Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1002/joc.5678 |
Estimation of wind speed using regional frequency analysis based on linear-moments | |
Fawad, Muhammad1; Ahmad, Ishfaq2,3; Nadeem, Falaq Ali4; Yan, Ting1; Abbas, Aamar5 | |
2018-10-01 | |
发表期刊 | INTERNATIONAL JOURNAL OF CLIMATOLOGY |
ISSN | 0899-8418 |
EISSN | 1097-0088 |
出版年 | 2018 |
卷号 | 38期号:12页码:4431-4444 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; Saudi Arabia; 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. |
英文关键词 | linear-moments Monte Carlo simulation quantile estimates wind speed |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000446279100008 |
WOS关键词 | GENERALIZED PARETO DISTRIBUTION ; EXTREME-VALUE ANALYSIS ; ORDER-STATISTICS ; DISTRIBUTIONS ; PARAMETERS ; TURKEY ; RAINFALL ; BASIN |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/36626 |
专题 | 气候变化 |
作者单位 | 1.Cent China Normal Univ, Sch Math & Stat, Wuhan, Hubei, Peoples R China; 2.King Khalid Univ, Dept Math, Abha 61413, Saudi Arabia; 3.Int Islamic Univ, Dept Math & Stat, Islamabad, Pakistan; 4.Univ Punjab, Coll Stat & Actuarial Sci, Lahore, Pakistan; 5.Univ Poonch Rawalakot, Dept Math, Rawalakot, Pakistan |
推荐引用方式 GB/T 7714 | Fawad, Muhammad,Ahmad, Ishfaq,Nadeem, Falaq Ali,et al. Estimation of wind speed using regional frequency analysis based on linear-moments[J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY,2018,38(12):4431-4444. |
APA | Fawad, Muhammad,Ahmad, Ishfaq,Nadeem, Falaq Ali,Yan, Ting,&Abbas, Aamar.(2018).Estimation of wind speed using regional frequency analysis based on linear-moments.INTERNATIONAL JOURNAL OF CLIMATOLOGY,38(12),4431-4444. |
MLA | Fawad, Muhammad,et al."Estimation of wind speed using regional frequency analysis based on linear-moments".INTERNATIONAL JOURNAL OF CLIMATOLOGY 38.12(2018):4431-4444. |
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