Method for realizing error prediction by combining tangent method and tropical cyclone prediction path

Abstract

The invention relates to a method for realizing error prediction by combining a tangent method and a tropical cyclone prediction path. The method comprises the steps of providing a current position point and a plurality of prediction nodes with the quantity of an integer number, creating an error range circle for each prediction node, joining tangent lines of the error range circles of two adjacent different prediction nodes by utilizing a circular tangent method and adopting the current position point as a starting point, forming an error range circle, and effectively verifying the accuracy of the future prediction data through the error range circle. The accuracy of the future prediction data is effectively verified through the error range circle, so that the application reference added value of the prediction data can be improved, and a more-intuitive exhibition application effect can be realized. Meanwhile, the controllability of the prediction range of the future prediction data by tropical cyclone prediction personnel can be improved, the prediction of the dotted line is upgraded to the regional prediction, and the prediction amplitude and anticipation degree are more complete.

Description

technical field [0001] The invention relates to the fields of flood control informatization and meteorological applications, in particular to an application method for realizing the forecast error range by using a tangent method combined with a tropical cyclone forecast path. Background technique [0002] The following steps are usually used to display the existing tropical cyclone track and personal forecast track: [0003] 1. Receive information such as longitude, latitude, central air pressure, central wind speed, moving speed, and influencing wind circle issued by the meteorological department at each time scale; [0004] 2. Receive forecasted longitude, latitude, central air pressure, central wind speed and other information for the next 24 hours, 48 ​​hours, and 72 hours; [0005] 3. Combining the historical path data and forecast path data at each time moment into a point set arranged in chronological order; [0006] 4. Create path nodes through point sets to combin...

AI Technical Summary

Problems solved by technology

However, there are usually large errors in the forecast path, which may deviate from the original forecast line, which reduces the reference value of this data for flood control customers and meteorological customers in information application and decision-making

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