VISUALIZATION: Advanced Weather Data Visualization

可视化：高级天气数据可视化

• 批准号: 0500467
• 负责人: David Ebert
• 金额: --
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-10-20 至 2007-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0500467&HistoricalAwards=false
• 关键词: VISUALIZATION; Advanced; Weather; Data; Visualization

The atmospheric science community requires visualization of observed, measured, and simulated data for accurate analysis of the atmosphere and improved weather prediction. Unlike many scientific communities, weather observers and atmospheric scientists rely heavily on important visual cues in the atmosphere to determine the potential severity of many storms.However, the current state-of-the-art in weather visualization from systems such as Vis5D, VisAD, or D3D, lack important visual information that is crucial for atmospheric scientists to fully understand the development and evolution of weather systems.Recognizing the importance of these visual cues, this project will significantly enhance the visualization of weather data through the development of innovative software techniques that will provide more accurate and effective visual representations of weather data. Simple visualization practices, such as depth cueing, isosurface texturing, volume shading, shadows, and correct natural color effects (such as sunlight) are absent in current weather data visualization software. While advanced computer graphics applications (e.g., movie production) have effectively used these techniques for some time, they have yet to be applied in a robust way to weather data. In this project, we will not only fill this gap to create improved, visually accurate weather data visualization, but also increase the quantity and clarity of the information conveyed from the resulting visualizations. Using mature numerical weather prediction software, the Advanced Regional Prediction System (ARPS), to generate numerically simulated severe weather events, new software techniques will be developed to enhance the visualization of this data and begin a new era in weather data visualization.Beyond current capabilities of standard isosurfaces, scalar volume renderings, and two-dimensional images lies important rendering capabilities for weather visualization, such as shaded volumes, shadows, light-transport, and simulated natural cloud modeling. In this project, we will develop, enhance, and apply these techniques to atmospheric data in ways which have yet to be attempted.The primary goal of our research is to produce visually accurate images of weather model data that will provide more accurate information than current methods and use the same cognitive model and analysis process as the forecasters already use, allowing them to increase their effectiveness. We will additionally develop techniques to effectively incorporate non-visual data and allow the selective visualization of the visual / non-visual weather data to enable better understanding of the relationships between these variables and quantities. Our goal is to develop these improved techniques, while also allowing interactive exploration of the observed, measured, and model data.Through the use of programmable graphics hardware with three-dimensional texture-mapping, we will implement techniques for interactive visually accurate weather visualization with low-albedo illumination, physics-based atmospheric scattering and attenuation, and volumetric shadowing. We will also implement slower high-albedo illumination models at coarser resolutions to give approximate multiple scattering effects and utilize this scattering information in the illumination calculation per-pixel fragment through three-dimensional texture mapping hardware. We will use perceptually motivated mapping of non-visual weather quantities (e.g., temperature, dewpoint, wind, atmospheric pressure, vorticity) to glyphs, particles, and isosurfaces to provide more information in an easily understandable manner, extending on our previous work in rceptually-motivated glyph rendering, fast isosurface rendering, and volume illustration. Given the capabilities of current graphics hardware, we won't be able to produce truly visually accurate images and animations of time-varying atmospheric data for at least the first half of the project, although we expect to be able to produce good approximations at interactive rates. We also plan to incorporate simple key-frame recording tools into the visualization system for off-line generation of atmospheric visualizations.The weather models produced contain multiple variables at each spatial location. By employing scientific-based combinations of these variables, it is possible to localize specific features contained in these models. We will extend our preliminary work in the development of multi-dimensional transfer function methods for multivariate data to effectively convey information from this complex model data. This improved interactive weather visualization system will increase the effectiveness of atmospheric analysis, improve severe storm forecasting, and enhance the formulation, parameterizations, and physics of numerical weather prediction models. Additionally, it will improve the training of weather observers and atmospheric science students (both undergraduate and graduate), and provide understandable animations to help in basic weather education at the K-12 level. The ultimate goal of this research is to produce a visually accurate, interactive rendering of a numerical severe thunderstorm simulation, thereby enhancing the ability of both the scientist and general user to discover and explore atmospheric processes in an unprecedented way.

大气科学界需要观测、测量和模拟数据的可视化，以便对大气进行准确分析和改进天气预报。与许多科学界不同，气象观测者和大气科学家严重依赖大气中重要的视觉线索来确定许多风暴的潜在严重程度。然而，目前最先进的天气可视化系统，如Vis5D、VisAD或D3D，缺乏重要的视觉信息，这对大气科学家充分了解天气系统的发展和演变至关重要。认识到这些视觉线索的重要性，该项目将通过开发创新的软件技术，显著增强天气数据的可视化，从而提供更准确和有效的天气数据可视化表示。简单的可视化实践，如深度线索、等面纹理、体阴影、阴影和正确的自然色彩效果（如阳光），在当前的天气数据可视化软件中是不存在的。虽然先进的计算机图形应用（例如，电影制作）已经有效地使用了这些技术一段时间，但它们尚未以一种可靠的方式应用于天气数据。在这个项目中，我们不仅将填补这一空白，创造更好的、视觉上准确的天气数据可视化，而且还将增加由此产生的可视化所传达的信息的数量和清晰度。利用成熟的数值天气预报软件“高级区域预报系统”（ARPS）生成数值模拟的恶劣天气事件，我们将开发新的软件技术，以加强这些数据的可视化，开创天气数据可视化的新时代。除了目前的标准等值面、标量体渲染和二维图像之外，还有重要的天气可视化渲染功能，如阴影体、阴影、光传输和模拟自然云建模。在这个项目中，我们将以尚未尝试的方式发展、加强和应用这些技术来处理大气数据。我们研究的主要目标是产生视觉上准确的天气模型数据图像，这将比目前的方法提供更准确的信息，并使用与预报员已经使用的相同的认知模型和分析过程，使他们能够提高效率。我们会进一步发展技术，有效地整合非目视数据，并可选择性地将目视/非目视天气数据可视化，以便更好地了解这些变量和数量之间的关系。我们的目标是开发这些改进的技术，同时也允许对观察、测量和模型数据进行交互式探索。通过使用具有三维纹理映射的可编程图形硬件，我们将实现具有低反照率照明、基于物理的大气散射和衰减以及体积阴影的交互式视觉精确天气可视化技术。我们还将在较粗的分辨率下实现较慢的高反照率照明模型，以提供近似的多重散射效果，并通过三维纹理映射硬件在每像素片段的照明计算中利用这些散射信息。我们将使用感知驱动的非视觉天气量（例如，温度，露点，风，大气压，涡度）映射到字形，粒子和等值面，以易于理解的方式提供更多信息，扩展我们之前在感知驱动的字形渲染，快速等值面渲染和体积插图方面的工作。考虑到当前图形硬件的能力，至少在项目的前半部分，我们将无法产生真正视觉上精确的图像和时变大气数据的动画，尽管我们希望能够在交互速率下产生良好的近似。我们还计划将简单的关键帧记录工具整合到可视化系统中，用于离线生成大气可视化。生成的天气模型在每个空间位置包含多个变量。通过采用基于科学的这些变量的组合，可以定位这些模型中包含的特定特征。我们将扩展我们在多维数据的多维传递函数方法的开发方面的初步工作，以有效地从这个复杂的模型数据中传递信息。这种改进的交互式天气可视化系统将提高大气分析的有效性，改进强风暴预报，并加强数值天气预报模式的制定、参数化和物理特性。此外，它将改善对天气观测员和大气科学专业学生（包括本科生和研究生）的培训，并提供易于理解的动画，以帮助K-12阶段的基础天气教育。这项研究的最终目标是产生一个视觉上准确的，交互式的数值雷暴模拟渲染，从而提高科学家和一般用户以前所未有的方式发现和探索大气过程的能力。