Cyclone center identification and radius evaluation method based on sea level air pressure data

Abstract

The invention relates to a cyclone center identification and radius evaluation method based on sea level air pressure data. A program language is used to read MSLP (Mean sea level pressure) data, theMSLP data of the global grids is projected to equivalent-area polar orthographic projection in the projection resolution of 100km*100km, a Laplacian value of each grid is calculated, and all the gridsare iterated cyclically to search for the cyclone center. Adjacent cyclone centers are merged, each cyclone center is calculated in eight direction gradients, and the effective radius of the cycloneis estimated. An image display window is established, and the MSLP data, identified cyclone center and radius can be visualized. The problem of cyclone data lack is solved, the accuracy and scientificlevel are higher, a user can adjust parameters of the algorithm according to requirements, and thus, an algorithm is more flexible to use, and an extraction result is more targeted.

Description

technical field [0001] The invention relates to a grid data processing step, in particular to a flow of a cyclone center identification and radius estimation method based on sea level air pressure data. Background technique [0002] Cyclone is a kind of extreme weather condition. Because of its wide range of influence, fast moving speed, and can cause severe changes in local weather, it has become the climate system that human beings are very concerned about and the earliest researched. Cyclones play an important role in the weather conditions in the areas they pass through, and the accompanying extreme weather may cause property damage and casualties. In addition, in the context of global climate change, as an important mobile local weather pattern, cyclone activity will also contribute to the fluctuation of atmospheric conditions, which in turn will lead to non-negligible climate impacts. However, due to the complexity of cyclone movement, there is a lack of long-term met...

AI Technical Summary

Problems solved by technology

However, due to the complexity of cyclone movement, there is a lack of long-term meteorological data on cyclones. Since 1979, the quantity and quality of MSLP reanalysis data have been significantly improved. Therefore, a method based on sea level pressure data is proposed. Cyclone center identification and radius estimation algorithm, in order to obtain long-term series of cyclone center and radius data, which can be used for later cyclone tracking, research on the distribution characteristics and changes of long-term scale cyclone activities, and explore the impact of cyclones on climate change and other topics Provide basic data, and the research results can also be applied to the forecast of some weather conditions

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