| DOI: | 10.1002/2014GL062937
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| 论文题名: | Global monthly sea surface nitrate fields estimated from remotely sensed sea surface temperature, chlorophyll, and modeled mixed layer depth |
| 作者: | Arteaga L.; Pahlow M.; Oschlies A.
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| 刊名: | Geophysical Research Letters
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| ISSN: | 0094-8960
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| EISSN: | 1944-8691
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| 出版年: | 2015
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| 卷: | 42, 期:4 | | 起始页码: | 1130
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| 结束页码: | 1138
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| 语种: | 英语
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| 英文关键词: | nitrate
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| Scopus关键词: | Atmospheric temperature
; Chlorophyll
; Nitrates
; Oceanography
; Optical correlation
; Optical properties
; Submarine geophysics
; Surface properties
; Time series
; Biological production
; Inorganic nitrogen
; Interannual variability
; Mixed layer depths
; Multiple linear regressions
; New Zealand region
; Sea surface temperature (SST)
; Temporal and spatial
; Surface waters
; algorithm
; biological production
; biological pump
; chlorophyll
; global ocean
; in situ measurement
; inorganic nitrogen
; mixed layer
; nitrate
; nutrient availability
; optical property
; remote sensing
; satellite data
; sea surface temperature
; spatiotemporal analysis
; Bermuda
; California
; Hawaii [United States]
; New Zealand
; United States
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| 英文摘要: | Information about oceanic nitrate is crucial for making inferences about marine biological production and the efficiency of the biological carbon pump. While there are no optical properties that allow direct estimation of inorganic nitrogen, its correlation with other biogeochemical variables may permit its inference from satellite data. Here we report a new method for estimating monthly mean surface nitrate concentrations employing local multiple linear regressions on a global 1 by 1 resolution grid, using satellite-derived sea surface temperature, chlorophyll, and modeled mixed layer depth. Our method is able to reproduce the interannual variability of independent in situ nitrate observations at the Bermuda Atlantic Time Series, the Hawaii Ocean Time series, the California coast, and the southern New Zealand region. Our new method is shown to be more accurate than previous algorithms and thus can provide improved information on temporal and spatial nutrient variations beyond the climatological mean at regional and global scales. Key Point Global estimation of oceanic nitrate variability through SST, Chl, and MLD ©2015. American Geophysical Union. All Rights Reserved. |
| URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84924853686&doi=10.1002%2f2014GL062937&partnerID=40&md5=29e7dd8f9f0fc6d306aa87e90d5c4456
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| Citation statistics: |
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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/8576
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| Appears in Collections: | 科学计划与规划
气候变化与战略
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作者单位: | GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
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| Recommended Citation: | |
Arteaga L.,Pahlow M.,Oschlies A.. Global monthly sea surface nitrate fields estimated from remotely sensed sea surface temperature, chlorophyll, and modeled mixed layer depth[J]. Geophysical Research Letters,2015-01-01,42(4).
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