globalchange  > 气候减缓与适应
DOI: 10.1002/joc.5678
论文题名:
Estimation of wind speed using regional frequency analysis based on linear-moments
作者: Fawad M.; Ahmad I.; Nadeem F.A.; Yan T.; Abbas A.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期:12
起始页码: 4431
结束页码: 4444
语种: 英语
英文关键词: linear-moments ; Monte Carlo simulation ; quantile estimates ; wind speed
Scopus关键词: Developing countries ; Frequency estimation ; Intelligent systems ; Mean square error ; Monte Carlo methods ; Public policy ; Rain ; Speed ; Structural design ; Weibull distribution ; Wind effects ; Generalized extreme value (GEV) distributions ; L-moment ratio diagrams ; Linear moments ; Meteorological station ; Quantile estimates ; Regional frequency analysis ; Root mean square errors ; Wind speed ; Uncertainty analysis ; estimation method ; frequency analysis ; Monte Carlo analysis ; regional climate ; weather station ; wind velocity ; Pakistan ; Punjab [Pakistan]
英文摘要: The quantiles of annual maximum wind speed (AMWS) can be estimated for different meteorological stations of interest by using at-site frequency analysis and extreme value theory. These estimates are of immense importance for the codification of wind speed. However, the historical data of wind speed at the number of meteorological stations are sometimes unavailable and often insufficient due to the shorter length, especially in developing countries like Pakistan. The scarcity of the data increases the uncertainty of the quantiles estimates regarding policy implications. To cope with the problem, an approach of Regional Frequency Analysis (RFA) is opted here. In this study, RFA of AMWS using linear-moments (L-moments) is carried out by considering wind speed data of nine meteorological stations of province Punjab, Pakistan. No station is found to be discordant. A single homogenous region is constituted from these nine stations using a subjective approach based on their geographical locations. Heterogeneity measures justify that these nine stations of Punjab form a single homogeneous region. Regional quantiles estimates are found through the most appropriate probability distribution among generalized normal (GNO), generalized logistic (GLO), Pearson Type 3 (P3), generalized Pareto (GPA), Weibull (WEI), log Pearson Type 3 (LP3) and generalized extreme value (GEV) distributions. Z-statistic and L-moment ratio diagram suggest that GLO and GNO distributions are better choices than others. Robustness of both distributions is evaluated through relative bias (RB) and relative root mean square error (RRMSE). Findings indicate that overall, GLO distribution is better than GNO. Further, we also find at-site quantiles from dimensionless quantities (regional quantiles) using the sample mean and median as scaling factors. Quantiles' estimates calculated from this study can be used in codified structural designs for policy implications. © 2018 Royal Meteorological Society
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116784
Appears in Collections:气候减缓与适应

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作者单位: School of Mathematics and Statistics, Central China Normal University, Wuhan, China; Department of Mathematics, King Khalid University, Abha, 61413, Saudi Arabia; Department of Mathematics and Statistics, International Islamic University, Islamabad, Pakistan; College of Statistical and Actuarial Sciences, University of the Punjab, Lahore, Pakistan; Department of Mathematics, University of Poonch Rawalakot, Pakistan

Recommended Citation:
Fawad M.,Ahmad I.,Nadeem F.A.,et al. Estimation of wind speed using regional frequency analysis based on linear-moments[J]. International Journal of Climatology,2018-01-01,38(12)
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