Collaborative Research: Analysis of the INSTANT Observations of the Indonesian Throughflow
Collaborative Research: Analysis of the INSTANT Observations of the Indonesian Throughflow
批准号:
0725476
负责人:
Janet Sprintall
金额:
$27.14万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-09-15 至 2011-08-31
中文摘要
OCE-0725935印度尼西亚洋流(ITF)是太平洋和印度洋热量和淡水收支的基本组成部分,也是气候系统的基本组成部分,但在海洋和气候模式中观测和模拟得很差。在过去,主要的通流通道一直受到监测,但在不同的年份和不同的时间长度,使得它不可能同时组装的多个走廊的ITF的图片。来自印度尼西亚、法国、荷兰、美国和澳大利亚的研究人员参与了该项目,(2003年12月至2006年12月)的海流、温盐分层和浅层压力计数据,这些数据来自一系列系泊装置,这些系泊装置直接测量来自马卡萨尔海峡和利法马托拉海峡太平洋水取水口的ITF,在该项目中,美国研究人员将与国际团队合作,对这一综合ITF数据集进行分析。将使用气象卫星的现场数据沿着卫星数据,以实现气象卫星的目标,即对热带气旋、热带气旋的变异性及其与远程、区域和当地强迫的关系进行定量分析。利用ECOMANT数据集,我们可以对平均ITF以及季节内、季节性和年际时间尺度上相关质量和财产通量的变化进行有意义的估计,这是ECOMANT计划的所有目标。此外,还将使用ITF时间序列与一系列模型的输出进行比较,以评估这些模型在模拟ITF方面的技能。对ITF的直接测量将有助于塑造和地面实况所需的算法,将区域原位和卫星数据转换为ITF传输代理,作为有效的长期监测战略的一个组成部分。智力优势:ITF行为的定量知识对广泛的海洋和气候研究至关重要。确定的ITF数据集将允许对ITF的模型模拟及其与大规模和区域海洋和气候条件的联系进行定量评估。的EQUAANT测量将作为一个长期的代理监测系统的基础,需要捕捉低频ITF variability.Broader Impacts:作为EQUAANT教育和推广组成部分的一系列研讨会的一部分,建议将受益于学生和博士后从印度尼西亚,美国,和其他国际合作伙伴。能力建设活动包括由印度尼西亚/东帝汶学生到SIO和LDEO进行培训访问,以进行分析,并为LDEO的一名印度尼西亚研究生提供支助。该项目是对美国CLIVAR(CLImate Variability and Predictability)计划的贡献。
英文摘要
OCE-0725935The Indonesian Throughflow (ITF) is a fundamental component of the heat and freshwater budgets of the Pacific and Indian Oceans, and of the climate system, yet it is poorly observed and simulated in ocean and climate models. In the past, the main throughflow passages have been monitored but over different years and for varied lengths of time, making it impossible to assemble a simultaneous picture of the multiple corridors of the ITF. The INSTANT program, involving researchers from Indonesia, France, the Netherlands, United States and Australia, has now gathered 3 years (December 2003-December 2006) of current, thermohaline stratification and shallow pressure gauge data from an array of moorings that directly measure the ITF from the intake of Pacific water at Makassar Strait and Lifamatola Passage, to the Nusa Tenggara exit channels into the Indian Ocean.In this project US researchers will pursue, in collaboration with the international team the analysis of this comprehensive ITF data set. The INSTANT in situ data along with coincident satellite data will be used to meet the INSTANT goal of developing a quantitative view of the ITF, its variability and its relationship to remote, regional and local forcing. With the INSTANT data set, we can provide meaningful estimates of the mean ITF and the variability of the associated mass and property fluxes over intra-seasonal, seasonal and inter-annual time scales, all objectives of the INSTANT program. Additionally the INSTANT ITF time series will be used for comparison to output from an array of models to evaluate the skill of these models at simulating aspects of the ITF. The direct measurements of INSTANT will help to mold and ground-truth the required algorithms necessary to convert regional in situ and satellite data into ITF transport proxies as a component of an effective long-term monitoring strategy.Intellectual Merit: Quantitative knowledge of the behavior of the ITF is of fundamental importance to a wide range of ocean and climate research. The definitive INSTANT ITF data set will allow for quantitative evaluation of model simulation of the ITF and its links with large scale and regional ocean and climate conditions. The INSTANT measurements will serve as the basis of a long-term proxy monitoring system as required to capture the low-frequency ITF variability.Broader Impacts: As part of the INSTANT educational and outreach component a series of workshops are proposed that will be of benefit to students and post-docs from Indonesia, the USA, and other international partners. Capacity building activities include training visits by Indonesian/East Timor students to SIO and LDEO to work on INSTANT analysis, and support for an Indonesian graduate student at LDEO. Validation of the models with the INSTANT data will benefit a wide range of ocean, climate, and management needs.This project is a contribution to the US CLIVAR (CLImate VARiability and predictability) Program.
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