Collaborative Research: An Advanced Interactive Multifield, Multisource Atmospheric Visual Analysis Environment
协作研究:先进的交互式多领域、多源大气可视化分析环境
基本信息
- 批准号:0513464
- 负责人:
- 金额:$ 62.16万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2005
- 资助国家:美国
- 起止时间:2005-07-15 至 2010-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
该项目将开发一个新的系统来调查和分析积云动力学、云演化和降水形成的许多重要方面,其程度在以前是不可能的。云和降水影响着我们的日常生活、人身安全、商业决策以及地球未来的可持续性。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,云影响我们家中的每日最高和最低温度,它们通过影响入射的太阳辐射量和传出的长波辐射量来调节全球温度。随着地球上的居民越来越关注全球变暖和全球和区域层面的气候变化,有必要了解云和降水在地球系统中的作用,以预测我们星球的未来状态。然而,理解和预测大气现象是一项非常困难的任务,它需要对各种尺度(云尺度、风暴尺度、中尺度、全球尺度)的特性进行测量和建模,融合计算模型数据、测量数据,以及同时融合数百个随时间变化的标量场和矢量场。目前的大气可视化工具无法整合这些不同的数据源,无法传达复杂的三维时变信息,而这些信息是准确理解和预测大气事件所必需的,也无法将可视化表示整合到科学分析和发现过程中。该项目将提供可视化和交互技术的基础进步,以解决这些多尺度、多领域、数据融合、分析、时间关键决策和交互问题。这些新的多尺度、多领域大气可视化工具将:结合新颖、有效、逼真和说明性强的多领域可视化技术;融合观测和模式数据;提高对云动力学、云演化和降水形成的认识;创建有效的多尺度视觉表现;可迅速用于研究、培训和教育;并为可操作、全面和高效的可视化分析创造一个环境。本项目解决的计算机科学和大气科学研究挑战将使其他领域受益:1。提高对积云卷带和暖雨形成的认识,使天气预报模式和可能的全球气候模式能够更好地参数化。2 .加强对学生和大气科学家在三维环境中进行科学研究的训练。统一访问跨多个尺度的共同注册模型和测量数据,极大地提高了对大气的理解,并推进了大气模型和天气预测。创建一个融合的、比较的可视化分析环境,通过校准多个、测量和模拟数据源来减少使用各种数据源所固有的模糊性。创建一个物理上合理的、参数化的标准云模型数据库,用于大气科学研究、渲染研究、照明模拟和验证(例如,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。开发面向高中生和大学生的云与降水形成原理教育模块。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-微尺度集成。通过先进的可视化分析工具进行先进的信息交流,将通过提高科学家和预报员的效率来提高科学发现的速度。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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David Ebert其他文献
Evaluation of deep learning frameworks coupled with an interactive user interface to predict clinical complications after aneurysmal subarachnoid hemorrhage
评估深度学习框架与交互式用户界面相结合以预测动脉瘤性蛛网膜下腔出血后的临床并发症
- DOI:
10.1117/12.3006983 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Rowzat Faiz;Gopichandh Danala;Bappaditya Ray;Warid Islam;David Ebert - 通讯作者:
David Ebert
Deep-sea hydrothermal vents as natural egg-case incubators at Deep-sea hydrothermal vents as natural egg-case incubators at the Galapagos Rift the Galapagos Rift
深海热液喷口作为加拉帕戈斯裂谷的天然蛋壳孵化器 深海热液喷口作为加拉帕戈斯裂谷的天然蛋壳孵化器
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
P. Salinas‐de‐León;Brennan Philips;David Ebert;M. Shivji;F. Cerutti;Cassandra Ruck;Charles R. Fisher;L. Marsh - 通讯作者:
L. Marsh
You Are What You Tweet: A New Hybrid Model for Sentiment Analysis
你发的推文就是你:一种新的情感分析混合模型
- DOI:
10.1007/978-3-319-62416-7_29 - 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Arthur Huang;David Ebert;Parker Rider - 通讯作者:
Parker Rider
Exploring geographic hotspots using topological data analysis
使用拓扑数据分析探索地理热点
- DOI:
10.1111/tgis.12816 - 发表时间:
2021 - 期刊:
- 影响因子:2.4
- 作者:
Rui Zhang;Jonas Lukasczyk;Feng Wang;David Ebert;P. Shakarian;Elizabeth A. Mack;Ross Maciejewski - 通讯作者:
Ross Maciejewski
Correction to: Effectiveness and acceptance of a web-based depression intervention during waiting time for outpatient psychotherapy: study protocol for a randomized controlled trial
- DOI:
10.1186/s13063-018-2806-1 - 发表时间:
2018-07-19 - 期刊:
- 影响因子:2.000
- 作者:
Sasha-Denise Grünzig;Harald Baumeister;Jürgen Bengel;David Ebert;Lena Krämer - 通讯作者:
Lena Krämer
David Ebert的其他文献
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{{ truncateString('David Ebert', 18)}}的其他基金
ART: Intensifying Translation of Research in Oklahoma (InTRO)
艺术:俄克拉荷马州研究的强化转化(InTRO)
- 批准号:
2331409 - 财政年份:2024
- 资助金额:
$ 62.16万 - 项目类别:
Cooperative Agreement
PIPP Phase I: Next Generation Surveillance Incorporating Public Health, One Health, and Data Science to Detect Emerging Pathogens of Pandemic Potential
PIPP 第一阶段:结合公共卫生、单一健康和数据科学的下一代监测,以检测潜在大流行的新兴病原体
- 批准号:
2200299 - 财政年份:2022
- 资助金额:
$ 62.16万 - 项目类别:
Standard Grant
FEW: Technology and Information Fusion Needs to Address the Food, Energy, Water Systems (FEWS) Nexus Challenges
FEW:技术和信息融合需要解决食品、能源、水系统 (FEWS) 的挑战
- 批准号:
1541863 - 财政年份:2015
- 资助金额:
$ 62.16万 - 项目类别:
Standard Grant
FODAVA II - The Science of Interaction Workshop
FODAVA II - 交互科学研讨会
- 批准号:
1144379 - 财政年份:2011
- 资助金额:
$ 62.16万 - 项目类别:
Standard Grant
TLS - Applied Visual Analytics for Economic Decision-Making
TLS - 用于经济决策的应用可视化分析
- 批准号:
0915605 - 财政年份:2009
- 资助金额:
$ 62.16万 - 项目类别:
Standard Grant
VISUALIZATION: Advanced Weather Data Visualization
可视化:高级天气数据可视化
- 批准号:
0500467 - 财政年份:2003
- 资助金额:
$ 62.16万 - 项目类别:
Continuing Grant
Quantifying and Increasing Information Transmission with Data Perceptualization
通过数据感知量化并增加信息传输
- 批准号:
0328984 - 财政年份:2003
- 资助金额:
$ 62.16万 - 项目类别:
Continuing Grant
VISUALIZATION: Advanced Weather Data Visualization
可视化:高级天气数据可视化
- 批准号:
0222675 - 财政年份:2002
- 资助金额:
$ 62.16万 - 项目类别:
Continuing Grant
ITR/AP+IM: Procedural Representation and Visualization Enabling Personalized Computational Fluid Dynamics
ITR/AP IM:程序表示和可视化实现个性化计算流体动力学
- 批准号:
0121288 - 财政年份:2001
- 资助金额:
$ 62.16万 - 项目类别:
Continuing Grant
Visualization and Software Architectures for Volumetric Displays
体积显示的可视化和软件架构
- 批准号:
0196351 - 财政年份:2001
- 资助金额:
$ 62.16万 - 项目类别:
Standard Grant
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