20 results about "Wind profiler" patented technology

The invention relates to the technical field of new energy power generation prediction, in particular to a new energy power prediction method fusing typhoon meteorological information and a micrometeorological prediction result, which comprises the following steps: collecting multi-source observations such as a satellite scatterometer, a radar wind profile and laser wind measurement, and unifying coordinates; constructing a mesoscale wind field by adopting four-dimensional variational assimilation, inferring a micrometeorological field by utilizing a spectrum embedding diffusion network, and generating a multi-scale meteorological field by frequency domain phase consistency fusion; probabilistic wind speed is sampled in the countercurrent model meeting the condition of mass and momentum conservation, an energy conservation graph neural network is input, the wake effect is coupled, and a unit power quantile value is obtained; the power probability is sent to a risk weighting model, the weight is adjusted in real time according to the peak load, the reserve capacity and the climbing rate risk, a dispatching power curve and uncertainty are output, and grid-connected power errors are used for periodically updating the weight and the parameters of the last layer of the reversible model. According to the invention, the safety acceptance margin of the power grid to new energy is obviously improved.

The invention discloses a wind profile radar radial speed quality control and horizontal wind field inversion method. According to the method, through the steps of multi-mode detection splicing, signal-to-noise ratio threshold value quality control, beam consistency inspection, horizontal wind component inversion, space and time continuity inspection and the like, the quality control process of the wind field data is optimized, the precision of the horizontal wind field data is remarkably improved, and particularly, the root-mean-square error and deviation in high-level data are remarkably reduced. The core innovation comprises a mode splicing strategy based on sounding data comparison, dynamic signal-to-noise ratio threshold calculation, threshold setting of beam consistency check and a wind component compensation algorithm when a vertical beam is missing. Through experimental verification, compared with a traditional wind profile radar data processing method, the wind profile radar data processing method has remarkable advantages in data accuracy and stability.

The invention relates to a wind resource prediction method based on quality control assimilation of multi-source observation data, and the method comprises the steps: integrating the multi-source observation data, including a multi-band radar reflectivity factor, a radial speed, a ground observation station, and wind profile radar data; quality control processing such as mottle removal, data filling, speed folding removal and discontinuous data removal is carried out, so that the accuracy and continuity of the data are improved; then, through lattice point interpolation and three-dimensional variation assimilation technologies, the processed observation data are fused into an initial background field, and an analysis field closer to the actual atmospheric state is generated, so that the reliability of severe convective weather risk assessment is remarkably improved, and the accuracy of wind energy prediction is also enhanced; and more comprehensive, detailed and stable information support is provided for weather forecast and energy management.

The invention relates to a thunderstorm and gale identification method based on multi-dimensional characteristic parameter fusion, and belongs to the field of radio, and the method comprises the steps: employing a neighborhood value method to remove the electromagnetic interference of dual-line polarization Doppler weather radar data, carrying out the rollback fuzzy processing, and then carrying out the meshing; dual-polarization radar data, wind profile radar data, sounding data and ground automatic station data are respectively obtained, and respective characteristic parameters are extracted from the data; carrying out normalization processing on the characteristic parameters, and obtaining corresponding parameters; constructing a multi-parameter integrated early warning model based on the plurality of fusion parameters, and training and verifying the model; and inputting parameters into the trained model for operation, and outputting the thunderstorm gale probability P. According to the thunderstorm gale identification method, through combination of multi-source data fusion and multiple physical mechanism fusion and integration of innovation of a machine learning model, the technology of thunderstorm gale identification from single index dependence to multi-dimensional collaboration and from static threshold value to dynamic self-adaption is realized.

The invention provides a wind profile radar spectrum peak estimation method based on a three-parameter dynamic cost function, and the method comprises the steps: 1, carrying out the preprocessing of distance and Doppler spectrum data, and carrying out the three-point moving average smoothing; step 2, noise level estimation based on statistics is carried out; step 3, carrying out candidate spectrum peak selection based on space Doppler window smoothing; 4, performing dynamic weight calculation based on covariance matrix eigenvalue decomposition; step 5, constructing a three-parameter cost function of a distance spectrum peak value RSP power item, a continuity item and a spectrum width consistency item, and performing optimization; and step 6, outputting the optimal spectrum peak trajectory to form a complete wind speed profile trajectory. According to the method, the spectrum peak identification precision and stability in a complex environment can be improved, and the u and v wind correlation coefficients of the estimation method are verified to reach 0.880 and 0.879 through a data set disclosed by an atmospheric radiation measurement website.

This invention provides a method for inverting horizontal divergence profiles based on a network of wind profiler radars. The method includes: employing simulation analysis to evaluate the sensitivity of the horizontal divergence inversion results of each wind profiler radar to its horizontal wind, as well as the rules for determining the distance to the wind profiler radars and the rules for determining the maximum interior angle and area of ​​the triangle; based on the determined results, selecting three target wind profiler radars, and obtaining the horizontal divergence at a certain vertical height layer within the triangle formed by the three target wind profiler radars using near-real-time wind vertical profile product data files from the mesoscale network of wind profiler radars. This invention provides a method for inverting horizontal divergence profiles based on a network of wind profiler radars, which is an optimal method for inverting horizontal divergence vertical profiles suitable for monitoring and warning of signals in the early stages of convection. It can reduce horizontal divergence inversion errors, improve the precision and accuracy of strong convection monitoring and short-term warnings, and thus provide support for optimizing the layout of the mesoscale network of wind profiler radars.

The present invention belongs to the field of meteorological technology, and particularly relates to a cobweb warning method based on the PPI scanning mode of a lidar wind profiler, including: Step 1, collecting the wind speed and wind direction values of warning points by using the PPI scanning mode of the lidar wind profiler; Step 2, obtaining the wind speed and wind direction values around the warning points and the wind speed and wind direction values of each component based on the wind speed and wind direction values of the warning points; Step 3, calculating the difference result by using the difference method based on the warning points and the wind speed and wind direction values of each surrounding component, and comparing it with a preset threshold to determine the warning color around the warning points. The technical solution of the present invention is different from the vertical profile of the RHI mode and the top of the radar in the wind profile mode. The cone surface with the radar as the vertex is obtained by scanning in the PPI mode, which can measure a wider wind field and can detect the wind shear in the entire area during the takeoff and landing of the aircraft.

This invention relates to an intelligent processing method for wind profiler data, which solves the problems of existing wind profiler data processing methods, such as reliance on manual intervention for identifying missing height layers and the lack of structural consistency guarantees in interpolation methods. This method achieves automatic structural analysis and intelligent completion of missing height layers in wind profiler data through multi-step collaborative processes. The steps sequentially execute data access and format standardization, height layer structure parsing and index construction, intelligent identification of missing height layers, interpolation condition judgment, adaptive interpolation calculation, data structure reconstruction, and database storage. It automatically identifies missing height layers and adaptively selects interpolation algorithms to generate interpolation results based on data change trends, ensuring the integrity and continuity of the data structure and providing a reliable data foundation for wind field analysis models. This invention can be widely applied to wind profiler radar data platforms, meteorological data operational processing systems, and other scenarios.

This invention discloses a method for inverting atmospheric precipitation particle spectra, belonging to the field of inversion technology. It addresses the limitations of existing technologies in accurately obtaining inversion parameters for ground and atmospheric microphysical parameters, thus hindering understanding of the formation, development, and variation mechanisms of atmospheric cloud precipitation and consequently preventing accurate prediction and interpretation of atmospheric processes and meteorological disasters. The method includes: acquiring the observed power spectrum using C-band frequency-modulated continuous wave radar and employing denoising methods to remove noise levels; constructing the atmospheric power spectrum based on horizontal wind data acquired from wind profiler radar; constructing the raindrop spectrum using ground raindrop data acquired from a ground raindrop spectrometer and a standardized gamma distribution; and performing ground and atmospheric microphysical parameter inversion based on the above results. This invention is used for inverting and obtaining ground and atmospheric microphysical parameters.

This invention discloses a method and apparatus for horizontal wind field inversion based on the radial velocity of a wind profiler radar, relating to the field of wind profiler radar technology. The method includes: reading the radial velocity data of the wind profiler radar beams in each direction; rearranging and splicing the radial velocity data of each beam in a preset order to form a beam radial velocity profile; sequentially performing data identification, one-dimensional median filtering, and one-dimensional moving average filtering on the beam radial velocity profile to ensure data consistency; performing spatiotemporal continuity processing, followed by time-consistent averaging; and obtaining the inverted horizontal wind field based on the spatial geometric relationship between the wind field and the radial velocity data of each beam, according to the processed radial velocity data of each beam. This invention solves the problem of low accuracy in horizontal wind field inversion in existing technologies.

The present invention provides a portable ground-based lidar wind profiler. It includes a frame. On the front and rear sides of the frame, there are respectively a first installation chamber and a second installation chamber for installing electronic components. At the upper end of the frame, there is an upper cover with a radar scanning port. Maintenance covers are provided on both the first installation chamber and the second installation chamber. In the middle of the frame, there is a heat dissipation air duct. Heat dissipation slots are provided on both sides of the heat dissipation air duct. At the lower end of the heat dissipation air duct, there is a heat dissipation fan. A radar lens module is arranged in the heat dissipation air duct. Ventilation gaps are provided on the front and rear sides at the upper end of the frame. The ventilation gaps cooperate with the upper cover to form a ventilation slot. When conducting detection work, the heat dissipation fan ventilates the heat dissipation air duct, and blows the hot air out from the ventilation slot. The present invention relates to the field of lidar wind profilers.

This invention provides a deep learning-based method and system for boundary layer height inversion from wind profiler radar. The method includes: first, proposing a sensitivity analysis theory for boundary layer height inversion to analyze the impact of the number of local peaks on boundary layer inversion, laying a theoretical foundation for algorithm improvement; then, selecting numerous atmospheric parameter profiles from wind profiler radar products based on boundary layer physical characteristics and their importance, filtering out the input parameter profiles for the inversion model; inputting the filtered profiles and the actual boundary layer height obtained from sounding inversion into a convolutional neural network model for training; and finally, the fully trained model can directly output high-precision boundary layer height inversion results. This invention combines the advantages of deep learning in discovering complex structures in high-dimensional data with the inclusion of multiple atmospheric parameter profiles, significantly improving the accuracy and stability of boundary layer height inversion, providing strong support for boundary layer research and global climate change studies.

The present invention discloses a method for predicting the falling trajectory of the main debris of an artificial rainfall enhancement rocket, comprising the following steps: obtaining the launch elevation angle, azimuth angle, and longitude and latitude coordinates of the artificial rainfall enhancement rocket launch point; calculating the longitude and latitude coordinates of the starting point of the main debris of the rocket after parachute deployment; fusing sounding, wind profiler radar, and the falling velocity data of the main debris of the rocket to construct a gridded meteorological falling velocity data space; establishing a unified storage and indexing strategy for managing the gridded data with the same longitude and latitude coordinates in the gridded meteorological falling velocity data space; and iteratively calculating the trajectory points of the main debris of the rocket on each data layer of the gridded meteorological falling velocity data space based on a longitude and latitude variation model between two points above the Earth, the falling starting point data of the main debris of the rocket after parachute deployment, and the constructed gridded meteorological falling velocity data space, layer by layer, to obtain the falling trajectory of the main debris of the rocket. The present invention can effectively predict the falling trajectory of the main debris of the rocket, thereby improving the safety of ground-based rocket rainfall enhancement operations.

The invention discloses a detection method and system based on resource reuse in a wind profile radar, and relates to the field of meteorological radar detection, and the detection method comprises the steps: dividing all detection beams of the wind profile radar into two polarization directions; the radar beam direction is controlled to be periodically switched in a polarization multiplexing mode in different detection modes of different detection periods, and atmosphere three-dimensional wind field information is generated according to a complete detection data set inversion wind profile obtained in each detection period; and from the first detection mode of the second detection period, inverting a wind profile according to a complete detection data set formed by the detection data of the wave beams of the current detection mode and a plurality of continuous detection modes before the current detection mode in a time data sequence multiplexing manner to generate atmosphere three-dimensional wind field information. According to the method, the purpose of prolonging the service life of the polarization switch can be achieved by reducing the switching frequency of the polarization switch of the wind profile radar, meanwhile, the purpose of encrypted observation is achieved by improving the time resolution of the wind profile radar through time data sequence multiplexing, and therefore the detection performance of the wind profile radar is comprehensively improved.

This application provides a method and apparatus for inverting typhoon boundary layer wind profiles based on multi-source data fusion. The method according to this application includes: based on the measurement height H of a ground-based automatic measuring station... start The starting height H of the wind-measuring lidar low Low-altitude wind profiles are obtained by combining wind-measuring lidar with ground-based automatic measurement stations; the maximum detectable height H of the wind-measuring lidar is based on... high With preset height H end The comparison results were obtained by measuring H using a combination of wind profiler radar and wind lidar. low To H end The wind speed within the specified range is used to obtain the upper-level wind profile; the lower-level and upper-level wind profiles are then combined to obtain a wind profile covering the entire boundary layer. The technical solution provided in this application can achieve wind profile inversion and wind field distribution characteristic analysis at the entire boundary layer height during different evolution stages of a typhoon.

This application relates to the field of meteorological monitoring equipment technology, and in particular to a low-altitude wind shear detection device based on wind profiler radar, which includes a base, a rotating detection mechanism, a height adjustment mechanism, and a data recording mechanism. The base has adjustable horizontal support legs to ensure stable installation. The wind cup assembly in the rotating detection mechanism senses wind force and converts it into rotation. The height adjustment mechanism uses components such as an inflatable airbag and a return spring to flexibly adjust the height of the detection mechanism. A transmission conversion component converts the rotation of the wind cup assembly into the up-and-down movement of a recording pen, which, in conjunction with recording paper wound around the outside of the active and driven rollers, completes the recording of wind shear data. This device has a reasonable structural design, effectively solving the problems of complex structure and poor environmental adaptability of existing equipment. It can achieve accurate detection and convenient data recording of low-altitude wind shear, providing reliable data support for fields such as aviation.

1. Name of the Design Product: Laser Wind Profiler (Cabinet Type). 2. Use of the Design Product: A wind profiler for providing wind field information. 3. Design Feature of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Indicates the Design Feature: Perspective view.

The present invention provides a satellite-ground synchronized inversion method for mesoscale atmospheric dynamic parameters, comprising the following steps: distributing multiple wind profiler radar stations in a study area; using an Aeolus satellite equipped with a Doppler wind lidar and flying along a set orbit to obtain satellite-ground synchronized wind profiler product data; and performing satellite-ground synchronized inversion of atmospheric dynamic parameters. The present invention utilizes new high-temporal and spatial resolution observational data and datasets, such as wind profiler radar, Aeolus satellites, Sunflower-8 satellites, and hourly reanalysis data from European centers, to construct a satellite-ground synchronized triangular observation network. The network inverts mesoscale atmospheric dynamic parameters, such as horizontal divergence and relative vorticity, to compensate for the shortcomings of wind profiler radar observations in remote areas and the lack of high-resolution atmospheric dynamic parameter observations before severe convection is triggered. This provides important observational support for monitoring, forecasting, and early warning of small and medium-scale convective weather.

This application provides a networking method for wind profiler radar and wind-measuring lidar, as well as a dynamic parameter fusion method, belonging to the field of digital signal processing. The networking method of this application analyzes and evaluates the influence characteristics of the geometric parameters of a triangle on the retrieved key dynamic parameters, the influence characteristics of wind field element observation errors on the retrieved key dynamic parameters, and the influence characteristics of different weather and geographical conditions on the retrieved key dynamic parameters. It employs an area-weighted averaging method to form an optimal triangle networking scheme and calculates the key dynamic parameters, fully utilizing the advantages of both radars to improve the accuracy of retrieved atmospheric dynamic parameters. The dynamic parameter fusion method, based on the retrieved key dynamic parameters, further fuses reanalysis data or numerical model initial fields to obtain multi-source fused data, thereby further improving the accuracy of the data.

The present invention provides a method, system, and storage medium for constructing a three-dimensional wind field based on wind profiler radars, relating to the technical field of three-dimensional wind field construction. The method comprises the following steps: S1. acquiring horizontal and vertical wind data from each wind profiler radar; S2. correcting the wind speed vectors at each height along the vertical wind profile based on known wind profiler station location information and the distribution of the horizontal and vertical wind data along the vertical height; S2. after correction, adaptively resampling the wind speed vectors along the vertical wind profiles to obtain wind speed data at the same height level; and S3. based on the wind speed data at the same height level, constructing a three-dimensional wind field using a distance-weighted approach by networking wind profiler radars. This method can overcome the effects of the Earth's curvature on wind field construction results.