Dean N. Williams, C. Doutriaux, B. Drach, R. McCoy
{"title":"The Flexible Climate Data Analysis Tools (CDAT) for Multi-model Climate Simulation Data","authors":"Dean N. Williams, C. Doutriaux, B. Drach, R. McCoy","doi":"10.1109/ICDMW.2009.64","DOIUrl":null,"url":null,"abstract":"Being able to incorporate, inspect, and analyze data with newly developed technologies, diagnostics, and visualizations in an easy and flexible way has been a longstanding challenge for scientists interested in understanding the intrinsic and extrinsic empirical assessment of multi-model climate output. To improve research ability and productivity, these technologies and tool must be made easily available to help scientists understand and solve complex scientific climate changes. To increase productivity and ease the challenges of incorporating new tools into the hands of scientists, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) developed the Climate Data Analysis Tools (CDAT). CDAT is an application for developing and bringing together disparate software tools for the discovery, examination, and intercomparison of coupled multi-model climate data. By collaborating with top climate institutions, computational organizations, and other science communities, the CDAT community of developers is leading the way to provide proven data management, analysis, visualization, and diagnostics capabilities to scientists. This communitywide effort has developed CDAT into a powerful and insightful application for knowledge discovery of observed and simulation climate data. As an analysis engine in the Earth System Grid (ESG) data infrastructure, CDAT is making it possible to remotely access and analyze climate data located at multiple sites around the world.","PeriodicalId":351078,"journal":{"name":"2009 IEEE International Conference on Data Mining Workshops","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2009.64","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Being able to incorporate, inspect, and analyze data with newly developed technologies, diagnostics, and visualizations in an easy and flexible way has been a longstanding challenge for scientists interested in understanding the intrinsic and extrinsic empirical assessment of multi-model climate output. To improve research ability and productivity, these technologies and tool must be made easily available to help scientists understand and solve complex scientific climate changes. To increase productivity and ease the challenges of incorporating new tools into the hands of scientists, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) developed the Climate Data Analysis Tools (CDAT). CDAT is an application for developing and bringing together disparate software tools for the discovery, examination, and intercomparison of coupled multi-model climate data. By collaborating with top climate institutions, computational organizations, and other science communities, the CDAT community of developers is leading the way to provide proven data management, analysis, visualization, and diagnostics capabilities to scientists. This communitywide effort has developed CDAT into a powerful and insightful application for knowledge discovery of observed and simulation climate data. As an analysis engine in the Earth System Grid (ESG) data infrastructure, CDAT is making it possible to remotely access and analyze climate data located at multiple sites around the world.