CN-122018042-A - Reconstruction and enhancement method and device for low-layer wind field of complex terrain

CN122018042ACN 122018042 ACN122018042 ACN 122018042ACN-122018042-A

Abstract

The invention relates to the technical field of meteorological detection and numerical weather analysis, and discloses a method and a device for reconstructing and enhancing a low-level wind field of complex terrain, wherein the method comprises the steps of obtaining terrain elevation data of a target area and multi-layer isobaric surface wind field data; the method comprises the steps of obtaining a ground air pressure field consistent with terrain fluctuation by calculation based on terrain elevation data, converting multi-layer isobaric surface air field data into air field data under a sigma coordinate system based on the ground air pressure field and preset atmospheric layer top air pressure, sequentially carrying out vertical layering and merging averaging on the air field data under the sigma coordinate system to obtain all sigma-layer average air field data, calculating dynamics diagnosis quantity of a low-layer air field based on all sigma-layer average air field data, and taking all sigma-layer average air field data and the dynamics diagnosis quantity as low-layer air field dynamic characteristic enhancement products.

Inventors

JIAO ZHIMIN
GUO WEI
WU YIBO
WEN QINGFENG
LI XUEGANG
LI ZHI
LI LONGJI
WU LEI
LI BAI
ZHOU CHENXI
WANG SONGBO
TAO FA
LI RUIYI
ZHANG GUOQIANG
WANG YANGMING

Assignees

中国气象局气象探测中心
国网天津市电力公司
国网天津市电力公司电力科学研究院
国网电力工程研究院有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (20)

1. A method for reconstructing and enhancing a low-level wind field of a complex terrain, the method comprising: Acquiring terrain elevation data and multi-layer isobaric wind field data of a target area; Based on the terrain elevation data, calculating to obtain a ground air pressure field consistent with the terrain fluctuation; Converting the multi-layer isobaric surface wind field data into wind field data under a sigma coordinate system based on the ground air pressure field and the preset atmospheric layer top air pressure; sequentially carrying out vertical layering and merging averaging on the wind field data under the sigma coordinate system, and calculating to obtain the average wind field data of each sigma layer after merging; And calculating the dynamics diagnosis quantity of the low-layer wind field based on the integrated sigma-layer average wind field data, and taking the sigma-layer average wind field data and the dynamics diagnosis quantity as a low-layer wind field dynamic characteristic enhancement product.
2. The method of claim 1, wherein the terrain elevation data comprises a digital elevation model or ground elevation data, and wherein calculating a ground barometric pressure field consistent with terrain relief based on the terrain elevation data comprises: Based on the digital elevation model or the ground elevation of each elevation point in the ground elevation data, calculating the ground air pressure of each elevation point by adopting a statics formula; And integrating the ground air pressure values of all elevation points to generate a ground air pressure field which covers the target area and is consistent with the relief of the terrain.
3. The method of claim 2, wherein the ground air pressure value of the ground air pressure field is expressed by the following formula: ; Wherein, the Is the ground air pressure value; H is the input ground altitude; gravitational acceleration; is a dry air gas constant; Is the reference air temperature.
4. The method of claim 1, wherein the converting the multi-layer iso-surface wind field data into wind field data in a sigma coordinate system based on the ground air pressure field and a preset atmospheric layer top air pressure comprises: Determining the vertical coordinate of each data point in a sigma coordinate system based on the air pressure value of each data point in the multi-layer isobaric surface wind field data, the air pressure value of the geographic position corresponding to the data point in the ground air pressure field and the preset atmosphere top air pressure; wind field data in a sigma coordinate system is generated based on the vertical coordinates of all the data points and the corresponding wind field data.
5. The method according to claim 1, wherein the vertically layering and merging and averaging are sequentially performed on the wind field data in the σ coordinate system, and the calculating of the merged average wind field data of each σ layer includes: determining a vertical layering thickness interval in a sigma coordinate system; and according to the vertical layering thickness interval, sequentially carrying out vertical layering and merging and averaging on the wind field data under the sigma coordinate system to obtain the average wind field data of each sigma layer after merging.
6. The method according to claim 5, wherein the vertically layering and merging the wind field data in the σ coordinate system according to the vertical layering thickness interval to obtain the merged average wind field data of each σ layer includes: dividing the wind field data under the sigma coordinate system into different sigma vertical layer intervals according to the vertical layering thickness interval; and respectively calculating the average value of the east-west wind speed component and the north-south wind speed component for all the wind field data points divided into the same sigma vertical layer interval to serve as corresponding sigma layer average wind field data.
7. The method according to claim 1, wherein calculating the dynamic diagnostic quantity of the lower-layer wind farm based on the integrated σ -layer average wind farm data, and using the σ -layer average wind farm data and the dynamic diagnostic quantity as the lower-layer wind farm dynamic characteristic enhancement product, comprises: calculating a first dynamic diagnosis quantity representing horizontal divergence or combination characteristics based on the average wind field data of each sigma layer after merging; calculating a second dynamic diagnosis quantity representing the air rotation intensity based on the integrated sigma-layer average wind field data; And integrating the average wind field data of each sigma layer, the first dynamic diagnosis quantity and the second dynamic diagnosis quantity to form a low-layer wind field dynamic characteristic enhancement product.
8. The method of claim 7, wherein calculating a first dynamic diagnostic quantity characterizing a horizontal divergence or a divergence characteristic based on the merged σ -layer mean wind field data comprises: Based on the integrated sigma-layer average wind field data, calculating the spatial change rate of east-west wind speed components in the east-west horizontal direction and the spatial change rate of north-south wind speed components in the north-south horizontal direction respectively; And adding the spatial change rate of the east-west wind speed component in the east-west horizontal direction and the spatial change rate of the north-south wind speed component in the north-south horizontal direction to obtain the horizontal divergence of the corresponding sigma layer, and taking the horizontal divergence as a first dynamics diagnosis quantity.
9. The method of claim 7, wherein calculating a second dynamic diagnostic quantity characterizing the air rotation intensity based on the integrated σ -layer mean wind field data comprises: Based on the average wind field data of each sigma layer after merging, calculating the spatial change rate of the east-west wind speed component in the north-south horizontal direction and the spatial change rate of the north-south wind speed component in the east-west horizontal direction respectively; Subtracting the spatial rate of change of the northeast wind speed component in the north-south horizontal direction from the spatial rate of change of the north-south wind speed component in the east-west horizontal direction, and obtaining the vertical vorticity of the corresponding sigma layer, and taking the vertical vorticity as a second mechanical diagnosis quantity.
10. A device for reconstructing and enhancing a low-rise wind field of a complex terrain, the device comprising: The data acquisition module is used for acquiring the terrain elevation data of the target area and the multi-layer isobaric wind field data; The ground air pressure field calculation module is used for calculating a ground air pressure field consistent with the relief of the terrain based on the terrain elevation data; The sigma coordinate conversion module is used for converting the multi-layer isobaric surface wind field data into wind field data under a sigma coordinate system based on the ground air pressure field and the preset atmospheric layer top air pressure; the layering merging module is used for sequentially vertically layering and merging and averaging the wind field data under the sigma coordinate system, and calculating to obtain the average wind field data of each sigma layer after merging; The dynamic characteristic enhancement module is used for calculating dynamic diagnosis quantity of the low-layer wind field based on the integrated sigma-layer average wind field data, and taking the sigma-layer average wind field data and the dynamic diagnosis quantity as a low-layer wind field dynamic characteristic enhancement product.
11. The apparatus of claim 10, wherein the terrain elevation data comprises a digital elevation model or ground elevation data, the ground barometric field calculation module comprising: the elevation point ground pressure calculation unit is used for calculating the ground pressure of each elevation point by adopting a statics formula based on the ground altitude of each elevation point in the digital elevation model or the ground altitude data; The ground air pressure field generating unit is used for integrating the ground air pressure values of all elevation points and generating a ground air pressure field which covers the target area and is consistent with the relief of the terrain.
12. The apparatus of claim 10, wherein the ground air pressure value of the ground air pressure field is expressed by the following formula: ; Wherein, the Is the ground air pressure value; H is the input ground altitude; gravitational acceleration; is a dry air gas constant; Is the reference air temperature.
13. The apparatus of claim 10, wherein the sigma coordinate conversion module comprises: The vertical coordinate determining unit is used for determining the vertical coordinate of each data point in the multi-layer isobaric surface wind field data based on the air pressure value of each data point, the air pressure value of the geographic position corresponding to the data point in the ground air pressure field and the preset atmospheric top air pressure; and the wind field data generation unit is used for generating wind field data under a sigma coordinate system based on the vertical coordinates of all the data points and the corresponding wind field data.
14. The apparatus of claim 10, wherein the hierarchical merging module comprises: a thickness interval determining unit for determining a vertical layered thickness interval in a sigma coordinate system; And the layering merging unit is used for sequentially carrying out vertical layering and merging and averaging on the wind field data under the sigma coordinate system according to the vertical layering thickness interval to obtain the average wind field data of each sigma layer after merging.
15. The apparatus of claim 14, wherein the hierarchical merging unit comprises: A sigma vertical layer dividing subunit, configured to divide the wind field data in the sigma coordinate system into different sigma vertical layer intervals according to the vertical layering thickness interval; and the sigma-layer average wind field data calculation subunit is used for respectively calculating the average value of the east-west wind speed component and the north-south wind speed component as corresponding sigma-layer average wind field data for all the wind field data points divided into the same sigma-vertical layer interval.
16. The apparatus of claim 10, wherein the dynamic feature enhancement module comprises: a first dynamic diagnosis amount calculation unit for calculating a first dynamic diagnosis amount representing a horizontal divergence or a divergence characteristic based on the integrated sigma-layer average wind field data; A second dynamic diagnosis amount calculation unit for calculating a second dynamic diagnosis amount representing the air rotation intensity based on the integrated σ -layer average wind field data; And the dynamic characteristic enhancement unit is used for integrating the average wind field data of each sigma layer, the first dynamic diagnosis quantity and the second dynamic diagnosis quantity to form a low-layer wind field dynamic characteristic enhancement product.
17. The apparatus of claim 16, wherein the first kinetic diagnostic amount calculation unit comprises: a first spatial change rate calculating subunit, configured to calculate, based on the integrated σ -layer average wind field data, a spatial change rate of the east-west wind speed component in the east-west horizontal direction and a spatial change rate of the north-south wind speed component in the north-south horizontal direction, respectively; And the horizontal divergence calculating subunit is used for adding the spatial change rate of the east-west wind speed component in the east-west horizontal direction and the spatial change rate of the north-south wind speed component in the north-south horizontal direction to obtain the horizontal divergence of the corresponding sigma layer, and taking the horizontal divergence as a first dynamics diagnosis quantity.
18. The apparatus according to claim 16, wherein the second dynamic diagnostic amount calculating unit includes: A second spatial variation rate calculating subunit, configured to calculate, based on the integrated σ -layer average wind field data, a spatial variation rate of the east-west wind speed component in the north-south horizontal direction and a spatial variation rate of the north-south wind speed component in the east-west horizontal direction, respectively; And the vertical vorticity calculation subunit is used for subtracting the spatial variation rate of the northeast wind speed component in the north-south horizontal direction from the spatial variation rate of the north-south wind speed component in the east-west horizontal direction to obtain the vertical vorticity of the corresponding sigma layer, and taking the vertical vorticity as a second mechanical diagnosis quantity.
19. An electronic device, comprising: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the method of reconstructing and enhancing a complex terrain low-level wind farm as defined in any of claims 1 to 9.
20. A computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of reconstruction and enhancement of a complex terrain low-level wind park according to any of claims 1 to 9.

Description

Reconstruction and enhancement method and device for low-layer wind field of complex terrain Technical Field The invention relates to the technical field of meteorological detection and numerical weather analysis, in particular to a method and a device for reconstructing and enhancing a low-level wind field of a complex terrain. Background In areas of complex terrain, conventional low-level wind field analysis products based on isobaric surfaces have significant limitations. Due to the direct cutting-off or lifting action of the terrain on the isobaric surface, systematic deletion or space discontinuity of near-stratum wind field data is caused, and key power structures under the influence of the terrain, such as near-ground radial lines, bypass flow, cyclone vortex and other small-medium-scale system features, are difficult to accurately capture and express. Although the sigma coordinate system (the terrain following vertical coordinate system, sigma-coordinate system) is applied as a terrain following coordinate in the numerical mode, the output result is usually converted back to an isobaric surface form, and a low-level wind field visualization and diagnosis product system directly facing the business analysis is not formed yet, so that the fine analysis and forecast business of the terrain-related weather process cannot be directly served. Disclosure of Invention The invention provides a reconstruction and enhancement method and device for a low-level wind field of a complex terrain, which are used for solving the problems that the traditional isobaric wind field is poor in continuity and unclear in power characteristics in the complex terrain area, and a low-level key power structure cannot be accurately identified. In a first aspect, the present invention provides a method for reconstructing and enhancing a low-level wind farm of a complex terrain, the method comprising: Acquiring terrain elevation data and multi-layer isobaric wind field data of a target area; Based on the terrain elevation data, calculating to obtain a ground air pressure field consistent with the terrain fluctuation; Converting the multi-layer isobaric wind field data into wind field data under a sigma coordinate system based on the ground air pressure field and the preset atmospheric layer top air pressure; Sequentially carrying out vertical layering and merging and averaging on the wind field data under the sigma coordinate system, and calculating to obtain the average wind field data of each sigma layer after merging; And calculating the dynamics diagnosis quantity of the low-layer wind field based on the integrated sigma-layer average wind field data, and taking the sigma-layer average wind field data and the dynamics diagnosis quantity as a low-layer wind field dynamic characteristic enhancement product. According to the reconstruction and enhancement method for the low-level wind field of the complex terrain, provided by the invention, continuous and stable reconstruction of the low-level wind field under the complex terrain is realized by introducing the sigma coordinate system and the terrain elevation data, the problems of data loss and structure breakage caused by terrain shielding of a traditional isobaric surface product are effectively solved, vertical layering merging and dynamics diagnosis quantity direct calculation is further carried out under the sigma coordinate system, the identification capacity of key power characteristics such as near-stratum combination, shearing and vortex is remarkably enhanced, finally, a low-level wind field power characteristic enhancement product capable of being directly used for business analysis is formed, the analysis and prediction accuracy of a small-scale weather system in a complex terrain area is improved, the purpose of accurately identifying a low-level key power structure is realized, and the problems that the continuity of the traditional isobaric surface wind field in the complex terrain area is poor, the power characteristics are not clear, and the low-level key power structure cannot be accurately identified are solved. In an alternative embodiment, the terrain elevation data comprises a digital elevation model or ground elevation data, and the computing of the ground air pressure field consistent with terrain relief based on the terrain elevation data comprises: Based on the digital elevation model or the ground elevation of each elevation point in the ground elevation data, calculating the ground air pressure value of each elevation point by adopting a statics formula; And integrating the ground air pressure values of all elevation points to generate a ground air pressure field which covers the target area and is consistent with the relief of the terrain. According to the reconstruction and enhancement method for the low-level wind field of the complex terrain, provided by the invention, the altitude of each elevation point in the terrain elevation data is directly c