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Extended period prediction method considering large-scale circulation background field

A background field, large-scale technology, used in forecasting, weather forecasting, instruments, etc., can solve the problem of less investigation of large-scale low-frequency background field applications, and achieve the effect of improving forecasting skills

Active Publication Date: 2018-10-12
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

Most of the previous statistical forecasts focused on the influence of tropical convection (MJO), seldom considered the joint effects of mid-high latitudes and the tropics at the same time, and seldom examined the application of large-scale low-frequency background fields above 30 days in the extended period prediction

Method used

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  • Extended period prediction method considering large-scale circulation background field
  • Extended period prediction method considering large-scale circulation background field
  • Extended period prediction method considering large-scale circulation background field

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Embodiment Construction

[0037] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0038] This embodiment uses 10-30 days to forecast the Jiangnan April-June precipitation, illustrates the general train of thought and effect of the present invention.

[0039]First, based on the daily precipitation data from China National Meteorological Observatory from 1979 to 2013, the daily global reanalysis data from NCEP (National Centers for Environmental Prediction) / NCAR (National Center for Atmospheric Research) and the daily data provided by NOAA (National Oceanic and Atmospheric Administration) Wave radiation data, fitted forecast for 1979-2003 and independent forecast for 2004-2013. Subtract the component below 10d from the component below 30d to get the low frequency component of 10-30d. Use the above filtering method to filter the data field to separate the 10-30d component and the above 30d component. This filtering method...

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Abstract

The invention discloses an extended period prediction method considering a large-scale circulation background field. By considering of different large-scale circulation backgrounds, in combination with the high-latitude and tropic interaction and influence thereof on the weather in an area extended period in a use process, optimal factors in different backgrounds are selected; and, due to regression of multiple factors, a target is predicted. According to the extended period prediction method considering the large-scale circulation background field disclosed by the invention, for different large-scale background fields, prediction is carried out by selection of proper factors; therefore, the prediction skill is improved; and the method has wide application prospect in diagnostic analysis and prediction for multi-scale characteristic variables.

Description

technical field [0001] The invention belongs to the technical field of atmospheric science forecasting, and in particular relates to an extended-period forecasting method considering a large-scale circulation background field. Background technique [0002] In recent years, frequent meteorological disastrous weather and the secondary disasters caused by it have drawn extensive attention from the state, society and the public. Faced with this sudden and repeated abnormal weather, the meteorological department has matured the short-term and medium-term weather forecasting technology for below 10 days at this stage, and the short-term climate forecast above the monthly scale has been gradually improved since 1985, and a complete forecasting system has been established. Relatively speaking, there is still a lot of room for development in the 10-30d extended-range forecast, and both academic research and operational applications deserve further attention. In addition to the inter...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/26G01W1/10
CPCG06Q10/04G06Q50/26G01W1/10
Inventor 谭桂容曲金华王一舒
Owner NANJING UNIV OF INFORMATION SCI & TECH
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