分水岭再分析:迈向模型-数据整合的国家战略

C. Duffy, Lorne Leonard, G. Bhatt, Xuan Yu, C. Lee Giles
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引用次数: 7

摘要

再分析或回顾性分析是将气候和天气观测资料与当前模式背景重新分析和同化的过程。再分析是一种在统一框架内综合所有信息来源(历史和实时观察)的客观定量方法。在此背景下,我们提出了一个自动化和虚拟化web服务软件的原型,该软件使用国家数据产品进行气候再分析、土壤、地质、地形和土地覆盖,用于水资源模拟、预测、数据同化、校准和存档。模型-数据集成的原型侧重于创建工具,用于从选定的国家数据库中快速存储数据,以及为美国大陆任何地方的动态分布式分水岭预测所需的计算资源。在未来,虚拟化服务的实施将受益于云网络基础设施的发展,因为原型将演变为大陆尺度水资源预测的数据和模型密集型计算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Watershed Reanalysis: Towards a National Strategy for Model-Data Integration
Reanalysis or retrospective analysis is the process of re-analyzing and assimilating climate and weather observations with the current modeling context. Reanalysis is an objective, quantitative method of synthesizing all sources of information (historical and real-time observations) within a unified framework. In this context, we propose a prototype for automated and virtualized web services software using national data products for climate reanalysis, soils, geology, terrain and land cover for the purpose of water resource simulation, prediction, data assimilation, calibration and archival. The prototype for model-data integration focuses on creating tools for fast data storage from selected national databases, as well as the computational resources necessary for a dynamic, distributed watershed prediction anywhere in the continental US. In the future implementation of virtualized services will benefit from the development of a cloud cyber infrastructure as the prototype evolves to data and model intensive computation for continental scale water resource predictions.
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