Improving estimates of ocean primary productivity:Coupling bio-optics into a semi-Lagrangian model of phytoplankton physiology and ocean mixing

改进海洋初级生产力的估计:将生物光学耦合到浮游植物生理学和海洋混合的半拉格朗日模型中

基本信息

  • 批准号:
    NE/D00960X/1
  • 负责人:
  • 金额:
    $ 29.24万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Fellowship
  • 财政年份:
    2006
  • 资助国家:
    英国
  • 起止时间:
    2006 至 无数据
  • 项目状态:
    已结题

项目摘要

There are increasing amounts of carbon dioxide (CO2) in our atmosphere from the burning of fossil fuels and changes in land use. Because of the 'greenhouse effect' our climate is getting warmer. To predict how much warmer our planet will become in the future we need to understand all the processes on Earth that affect climate - these occur not only in the atmosphere but also on the land and in the sea. Once we have done this we can build computer models (i.e. write computer programs) which simulate the interactions between all these processes and then tell us what our climate might be like in the future. However, there are many complicated biological, chemical and physical processes that we don't yet fully understand so we still need to collect lots of data and spend time examining individual systems before we can properly model the whole climate system. The system I propose to look at concerns biological processes in the oceans. The oceans influence climate due to the movement of heat and gas between the air and sea. The amount of CO2 in the atmosphere at the moment is out of balance with that in the sea so the CO2 in the air is currently being absorbed by the oceans. This is good news for us because if there is more CO2 in the ocean, and less in the atmosphere, then the rate of global warming will be slower. Once the CO2 is dissolved in the oceans it may sink down to the deep ocean when the surface water cools and sinks, or it may get transported downwards through marine biology. And once it gets there it may not return to the surface for thousands of years. If the CO2 stayed at the sea surface it would hinder the progress of more CO2 entering the sea so it is important that mechanisms exist for transporting it to the deep ocean, otherwise we would have more CO2 in the atmosphere than we do now. I propose to model how the marine biology converts the CO2 dissolved in the surface waters to plant matter. This is the first stage in the biological transport of atmospheric CO2 to the deep ocean and so it is crucial that we understand it fully. There are lots of tiny floating plants ('phytoplankton') in the ocean, and as long as they have nutrient and sunlight they can absorb the dissolved CO2 from the sea water and use it to grow. This process is known as photosynthesis or carbon fixation. These plants may then be eaten by small drifting animals, fish or even whales, thus moving the carbon up the food chain. If these plants, animals or fish die, they may sink from the surface to the deep ocean, trapping the carbon from the atmosphere deep within the ocean interior. Much of what we know about these little plants comes from measurements taken by satellites orbiting the Earth. They can measure the amount of sunlight reflected from the ocean surface - this is known as 'ocean colour' - and it tells us how much plant life is near the sea surface. The research I propose, involves developing a computer model to investigate photosynthesis. It is not a simple process to model because the little plants move up and down through the water as the sea water mixes or stratifies (caused by changes in wind and sunlight). This is important because the deeper the little plants go, the less light they have but the more nutrient. The more light and nutrient they have - the faster they can photosynthesize. To get a handle on this process I will link the amount of plant life and the amount of carbon fixed, to ocean colour. This is good for 2 reasons. First, our model results will help us to understand exactly what the satellite ocean colour data is telling us about the state of the marine ecosystem, and second if we want to start adding ocean colour data into our models then we will know how to do it. All this is important because it will help us to understand what is actually happening in the oceans at the moment and that will help us to predict what will happen in the future.
由于化石燃料的燃烧和土地利用的变化,我们大气中的二氧化碳 (CO2) 含量不断增加。由于“温室效应”,我们的气候正在变暖。为了预测我们的星球未来会变暖多少,我们需要了解地球上影响气候的所有过程——这些过程不仅发生在大气中,还发生在陆地和海洋中。一旦我们做到了这一点,我们就可以建立计算机模型(即编写计算机程序)来模拟所有这些过程之间的相互作用,然后告诉我们未来的气候可能会是什么样子。然而,有许多复杂的生物、化学和物理过程我们尚未完全了解,因此我们仍然需要收集大量数据并花时间检查各个系统,然后才能正确模拟整个气候系统。我建议研究的系统涉及海洋中的生物过程。由于空气和海洋之间热量和气体的移动,海洋影响气候。目前大气中的二氧化碳含量与海洋中的二氧化碳含量不平衡,因此空气中的二氧化碳目前正在被海洋吸收。这对我们来说是个好消息,因为如果海洋中的二氧化碳含量增加,大气中的二氧化碳含量减少,那么全球变暖的速度就会减慢。一旦二氧化碳溶解在海洋中,当表层水冷却并下沉时,它可能会沉入深海,或者可能通过海洋生物向下输送。一旦到达那里,它可能数千年都不会返回地表。如果二氧化碳停留在海面,就会阻碍更多二氧化碳进入海洋,因此存在将其输送到深海的机制很重要,否则我们大气中的二氧化碳会比现在更多。我建议模拟海洋生物学如何将溶解在地表水中的二氧化碳转化为植物物质。这是大气二氧化碳向深海生物迁移的第一阶段,因此我们充分了解它至关重要。海洋中有很多微小的漂浮植物(“浮游植物”),只要有营养和阳光,它们就可以吸收海水中溶解的二氧化碳并利用它来生长。这个过程被称为光合作用或碳固定。然后,这些植物可能会被小型漂流动物、鱼类甚至鲸鱼吃掉,从而使碳沿着食物链向上移动。如果这些植物、动物或鱼类死亡,它们可能会从表面沉入深海,将大气中的碳捕获在海洋内部深处。我们对这些小植物的了解大部分来自绕地球运行的卫星进行的测量。他们可以测量从海洋表面反射的阳光量——这被称为“海洋颜色”——它可以告诉我们海面附近有多少植物生命。我提议的研究涉及开发一个计算机模型来研究光合作用。这不是一个简单的建模过程,因为当海水混合或分层(由风和阳光的变化引起)时,小植物在水中上下移动。这很重要,因为小植物生长得越深,光照就越少,但养分就越多。它们拥有的光线和营养越多,光合作用的速度就越快。为了掌握这个过程,我将把植物生命的数量和固定碳的数量与海洋颜色联系起来。这有两个好处。首先,我们的模型结果将帮助我们准确理解卫星海洋颜色数据告诉我们有关海洋生态系统状态的信息;其次,如果我们想开始将海洋颜色数据添加到我们的模型中,那么我们将知道如何去做。所有这些都很重要,因为它将帮助我们了解目前海洋中实际发生的情况,并帮助我们预测未来会发生什么。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Lochnagar: The Natural History of a Mountain Lake
洛赫纳加尔:高山湖泊的自然历史
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Kettle H,;R Thompson
  • 通讯作者:
    R Thompson
Sensitivity analysis of an Ocean Carbon Cycle Model in the North Atlantic: an investigation of parameters affecting the air-sea CO<sub>2</sub> flux, primary production and export of detritus
北大西洋海洋碳循环模型的敏感性分析:影响海气 CO 的参数研究
  • DOI:
    10.5194/osd-7-1977-2010
  • 发表时间:
    2010
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Scott V
  • 通讯作者:
    Scott V
Using satellite-derived backscattering coefficients in addition to chlorophyll data to constrain a simple marine biogeochemical model
除了叶绿素数据之外,还使用卫星衍生的后向散射系数来约束简单的海洋生物地球化学模型
  • DOI:
    10.5194/bg-6-1591-2009
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    4.9
  • 作者:
    Kettle H
  • 通讯作者:
    Kettle H
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Helen Kettle其他文献

Modeling ocean primary production: Sensitivity to spectral resolution of attenuation and absorption of light
  • DOI:
    10.1016/j.pocean.2008.04.002
  • 发表时间:
    2008-08-01
  • 期刊:
  • 影响因子:
  • 作者:
    Helen Kettle;Chris J. Merchant
  • 通讯作者:
    Chris J. Merchant
Estimating the contribution of the porcine fecal core microbiota to metabolite production via mathematical modeling and emin vitro/em fermentation
通过数学建模以及体外/发酵试验来评估猪粪便核心微生物群对代谢物产生的贡献
  • DOI:
    10.1128/msystems.00366-23
  • 发表时间:
    2023-12-06
  • 期刊:
  • 影响因子:
    4.600
  • 作者:
    Salvatore Galgano;Helen Kettle;Andrew Free;Jos G. M. Houdijk;Vanni Bucci
  • 通讯作者:
    Vanni Bucci
Temperature and time of season are the predominant drivers of cabbage stem flea beetle, emPsylliodes chrysocephala/em, arrival at oilseed rape crops
温度和季节时间是甘蓝茎跳甲(Empsylliodes chrysocephala)到达油菜作物的主要驱动因素
  • DOI:
    10.1016/j.cropro.2024.106904
  • 发表时间:
    2024-11-01
  • 期刊:
  • 影响因子:
    2.500
  • 作者:
    David A. Ewing;Duncan J. Coston;Sacha White;Joe M. Roberts;Tom W. Pope;Helen Kettle
  • 通讯作者:
    Helen Kettle
Challenges in microbial ecology: building predictive understanding of community function and dynamics
微生物生态学中的挑战:建立对群落功能和动态的预测性理解
  • DOI:
    10.1038/ismej.2016.45
  • 发表时间:
    2016-03-29
  • 期刊:
  • 影响因子:
    10.000
  • 作者:
    Stefanie Widder;Rosalind J Allen;Thomas Pfeiffer;Thomas P Curtis;Carsten Wiuf;William T Sloan;Otto X Cordero;Sam P Brown;Babak Momeni;Wenying Shou;Helen Kettle;Harry J Flint;Andreas F Haas;Béatrice Laroche;Jan-Ulrich Kreft;Paul B Rainey;Shiri Freilich;Stefan Schuster;Kim Milferstedt;Jan R van der Meer;Tobias Groβkopf;Jef Huisman;Andrew Free;Cristian Picioreanu;Christopher Quince;Isaac Klapper;Simon Labarthe;Barth F Smets;Harris Wang;Orkun S Soyer
  • 通讯作者:
    Orkun S Soyer

Helen Kettle的其他文献

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{{ truncateString('Helen Kettle', 18)}}的其他基金

Arable: Modelling the impact of cabbage stem flea beetle on oilseed rape crops
耕地:模拟卷心菜茎跳甲对油菜作物的影响
  • 批准号:
    BB/X012123/1
  • 财政年份:
    2023
  • 资助金额:
    $ 29.24万
  • 项目类别:
    Research Grant
Quantifying the impact of anthropogenic nutrient imbalance on C flux from freshwater lakes: cellular mechanisms, community assembly and modelling
量化人为营养失衡对淡水湖泊碳通量的影响:细胞机制、群落组装和建模
  • 批准号:
    NE/X005240/1
  • 财政年份:
    2022
  • 资助金额:
    $ 29.24万
  • 项目类别:
    Research Grant

相似海外基金

Improving estimates of ocean productivity and carbon sequestration through a combination of autonomous observation- and model-based approaches
通过结合自主观测和基于模型的方法改进对海洋生产力和碳封存的估计
  • 批准号:
    RGPIN-2022-02975
  • 财政年份:
    2022
  • 资助金额:
    $ 29.24万
  • 项目类别:
    Discovery Grants Program - Individual
Collaborative Research: Bringing the Late Pleistocene into Focus: Better estimates of Ages and Ocean Circulation through Data-Model Comparison
合作研究:关注更新世晚期:通过数据模型比较更好地估计年龄和海洋环流
  • 批准号:
    1760838
  • 财政年份:
    2018
  • 资助金额:
    $ 29.24万
  • 项目类别:
    Standard Grant
Collaborative Research: Bringing the Late Pleistocene into Focus: Better Estimates of Ages and Ocean Circulation Through Data-Model Comparison
合作研究:关注更新世晚期:通过数据模型比较更好地估计年龄和海洋环流
  • 批准号:
    1760878
  • 财政年份:
    2018
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    $ 29.24万
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    Standard Grant
Collaborative Research: Bringing the Late Pleistocene into Focus: Better Estimates of Ages and Ocean Circulation Through Data-Model Comparison
合作研究:关注更新世晚期:通过数据模型比较更好地估计年龄和海洋环流
  • 批准号:
    1760958
  • 财政年份:
    2018
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    $ 29.24万
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    Standard Grant
FOR 1740: A New Approach toward Improved Estimates of Atlantic Ocean Freshwater Budgets and Transports as Part of the Global Hydrological Cycle
FOR 1740:作为全球水文循环一部分的改进大西洋淡水预算和运输估算的新方法
  • 批准号:
    198122929
  • 财政年份:
    2013
  • 资助金额:
    $ 29.24万
  • 项目类别:
    Research Units
A new Approach toward Improved Estimates of Atlantic Ocean freshwater Budgets and Tranports as Part of the Global Hydrological Cycle
作为全球水文循环一部分的改进大西洋淡水预算和运输估算的新方法
  • 批准号:
    225911830
  • 财政年份:
    2013
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    $ 29.24万
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    Research Units
Collaborative Research: Tracer Age-Based Estimates of Carbon Export and Ventilation Variability in the Indian Ocean
合作研究:基于示踪剂年龄的印度洋碳输出和通风变化估计
  • 批准号:
    1059886
  • 财政年份:
    2011
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    $ 29.24万
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    Standard Grant
Testing model estimates of recent ocean carbon uptake and deoxygenation using atmospheric and oceanic data
使用大气和海洋数据测试近期海洋碳吸收和脱氧的模型估计
  • 批准号:
    1130976
  • 财政年份:
    2011
  • 资助金额:
    $ 29.24万
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    Continuing Grant
Collaborative Research: Tracer Age-Based Estimates of Carbon Export and Ventilation Variability in the Indian Ocean
合作研究:基于示踪剂年龄的印度洋碳输出和通风变化估计
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Probabilistic estimates of tsunami heights from great earthquakes around the Pacific Ocean based on paleotsunami surveys
基于古海啸调查的太平洋周边大地震海啸高度的概率估计
  • 批准号:
    21310113
  • 财政年份:
    2009
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  • 项目类别:
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