由于天气数值预报产品不可避免地存在各种偏差，现有的天气预报需依靠预报员凭借数据分析和个人经验订正完成。本项目旨在依托气象预报订正这样一个对可视分析技术有巨大需求、对国计民生有重要意义的应用，针对气象数据所具有的大规模、多源异构、不确定性、实时性等挑战性问题，探索多模式、多趟、多变量数值模式数据不确定性及其随时间演变的可视分析方法、基于历史回报数据类比的模式预报可靠性可视分析方法、多模态监测和数值预报异构数据的对比分析建模及可视分析方法、预报偏差可视分析结果驱动的智能预报场订正方法，在可视分析的方法和理论上突破和创新。进而在最新的并行架构CPU+MIC+GPU上通过MPI+OpenMP+CUDA三级混合并行编程实现一个可应对大规模气象数据的实时可视分析和集合预报订正系统，大幅提升预报订正的合理性、有效性及便捷性，提高气象预报准确度，并在中国国家气象中心及美国NOAA地球系统实验室得到应用。

Numerical weather forecast products always have inevitable biases because of various reasons, such as the imperfection of the weather forecast models. Forecasters need to calibrate it based on data analysis and long-term personal working experiences in operational weather forecasts. There are great requirements in the calibration for visual analytic techniques in order to help forecasters analyze and calibrate the large-scale and heterogeneous data from multiple sources. This project aims at proposing novel methods and providing solutions for the challenging topics in the visual weather forecast calibration. First, the level of detail visual design and topology based visualization method are proposed to analyze and visualize the uncertainty and its evolution of multi-modal, multi-run, multi-variable and multi-timestep numerical weather data. Second, the reliability of numerical weather product is visually evaluated with the analog based method using the reforecast data. Third, a visual comparison model is set up to support the comparisons between the multi-modal observation data and the numerical weather data. Fourth, the bias results got from the previous comparisons are applied to drive the intelligent calibration. Furthermore, a real-time visual analysis system is developed to deal with large-scale meteorological data for the calibration in the project. It will be implemented using a three-level hybrid parallelization with MPI, OpenMP and CUDA on a high performance hybrid parallel architecture based on CPU+MIC+GPU. The system is expected to improve the rationality, effectiveness and efficiency of the calibration as well as the accuracy of the weather forecast. Besides, it will be verified in China Meteorological Administration and NOAA Earth System Research Laboratory.