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A visualization system for calibrating multimodel ensembles in weather forecast

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Abstract

Sophisticated numerical computation is widely used in weather forecast. Various computation models exist, and each of them is designed for different meteorological elements, areas, or seasons. Therefore, multimodel ensemble forecast is aimed at integrating various numerical model forecasts to obtain an accurate forecast result. The existence of deviations compels forecasters to calibrate ensemble forecast result. Traditional calibration methods are strongly dependent on the experience of the forecaster and are usually performed inefficiently with grid-by-grid or station-by-station mode. Such calibration methods experience several drawbacks, including the high complexity and the low comprehensiveness of searching for similar historical forecast results in a limited dataset and the lack of real-time interactive analysis. To solve these problems and improve the efficiency and the accuracy of calibration, we propose a visualization system for calibrating multimodel ensemble forecast result. This system can assist forecasters to quickly locate potential calibrating stations by visualizing the deviation of historical forecast and observation result. Then, associated regions are calculated automatically under similarity and connectivity constraints, and corresponding coefficients between associated stations are generated based on parameter learning of the factor graph. These associated regions and coefficients are used as a guide for forecasters in setting unified deviation and weight for each numerical model. Finally, automatic calibration is conducted on the rest stations in the associated area. The performance of the visualization system is evaluated with real meteorological data.

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Acknowledgments

This work was supported in part by the Special Scientific Research Fund of Meteorological Public Welfare Profession of China through Grant GYHY201306002 and GYHY201406004, and in part by the National Natural Science Foundation of China through Grant 61272225, 61572274, 91315302 and 51261120376. We thank the National Meteorological Center for providing multimodel ensemble forecast data and station observation data, and anonymous reviewers for their constructive criticism.

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Authors and Affiliations

  1. Institute of Computer-Aided Design, Computer Graphics and Visualization, Tsinghua University, Beijing, China

    Chao Gong, Li Chen & Zhu Zhu

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  1. Chao Gong
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  2. Li Chen
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  3. Zhu Zhu
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Correspondence to Li Chen.

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Gong, C., Chen, L. & Zhu, Z. A visualization system for calibrating multimodel ensembles in weather forecast. J Vis 19, 769–782 (2016). https://doi.org/10.1007/s12650-015-0341-7

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  • DOI: https://doi.org/10.1007/s12650-015-0341-7

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