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，以准确分析大气和改进天气预报。与许多科学界不同，天气观测员和大气科学家严重依赖大气中的重要视觉线索来确定许多风暴的潜在严重性。然而，目前最先进的Vis 5D、VisAD或D3 D等系统的天气可视化，缺乏对大气科学家充分了解天气系统的发展和演变至关重要的重要视觉信息。鉴于这些视觉提示的重要性，本项目将通过开发创新的软件技术，提供更准确和更有效的天气数据可视化表示，大大提高天气数据的可视化效果。简单的可视化实践，如深度提示，等值面纹理，体积阴影，阴影和正确的自然颜色效果（如阳光）是目前的天气数据可视化软件中缺乏。 虽然高级计算机图形应用（例如，电影制作）已经有效地使用这些技术一段时间了，但是它们还没有以稳健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，以创建改进的、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，将开发新的软件技术，以增强这种数据的可视化，并开始天气数据可视化的新时代。除了标准等值面、标量体绘制和二维图像的现有能力之外，天气可视化的重要绘制能力，例如阴影体积、阴影、光传输和模拟的自然云建模。在这个项目中，我们将开发，增强和应用这些技术的方式，还没有尝试大气数据，我们的研究的主要目标是产生视觉上准确的图像的天气模型数据，将提供更准确的信息比目前的方法，并使用相同的认知模型和分析过程，作为预报员已经使用，使他们能够提高他们的效率。我们还将开发技术，以有效地结合非视觉数据，并允许视觉/非视觉天气数据的选择性可视化，以便更好地理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，同时也允许交互式探索的观察，测量和模型data.Through使用可编程图形硬件与三维纹理映射，我们将实现交互式视觉准确的天气可视化技术与低照度，基于物理的大气散射和衰减，和体积阴影。我们还将在较粗糙的分辨率下实现较慢的高散射度照明模型，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个像素片段的照明计算中利用此散射信息。我们将使用非视觉天气量的感知动机映射（例如，温度，露点，风，大气压力，涡度）到字形，粒子和等值面，以易于理解的方式提供更多的信息，扩展了我们以前的工作，在基于概念的三维渲染，快速等值面渲染和体积插图。鉴于目前的图形硬件的能力，我们将无法产生真正的视觉上准确的图像和动画的时变大气数据至少在项目的前半部分，虽然我们希望能够产生良好的近似在互动的速度。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，以便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。通过采用这些变量的科学组合，有可能将这些模型中包含的具体特征本地化。我们将扩展我们的初步工作，在多元数据的多维传递函数方法的发展，有效地传达信息，从这个复杂的模型数据。这一改进的交互式天气可视化系统将提高大气分析的有效性，改善强风暴预报，并增强数值天气预报模型的公式化、参数化和物理学。此外，它将改善天气观测员和大气科学学生（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水平的基础天气教育。这项研究的最终目标是产生一个视觉上准确的，交互式渲染的数值严重雷暴模拟，从而提高科学家和普通用户的能力，发现和探索大气过程中前所未有的方式。