Collaborative Research: An Advanced Interactive Multifield, Multisource Atmospheric Visual Analysis Environment

该项目将开发一种新的系统，以调查和分析积云动力学，云的演变和降水形成的许多重要方面，在一定程度上，以前是不可能的。 云和降水影响着我们的日常生活、人身安全、商业决策以及我们未来在地球上的可持续性。云和降水在所有区域尺度上都很重要：地方，州，国家和全球。例如，云会影响我们家中每天的最高和最低温度，并通过影响入射太阳辐射和射出长波辐射的量来调节全球温度。随着地球居民对全球变暖和全球和区域气候变化的日益关注，为了预测地球的未来状态，有必要了解云和降水在地球系统中的作用。然而，了解和预测大气现象是非常困难的任务，需要在各种尺度上测量和模拟各种性质（云尺度、风暴尺度、中尺度、全球）、计算模型数据、测量数据的融合以及随时间变化的数百个标量场和矢量场的同时融合。目前的大气可视化工具无法整合这些不同的数据源，传达准确理解和预测大气事件所需的复杂的三维时变信息，或将视觉表示融入科学分析和发现过程。该项目将提供可视化和交互技术的根本进步，以解决这些多尺度，多领域，数据融合，分析，时间关键的决策和交互问题。这些新的多尺度、多场大气可视化工具将：采用新颖、有效、逼真和说明性的多场可视化技术;融合观测和模型数据;提高对云动态、云演变和降水形成的理解;创建有效的多尺度可视化表示;迅速用于研究、培训和教育;并为可操作、全面且高效的视觉分析创造环境。在这个项目中解决的计算机科学和大气科学研究挑战将有利于其他领域：1。提高对积云卷吸和暖雨形成的理解，从而在天气预报模型和可能的全球气候模型中实现更好的参数化。加强对学生和大气科学家的培训，使他们能够在三维环境中开展科学研究。统一获取多个尺度的模式和实测数据，大大提高对大气的认识，推进大气模式和天气预报.创建一个融合的、比较性的可视化分析环境，通过校准多个测量和模拟数据源，减少使用各种数据源时固有的模糊性。5.创建一个物理上合理的、参数化的规范云模型数据库，用于大气科学研究、渲染研究、照明模拟和验证（例如，在各种天气条件下的前照灯能见度）和视觉效果行业。开发一种新的架构和可视化工具，用于大规模，多尺度，多领域的数据集成，融合，分析和实验，供更大的大气科学界使用。为高中和大学生开发关于云和降水形成原理的教育模块。待开发的技术将显著改变可视化和大规模数据分析的最新技术，并对使用多领域，多尺度数据的许多领域产生巨大影响，包括计算流体动力学，生物学，医学，天体物理学和纳米尺度-微米尺度集成。通过先进的视觉分析工具进行先进的信息交流，将提高科学家和预报员的效率，从而提高科学发现的速度。

This project will develop a novel system to investigate and analyze many important aspects of cumulus cloud dynamics, cloud evolution, and precipitation formation to an extent that has previously been impossible. Clouds and precipitation affect our daily lives, personal safety, commercial decisions, and our future sustainability on Earth. Clouds and precipitation are important at all regional scales: local, state, national, and global. For example, clouds influence the daily maximum and minimum temperatures over our homes and they modulate the global temperature by affecting the amount of incoming solar radiation and outgoing longwave radiation. As the inhabitants of earth become increasingly concerned about global warming and climate change on global and regional levels, it is necessary to understand the roles of clouds and precipitation in the Earth System in order to predict the future state of our planet.However, understanding and predicting atmospheric phenomena are very difficult tasks which require the measurement and modeling of properties on a wide variety of scales (cloud scale, storm scale, mesoscale, globally), fusion of computational model data, measured data, and the simultaneous fusion of hundreds of scalar and vector fields that vary over time. Current tools for atmospheric visualization are not capable of integrating these various data sources, communicating the complex three-dimensional, time-varying information necessary to accurately understand and predict atmospheric events, or for the integration of visual representations into the scientific analysis and discovery process. This project will provide a fundamental advance in visualization and interaction techniques to solve these multiscale, multifield, data fusion, analysis, time-critical decision making, and interaction problems. These new multiscale, multifield, atmospheric visualization tools will: incorporate novel, effective, photorealistic and illustrative multifield visualization techniques; fuse observational and model data; improve the understanding of cloud dynamics, cloud evolution and precipitation formation; create effective multiscale visual representations; be rapidly deployed for research, training, and education; and produce an environment for actionable, comprehensive and efficient visual analysis. Both computer science and atmospheric science research challenges addressed in this project will benefit other fields by: 1. Improving understanding of cumulus entrainment and warm rain formation, leading to better parameterizations in weather forecasting models and possibly global climate models.2. Improving training of students and atmospheric scientists to perform their science in three dimensional environments.3. Unifying access to co-registered model and measured data across multiple scales, greatly improving the understanding of the atmosphere, and advancing atmospheric models and weather prediction.4. Creating a fused, comparative visual analysis environment to reduce the ambiguity inherent in the use of a variety of data sources by calibrating multiple, measured and simulation data sources.5. Creating a physically plausible, parameterized database of canonical cloud models for use in atmospheric science research, rendering research, illumination simulation and validation (e.g., headlamp visibility in various weather conditions) and in the visual effects industry.6. Developing a new architecture and visualization tools for large scale, multiscale, multifield data integration, fusion, analysis, and experimentation for use by the larger atmospheric science community.7. Developing modules for educating high school and undergraduate students about the principles of cloud and precipitation formation. The techniques to be developed will significantly change the state-of-the-art of visualization and large-scale data analysis, and have a dramatic impact on many fields using multifield, multiscale data, including computational fluid dynamics, biology, medicine, astrophysics, and nanoscale-microscale integration. Advanced information communication through advanced visual analysis tools will increase the rate of scientific discovery by improving the effectiveness of scientists and forecasters.