DOI: 10.1002/2016GB005600
Scopus记录号: 2-s2.0-85022226117
论文题名: Assessing trends and uncertainties in satellite-era ocean chlorophyll using space-time modeling
作者: Hammond M ; L ; , Beaulieu C ; , Sahu S ; K ; , Henson S ; A
刊名: Global Biogeochemical Cycles
ISSN: 8866236
出版年: 2017
卷: 31, 期: 7 起始页码: 1103
结束页码: 1117
语种: 英语
英文关键词: Bayesian inference
; chlorophyll
; climate change
; phytoplankton
; spatiotemporal modeling
; trend detection
Scopus关键词: Bayesian analysis
; chlorophyll
; climate change
; correlation
; model test
; phytoplankton
; satellite data
; spatiotemporal analysis
; trend analysis
; uncertainty analysis
英文摘要: The presence, magnitude, and even direction of long-term trends in phytoplankton abundance over the past few decades are still debated in the literature, primarily due to differences in the data sets and methodologies used. Recent work has suggested that the satellite chlorophyll record is not yet long enough to distinguish climate change trends from natural variability, despite the high density of coverage in both space and time. Previous work has typically focused on using linear models to determine the presence of trends, where each grid cell is considered independently from its neighbors. However, trends can be more thoroughly evaluated using a spatially resolved approach. Here a Bayesian hierarchical spatiotemporal model is fitted to quantify trends in ocean chlorophyll from September 1997 to December 2013. The approach used in this study explicitly accounts for the dependence between neighboring grid cells, which allows us to estimate trend by “borrowing strength” from the spatial correlation. By way of comparison, a model without spatial correlation is also fitted. This results in a notable loss of accuracy in model fit. Additionally, we find an order of magnitude smaller global trend, and larger uncertainty, when using the spatiotemporal model: −0.023 ± 0.12% yr−1 as opposed to −0.38 ± 0.045% yr−1 when the spatial correlation is not taken into account. The improvement in accuracy of trend estimates and the more complete account of their uncertainty emphasize the solution that space-time modeling offers for studying global long-term change. ©2017. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/77719
Appears in Collections: 气候变化事实与影响
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作者单位: Ocean and Earth Science, University of Southampton, Southampton, United Kingdom; Mathematical Sciences, University of Southampton, Southampton, United Kingdom; National Oceanography Centre, Southampton, United Kingdom
Recommended Citation:
Hammond M,L,, Beaulieu C,et al. Assessing trends and uncertainties in satellite-era ocean chlorophyll using space-time modeling[J]. Global Biogeochemical Cycles,2017-01-01,31(7)