Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding
Climate Engine: Cloud Computing and Visualization of Climate and Remote Sensing Data for Advanced Natural Resource Monitoring and Process Understanding
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DOI：
10.1175/bams-d-15-00324.1
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发表时间：
2017-11-01
影响因子：
8
通讯作者：
Erickson, Tyler
中科院分区：
文献类型：
--
作者：
Huntington, Justin L.;Hegewisch, Katherine C.;Erickson, Tyler
缺乏长期观测，特别是在气候和土地覆盖不均匀的地区，可能妨碍在适当的空间尺度上纳入气候数据，用于决策和科学研究。为满足土地管理者和科学家的需要，开发了许多网格化的气候、天气和遥感产品，从而增加了科学知识，加强了预警系统。然而，鉴于大数据的计算需求，这些数据在很大程度上仍然无法为更广泛的用户所用。Climate Engine（ClimateEngine.org）是一个基于网络的应用程序，它克服了用户面临的许多计算障碍，采用谷歌的并行云计算平台，谷歌地球引擎，处理，可视化，下载和真实的实时共享气候和遥感数据集。简要介绍了气候引擎的软件应用程序开发和设计，以说明使用云计算高性能处理大数据的潜力。其次，介绍了几个例子，以突出一系列的气候研究和应用相关的干旱，火灾，生态和农业，可以快速生成使用气候引擎。通过按需并行云计算访问气候和遥感数据档案的能力为先进的自然资源监测和过程理解创造了巨大的机会。
The paucity of long-term observations, particularly in regions with heterogeneous climate and land cover, can hinder incorporating climate data at appropriate spatial scales for decision-making and scientific research. Numerous gridded climate, weather, and remote sensing products have been developed to address the needs of both land managers and scientists, in turn enhancing scientific knowledge and strengthening early-warning systems. However, these data remain largely inaccessible for a broader segment of users given the computational demands of big data. Climate Engine (http://ClimateEngine.org) is a web-based application that overcomes many computational barriers that users face by employing Google's parallel cloud-computing platform, Google Earth Engine, to process, visualize, download, and share climate and remote sensing datasets in real time. The software application development and design of Climate Engine is briefly outlined to illustrate the potential for high-performance processing of big data using cloud computing. Second, several examples are presented to highlight a range of climate research and applications related to drought, fire, ecology, and agriculture that can be rapidly generated using Climate Engine. The ability to access climate and remote sensing data archives with on-demand parallel cloud computing has created vast opportunities for advanced natural resource monitoring and process understanding.