| DOI: | 10.1002/grl.50320
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| 论文题名: | Modeling errors in daily precipitation measurements: Additive or multiplicative? |
| 作者: | Tian Y.; Huffman G.J.; Adler R.F.; Tang L.; Sapiano M.; Maggioni V.; Wu H.
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| 刊名: | Geophysical Research Letters
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| ISSN: | 0094-9066
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| EISSN: | 1944-8797
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| 出版年: | 2013
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| 卷: | 40, 期:10 | | 起始页码: | 2060
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| 结束页码: | 2065
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| 语种: | 英语
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| 英文关键词: | error modeling
; precipitation
; remote sensing
; uncertainty
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| Scopus关键词: | Daily precipitations
; Error characteristics
; Error modeling
; Multiplicative errors
; Precipitation measurement
; Prediction capability
; uncertainty
; Uncertainty representation
; Precipitation (chemical)
; Remote sensing
; Uncertainty analysis
; error analysis
; measurement method
; numerical model
; precipitation (climatology)
; precipitation assessment
; remote sensing
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| 英文摘要: | The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application. In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as nonconstant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice. © 2013 American Geophysical Union. All Rights Reserved. |
| URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879957133&doi=10.1002%2fgrl.50320&partnerID=40&md5=93be31c5e04bc62a1955e6cae08cd53f
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/6330
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| Appears in Collections: | 气候减缓与适应
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作者单位: | Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, United States
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| Recommended Citation: | |
Tian Y.,Huffman G.J.,Adler R.F.,et al. Modeling errors in daily precipitation measurements: Additive or multiplicative?[J]. Geophysical Research Letters,2013-01-01,40(10).
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