17 results about "Radiosonde" patented technology

This invention relates to the field of AI weather forecasting technology and discloses a weather forecasting method based on an AI weather forecasting model and a WRF model. The method includes: inputting ERA5 global atmospheric reanalysis gridded data into the AI ​​weather forecasting model to obtain an assimilated background field; constructing an effective multi-source observation vector based on observation data from ground automatic weather stations, radiosonde observation data, geostationary meteorological satellite radiance data, and Doppler radar VAD wind profile data; solving for the optimal atmospheric analysis field; extracting atmospheric state variables from the optimal atmospheric analysis field and writing them into the WRF model's side boundary driving file, driving the WRF model to complete the integration operation, and obtaining a gridded forecast field of meteorological elements. This method enables the WRF boundary condition update frequency to be higher than the traditional 6-hour static scheme, effectively characterizing the rapid evolution of the atmospheric state in the boundary region at the sub-hourly scale, thereby improving the WRF model's forecasting capability for high-impact weather events such as severe convection.

This application discloses a method, device, and medium for identifying the phase state of water condensate using dual-polarization radar in winter, relating to the field of radar meteorological detection technology. The method includes: acquiring radar data from a dual-polarization radar; performing spatiotemporal matching between the radar data and radiosonde data to obtain matched radiosonde data; extracting zero-degree layer height information based on the matched radiosonde data and obtaining the average melting layer height in real time by combining it with a quasi-vertical profile; adaptively switching to a summer two-dimensional melting layer feature detection algorithm or a winter three-dimensional melting layer feature detection algorithm based on the height difference between the average melting layer height and the radar station's altitude to obtain refined melting layer spatial information; identifying the phase state of water condensate for each polarization parameter to obtain an initial phase state identification result, and constraining the initial phase state identification result using the refined melting layer spatial information to obtain the final water condensate phase state identification result, thereby improving the accuracy of water condensate phase state identification using dual-polarization radar in winter.

The invention discloses a multi-source sounding data fusion processing method and a related device. The method comprises the steps of filtering a plurality of pieces of sounding second data received in real time based on a detection range and a geographic position range of sounding related equipment, then calculating a data quality score of each piece of sounding second data by using an established multi-dimensional sounding second data quality evaluation model, and calculating a data quality score of each piece of sounding second data according to the data quality score. And in the sounding second data from the same sonde, the sounding second data with the highest quality score in each second is spliced and fused into the complete sounding data of the sonde, and then the complete sounding data of each sonde is obtained through statistical arrangement. According to the data fusion method and device, it can be guaranteed that the data quality of each piece of sounding second data is high, then the data quality, integrity and reliability of the sounding second data obtained through splicing fusion can be guaranteed, and the data fusion mode is more efficient and reliable.

This specification discloses a method and system for optimizing radiosonde data based on time-varying characteristics, comprising: acquiring radiosonde data to be processed; obtaining minute-level radiosonde data based on the radiosonde data to be processed using a linear interpolation method; obtaining minute-level reanalysis data based on the location reanalysis data of the radiosonde station to be processed using a linear interpolation method; and obtaining final radiosonde data based on the minute-level radiosonde data and its weights, and the minute-level reanalysis data and its weights, thereby optimizing the radiosonde data to be processed.

This invention provides a method and apparatus for reconstructing the three-dimensional temperature and humidity field of a tropical cyclone based on deep learning and sparse observations. The method includes: acquiring radiosonde observation data and satellite remote sensing data for a target tropical cyclone region; mapping the radiosonde observation data onto a two-dimensional grid on multiple preset pressure layers to generate an initial temperature and humidity field containing missing data regions, and generating a mask to identify the missing data locations; interpolating and aligning the satellite remote sensing data onto the two-dimensional grid to form an auxiliary remote sensing field; combining the initial temperature and humidity field, the mask, and the auxiliary remote sensing field at each pressure layer to form a multi-channel input tensor, which is then input into a pre-trained deep neural network model. The model infers and completes the missing data regions, outputting the complete two-dimensional temperature and humidity field for the current layer; and vertically synthesizing the complete two-dimensional temperature and humidity fields corresponding to all pressure layers to obtain the three-dimensional temperature and humidity field of the target tropical cyclone.

The invention discloses a hail precursor stage area intelligent identification method based on equal-height reflectivity constraint. Belongs to the technical field of meteorological monitoring and disaster prevention and reduction. Comprising the following steps: acquiring radar body scanning and air sounding data, solving a target temperature isothermal surface height by adopting a first cross height method, and carrying out gridding; performing quality control and texture extraction on the dual-polarization parameters, and realizing preliminary classification of the phase state of the hydrogel through fuzzy logic; projecting an isothermal surface and a melting layer to the radial direction of the radar based on a 4 / 3 earth radius model to form geometric consistency constraint, and performing physical constraint on a classification result in combination with convection / layered division; based on the constrained phase state field and isothermal surface height, four types of key operation areas including a strong upflow area, a freezing drop type and vaterite type hail embryo area and a hail wet growth area are identified, equal-high-reflectivity constraint is applied to the strong upflow area to suppress false signals, and KDP missing measurement is used as a forward criterion for the wet growth area. According to the invention, advanced, accurate and business identification of the hail precursor stage is realized.

This invention discloses a method for evaluating near-space atmospheric environment data, comprising: acquiring raw near-space atmospheric environment data; preprocessing the raw data to obtain preprocessed data; establishing a near-space atmospheric variation range based on the preprocessed data; filtering and judging the preprocessed data based on the near-space atmospheric variation range to obtain valid data; gridding the valid data to obtain a verification data source; inputting an evaluation object; matching the evaluation object and the verification data source based on the principle of proximity matching to obtain a matching result; and verifying and evaluating the matching result. This invention rationally establishes threshold ranges for near-space temperature, density, air pressure, zonal wind, meridional wind, wind speed, and wind direction based on statistical results from a large amount of observational data. This invention is applicable to evaluating near-space atmospheric environment data such as reanalysis data, radiosonde data, rocket sounding data, and lidar data.

This invention discloses a method and system for atmospheric temperature profile inversion based on graph neural networks. The method includes acquiring GIIRS long-wave infrared radiation data, ERA5 temperature profile data, and radiosonde station observation data, and performing preprocessing to obtain GIIRS brightness temperature data, preprocessed ERA5 temperature profile data, and preprocessed radiosonde station observation data, respectively. A spatial graph inversion network is constructed, and the GIIRS brightness temperature data and its coordinates are input into the spatial graph inversion network to obtain deep features including location context information. A graph structure is constructed based on the deep features and K-NN. Based on the deep features and the edges of the graph structure, depth features and an adjacency matrix are obtained. The adjacency matrix and depth features are jointly input into a feature aggregator to obtain the atmospheric temperature profile. This invention fully utilizes the spatial information of the data, giving it a significant advantage in atmospheric temperature profile inversion tasks.

The invention discloses a sounding data center management method, system and device and a storage medium. The method comprises the following steps: receiving a health state of a respective processing node monitored by each service probe in real time through a management node, and periodically calculating a health score of each processing node; when a transmission party requests to access, the management node preferentially allocates a current access request to a processing node of which the health score meets a first constraint condition to execute the following steps: based on the access request, selecting an authentication server meeting a second constraint condition from the distributed authentication servers to perform equipment authentication and equipment registration on the transmission party; filtering the equipment of the transmission amplifier according to a built-in data counter; performing data analysis and partition storage on the received sounding data; and distributing the analyzed sounding data to different back-end services according to a set routing rule. According to the invention, the sounding data full life cycle management is realized, the sounding data transmission rate is improved, the authentication pressure is effectively dispersed, and the authentication and management cost is reduced.

This utility model discloses an automatic power-on device for a radiosonde, comprising the following structure: a bracket, a positioning pin, a power-on module, and a limit sensor. The bracket is a fixed structure, the positioning pin is mounted on the bracket, and the power-on module is located at the front end of the bracket, equipped with a cable and a controllable power supply connection. The limit sensor is located inside the bracket. This utility model is suitable for unattended operations in deserts, mountains, extremely cold, and extremely hot uninhabited areas. It utilizes a positioning pin, a power-on module, and a limit sensor, all integrated on a single bracket to form an automatic power-on device. The positioning pin ensures precise positioning and installation of the radiosonde carrier. The limit sensor detects whether the radiosonde carrier is properly installed. A control computer powers the automatic power-on device, thus automatically powering on the radiosonde. This utility model features a scientifically designed structure, convenient operation, strong practicality, and broad application prospects.

This invention relates to the field of meteorological monitoring technology, specifically to a sea front identification method based on machine learning, comprising the following steps: S1, acquiring meteorological station, radiosonde station, and radar echo data of the target area, extracting meteorological element gradients, abrupt change intensity, and land-sea difference, and extracting radar echo features to form multi-source feature data; S2, collecting sea front and non-sea front data to construct samples and dividing them into training, validation, and test sets; S3, jointly analyzing meteorological features to identify the land-sea interaction boundary and constructing a sea front probability field; S4, constructing a machine learning model to fuse multi-modal features and training and evaluating it; S5, inputting multi-source data in real time for sea front identification and outputting early warnings. This invention, by fusing multi-source meteorological data and combining it with a machine learning model, achieves accurate identification and real-time early warning of sea fronts, thereby improving the accuracy and automation level of sea front monitoring.

This invention relates to a method for calculating the relative altitude of a dropsonde, comprising acquiring a dropsonde data set during the current drop process of a dropsonde, obtaining effective surface data from the dropsonde data set, and calculating the surface air pressure value p of the dropsonde based on the effective surface data. g and ground elevation value h g This updates the initial ground elevation h. g0 and the initial value of surface air pressure p g0 The next radiosonde is deployed, and the above steps are repeated. This application proposes a method for calculating the relative altitude of a drop-sonde by processing and analyzing the landing data of the drop-sonde, thus solving the problem that drop-sondes cannot directly obtain relative altitude. This invention also relates to a device, equipment, and storage medium for calculating the relative altitude of a drop-sonde.

This invention relates to a method and system for individually calibrating channel coefficients used in a radiosonde. The method includes: S1, sending a command to the radiosonde; S2, if the radiosonde does not respond, returning to S1; if the radiosonde responds, proceeding to S3; S3, outputting a known standard resistance value to the radiosonde, calibrating the actual ADC sampling value according to the known standard resistance value, obtaining calibration result parameters, calculating a target resistance value based on the calibration result parameters, and returning to S1 to store the calibration result parameters; S4, establishing a resistance-ADC mapping model based on the calibrated actual ADC sampling value and the target resistance value, and obtaining the actual resistance value corresponding to the ADC value based on the resistance-ADC mapping model. This invention can effectively improve calibration accuracy.

This invention discloses a method for extracting oceanic low-altitude waveguide features based on meteorological gradients, relating to the fields of marine atmospheric environment detection and radio wave propagation technology. This method constructs a standardized multi-scale meteorological gradient dataset through data preprocessing, and then uses a gradient fusion algorithm to achieve global optimization of the physical constraint fusion factor of the mesoscale meteorological gradient and local modeling of small-scale non-uniform features, forming a high-resolution feature field. Based on this, combined with radiosonde data, a waveguide comprehensive inversion algorithm is used to invert and obtain a full-space waveguide feature parameter set. Finally, the coefficients are adaptively optimized through closed-loop verification using independent measured data. This invention achieves high-resolution integration of mesoscale global constraints and small-scale local features, improving the accuracy of oceanic low-altitude atmospheric environment characterization. Relying on the waveguide comprehensive inversion and closed-loop optimization mechanism, it integrates measured data and multi-dimensional verification, adaptively optimizing core coefficients, enhancing the reliability of waveguide feature extraction and its adaptability to complex ocean-atmosphere environments.

The invention discloses a sonde ball releasing whole process data transmission method, and relates to the technical field of meteorological detection, and the method comprises the following steps: S1, dynamically adjusting the transmitting power through the linear distance between a sonde and a ground station and environment parameters; s2, fusing acceleration, air pressure and speed abrupt change information, and completing sonde ball falling judgment; s3, predicting the falling point of the falling ball of the sonde in combination with the real-time wind speed; s4, constructing an operator evaluation model according to the predicted drop point of the sonde; and S5, formulating an operator network switching rule based on the operator evaluation model. According to the method, the data transmission stability of the sonde is improved by dynamically adjusting the transmitting power, the possible drop point area is predicted, the optimal 4G operator in the area is identified so as to switch the 4G channel in advance, and the data receiving rate of the whole process of lift-floating-ball falling of the sonde is improved.

This invention discloses an on-orbit radiometric calibration method for the thermal infrared channel of a meteorological satellite, comprising the following steps: selecting a suitable working time for the field calibration test based on satellite transit information and weather conditions at the calibration site; using an unmanned surface vessel (USV) carrying an infrared radiometer CE312, releasing the USV via a dock approximately two hours before satellite transit, and navigating on a pre-set route on the lake surface. This invention significantly saves manpower, material resources, and financial investment by utilizing the USV to automatically observe and acquire water surface radiation brightness temperature; by combining this with the acquisition of encrypted atmospheric profile data from radiosondes, the calibration frequency can be greatly increased, and calibration accuracy can be further improved; by comparing the entrance pupil brightness temperature information obtained from the thermal infrared channels of various satellites, the spatial distribution of brightness temperature during the synchronous test period at the calibration site and the degree of influence of cloud and weather conditions on the lake surface can be analyzed, providing significant reference for the selection of the synchronous testing area.

The invention relates to a manufacturing method of a high-precision high-altitude wind field reanalysis data set, and belongs to the technical field of meteorological high-altitude wind field fusion. According to the method, standard atmospheric pressure layer division with the interval of 250 meters of sounding second data and a standard atmospheric model, background field wind field processing based on ERA5, ERA5 and high-altitude detection wind field fusion adopting an optimal interpolation method are integrated, and a high-altitude wind field reanalysis data set is manufactured. According to the method, ERA5 reanalysis data and national high-altitude wind field detection data are fused, a high-precision high-altitude wind reanalysis data set of 80 layers below 20000 meters is made, and the data set can more finely and accurately reflect the wind field conditions of China and surrounding areas thereof.