Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2017.07.016 |
Multiple imputation of rainfall missing data in the Iberian Mediterranean context | |
Javier Miro, Juan1; Caselles, Vicente1; Jose Estrela, Maria2 | |
2017-11-15 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2017 |
卷号 | 197 |
文章类型 | Article |
语种 | 英语 |
国家 | Spain |
英文摘要 | Given the increasing need for complete rainfall data networks, in recent years have been proposed diverse methods for filling gaps in observed precipitation series, progressively more advanced that traditional approaches to overcome the problem. The present study has consisted in validate 10 methods (6 linear, 2 non-linear and 2 hybrid) that allow multiple imputation, i.e., fill at the same time missing data of multiple incomplete series in a dense network of neighboring stations. These were applied for daily and monthly rainfall in two sectors in the Jucar River Basin Authority (east Iberian Peninsula), which is characterized by a high spatial irregularity and difficulty of rainfall estimation. A classification of precipitation according to their genetic origin was applied as pre-processing, and a quantile-mapping adjusting as post-processing technique. The results showed in general a better performance for the non-linear and hybrid methods, highlighting that the non-linear PCA (NLPCA) method outperforms considerably the Self Organizing Maps (SOM) method within non-linear approaches. On linear methods, the Regularized Expectation Maximization method (RegEM) was the best, but far from NLPCA. Applying EOF filtering as post-processing of NLPCA (hybrid approach) yielded the best results. |
英文关键词 | Rainfall Missing data Gap filling Daily data Monthly data Imputation method comparison Dense network |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000412250700026 |
WOS关键词 | PRINCIPAL COMPONENT ANALYSIS ; DAILY PRECIPITATION CONCENTRATION ; SEA-SURFACE TEMPERATURE ; VALENCIA REGION ; INCOMPLETE DATA ; TIME-SERIES ; SPATIAL-DISTRIBUTION ; PCA METHODS ; VALUES ; EXTREMES |
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/15258 |
专题 | 地球科学 |
作者单位 | 1.Univ Valencia, Dept Fis Terra & Termodinam, Fac Fis, Doctor Moliner 50, Valencia 46100, Spain; 2.Univ Valencia, Dept Geog, Fac Geog & Hist, Avda Blasco lbanez 28, Valencia 46010, Spain |
推荐引用方式 GB/T 7714 | Javier Miro, Juan,Caselles, Vicente,Jose Estrela, Maria. Multiple imputation of rainfall missing data in the Iberian Mediterranean context[J]. ATMOSPHERIC RESEARCH,2017,197. |
APA | Javier Miro, Juan,Caselles, Vicente,&Jose Estrela, Maria.(2017).Multiple imputation of rainfall missing data in the Iberian Mediterranean context.ATMOSPHERIC RESEARCH,197. |
MLA | Javier Miro, Juan,et al."Multiple imputation of rainfall missing data in the Iberian Mediterranean context".ATMOSPHERIC RESEARCH 197(2017). |
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