Satellite data acquisition type sea surface typhoon prediction method
A satellite data and prediction method technology, applied in the direction of prediction, data processing application, complex mathematical operations, etc., can solve the problems of inaccurate analysis and dependence on satellite images, etc., and achieve the effect of accurate prediction results and convenient prediction steps
Inactive Publication Date: 2021-10-29
周明
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[0004] Aiming at the deficiencies of the prior art, the present invention provides a sea surface typhoon forecasting method based on satellite data collection, which solves the problem that the analysis is not accurate enough for meteorological collection and seawater temperature collection located in remote sea areas only by relying on satellite images
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[0095] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0096] see Figure 8-12 , the present invention provides a technical solution: a satellite data acquisition type sea surface typhoon prediction method, specifically comprising the following steps:
[0097] Step 1: Study the physical process of monthly, seasonal and interannual changes in the frequency and track of tropical cyclones in the Northwest Pacific: Correlation analysis between the frequency of tropical cyclones and global sea temperature, ENSO index, ...
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The invention discloses a satellite data acquisition type sea surface typhoon prediction method. The method comprises the following steps: 1, researching a physical process of monthly, seasonal and inter-annual change of tropical cyclone frequency and path of northwest Pacific Ocean; 2, establishing a physical statistical prediction model of the northwest Pacific Ocean second season scale tropical cyclone; 3, researching a power prediction model of the northwest Pacific Ocean second season scale tropical cyclone; 4, researching a power-statistics combined prediction model of the northwest Pacific Ocean second season scale tropical cyclones; and 5, establishing northwest Pacific Ocean second season scale tropical cyclone prediction system demonstration software. According to the satellite data acquisition type sea surface typhoon prediction method, the sea surface meteorological detection device is arranged on the sea surface, field meteorological acquisition and seawater temperature acquisition are performed on the sea surface, and analysis is performed in cooperation with satellite acquisition data, so that the problem that the prediction result is not accurate enough due to analysis only depending on satellite image data is effectively avoided.
Description
technical field [0001] The invention relates to the technical field of meteorological prediction, in particular to a satellite data collection type sea surface typhoon prediction method. Background technique [0002] The Northwest Pacific Ocean is the sea area that produces the most tropical cyclones every year, accounting for 30% of the global annual tropical cyclones. From June to October every year is the period of frequent tropical cyclone activities. During this period, about 25 typhoons are generated in the Northwest Pacific Ocean, and about 6.9 tropical cyclones enter my country's coastal waters and land in my country every year. Severe weather such as , torrential rain and storm surge can have a huge impact. Therefore, tropical cyclones are one of the most concerned weather systems in summer, and improving the forecast accuracy of tropical cyclones is of great significance for disaster prevention and mitigation. [0003] The main steps of typhoon prediction are data...
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IPC IPC(8): G06Q10/04G06K9/62G06F17/11G06F17/16G06F17/18
CPCG06Q10/04G06F17/11G06F17/16G06F17/18G06F18/2135Y02A90/10
Inventor 周明
Owner 周明