Systematic Approach for Variable Selection in the Weather Generator Model

• 발행기관: 한국방재학회
• 저자명: Hyung-Il Eum Slobodan P Simonovic
• 간행물 정보: 『Journal of Disaster Management』Journal of Disaster Management Vol.1 No.3, 22~37쪽, 전체 16쪽
• 주제분류: 공학 > 기타공학
• 파일형태: PDF
• 발행일자: 2016.07.31

영문 초록

This study provides an analytical procedure for selecting variables for the Weather Generator (WG) model to be used in the assessment of climatic change impacts at a local scale. The approach integrates the K-NN technique with the Principle Component Analysis (PCA), termed of WG-PCA. The Upper Thames River Basin in South-Western Ontario, Canada is selected as a case study. The outcome of the WG model includes 38 years of synthetically generated data. In the study we tested three models: (a) the WG-1Var employing only one variable (precipitation); (b) WG-3Var employing three variables (precipitation, maximum temperature, and minimum temperature); and (c) WG-PCA. The simulation results indicate that WG models employing three variables (WG-3Var and WG-PCA) produce the meteorological variables with better temporal and spatial correlation compared to the WG-1Var. More notable result is that the WG-PCA employing only the first principle component provides the comparable results to those of WG-3Var and much better results than WG-1Var.

목차

INTRODUCTION

METHODOLOGY

APPLICATION

RESULTS

CONCLUSIONS AND FUTURE WORK

ACKNOWLEDGMENTS

키워드

Weather generator K nearest neighbor Principle component analysis