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Spatial Cyberinfrastructure Special Feature: Spatial characterization of the meltwater field from icebergs in the Weddell Sea

机译:空间网络基础设施的特色:韦德尔海冰山融水场的空间特征

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摘要

We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.
机译:我们描述了为表征单个冰山周围的融水场而开发的空间网络基础设施的结果,并将结果与​​区域和全球规模的数据相结合。在网络基础设施发展的过程中,很明显,我们还在跨多学科团队的基础上建立了综合的采样计划能力,从而为分配探险资源提供了更大的灵活性,从而产生了新的科学见解。启用电子基础设施的方法是对常规水文采样方法的补充,在常规水文采样中,船舶逐站提供了静态平台。我们采用了海底地图绘制方法,以更快速地从地理上和生物学上表征海面。通过使用全球定位系统时间作为数据融合关键,通过联合分析多源,连续采样的生物,化学和物理参数,这种表面映射方法使我们能够检查冰山融水场与更大尺度之间的关系。南部海洋的海洋生态系统。通过地理空间数据融合,我们可以将动态过程的非常精细的地图与来自卫星系统的天气概要但分辨率较低的数据相结合。我们的结果说明了空间网络基础设施在整个科学企业中的重要性,并确定了关键的接口和错误源,随着我们进入Peta级和Exascale级,数据密集型计算的时代,需要改进控制措施来开发未来的地球观测系统。

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