Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Gaussian weight-based LBGM method initial value disturbance generation method

A technique of weight and Gaussian function, applied in the field of ensemble forecasting, can solve the problem of ignoring the difference of lattice points, and achieve the effect of improving the effectiveness

Pending Publication Date: 2021-06-25
NAT UNIV OF DEFENSE TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, there are still shortcomings in this method, that is, the contribution weight of the grid points in the local range to the adjustment coefficient is equal, and the differences between the grid points in the local range are ignored

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Gaussian weight-based LBGM method initial value disturbance generation method
  • Gaussian weight-based LBGM method initial value disturbance generation method
  • Gaussian weight-based LBGM method initial value disturbance generation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] In this example, two examples are selected as follows:

[0056] Case 1 selects a squall line process that occurred in South my country at the end of March 2014. From the evening of March 29th to the afternoon of March 31st, 2014, South China suffered a severe convective weather process, and Guangxi, Guangdong, Yunnan and other provinces were affected to varying degrees. Among them, from 20:00 on the 30th (UTC, the same below) to 04:00 on the 31st, a long squall line passed through Guangdong Province from northwest to southeast. Some cities experienced disastrous weather such as hail and strong winds. The cumulative precipitation in the central region reached 160mm. image 3 (a) and (b) show the large-scale circulation situation at 12:00 on March 30, 2014. In the high altitude of 500hPa, affected by the strong high-pressure ridge in the high latitude area, a steady stream of cold air is input into South China, which provides the middle-level cold air conditions for the ...

Embodiment 2

[0067] The experimental object and method in this example are the same as in Example 1. In order to better understand the impact of Gaussian weight and equal weight on the scale information of the disturbance generated by LBGM, this example uses the DCT method to perform kinetic energy Spectral analysis Kinetic energy spectral analysis can effectively describe the scale information contained in the initial disturbance. For a more successful ensemble forecasting system, its initial disturbance should consider uncertain information of different scales.

[0068] Image 6 and Figure 7The kinetic energy spectrum distribution of the initial perturbation of member 5 at different altitudes in two cases is given respectively. It can be seen from the figure that no matter in case 1 or case 2, the peaks of the disturbance spectrum energy under the two weighting methods are all concentrated in the large-scale area with a wavelength of about 1000 km. It is worth noting that, compared w...

Embodiment 3

[0070] The relationship between the root mean square error of the ensemble average forecast and the dispersion is often an important evaluation index to measure the forecasting ability of an ensemble forecast system. When the RMSE is consistent with the dispersion, it shows that the ensemble disturbance represents the uncertainty of the analysis field to a certain extent, and the ensemble forecast results cover the real state of the atmosphere in the future to the greatest extent possible.

[0071] The experimental object and method of this example are the same as those in Example 1, but considering that the application focus of the present invention is on the initial disturbance, the hypothesis of "perfect model" is adopted when testing the non-precipitation variable forecast, that is, the same model is used for the collective test Combined with physical parameterization, the model error is ignored, and the control forecast results replace the real atmospheric state. Therefor...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of ensemble forecasting. The invention provides an LBGM-based disturbance generation method for solving the problem that in an existing LBGM method, contribution weights of lattice points in a local range to an adjustment coefficient are equal, and differences among the lattice points in the local range are neglected, a local radius is introduced, each lattice point in a limited area is taken as a center, a corresponding local range is delimited, gaussian weights of surrounding grid points to a central grid point in a local range are calculated through a Gaussian function, so that a forecast root-mean-square error of the central grid point is obtained, and a disturbance formula is determined; Gaussian weights of surrounding grid points to a central grid point in a local range are calculated through a Gaussian function. On the basis of an original LBGM method, Gaussian weight is provided to express correlation among lattice points in a local range more finely, so that the effectiveness of convective distinguishable scale ensemble forecasting is improved.

Description

technical field [0001] The invention belongs to the technical field of ensemble forecasting, and in particular relates to a disturbance generating method. Background technique [0002] The chaotic characteristics of the atmosphere, as well as the errors in the initial field and the numerical model, make the numerical prediction result inevitably have a gap with the actual state in the future, thus giving rise to the ensemble prediction technology. At present, the technologies of global medium-range ensemble forecast (forecast time of 3-15 days and resolution of 30-70km) and regional mesoscale ensemble forecast (forecast time of 1-3 days and resolution of 7-30km) are relatively mature. With the increasing demand for severe weather forecast and the improvement of scientific computing level, ensemble forecasting technology is gradually developing in the direction of convective scale (prediction time is less than 24h, resolution is 1-4km). [0003] The design of the initial per...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F16/29G06F16/245
CPCG06F16/29G06F16/245
Inventor 陈超辉李坤何宏让陈雄陈祥国智协飞姜勇强张玲马申佳张入财
Owner NAT UNIV OF DEFENSE TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com