A Methodological Study of Big Data and Atmospheric Science

该奖项支持一个为期两年的项目，该项目调查大气科学中大数据的基本方法学方面。国际大气研究所与国家大气研究中心的科学家和几名研究助理(一名博士后和一些研究生)合作，计划建立一些基本基础，了解和分析大气科学和建模中大数据分析和应用的各种方法的相对优点。研究人员和她的合作者要解决的主要问题包括以下几个。收集、传播和使用数据的做法和技术如何影响科学知识的生产？理论和假设在研究实践和数据分析中的作用是什么？如果数据驱动的研究构成了一种独特的知识生产模式，那么这种知识是如何最好地交付的呢？这位研究人员打算在大气科学中建立大数据哲学；她计划通过为不同的专业期刊撰写几篇论文，将她的研究成果传播给不同的受众。这位研究人员还打算制定和交流她的大数据研究可能产生的任何政策知识。她还计划培训一名博士后和一些研究生，以便他们可以为政策制定者提供资源，促进将大气科学有效地应用于公共政策。PI和她的合作者将研究从涉及TB级数据的多个大气模型的输出的大数据环境中转移到应用和简化这些数据，以满足特定城市对特定温度预报的请求所涉及的内容，以及这种分析如何通过以目前尚未完成的方式对大数据进行分析而变得更加自动化。在世界各地的建模小组中，区域建模人员面临的一个根本问题是，有数以万计的城市和区域规划者需要区域天气模型的信息，但如果没有创建模型的科学家的帮助，这些用户和影响人员所需的信息无法读出。他们需要在模型和影响之间进行翻译--人员和用户。PI将在国家大气研究中心与一个建模小组合作，该小组正试图开发各种自动化来回答用户和影响人员提出的一系列问题，将大数据简化为小问题的自动化，并针对特定问题提供具体答案，以避免各种陷阱和模型的特殊性。也就是说，他们正在努力构建可以充当翻译器的大数据软件系统。这些问题在某种程度上因数据庞大而显著加剧，而且他们发现，可用的大数据分析并没有以理想的方式帮助他们。PI和合作者建议更准确地强调、澄清和定义这个群体和其他人在他们的社会背景应用中到底可以使用什么。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award supports a two-year project that investigates fundamental methodological aspects of Big Data in atmospheric science. The PI, in collaboration with scientists at the National Center for Atmospheric Research and several research assistants (a post-doctoral fellow and some graduate students), plans to establish some basic foundations, understandings and analysis of the relative merits of a variety of methods in the analysis and application of Big Data within atmospheric science and modeling. The main questions to be addressed by the researcher and her collaborators include the following. How do practices and technologies for data collection, dissemination and use affect the production of scientific knowledge? What is the role of theories and hypotheses within research practices and data analysis? If data-driven research constitutes a distinctive mode of knowledge production, how is that knowledge best delivered? The researcher intends to establish a philosophy of Big Data in atmospheric science; she plans to disseminate the results of her research to different audiences by producing several papers for diverse professional journals. The researcher also intends to formulate and communicate any knowledge for policy that might result from her Big Data research. She also plans to train a post-doc and some grad students so that they may serve as resources for policy makers to facilitate effective application of atmospheric science to public policy.The PI and her collaborators will examine what is involved in moving from the Big Data context of the outputs of multiple atmospheric models involving terabytes of data, to the applications and reduction of that data to a particular city's request for specific temperature forecasts, and how this analysis might become more automated through analysis of Big Data in a way not being done at present. This fundamental problem facing the regional modelers in modeling groups around the world is that there are tens of thousands of city and regional planners who need information from the regional weather models, but the information these users and impact-personnel need is not available to read off of the model without the help of the scientists who created it. They need translators between the models and the impact-personnel and users. One modeling group the PI would be working with at the National Center for Atmospheric Research is attempting to develop automation of various kinds to answer a range of questions from users and impact-personnel, automation that reduces Big Data into small and specific answers to specific questions that avoids various pitfalls and peculiarities of the models. That is, they are trying to build Big Data software systems that could act as translators. These problems are significantly exacerbated by the data being Big in one way or another, and they find that the available Big Data analytics are not helping them in the way they ideally could. The PI and collaborators propose to highlight, clarify, and define more precisely what exactly this group and others could use in their applications to social contexts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.