globalchange  > 气候变化与战略
DOI: 10.1007/s11069-020-04011-x
论文题名:
A principal component analysis approach to assess CHIRPS precipitation dataset for the study of climate variability of the La Plata Basin, Southern South America
作者: Cerón W.L.; Molina-Carpio J.; Ayes Rivera I.; Andreoli R.V.; Kayano M.T.; Canchala T.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期:1
起始页码: 767
结束页码: 783
语种: 英语
中文关键词: CHIRPS ; La Plata Basin ; Performance metrics ; Principal component analysis ; Satellite precipitation estimate
英文关键词: climate change ; data set ; meteorological hazard ; precipitation assessment ; principal component analysis ; raingauge ; satellite data ; spatiotemporal analysis ; La Plata Basin
英文摘要: This article assesses the consistency of the satellite precipitation estimate CHIRPS v.2 to describe the spatiotemporal rainfall variability in the La Plata Basin (LPB), the second largest hydrographic basin in South America, by (a) pixel-to-point comparison of CHIRPS data with 167 observed monthly precipitation time series using three pairwise metrics (coefficient of correlation, bias and root mean square error) and (b) principal component analysis (PCA) to evaluate the large-scale coherence between CHIRPS and rain gauge data. The pairwise metrics indicate that CHIRPS better represents the rainfall in the coastal, northeastern and southeastern parts of the basin than in the Andean region to the west. The PCA shows that CHIRPS describes most of the observed rainfall variability in the LPB, but contains more variability, especially during December–February and March–May seasons. The two major modes observed are highly correlated spatially (empirical orthogonal functions—EOFs) and temporally (principal components—PCs) with the corresponding CHIRPS modes. The PCA allows the determination of the main rainfall variability modes and their possible relations with climate variability modes. Besides, the analyses of the precipitation anomaly modes show that the El Niño Southern Oscillation explains the first EOF modes of datasets. The PCA provides an alternative and effective means of assessing the consistency of CHIRPS data in representing spatial and temporal rainfall variability in the LPB. © 2020, Springer Nature B.V.
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168421
Appears in Collections:气候变化与战略

Files in This Item:

There are no files associated with this item.


作者单位: Department of Geography, Faculty of Humanities, Universidad del Valle, Calle 13 #100-00, Cali, 25360, Colombia; Programa de Pós-Graduação em Clima e Ambiente (CLIAMB, INPA/UEA), Av. André Araújo, 2936, Campus II, Aleixo, Manaus, AM 69060-001, Brazil; Instituto de Hidráulica e Hidrología, Universidad Mayor de San Andrés, calle 30 Cota Cota, La Paz, Bolivia; Escola Superior de Tecnologia, Universidade do Estado do Amazonas, Av. Darcy Vargas, 1200, Parque 10 de Novembro, Manaus, AM 69065-020, Brazil; Centro de Previsão de Tempo e Estudos Climáticos, Divisão de Modelagem e Desenvolvimento, Instituto Nacional de Pesquisas Espaciais, Av. dos Astronautas, 1758, São José dos Campos, SP 12227-010, Brazil; Research Group in Water Resources Engineering and Soil (IREHISA), School of Natural Resources and Environmental Engineering, Universidad del Valle, Cali, Colombia

Recommended Citation:
Cerón W.L.,Molina-Carpio J.,Ayes Rivera I.,et al. A principal component analysis approach to assess CHIRPS precipitation dataset for the study of climate variability of the La Plata Basin, Southern South America[J]. Natural Hazards,2020-01-01,103(1)
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Cerón W.L.]'s Articles
[Molina-Carpio J.]'s Articles
[Ayes Rivera I.]'s Articles
百度学术
Similar articles in Baidu Scholar
[Cerón W.L.]'s Articles
[Molina-Carpio J.]'s Articles
[Ayes Rivera I.]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Cerón W.L.]‘s Articles
[Molina-Carpio J.]‘s Articles
[Ayes Rivera I.]‘s Articles
Related Copyright Policies
Null
收藏/分享
所有评论 (0)
暂无评论
 

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.