Support Vector Machine (SVM) was considered as downscaling methods. Also, a complete set of comparative tests considering all dimensions was employed to identify the best subset of predictors. Results indicated that the skill of various selection methods in different tests is significantly different. Despite a few partial superiorities viewed between selection models, they not presented an obvious distinction. However, regarding all related factors, it may be deduced that the Stepwise Regression Analysis (SRA) and Bayesian Model Averaging (BMA) are better than others. Also, the finding of this study showed that there are some weaknesses in the interpretation of SRA, so concerning this issue, it may be concluded that BMA has more reliable performance. Furthermore, results indicated that generally, the downscaling procedure has more accuracy in arid climate than cold-semi arid climate.

Keywords: Statistical downscaling; Penalized multiple linear regressions; Bayesian selection method; Multi-Colinearity; Wet spell; Least absolute shrinkage (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11269-020-02701-6

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