Collaborative Research: From Data to Users: A Prototype Open Modeling Framework

协作研究：从数据到用户：原型开放建模框架

• 批准号: 1245171
• 负责人: Yao Liang
• 金额: $ 8.85万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-15 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1245171&HistoricalAwards=false
• 关键词: Collaborative; Research; Data; Users; Prototype

Because Earth is a complex coupled interacting system, where no one element is independent of any other, there are both pressing scientific and societal needs to improve our understanding how various physical, biological, and hydrological processes interact in surface Earth systems. This requires the development of new and increasingly more sophisticated ways of mathematically describing these systems and improvements in software and user interfaces that will dramatically enhance our ability to simulate these systems to improve the accuracy and reliability of model predictions of weather, floods, droughts, and climate variability. Such improved models will allow researchers to make better use of available data across disciplines and improve theory and algorithms that are essential to understanding Earth system behavior. Unfortunately, at present there is significant overhead of time and effort needed for discovering, accessing, understanding, and preparing data required to populate these models, as well as long learning lead times on how to use presently available models, owing to their complexity. This research overcomes some of these limitations by developing an innovative open modeling framework that can integrate data and models easily and is easy to use so that not only the research community and operational professionals can use it, but also policy makers and other interested parties. This EAGER award allows the construction of a prototype open meta-modeling framework that significantly reduces the time and effort on the part of users in the preparatory work for data and model comparisons, model testing and validations, for making fundamental knowledge discoveries in surface and ground water hydrological systems. In this framework, components/modules interact via user-configured open interfaces that allow the addition and integration of hydrological models and data sources using a common meta-level architecture and scientific workflows. The proposed prototype is based on a recently completed modeling framework, HS-NWSRFS (Hydro-information System for improving the National Weather Service River Forecast System). It represents a collaboration between investigators from three institutions, NASA, and NWS Ohio River Forecast Center (OHRFC). The funded effort will significantly expand the present code into an open community framework prototype. Broader impacts of the work include interagency collaboration, improved hydrological forecasting for rivers, and support of a PI whose gender is under-represented in the sciences.

由于地球是一个复杂的耦合相互作用系统，其中没有一个元素是独立于其他元素的，因此有迫切的科学和社会需求来提高我们对地球表面系统中各种物理、生物和水文过程如何相互作用的理解。这需要开发新的、越来越复杂的数学描述这些系统的方法，并改进软件和用户界面，这将极大地增强我们模拟这些系统的能力，以提高天气、洪水、干旱和气候变异性模型预测的准确性和可靠性。这种改进的模型将使研究人员能够更好地利用跨学科的可用数据，并改进对理解地球系统行为至关重要的理论和算法。不幸的是，目前发现、访问、理解和准备填充这些模型所需的数据需要大量的时间和精力，而且由于它们的复杂性，关于如何使用现有模型的学习准备时间很长。这项研究通过开发一种创新的开放式建模框架克服了其中的一些限制，该框架可以轻松整合数据和模型，并且易于使用，因此不仅研究界和操作专业人员可以使用它，而且政策制定者和其他感兴趣的各方也可以使用它。这项急切的奖励使原型开放式元模型框架的构建大大减少了用户在数据和模型比较、模型测试和验证的准备工作中的时间和精力，以便在地表水和地下水水文系统中发现基本知识。在该框架中，组件/模块通过用户配置的开放接口进行交互，允许使用通用的元级架构和科学工作流程添加和集成水文模型和数据源。拟议的原型是基于最近完成的建模框架HS-NWSRFS(改进国家气象局河流预报系统的水文信息系统)。它代表了来自NASA和NWS俄亥俄河预报中心(OHRFC)三个机构的研究人员之间的合作。资助的工作将极大地将目前的代码扩展为一个开放的社区框架原型。这项工作的更广泛影响包括机构间合作、改进河流的水文预报，以及支持在科学界性别代表性不足的PI。