Tropical cyclone and business English cross-cultural communication based on temporal big data

Numerical simulation has always been the most important method for predicting tropical cyclone activity and has also been widely used in tropical cyclone climate research in recent years. However, the ability of numerical models to simulate tropical cyclone activities on a climate scale is still uncertain. Therefore, it is necessary to strengthen the modeling of the physical process of the model and strengthen the understanding of the impact of simulated tropical cyclone activities. In this article, time information is used to study the activities of tropical cyclones. Since time information is everywhere, a large amount of time information is now generated. This paper proposes a Spark-based auxiliary catalog system for managing large amounts of time data in a distributed environment. It uses a local index structure to significantly improve the query efficiency of temporal operations. Using this technology to explore tropical cyclones in the sea can improve the accuracy of tropical cyclone activity simulation and further the research on tropical cyclone climatology. In this article, we also apply tense big data to business English cross-cultural communication and use tense big data to manage a large amount of information that exists in business English cross-cultural communication, so that researchers can use relevant information to find problems in cross-cultural communication in the company language, and then study these problems. From the perspective of cross-cultural communication theory, this helps to enhance students’ phonological awareness and improve their use of business English. This paper uses a large amount of time data as the research basis and applies it to tropical cyclones at sea and business English to promote the vigorous development of cross-cultural communication.