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Rainfall falling area determination method based on multi-source big data

A determination method, big data technology, applied in data processing applications, weather condition forecasting, forecasting, etc.

Pending Publication Date: 2021-12-24
海南省气象科学研究所
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention is designed to solve the problem of determining the precipitation falling area, a method for determining the precipitation falling area based on multi-source big data

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  • Rainfall falling area determination method based on multi-source big data

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0029] like figure 1 As shown, in the present invention, a method for determining precipitation fall areas based on multi-source big data, first, comprehensively utilizes multi-source Internet of Things big data to determine minute-by-minute precipitation fall areas; then, converts to precipitation fall areas on a time scale of ΔT minutes; The method comprises the steps of:

[0030] Step 1: Select the range D of the precipitation area to be determined, and establish a discrete grid within D;

[0031] Step 2: Obtain minute-by-minute multi-source IoT big data in area D;

[0032] Step 3: Use corresponding algorithms for each type of big data to calculate the probability of precipitation at the space-time location of each networked device; and store the processing results for later use;

[0033] Step 4: Read the precipitation occurrence probability corre...

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Abstract

The invention discloses a rainfall falling area determination method based on multi-source big data. The rainfall falling area determination method comprises the following steps: selecting a rainfall falling area range to be determined and establishing a discrete grid; acquiring minute-by-minute multi-source Internet of Things big data; for each type of big data, using a corresponding algorithm to judge the rainfall occurrence probability of the spatial-temporal position where each networking device is located; combining rainfall occurrence probabilities corresponding to the minute-by-minute multi-source Internet of Things big data in the to-be-determined rainfall falling area in a certain time period before and after the to-be-determined moment into a rainfall occurrence probability sample set; calculating rainfall occurrence probabilities of all grid points in the to-be-determined rainfall falling area range by adopting an interpolation method; and converting the minute-by-minute rainfall occurrence probability into rainfall occurrence probabilities of other time scales by adopting logic or operation. The beneficial effects of the invention are that the introduction of the multi-source Internet of Things big data is equivalent to the great increase of the density of the rainfall observation station network, so that the spatial and temporal distribution of the rainfall falling area can be described more accurately.

Description

technical field [0001] The invention relates to the field of objective analysis of precipitation in meteorology, in particular to a method for determining precipitation falling areas based on multi-source big data. Background technique [0002] Precipitation is the most basic weather and climate element, which has an important impact on human production and life. When precipitation occurs, it can affect almost all outdoor activities. For example, low visibility and slippery roads caused by precipitation can easily lead to traffic accidents. Therefore, the realization of precise monitoring of precipitation has always been the goal pursued by human beings. [0003] The monitoring of precipitation includes two aspects, one is the precipitation area, that is, where the precipitation occurs, and the other is the precipitation level, that is, the amount of precipitation at the location where the precipitation occurs. However, precipitation usually has the characteristics of dra...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/26G01W1/10
CPCG06Q10/04G06Q50/26G01W1/10
Inventor 张国峰佟金鹤蔡大鑫
Owner 海南省气象科学研究所
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