467 results about "Typhoon" patented technology

The invention discloses a physical information neural network-driven ocean island typhoon scene generation method and system. The method comprises the steps of collecting multi-source heterogeneous meteorological data and performing space-time alignment preprocessing; constructing a coarse-scale space-time probability prediction model, capturing space correlation of meteorological elements by using a graph topology learning network, efficiently processing long-time-sequence dependence of typhoon evolution by integrating a state space model with linear complexity, and generating a probabilistic typhoon scene with coarse resolution through a multivariable joint distribution probability model; further constructing a physical downscaling model, taking a coarse-scale prediction result as condition input, and performing physical consistency downscaling on a coarse-scale scene by embedding an atmospheric fluid mechanics equation in a loss function as a physical hard constraint; and finally, outputting a high-resolution typhoon scene with probability reliability and physical authenticity.

The invention discloses a numerical simulation prediction method and system for typhoon binocular wall structure reconstruction judgment and maintenance duration after terrain interference and a medium, and relates to the technical field of typhoon fine structure evolution description and numerical simulation. According to the method, the binocular wall typhoon is identified through multi-source data fusion, a high-resolution numerical simulation system is constructed, and a typhoon structure is divided into four quadrants for differential diagnosis according to the wind shear direction based on vertical wind shear phase limit analysis. And the distribution characteristics of the rapid vortex silking area are captured by calculating vortex silking time parameters. And establishing a ditch sinking airflow detection mechanism, and quantitatively evaluating the contribution of radial advection, tangential advection, vertical advection and friction force items to tangential wind evolution by using tangential wind income and expenditure diagnostic analysis. And calculating an energy growth rate, and predicting a double-eye wall maintaining time length. According to the method, the outer eye wall re-formation judgment is output, the outer eye wall radius zone, the maintenance duration interval and the uncertainty are predicted, and the method is suitable for real-time business and research.

The invention relates to the technical field of typhoon path prediction, and discloses a typhoon path prediction method, system, terminal and storage medium based on multi-modal data of sounding equipment and a sky big model, and the method comprises the steps: obtaining multi-source heterogeneous data collected by detection equipment related to typhoon prediction, carrying out fusion and adaptive enhancement on the multi-source heterogeneous data on the basis of a big Pantou meteorological model, and generating a high-resolution three-dimensional field; constructing a cascaded AI downscaling network, introducing a physical constraint layer, carrying out local refined modeling on a typhoon eye region according to the high-resolution three-dimensional field, and outputting a high-resolution three-dimensional meteorological field; and designing a typhoon-environment field interaction model based on a graph neural network, performing typhoon prediction according to the high-resolution three-dimensional meteorological field, and outputting a typhoon path ensemble forecast containing a confidence interval and a typhoon thermodynamic structure analysis report. The typhoon path prediction speed and precision are improved, the prediction time is shortened, the prediction error is reduced, and calculation resources are saved.

The invention relates to the technical field of storm surge disaster monitoring and intelligent forecasting, and provides a regional collaborative storm surge water increase forecasting method of a coupling graph attention and gated circulation network, which comprises the following steps of: obtaining storm surge water increase residual field data based on a mixed wind field driving two-dimensional hydrodynamic model formed by typhoon parameterization and reanalysis data fusion, registering the water-increasing residual field data and the observation time sequence in time and space, and taking the registered data as physical prior input; constructing a dynamic edge weight graph structure based on a space-time causal correlation analysis method, and adaptively updating the dependency relationship among multiple observation stations; physical priori and key features are used as node input, a graph attention mechanism of GATv2 and a time sequence feature extraction capability of GRU are fused, and time-space coupling modeling is carried out on storm surge water increase; and carrying out multi-station joint prediction through regional cooperation, carrying out model evaluation and result optimization, and outputting a storm surge water increase prediction sequence with 15-minute time steps and 15-4-hour advance.

The invention discloses a near-shore wave-flow field-sediment coupling simulation method considering a wave breaking nonlinear effect, and belongs to the field of near-shore hydrodynamics, and the method comprises the steps: inputting WRF high-resolution wind field, tide boundary conditions and water depth information, and initializing a wave module, a flow field module and a sediment module; calculating local wave breaking dissipated energy by adopting an improved wave breaking energy dissipation formula to obtain a wave energy density spectrum and a breaking probability; a near-shore flow field is calculated under radiation stress nonlinear correction, and hydrodynamic boundary conditions are updated; calculating sediment suspension and deposition by using a coupling diffusion coefficient, and updating sediment concentration distribution; waves, flow fields and sediment are mutually coupled through loop iteration, and coastal wave-flow field-sediment simulation is achieved under extreme conditions such as typhoons, storm surge and strong storm waves. The method can improve the prediction precision of the wave height, the flow velocity and the sediment concentration under the condition of offshore strong storm waves, and is used for typhoon storm surge prediction, harbor basin deposition evaluation and offshore ecological environment management.

The invention discloses a typhoon wave height prediction method based on a deep learning MOE-Transform model, and the method comprises the following specific steps: collecting historical typhoon data of a research region, and constructing a virtual typhoon data set in combination with a central pressure difference formula; processing the historical and virtual typhoon data sets through a Holland typhoon empirical model and a storm growth relation to obtain a wind field, an air pressure field and a significant wave height field; correcting the field data by using an error model on the basis of the ERA5 data set to form a typhoon space-time fusion database containing meteorological data, the significant wave height field and typhoon data; and training and testing the MOE-Transform model to obtain a typhoon wave significant wave height prediction model for typhoon wave height prediction. According to the method, the multi-task adaptability and generalization ability are improved, and the precision and timeliness of typhoon wave height prediction are improved.

Disclosed in the present invention are an optimization-based regulation and control method and apparatus for distributed energy storage, a device, and a storage medium. The method comprises: on the basis of current weather parameters, constructing an extreme weather model; determining a plurality of faulted and out-of-service elements in which faults will occur in a power distribution network; then on the basis of the faulted and out-of-service elements, system parameters of a distributed energy storage system, and an operation parameter of the power distribution network, constructing a dual-objective optimization model taking load loss minimization and power failure time minimization as objectives; and finally, solving for the dual-objective optimization model to generate an optimal regulation and control scheme applied to the distributed energy storage system. Therefore, when a fault has occurred in the power distribution network, the distributed energy storage system is regulated and controlled by means of the optimal regulation and control scheme, such that power supply of the power distribution network is restored as soon as possible in extreme typhoon weather, and the transient power deficit of the power distribution network is made up promptly. Therefore, the present invention can effectively guarantee the safe operation of power distribution networks under the condition of extreme typhoon weather.

According to the typhoon disaster dynamic risk estimation method and system based on intelligent grid forecasting, meteorological data of an intelligent grid forecasting system with high refinement degree and good accuracy are adopted, intelligent grid forecasting data are corrected by fusing observation data, and data deviation is effectively reduced. The typhoon wind and rain comprehensive index can objectively reflect the typhoon composite disaster-inducing effect, and the typhoon wind and rain comprehensive index is based on the nature of a disaster-inducing mechanism, and the limitation of single-element evaluation is solved by dynamically fusing wind speed and rainfall data. The disaster-pregnant environment influence coefficient considering the dynamic influence of the terrain factors is constructed, the limitation of traditional fixed geographic parameters is broken through, and the risk assessment error caused by neglecting the dynamic nature of the disaster-pregnant environment in a traditional model is solved. A typhoon disaster risk assessment model based on index weight is designed, the risk assessment model focuses on disaster-causing risk, exposure degree and vulnerability key factors, the model structure is simplified, and the calculation efficiency is improved.

The invention provides a typhoon disaster risk traceability and prediction method based on disaster grade clustering and an interpretable model. Comprising the following steps: constructing an index system containing multi-dimensional typhoon disaster influence variables, carrying out clustering analysis on disaster consequences by utilizing a Gaussian mixture model based on historical typhoon disaster event data, and dividing severity levels of typhoon disasters; a Borderline-SMOTE algorithm is adopted to process the problem of class imbalance, and an XGBoost model is utilized to construct a nonlinear mapping relation between disaster influence variables and disaster grades; an SHAP method is introduced, the contribution degree of each input variable to disaster grade prediction is clarified, key disaster-inducing factors and disaster-inducing paths thereof are disclosed, and the interpretability of a model result is realized. The method also supports typhoon information input before a disaster, realizes disaster grade prediction and risk tracing, proposes targeted disaster prevention and reduction suggestions based on an SHAP analysis result, provides real-time and accurate typhoon disaster early warning and risk intervention basis for coastal cities, and has relatively strong practical guidance significance and popularization and application values.

The invention discloses a typhoon influence distinguishing method and system based on seawater CO2 partial pressure data, and the method comprises the steps: obtaining sea area situation monitoring data in a target sea area typhoon transit period through a multi-source observation platform, and constructing a standardized data set and a climate state background field; a DBSCAN clustering algorithm is adopted to perform water mass division, and the typhoon characteristic water mass distribution is determined in combination with a Manchester-HuitiniU test and correlation analysis. And calculating a seawater carbon dioxide partial pressure abnormal field based on the climate state background field, constructing a typhoon influence index sequential sequence, identifying a core influence area, and generating a typhoon influence trace path. And then seawater carbon dioxide partial pressure grid point reconstruction is carried out, and a typhoon influence space map is constructed. And finally, analyzing space-time change of carbon dioxide flux of air-sea, evaluating carbon sink stability, and generating a typhoon-carbon sink sensitivity zoning map. Seawater carbon dioxide partial pressure is used as a core index, limitation of a traditional method is overcome, and reliable technical support is provided for typhoon marine environment influence assessment.

The invention relates to the technical field of artificial intelligence, is applied to financial or medical insurance claim settlement scenes, and particularly relates to a typhoon claim settlement disaster damage assessment method, device and equipment and a medium, and the method comprises the steps: obtaining a multi-source typhoon data set, carrying out the feature data recognition of the multi-source typhoon data set, and constructing a target claim settlement knowledge base according to the feature data; and inputting the obtained real-time typhoon data and early warning city information into the target claim settlement evaluation model based on the target claim settlement knowledge base to obtain a claim settlement evaluation result. Visibly, according to the method, feature data identification is performed on the multi-source typhoon data set, the target claim knowledge base is constructed according to the feature data, and then the acquired real-time typhoon data and early warning city information are input into the target claim evaluation model according to the target claim knowledge base, so that accurate evaluation of typhoon claim disaster damage is realized; and the insurance claim settlement efficiency is improved, so that an insurance claim settlement reference for typhoon disasters is provided for an insurance company.

The invention belongs to the technical field of intelligent monitoring, and discloses a typhoon safety evaluation system and method for an ocean engineering structure. The method comprises the steps of collecting original data, preprocessing the original data to obtain standard data, and performing time-frequency analysis on the standard data to obtain time-frequency characteristics; performing analysis based on the time-frequency characteristics to obtain modal parameters; analyzing according to the modal parameters to obtain a non-linear state judgment result; carrying out damage positioning according to a non-linear state judgment result; carrying out residual safety life prediction according to a damage positioning result; the safety guarantee level of the ocean engineering structure in the typhoon period is remarkably improved.

The invention discloses a storm surge nearshore disaster identification method, device and equipment fused with a typhoon dynamic influence domain, a medium and a product, and relates to the technical field of meteorological disaster monitoring. The method comprises the following steps: acquiring a meteorological ocean reanalysis data set in a historical set age limit of a target area, and preprocessing multi-source data; then background field elimination processing is carried out; determining a dynamic influence radius based on the typhoon intensity grade and the storm surge abnormal data; determining the center position of the typhoon according to the dynamic influence radius, and generating a typhoon dynamic influence domain space mask by adopting a spherical distance calculation method; a near-shore buffer area is determined according to the typhoon dynamic influence domain space mask, and a storm surge disaster area is determined based on a near-shore buffer area constraint and water increase threshold value judgment method; and carrying out storm surge near-shore disaster identification on the basis of the storm surge disaster area by adopting a geographic space visualization method to obtain an identification result. According to the invention, accurate storm surge disaster discrimination can be realized.

The invention discloses a floating fan numerical simulation method based on a cross-scale typhoon modeling algorithm, and aims to solve the problems that a typhoon unsteady-state wind field cannot be accurately simulated and the influence of the typhoon unsteady-state wind field on the coupling dynamic response of a floating fan cannot be accurately simulated in the prior art. The method comprises the following steps: firstly, dividing the whole typhoon process into a plurality of typical stages according to meteorological characteristics; for each stage, calculating a time-varying average wind field by adopting a parameterized mesoscale typhoon model, and embedding a three-dimensional turbulence component generated based on a microscale turbulence model to generate a high-fidelity stage wind field file; integrating the wind fields of all stages into a complete and continuous unsteady typhoon wind field input file by using a splicing algorithm; and finally, inputting the wind field file into a pneumatic-hydrodynamic-servo-elastic coupling simulation platform OpenFAST, and carrying out full-coupling dynamic response analysis on the floating fan. According to the method, the prediction precision of the load and motion response of the floating fan system under the extreme typhoon working condition is improved, and a reliable method is provided for typhoon resistance design and safety evaluation of the floating fan.

The invention relates to the technical field of data assimilation processing, in particular to a WRFDA assimilation method, system and device based on GIIRS data. The method comprises the following steps: acquiring GIIRS data, extracting data from the GIIRS data, and merging and checking the data to obtain checked GIIRS observation information; performing deviation correction on the background field data of the numerical weather forecasting mode by using an RTTOV rapid radiation transmission mode to obtain simulation data after stable deviation correction; performing cloud pollution screening on the GIIRS observation information after inspection and the simulation data after deviation correction to obtain GIIRS observation information without cloud pollution; wRFDA numerical assimilation is carried out on the GIIRS observation information without cloud pollution, an initial field file is obtained, and the initial field file is used for adjusting and optimizing an output weather forecast result. According to the method, a more accurate initialization file is obtained, and the simulation accuracy of the typhoon precipitation area is more accurately improved.

The invention discloses a typhoon intensity prediction method and device fused with a space-time deep network, and a medium, and the method comprises the following steps: 1), collecting typhoon historical observation data, and obtaining typhoon data; 2) data preprocessing; 3) extracting data features; 4) feature fusion; 5) establishing a typhoon intensity prediction model; 6) model training; and 7) performing prediction by using the trained model, outputting a final prediction value, and restoring a prediction result into an actual typhoon intensity value through reverse normalization processing. The influence of the remote sensing satellite image and the characteristics of the tropical cyclone on the tropical cyclone strength estimation accuracy is considered, the typhoon strength prediction integrated with the spatio-temporal information is carried out, the spatio-temporal representation of the typhoon focus area is enhanced through the integration of the spatial characteristics and the time sequence characteristics of the typhoon, and the accuracy of the strength prediction result is improved.

The invention provides a method, a device and equipment for identifying vulnerability driving factors of disaster-bearing bodies under typhoon disasters and a storage medium. The method comprises the following steps: obtaining a comprehensive data set according to obtained historical typhoon disaster intensity data and historical typhoon disaster loss characterization data of a plurality of areas; obtaining an optimal function and a target disaster-causing intensity variable according to the comprehensive data set and a plurality of preset candidate functions; according to the optimal function and the target disaster-causing intensity variable, obtaining a disaster-bearing body loss rate and a disaster-bearing body absolute loss value; performing typhoon disaster vulnerability assessment according to the disaster-bearing body loss rate and the disaster-bearing body absolute loss value to obtain a typhoon disaster vulnerability assessment result; and according to the typhoon disaster vulnerability assessment result and a plurality of preset driving factors, determining an identification result of the vulnerability driving factors of the disaster-bearing body under the typhoon disaster. According to the invention, the accuracy of typhoon disaster vulnerability assessment and driving factor identification can be improved, and the pertinence and scientificity of typhoon disaster risk management are effectively improved.

The invention discloses an inland area TRP feature recognition and evaluation method based on data driving and numerical simulation, a medium and a program product, and relates to the technical field of meteorological disaster monitoring and early warning and numerical simulation. And objectively identifying a TRP event which occurs outside the typhoon circulation and is connected with the strong water vapor conveying belt by combining the typhoon peripheral circulation radius, the distance constraint and the whole-layer water vapor conveying flux. Key physical fields such as whole-layer water vapor flux, water vapor income and expenditure, dry invasion and monsoon water vapor surge are diagnosed by utilizing a regional numerical mode and reanalysis data, and a characteristic index set reflecting typhoon, monsoon and dry and cold air coupling influence is formed; on the basis, a data-driven learning algorithm is introduced, a TRP occurrence and rainstorm intensity grading recognition model is obtained through training, a risk assessment product is generated through calibration and risk grading, and therefore the inland typhoon long-distance rainstorm recognition and assessment capacity is improved.

The invention relates to the technical field of forecast correction, in particular to a multi-mode forecast correction method and system based on ensemble learning, and the method comprises the following steps: S1, mapping a multi-mode original forecast field of a target region to a phase space, and generating a phase space state vector comprising key elements; s2, on the basis of the phase space state vector in the S1, calculating a state mutual coupling matrix between modes through a transfer entropy algorithm; and S3, when the maximum entropy value in the state mutual coupling matrix in the S2 exceeds a bit threshold value, triggering a phase space trajectory corrector to reconstruct a forecast trajectory and output a correction result, otherwise, directly outputting an original forecast optimal integration. According to the method, systematic risks such as typhoon peripheral vortex pollution and frontal resonance errors which are difficult to detect by a single mode are effectively identified, and scientific quantification of correction triggering is realized.

The invention belongs to the technical field of meteorology, and discloses a typhoon intensity prediction and residual error correction method and system based on a double-branch convolutional neural network, and the method comprises the steps: obtaining satellite-typhoon data; data preprocessing and space-time matching: constructing and cleaning a sample set; building a double-branch CNN (Content Node Network)-DenseNet network; model training; and carrying out residual analysis and system error correction. According to the method, key physical information such as severe convection and rapid enhancement of a typhoon core area is fully mined by combining a traditional multi-channel satellite cloud picture and an infrared-water vapor channel difference physical indication factor, and the perception ability of the model to a complex typhoon structure and a development process is effectively improved.

The invention provides an urban storm surge forecasting method based on multi-source information coupling, and the method comprises the steps: taking multi-source typhoon driving element data as the input information of a preset typhoon structure reconstruction model, and outputting typhoon key physical parameters through the typhoon structure reconstruction model; based on a Kriging interpolation and radial basis function mixing method, carrying out fusion processing on the multi-source topographic data, and constructing topographic grid information; extracting tide harmonic constants of a specified number of partial tides from the multi-source tide factor data; based on the typhoon key physical parameters, the terrain grid information and the tide harmonic constants, determining input information of a predetermined urban storm surge forecasting model; and outputting a storm surge level abnormal value and a horizontal flow velocity component corresponding to the multi-source prediction associated data through the urban storm surge prediction model. According to the scheme, the precision of urban storm surge forecasting is improved.

The invention discloses an electric power system flexible resource planning method, system and device considering multi-time scale extreme weather and a storage medium, and relates to the technical field of electric power system planning, and the method comprises the steps: generating a multi-time scale extreme weather scene based on a conditional diffusion model; constructing a flexible resource planning model of the mixed time scale power system; and calling a Gurobi solver by using a Yalmip toolkit of Matlab to solve the flexible resource planning model of the mixed time scale power system, and outputting an optimal planning scheme of flexible resources of the power system. According to the method, the multi-day extreme weather scene is generated based on the conditional diffusion model, spatial-temporal characteristics of multi-day extreme weather such as typhoon and high temperature can be accurately described, and compared with other methods, a diversified scene set with more statistical coverage can be reconstructed under limited historical extreme data; and a multi-time-scale operation scene basis with typicality and extreme property is provided for power system planning.

The invention discloses a typhoon disaster refuge population estimation method for service shelter planning. The typhoon disaster refuge population estimation method comprises the steps of collecting multi-source data related to emergency transfer placement population caused by typhoon disasters; processing the multi-source data to obtain a plurality of predictive factors, assigning the predictive factors to grid units, and arranging emergency transfer and placement population records to a unified administrative division spatial scale; constructing an emergency transfer placement population simulation model, and performing training and testing; simulating a grid-level transferred population estimation result corresponding to the artificially synthesized typhoon event, and aggregating the grid-level transferred population estimation result to a planning unit to obtain transferred population simulation data of each planning unit in a typhoon scene in a preset year range; and calculating the relationship between the recurrence period and the transferred population of each planning unit to obtain a recurrence period transferred population curve of each planning unit, and then setting the refuge demand of the planning unit in combination with the actual situation. The present invention can generate emergency transfer placement population estimates covering different probability levels.

The invention discloses a meteorological radar grading identification method combined with a meteorological numerical model, and relates to the technical field of intelligent meteorological perception, and the method comprises the steps: generating a unified initial state vector in a preset calibration region through employing historical typhoon similar sample statistical information, and achieving the cold start calibration under the condition of no radar data; then distributing a radar extrapolation field within two hours and a numerical mode field weight after two hours based on a time gating function, respectively calculating an observation residual error covariance matrix and an observation error covariance matrix, and carrying out joint correction on an amplitude component and a deformation component by adopting Kalman updating; through mode CLDAS field large-scale extrapolation, spatial resolution refinement, terrain factor correction and radar extrapolation field high-precision fusion, a fusion precipitation field is obtained, a hierarchical graph is generated based on an adaptive quantile threshold value, and iterative updating is completed; according to the method, through unified initial state vector generation of historical typhoon similar sample statistics, the stability of water field initialization under a radar-free condition is realized.

The invention belongs to the field of meteorological disaster forecasting, and discloses a physical meteorological factor guidance-based generative typhoon prediction method, which comprises the following steps of: inputting typhoon historical time sequence multi-attribute data, typhoon external environment meteorological variable data and a typhoon inclination coefficient into a physical constraint coding module to obtain a physical constraint preliminary feature; inputting the physical constraint preliminary features into a multi-constraint fusion alignment coding module to obtain a historical multi-attribute information constraint, a typhoon external environment constraint and a typhoon internal structure constraint after fusion alignment coding; and inputting the standard noise, the historical multi-attribute information constraint, the typhoon external environment constraint and the typhoon internal structure constraint which are consistent with the predicted attribute in shape and have uncertainty higher than a threshold value into an uncertainty reduction module under the guidance of the physical constraint to obtain a predicted value of the typhoon target attribute after uncertainty reduction. According to the method, the uncertainty is reduced, and transferable and accurate global typhoon prediction with low computing resource requirements is realized.

The invention discloses a buoy attitude self-adaptive wind wave calibration method for a typhoon landing path sea area, and relates to the field of ocean monitoring, and the method comprises the steps: obtaining attitude information, original wave height information and wind speed and direction information of a target buoy through a six-degree-of-freedom IMU, a micropressure array wave height meter and a three-axis ultrasonic wind speed sensor carried by the target buoy; compensating the original wave height information based on the attitude information and the wind speed and direction information to obtain compensated wave height information; based on remote sensing inversion data, a storm surge numerical forecasting model or historical tide level data, obtaining a storm surge lifting height of the current area, and taking the storm surge lifting height as a zero drift error of the micropressure array wave height meter; and outputting target wave height data based on the zero drift error and the compensated wave height information. According to the calibration mechanism of fusion compensation and multi-source correction provided by the method, the adaptability and practicability of a traditional buoy system under extreme meteorological conditions are remarkably improved.

The invention provides a simulation system and method for a typhoon rainstorm induced combined flow-slip disaster, and the system comprises a side slope simulation box which is used for simulating a side slope covered by vegetation; the wind load control system is used for simulating a wind load applied to the slope simulation box and controlling a wind load time history according to a set typhoon level; the rainfall control system comprises a variable-frequency water pump and is used for determining the rainfall intensity according to the set typhoon level, determining the target power of the variable-frequency water pump according to the rainfall intensity, simulating rainfall and controlling the rainfall time history; and the spatial three-dimensional visual data acquisition system is used for acquiring multi-section visual three-dimensional data of the three-mechanism coupling catastrophe simulation process of the slope model in real time under the action of the wind load, rainfall and the plant model. Through the application, the three-mechanism coupling catastrophe process of the slope model under the action of wind load, rainfall and the plant model is accurately simulated, the three-mechanism coupling catastrophe mechanism in the soil body is disclosed, and dynamic three-dimensional analysis of engineering is realized.

A method for estimating typhoon structural parameters by fusing spaceborne GNSS reflectometer data and radiometer data, which relates to the technical fields of data fusion and typhoon monitoring. The method comprises: acquiring GNSS-R reflectometer data and radiometer data; filtering typhoon data from the GNSS-R reflectometer data and the radiometer data to obtain filtered GNSS-R reflectometer data and radiometer data; performing data spatio-temporal matching on the filtered GNSS-R reflectometer data and radiometer data to obtain a spatio-temporally matched region; performing data fusion processing on the spatio-temporally matched region to obtain fused data; and performing typhoon structural parameter estimation on the obtained fused data to obtain structural parameters of a typhoon at each development stage. Fused data of spaceborne GNSS-R reflectometer data and radiometer data is used for typhoon structural parameter estimation, such that the temporal resolution and accuracy of parameter estimation can be improved, and the algorithm complexity is low.

The invention discloses a meteorological data spatial downscaling training method and system based on self-supervised learning. An inverted meteorological data pyramid is constructed, pre-training is performed based on meteorological data internal repeatability, and self-supervised fine tuning is performed based on a spatial position relation. According to the invention, the spatial downscaling of the meteorological data can be realized without using high-resolution data, so that the dependence on the high-resolution data in the meteorological downscaling process is reduced; the method can be flexibly applied to various deep learning models to realize self-supervised downscaling of meteorological data; in actual tasks such as typhoon positioning, the method can achieve the same downscaling effect as a supervised learning method. Experimental results show that the method is small in size under the condition that a high-resolution training set is not needed, high-quality meteorological variable downscaling is achieved, and the problem that actual meteorological forecast lacks a high-resolution data set is solved.

The invention discloses an atmospheric ocean multi-source data high-precision assimilation method and device, and relates to the technical field of ocean multi-source data assimilation, and the assimilation method comprises the steps: collecting multi-source observation data of a typhoon region of the South China Sea; preprocessing the data; decomposing the observation field into different scales by using wavelet transform; acquiring a background field from the numerical model, interpolating the background field to a grid consistent with observation, projecting the background field to an observation space, and performing multi-scale decomposition to enable the background field to correspond to an observation scale; calculating a difference vector of observation and background fields on each scale, and dynamically calculating an adaptive weight of each point on each scale according to an observation error, a background error and a current deviation; and constructing a cost function, solving through an optimization algorithm to obtain an analysis field, and outputting a final analysis field. According to the method, a multi-scale decomposition and self-adaptive regularization cooperation mechanism is introduced, so that high-precision dynamic fusion of the multi-source observation data and the numerical model can be realized.