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Regional surface chlorophyll trends and uncertainties in the global ocean

机译:区域表面表面叶绿素趋势和全球海洋的不确定性

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Changes in marine primary productivity are key to determine how climate change might impact marine ecosystems and fisheries. Satellite ocean color sensors provide coverage of global ocean chlorophyll with a combined record length of ~?20?years. Coupled physical–biogeochemical models can inform on expected changes and are used here to constrain observational trend estimates and their uncertainty. We produce estimates of ocean surface chlorophyll trends, by using Coupled Model Intercomparison Project (CMIP5) models to form priors as a “first guess”, which are then updated using satellite observations in a Bayesian spatio-temporal model. Regional chlorophyll trends are found to be significantly different from zero in 18/23 regions, in the range ±?1.8%?year?1. A global average of these regional trends shows a net positive trend of 0.08?±?0.35%?year?1, highlighting the importance of considering chlorophyll changes at a regional level. We compare these results with estimates obtained with the commonly used “vague” prior, representing no independent knowledge; coupled model priors are shown to slightly reduce trend magnitude and uncertainties in most regions. The statistical model used here provides a robust framework for making best use of all available information and can be applied to improve understanding of global change.
机译:海洋初级生产力的变化是确定气候变化如何影响海洋生态系统和渔业的关键。卫星海洋颜色传感器提供全球海洋叶绿素的覆盖范围,综合记录长度〜?20?年。耦合物理生物地球化学模型可以通知预期的变化,这里用于约束观察趋势估计和不确定性。我们通过使用耦合模型离心的项目(CMIP5)模型来形成海洋表面叶绿素趋势的估计,以形成前沿作为“第一猜测”,然后在贝叶斯时空模型中使用卫星观测更新。在±1.8%的范围内,发现区域叶绿素趋势与18/23区的零有显着不同,在±1.8%?一年?1。这些区域趋势的全球平均水平显示出净积极趋势为0.08?±0.35%?一年?1,突出了考虑叶绿素在区域一级变化的重要性。我们将这些结果与在常用的“模糊”之前获得的估算结果进行比较,代表没有独立的知识;耦合模型前沿显示在大多数地区的趋势幅度和不确定性略微降低。这里使用的统计模型提供了一种充分利用所有可用信息的强大框架,可以应用于提高对全局变化的理解。

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