An intelligent forecasting tool crowd-creation platform system and sharing method

Abstract

The invention belongs to the technical field of meteorological forecast data processing, and discloses an intelligent forecast tool crowd-creation platform and a sharing method, which transforms the existing refined forecast production platform, abstracts the basic forecast data and the secondary development interface, and makes it support two development, to achieve the goal of everyone's participation and forecasting crowd-creation; to develop a crowd-creation platform for intelligent forecasting tools, to realize online management of intelligent forecasting tools, to provide monitoring, management and evaluation of intelligent correction tools, statistics and management of developers, development resources and Help and other functions, and calculate the comprehensive index from the dimensions of usage index, technical difficulty, download times, likes, comments, etc., providing a reliable reference for forecasters to apply intelligent tools, and providing technical communication support for developers and users . The invention provides an intelligent correction tool of a visual parameter panel, which facilitates rapid adjustment and application of correction parameters for different weather types, and realizes free combination and serialized execution of forecast tools in a plug-in manner.

Description

technical field [0001] The invention belongs to the technical field of weather forecast data processing, and in particular relates to an intelligent forecast tool crowd-creation platform system and a sharing method. Background technique [0002] At present, the development of weather forecasting has been based on high-performance computing model forecasting. Forecasters make manual corrections based on years of accumulated forecasting experience and ideas, and finally release high-resolution refined grid forecasts to users. In order to realize the interactive correction and production of grid weather forecasts, many refined grid forecast production platforms with different characteristics have been developed in the industry. [0003] However, there is a common problem in these platforms - "it cannot meet the needs of forecasters to participate in technology research and development and share results". The specific performance is as follows: 1) The existing grid forecast pro...

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Problems solved by technology

[0003] However, there is a common problem in these platforms - "it cannot meet the needs of forecasters to participate in technology research and development and share results"

The specific performance is as follows: 1) The existing grid forecast production platform in the industry provides common forecast editing functions, but usually does not support the secondary development of forecasters, because for personalized editing and correction needs, usually only rely on the original software Development company for redevelopment

2) Forecasters make subjective corrections based on accumulated forecasting experience, but due to differences in experience accumulation among forecasters, there are certain differences in the correction results; Therefore, the forecast experience should be condensed into an intelligent forecast correction tool, installed and integrated into the forecast production platform in the form of a custom plug-in, so as to realize the co-construction and sharing of forecast experience and shared

[0006] (1) The existing grid forecast production platform in the industry provides common forecast editing functions, but usually does not support the secondary development of forecasters, because the original software development company can only rely on the original software development company for personalized editing and correction needs redevelopment

[0007] (2) The forecaster makes subjective corrections based on the accumulated forecasting experience, but due to the differences in experience accumulation among forecasters, there are some differences in the correction results; The same forecasting idea brings inconsistency in the revised results

[0008] (3) Existing technologies cannot share forecast data conveniently and quickly

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