GSTDTAP  > 气候变化
DOI10.1002/joc.5508
Cautionary note on the use of genetic programming in statistical downscaling
Sachindra, D. A.1; Ahmed, K.2; Shahid, S.3; Perera, B. J. C.1
2018-06-30
发表期刊INTERNATIONAL JOURNAL OF CLIMATOLOGY
ISSN0899-8418
EISSN1097-0088
出版年2018
卷号38期号:8页码:3449-3465
文章类型Article
语种英语
国家Australia; Pakistan; Malaysia
英文摘要

The selection of inputs (predictors) to downscaling models is an important task in any statistical downscaling exercise. The selection of an appropriate set of predictors to a downscaling model enhances its generalization skills as such set of predictors can reliably explain the catchment-scale hydroclimatic variable (predictand). Among the predictor selection procedures seen in the literature, the use of genetic programming (GP) can be regarded as a unique approach as it not only selects a set of predictors influential on the predictand but also simultaneously determines a linear or nonlinear regression relationship between the predictors and the predictand. In this short communication, the details of an investigation on the assessment of effectiveness of GP in identifying a unique optimum set of predictors influential on the predictand and its ability to generate a unique optimum predictor-predictand relationship are presented. In this investigation, downscaling models were evolved for relatively wet and dry precipitation stations pertaining to two study areas using two different sets of reanalysis data for each calendar month maintaining the same GP attributes. It was found that irrespective of the climate regime (i.e., wet and dry) and reanalysis data set used, the probability of identification of a unique optimum set of predictors influential on precipitation by GP is quite low. Therefore, it can be argued that the use of GP for the selection of a unique optimum set of predictors influential on a predictand is not effective. However, when run repetitively, GP algorithm selected certain predictors more frequently than others. Also, when run repetitively, the structure of the predictor-predictand relationships evolved by GP varied from one run to another, indicating that the physical interpretation of the predictor-predictand relationships evolved by GP in a downscaling exercise can be unreliable.


英文关键词climate change genetic programming precipitation predictor selection reanalysis statistical downscaling statistical methods
领域气候变化
收录类别SCI-E
WOS记录号WOS:000439793900018
WOS关键词CIRCULATION MODEL OUTPUTS ; SUPPORT VECTOR MACHINE ; CLIMATE-CHANGE ; EXTREME TEMPERATURES ; VARIABLE SELECTION ; PRECIPITATION ; PAKISTAN ; SCENARIOS ; RAINFALL ; BASIN
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/37550
专题气候变化
作者单位1.Victoria Univ, Coll Engn & Sci, Inst Sustainabil & Innovat, Footscray Pk Campus,POB 14428, Melbourne, Vic 8001, Australia;
2.Lasbela Univ Agr Water & Marine Sci, Fac Water Resources Management, Uthal, Pakistan;
3.Univ Teknol Malaysia, Fac Civil Engn, Johor Baharu, Malaysia
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GB/T 7714
Sachindra, D. A.,Ahmed, K.,Shahid, S.,et al. Cautionary note on the use of genetic programming in statistical downscaling[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2018,38(8):3449-3465.
APA Sachindra, D. A.,Ahmed, K.,Shahid, S.,&Perera, B. J. C..(2018).Cautionary note on the use of genetic programming in statistical downscaling.INTERNATIONAL JOURNAL OF CLIMATOLOGY,38(8),3449-3465.
MLA Sachindra, D. A.,et al."Cautionary note on the use of genetic programming in statistical downscaling".INTERNATIONAL JOURNAL OF CLIMATOLOGY 38.8(2018):3449-3465.
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