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.
