Estimation and reduction of random noise in mass anomaly time-series from satellite gravity data by minimization of month-to-month year-to-year double differences
文献类型：期刊论文
| 作者 | Klees, Roland3; Ran, Jiangjun1,3; Tangdamrongsub, Natthachet2,3; Ditmar, Pavel3 |
| 刊名 | JOURNAL OF GEODYNAMICS
 |
| 出版日期 | 2018-09-01 |
| 卷号 | 119页码:9-22 |
| 关键词 | Mass transport GRACE Tikhonov regularization Variance Component Estimation Tonle Sap Greenland Ice Sheet |
| ISSN号 | 0264-3707 |
| DOI | 10.1016/j.jog.2018.05.003 |
| 英文摘要 | We propose a technique to regularize a GRACE-based mass-anomaly time-series in order to (i) quantify the Standard Deviation (SD) of random noise in the data, and (ii) reduce the level of that noise. The proposed regularization functional minimizes the Month-to-month Year-to-year Double Differences (MYDD) of mass anomalies. As such, it does not introduce any bias in the linear trend and the annual component, two of the most common features in GRACE-based mass anomaly time-series. In the context of hydrological and ice sheet studies, the proposed regularization functional can be interpreted as an assumption about the stationarity of climatological conditions. The optimal regularization parameter and noise SD are obtained using Variance Component Estimation. To demonstrate the performance of the proposed technique, we apply it to both synthetic and real data. In the latter case, two geographic areas are considered: the Tonle Sap basin in Cambodia and Greenland. We show that random noise in the data can be efficiently (1.5-2 times) mitigated in this way, whereas no noticeable bias is introduced. We also discuss various findings that can be made on the basis of the estimated noise SD. We show, among others, that knowledge of noise SD facilitates the analysis of differences between GRACE-based and alternative estimates of mass variations. Moreover, inaccuracies in the latter can also be quantified in this way. For instance, we find that noise in the surface mass anomalies in Greenland estimated using the Regional Climate Model RACMO2.3 is at the level of 2-6 cm equivalent water heights. Furthermore, we find that this noise shows a clear correlation with the amplitude of annual mass variations: it is lowest in the north-west of Greenland and largest in the south. We attribute this noise to limitations in the modelling of the meltwater accumulation and run-off. |
| 资助项目 | Netherlands Organization for Scientific Research, NWO[620 842.00.006] ; Chinese Scholarship Council ; National Natural Science Foundation of China[41774094] ; National Natural Science Foundation of China[41431070] ; National Natural Science Foundation of China[41674006] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB23030100] ; Stichting Nationale Computerfaciliteiten (National Computing Facilities Foundation, NCF) ; Nederlandse organisatie voor Wetenschappelijk Onderzoek (Netherlands Organization for Scientific Research, NWO)[SH-053] |
| WOS研究方向 | Geochemistry & Geophysics |
| 语种 | 英语 |
| WOS记录号 | WOS:000444663800002 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 源URL | [http://202.127.146.157/handle/2RYDP1HH/5771]  |
| 专题 | 中国科学院武汉植物园 |
| 通讯作者 | Ran, Jiangjun |
| 作者单位 | 1.Chinese Acad Sci, Inst Geodesy & Geophys, State Key Lab Geodesy & Earths Dynam, Wuhan, Hubei, Peoples R China 2.Univ Newcastle, Callaghan, NSW, Australia 3.Delft Univ Technol, Stevinweg 1, NL-2628 CN Delft, Netherlands |
| 推荐引用方式 GB/T 7714 | Klees, Roland,Ran, Jiangjun,Tangdamrongsub, Natthachet,et al. Estimation and reduction of random noise in mass anomaly time-series from satellite gravity data by minimization of month-to-month year-to-year double differences[J]. JOURNAL OF GEODYNAMICS,2018,119:9-22. |
| APA | Klees, Roland,Ran, Jiangjun,Tangdamrongsub, Natthachet,&Ditmar, Pavel.(2018).Estimation and reduction of random noise in mass anomaly time-series from satellite gravity data by minimization of month-to-month year-to-year double differences.JOURNAL OF GEODYNAMICS,119,9-22. |
| MLA | Klees, Roland,et al."Estimation and reduction of random noise in mass anomaly time-series from satellite gravity data by minimization of month-to-month year-to-year double differences".JOURNAL OF GEODYNAMICS 119(2018):9-22. |
入库方式： OAI收割
来源：武汉植物园
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