Song Yuyan, Ye Jing, Svakhine Nikolai, Lasher-Trapp Sonia, Baldwin Mike, Ebert David S
Purdue University, USA.
IEEE Trans Vis Comput Graph. 2006 Sep-Oct;12(5):1157-64. doi: 10.1109/TVCG.2006.117.
Meteorological research involves the analysis of multi-field, multi-scale, and multi-source data sets. In order to better understand these data sets, models and measurements at different resolutions must be analyzed. Unfortunately, traditional atmospheric visualization systems only provide tools to view a limited number of variables and small segments of the data. These tools are often restricted to two-dimensional contour or vector plots or three-dimensional isosurfaces. The meteorologist must mentally synthesize the data from multiple plots to glean the information needed to produce a coherent picture of the weather phenomenon of interest. In order to provide better tools to meteorologists and reduce system limitations, we have designed an integrated atmospheric visual analysis and exploration system for interactive analysis of weather data sets. Our system allows for the integrated visualization of 1D, 2D, and 3D atmospheric data sets in common meteorological grid structures and utilizes a variety of rendering techniques. These tools provide meteorologists with new abilities to analyze their data and answer questions on regions of interest, ranging from physics-based atmospheric rendering to illustrative rendering containing particles and glyphs. In this paper, we will discuss the use and performance of our visual analysis for two important meteorological applications. The first application is warm rain formation in small cumulus clouds. Here, our three-dimensional, interactive visualization of modeled drop trajectories within spatially correlated fields from a cloud simulation has provided researchers with new insight. Our second application is improving and validating severe storm models, specifically the Weather Research and Forecasting (WRF) model. This is done through correlative visualization of WRF model and experimental Doppler storm data.
气象研究涉及对多领域、多尺度和多源数据集的分析。为了更好地理解这些数据集，必须分析不同分辨率下的模型和测量数据。不幸的是，传统的大气可视化系统仅提供查看有限数量变量和数据小段的工具。这些工具通常限于二维等高线图或矢量图或三维等值面图。气象学家必须在脑海中综合多个图的数据，以获取生成感兴趣天气现象连贯图像所需的信息。为了向气象学家提供更好的工具并减少系统限制，我们设计了一个用于天气数据集交互式分析的综合大气视觉分析与探索系统。我们的系统允许在常见气象网格结构中对一维、二维和三维大气数据集进行综合可视化，并利用多种渲染技术。这些工具为气象学家提供了分析数据以及回答有关感兴趣区域问题的新能力，范围从基于物理的大气渲染到包含粒子和符号的说明性渲染。在本文中，我们将讨论我们的视觉分析在两个重要气象应用中的使用和性能。第一个应用是小积云中暖雨的形成。在此，我们对云模拟中空间相关场中的模拟液滴轨迹进行的三维交互式可视化，为研究人员提供了新的见解。我们的第二个应用是改进和验证强风暴模型，特别是天气研究与预报（WRF）模型。这是通过对WRF模型和实验性多普勒风暴数据进行相关可视化来完成的。
