A Spark-Based High Performance Computational Approach for Simulating Typhoon Wind Fields

• Main Authors: Shaofu Lin, Weihua Fang, Xinyu Wu, Yiran Chen, Zhou Huang
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Typhoon wind; risk assessment; cloud computing; Spark; geographic information system
• Online Access: https://ieeexplore.ieee.org/document/8396261/

The impacts of typhoons on coastal areas around the globe necessitate the risk assessments of typhoon events to analyze their paths, intensity, and impacts on the environment for disaster prevention and reduction as well as for the scientific assessments of typhoon impacts. To this end, the typhoon wind field needs to be obtained by inversion to attain its temporal and spatial scopes of influence and disaster-inducing intensities using simulation algorithms that are based on the existing typhoon path data. The wind field calculation is a typical kind of compute-intensive processing. It is time-consuming (especially when the temporal resolution and the spatial resolution are high) to an extent, which makes it difficult for a traditional stand-alone computation to meet the application needs for typhoon risk assessments. Therefore, studies need to be conducted to accelerate the wind field calculations. Currently, the most economical and relatively feasible method is to rapidly generate a large quantity of typhoon risk data using multi-thread, graphics processing unit computing or clustering technologies (e.g., cloud computing). Hence, we have attempted to use the latest cloud computing framework, Spark, for the rapid simulation of the typhoon wind field. This paper proposed a storage model for typhoon paths and wind fields under the Spark environment, as well as a wind field parallel acceleration method based on Spark. Using this approach, we have calculated a total of 1038 historical wind fields that impacted the northwestern Pacific Ocean from 1949 to 2014. The results indicate that the Spark-based wind field computation method proposed in this paper has a greater advantage in terms of performance, which facilitates the typhoon risk assessment feasibility.