An Artificial Neural Networks-Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation
文献类型：期刊论文
| 作者 | Fang, Miao1; Li, Xin2,3 |
| 刊名 | JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
 |
| 出版日期 | 2019-04-01 |
| 卷号 | 11期号:4页码:892-904 |
| 关键词 | paleoclimate data assimilation proxy system model of tree ring width artificial neural netwok climate reconstruction |
| ISSN号 | 1942-2466 |
| DOI | 10.1029/2018MS001525 |
| 通讯作者 | Fang, Miao(mfang@lzb.ac.cn) |
| 英文摘要 | Constructing suitable tree ring width (TRW) proxy system models (PSMs) is an emerging research focus in paleoclimate data assimilation (PDA). Currently, however, it is unknown as to which TRW PSMs are optimal for practical PDA applications. This study proposes an artificial neural networks (ANN)-based TRW PSM and compares its performance with those of existing TRW PSMs, including linear univariate model, linear multivariate model, and physically based VS-Lite model. The results show that ANN-based TRW PSM is more suitable for practical PDA applications than other three TRW PSMs in terms of performance and universality. Overall, the performances of the four TRW PSMs in PDA can be ranked as follows (from best to worst): ANN, linear multivariate model, linear univariate model, and physically based VS-Lite model. In addition, the results of our study not only indicate that the ANN model is a really effective tool for constructing TRW PSM in practical PDA applications but also imply that the ANN model has the potential to provide new insights into the construction of other types of PSMs (e.g., speleothem delta O-18 PSM) when physics of the climate-proxy relationships cannot be described fully in advance. |
| 收录类别 | SCI |
| WOS关键词 | GROWTH-RESPONSES ; CLIMATE ; RECONSTRUCTION ; OPTIMIZATION ; UNCERTAINTIES ; DELTA-O-18 ; RESOLUTION |
| WOS研究方向 | Meteorology & Atmospheric Sciences |
| WOS类目 | Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000467399500003 |
| 出版者 | AMER GEOPHYSICAL UNION |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2555471 |
| 专题 | 寒区旱区环境与工程研究所 |
| 通讯作者 | Fang, Miao |
| 作者单位 | 1.Chinese Acad Sci, Northwest Inst Ecoenvironm & Resource, Lanzhou, Gansu, Peoples R China 2.Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing, Peoples R China 3.Chinese Acad Sci, CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fang, Miao,Li, Xin. An Artificial Neural Networks-Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation[J]. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,2019,11(4):892-904. |
| APA | Fang, Miao,&Li, Xin.(2019).An Artificial Neural Networks-Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation.JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS,11(4),892-904. |
| MLA | Fang, Miao,et al."An Artificial Neural Networks-Based Tree Ring Width Proxy System Model for Paleoclimate Data Assimilation".JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 11.4(2019):892-904. |
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来源：寒区旱区环境与工程研究所
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