Regional Ecosystem Model Testbeds: A JGOFS Synthesis and Modeling Project
Regional Ecosystem Model Testbeds: A JGOFS Synthesis and Modeling Project
批准号:
0097285
负责人:
Marjorie Friedrichs
金额:
$27.19万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2001
资助国家:
美国
项目状态:
已结题
起止时间:
2001-06-15 至 2006-05-31
中文摘要
美国联合全球通量研究(JGOFS)综合和建模项目(SMP)的一项重要遗产将是制定一套广泛的模型,旨在模拟各种过程研究地点的生物地球化学循环。虽然这组模型和建模研究已经大大提高了我们对这些系统的理解,但这些模型之间的定量比较很少。该项目将开始进行这些内部比较,以便严格检查哪种生态系统结构和配方最稳健,并调查和探索其成功的原因。此外,它将严格评估开发适用于各种不同生态系统的生物地球化学模型的可行性。本研究的主要目标是:(1)从机制上理解不同海洋区域间生光带的产生和相关的碳输出是如何以及为什么会发生变化的;(2)加速基于机械的生态系统模型的发展,该模型能够同时描述多种海洋环境的主要生物地球化学特征。为了实现这些目标,并为测试和比较各种生态系统模型提供一个论坛,研究人员将开发一系列“区域试验台”,基于(i)阿拉伯海过程研究(asp)、(ii)南极环境和南大洋过程研究(AESOPS)、(iii)赤道太平洋过程研究(EqPac)、(iv)第二次铁富集实验(IronEx-II)、(v)百慕大大西洋时间序列研究(BATS)和(vi)夏威夷海洋时间序列(HOT)提供的高质量和大量观测数据。将为所有试验台建立网站,并将包括访问强制模型所需的物理场,以及将用于评估或优化/同化的生物地球化学数据的时间序列。这些网站将作为社区资源提供,在本研究中,将用于促进站点内和站点间的模式比较。这项研究将利用以前在JGOFS SMP下完成的工作:参与该项目的12名共同研究人员(见合作函)将免费为该项目提供他们的区域专业知识、模型代码、强迫场和生物地球化学数据集。为了进一步促进模型之间的相互比较,该项目将包括每年一次的实践研讨会,科学家(包括但不限于本提案的共同研究者)将共同努力,定量评估一些不同的生物地球化学模型和建模方法。通过这些相互比较的练习和精心设计的模拟,生物地球化学模型的改进将加快,科学界将大大接近于拥有一套经过严格测试的模型,可用于海洋碳循环预测。
英文摘要
An important legacy of the U.S. Joint Global Flux Study (JGOFS) Synthesis and Modeling Project (SMP) will be the formulation of a broad suite of models designed to simulate biogeochemical cycling at the various process study sites. Although this set of models and modeling studies has already substantially advanced our understanding of these systems, few quantitative inter-comparisons of these models have been made. This project will begin to conduct these inter-comparisons, in order to critically examine which ecosystem structures and formulations are most robust, and to investigate and explore the reasons for their success. Furthermore, it will critically evaluate the feasibility of developing biogeochemical models that are applicable over a wide range of diverse ecosystems. The main objectives of the proposed work are: (1) to add to the mechanistic understanding of how and why euphotic zone production, and the associated export of carbon, vary among diverse oceanographic regions, and (2) to accelerate the development of mechanistically-based ecosystem models that are capable of simultaneously describing the primary biogeochemical features of multiple oceanographic regimes. In order to accomplish these goals, and to provide a forum for testing and comparing various ecosystem models, the investigators will develop a series of "regional test-beds," based on the high quality and large quantity of observations available from (i) the Arabian Sea Process Study (ASPS), (ii) the Antarctic Environment and Southern Ocean Process Study (AESOPS), (iii) the Equatorial Pacific Process Study (EqPac), (iv) the second iron enrichment experiment (IronEx-II), (v) the Bermuda Atlantic Time-Series Study (BATS), and (vi) the Hawaii Ocean Time-series (HOT). Websites will be constructed for all test-beds and will include access to the physical fields required to force the models, as well as time-series of biogeochemical data that will be used for either evaluation or optimization/assimilation. These websites will be available as a community resource, and, in this study, will be used to facilitate both intra-site and inter-site model comparisons. This research will capitalize on work previously accomplished under the JGOFS SMP: the twelve co-investigators involved in this project (see letters of collaboration) will freely provide their regional expertise, model code, forcing fields, and biogeochemical data sets to this project. To further promote model inter-comparisons, this project will involve annual hands-on workshops in which scientists (including but not limited to the co-investigators of this proposal) will work together to quantitatively assess a number of different biogeochemical models and modeling approaches. Through these inter-comparison exercises and carefully designed simulations, the improvement of biogeochemical models will be accelerated, and the scientific community will be significantly closer to having a set of rigorously tested models that can be used for ocean carbon cycle prediction.
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