Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR026331 |
Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity | |
Papalexiou, Simon Michael1,2,3; Serinaldi, Francesco4,5 | |
2020-02-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2020 |
卷号 | 56期号:2 |
文章类型 | Article |
语种 | 英语 |
国家 | Canada; Czech Republic; England |
英文摘要 | Nature manifests itself in space and time. The spatiotemporal complexity of processes such as precipitation, temperature, and wind, does not allow purely deterministic modeling. Spatiotemporal random fields have a long history in modeling such processes, and yet a single unified framework offering the flexibility to simulate processes that may differ profoundly does not exist. Here we introduce a blueprint to efficiently simulate spatiotemporal random fields that preserve any marginal distribution, any valid spatiotemporal correlation structure, and intermittency. We suggest a set of parsimonious yet flexible marginal distributions and provide a rule of thumb for their selection. We propose a new and unified approach to construct flexible spatiotemporal correlation structures by combining copulas and survival functions. The versatility of our framework is demonstrated by simulating conceptual cases of intermittent precipitation, double-bounded relative humidity, and temperature maxima fields. As a real-word case we simulate daily precipitation fields. In all cases, we reproduce the desired properties. In an era characterized by advances in remote sensing and increasing availability of spatiotemporal data, we deem that this unified approach offers a valuable and easy-to-apply tool for modeling complex spatiotemporal processes. |
英文关键词 | Random field simulation Stochastic modelling Spatiotemporal correlation structures Precipitation simulation Hydroclimatic processes simulation Spatiotemporal risk analysis |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000535672800021 |
WOS关键词 | CROSS-COVARIANCE FUNCTIONS ; SPACE-TIME MODELS ; SPATIOTEMPORAL COVARIANCE ; STOCHASTIC-MODEL ; FAST SIMULATION ; GENERATION ; EXTREME ; FRAMEWORK ; SATELLITE ; MATRIX |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
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/280500 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Saskatchewan, Dept Civil Geol & Environm Engn, Saskatoon, SK, Canada; 2.Global Inst Water Secur, Saskatoon, SK, Canada; 3.Czech Univ Life Sci Prague, Fac Environm Sci, Prague, Czech Republic; 4.Newcastle Univ, Sch Engn, Newcastle Upon Tyne, Tyne & Wear, England; 5.Willis Res Network, London, England |
推荐引用方式 GB/T 7714 | Papalexiou, Simon Michael,Serinaldi, Francesco. Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity[J]. WATER RESOURCES RESEARCH,2020,56(2). |
APA | Papalexiou, Simon Michael,&Serinaldi, Francesco.(2020).Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity.WATER RESOURCES RESEARCH,56(2). |
MLA | Papalexiou, Simon Michael,et al."Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity".WATER RESOURCES RESEARCH 56.2(2020). |
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