73 results about "Meteorological models" patented technology

Methods and mobile platforms are disclosed for using vehicles to gather meteorological data. A method identifies a location that is relevant to a particular meteorological model based on modeling parameters of the particular meteorological model. Meteorological data is collected aboard a vehicle. The meteorological data is indicative of a meteorological condition in an area within sensor range of the vehicle. At least a portion of the meteorological data is transmitted to a modeling station remote from the vehicle in response to determining that the vehicle is proximate the location.

The invention provides an atmospheric pollution source grading method based on a pollutant source identification technology. The atmospheric pollution source grading method based on a pollutant source identification technology belongs to the technical field of atmospheric environment planning management, and prevention and control of pollution. The atmospheric pollution source grading method based on a pollutant source identification technology comprises the following steps of carrying out high spatio-temporal resolution meteorological simulation of a researched area based on a meteorological model, carrying out grid division of the researched area based on the geographic information system (GIS), arranging concentration contribution evaluation points, collecting pollution source discharge information, building a weather-air quality model coupled system, computing a sensitive factor, identifying sensitive discharge areas, carrying out unitization processing of the sensitive factor, and carrying out grading identification of pollution sources according to pollutant discharge loads and the order of the sensitive discharge areas. The invention aims at providing the atmospheric pollution source grading method based on a pollutant source identification technology so that the evaluation and quantitative grading of sensibility of atmospheric pollution sources are realized and an effective technical support for scientific pollutant-discharge reduction is provided.

Airborne meteorological radars and related networks and models. In one embodiment a network for creating a meteorological model includes a mobile sensing node and a modeling node. The sensing node includes a meteorological RADAR that senses the wind velocity. Data from the meteorological RADAR regarding the wind velocity is received by a processor of the modeling node which determines a model of the wind from the wind velocity. The modeling node combines data from a second sampling node with the data from the first sampling node to create a resultant wind velocity vector. Preferably, the modeling node and the sampling node(s) communicate over an airborne WAN. Another embodiment provides a method of measuring the wind velocity. The method includes steering an RADAR signal out of the plane of travel of the mobile platform. The wind velocity is measured using a return of the RADAR signal.

The invention discloses a regional mountain torrent risk prediction method and system. The method comprises the steps: S1, predicting the weather information of all hills in a region based on a meteorological model; S2, screening out hills needing risk prediction based on the weather information; S3, dividing hills needing risk prediction into different risk prediction levels according to the basic information of the hills; wherein different risk prediction levels correspond to different risk prediction periods; S4, preliminarily determining disaster-causing factors for mountain torrent evaluation; S5, screening the preliminarily determined disaster-causing factors to obtain main disaster-causing factors influencing the mountain torrent; S6, training and generating a plurality of mountaintorrent risk prediction models based on the main disaster-causing factors; S7, several risk prediction models with the best performance are selected to be combined to form a final risk prediction model; and S8, performing mountain torrent risk prediction on the hill to be predicted. According to the method, the risk prediction of the regional hill is realized, the realization cost is low, the coverage is wide, the processing efficiency is high, and the safety of the hill is improved.

The invention provides a three-dimensional iterative computing method for environment capacity of multiple atmospheric pollutants. The method comprises the steps of building a regional complex atmospheric pollution environment capacity three-dimensional iterative computing model based on a pollution source emission list and a meteorological model; establishing a pollution source three-dimensional classification method and an acceptor site optimization selection hierarchical classification method according to space distribution of pollution sources, industry types and pollutant indexes; establishing a dynamic iterative computing method for a space transmission matrix, an industry contribution matrix and a precursor contribution matrix by utilizing the environment capacity three-dimensional iterative model; and iteratively computing the environment capacity of the atmospheric pollutants such as SO2, NOx, particulate matters, NH3, VOCs and the like in regions and sub-industries by adopting a multi-objective nonlinear optimization technology according to the space, industry and precursor contribution matrixes. According to the method, the effects of regional transfer of PM2.5, industry coupling, precursor nonlinear collaboration and the like are comprehensively considered and the deficiencies of an existing environment capacity computing method are made up for.

The invention provides a new algorithm for an atmospheric environment capacity by using a region air quality model (RAQM). The new algorithm comprises the following computation steps: utilizing a meso-scale meteorological model to perform analog computation on an average value of year-round meteorological elements per hour in an estimation region to obtain uout and uin; utilizing the RAQM to perform analog computation on an average value of pollutant concentration per hour in an estimation year in the estimation region to obtain c; using a process analysis module to output transportation volumes Fout and Fin, dry deposition volume Ddry, wet deposition volume Dwet and chemical conversion volume T of pollutants per hour; performing the computation to obtain V and Asection; using cstandard to obtain a static volume of each atmospheric pollutant in the estimation region; and according to an expression of atmospheric environment capacity Q, performing the calculation to obtain a total environmental volume of atmospheric pollutants in the estimation region. With the adoption of the new algorithm provided by the invention, not only is the maximal capacity of atmospheres to contain the pollutants, regional transportation features of the atmospheric pollutants are reflected, but also key factors of influencing the pollutants in the estimation region are obtained, and assessment judgment basis such as more reasonable theories, more reliable data and more credible result can be provided for atmospheric environmental impact assessment.

A gas-condition predicting device includes an auxiliary storage device for storing each atmospheric condition in association with gas flow-field data in a target area under the atmospheric condition; a meteorological-modeling unit for calculating, using a meteorological model calculation, meteorological parameters at a plurality of evaluation points defined in an enlarged area that includes the target area and that is larger than the target area; and an extraction unit for determining atmospheric conditions in the target area from the meteorological parameters calculated by the meteorological-modeling unit and extracting from the auxiliary memory device gas flow-field data corresponding to the atmospheric conditions.

The invention, which relates to the field of meteorological element forecasting in the near-ground layer, discloses a refined meteorological element forecasting system of a near-ground layer and a forecasting method thereof. Different values of weather forecasting modes are integrated, coupled, and optimized to realize rapid cycle data assimilation. A forecasting area is designed and real-time dynamic refined near-ground meteorological element forecasting of an area and a single point under any landform is realized. The refined meteorological element forecasting system comprises a data downloading subsystem, a mesoscale weather forecasting mode subsystem, a three-dimensional variational assimilation subsystem, a CALMET small-scale meteorological model subsystem and a post-processing subsystem. In addition, the method includes: downloading grid data as well as conventional and unconventional meteorological observation data of the forecasting system; carrying out quality control and WRF mode pre-processing; carrying out rapid cycle data assimilation to obtain an optimized atmospheric initial field; carrying out area and single-point forecasting; acquiring an initial guess field and an underlying surface static field; carrying out downscaling forecasting based on a micro-topographic dynamics effect to obtain forecasting results of the near-ground layer at different heights; and carrying out post processing to obtain a final chart and a statistical result for outputting and displaying.

The invention discloses a judgment method of an icing thickness of an icing area electric transmission line. Based on collecting perennial historical meteorological data of a meteorological station, the judgment method of the icing thickness of the icing area electric transmission line includes summarizing meteorological and terrain feature law, structuring a meteorological model of relation between a surface feature lead wire icing thickness and meteorological elements, combining geographical and topographic feature elements to correct the model, computing icing thicknesses of areas of recurrence intervals of 30 years, 50 years and 100 years, and verifying and revising for the icing thicknesses according to operational experience. An ice distribution image which is mapped by adopting of the method can accurately reflect a distribution law of power grid icing thicknesses, can cover all areas, provides basis for power grid design, operating maintenance and technology improvement, and simultaneously has a guiding function for novel construction of areas without electric power facilities.

The invention proposes a time-series InSAR analysis method for integrating tropospheric atmospheric delay correction, thereby correcting the tropospheric atmospheric delay phase error in surface deformation monitoring of the steep mountainous terrain. In the time series InSAR data processing flow, the tropospheric atmospheric delay correction process is added and specifically, vertical stratification atmospheric delay and turbulent mixing delay are carried out. The vertical stratification atmospheric delay is estimated jointly by using a numerical meteorological model and an iterative linear phase-elevation regression model. According to the iterative linear phase-elevation regression model, a coherent point with deformation is rejected by using iterative execution of a linear phase-elevation regression model, so that only the coherent point without the deformation is kept to calculate the linear model. Therefore, the vertical stratification atmospheric delay correction in the time series InSAR analysis method is realized and thus the iterative linear phase-elevation regression model is not affected by the coherent point target without deformation, so that the interference on the mountain surface deformation signal extraction by the atmospheric delay is reduced effectively.

The invention provides an integral coupling method of an ocean model and a meteorological model. The integral coupling method comprises the steps of: establishing a weather numerical forecasting model based on the meteorological model; establishing an ocean numerical forecasting model based on the ocean model; and achieving integral coupling of the ocean model and the meteorological model by adopting a non-flux correction method. Through the coupling of the ocean model and the meteorological model, exchange process of energy and water vapour between an ocean underlying surface and the atmosphere is described in a more detailed and accurate manner, thereby establishing the weather numerical forecasting model suitable for offshore wind plant power prediction. By adopting a coupler technology, development and maintenance of subcomponent modes of an ocean-atmosphere coupling model are facilitated; and the adoption of the ''non-flux correction'' coupling method can ensure the flux conservation of an ocean-atmosphere interface.

Method for the quantification of the fugitive gas flow from a dispersed source (A) by monitoring with a remote detection optical instrument mounted on an aircraft (UAV) which moves at a determined height along a plane (5) perpendicular to the direction of the wind field (u), such wind field being known through suitable positioning of meteorological stations within and in areas neighbouring the site to be monitored according to known techniques and use of commercially available diagnostic meteorological models. By this instrument discrete vertical measurements are carried out of the fugitive gas concentration averaged over said height along the whole width (W) of the plane (S) to yield corresponding mean vertical concentration values and, according to mean wind speed values detected at said discrete vertical measurements, a value of the fugitive gas flow (Q) is obtained by integrating the product of the mean vertical concentration values and of the corresponding mean wind speed values with respect to the surface of the sampling plane (5). The obtained value of the fugitive gas flow (Q) is corrected by a corrective factor (a) obtainable by comparing concentration values obtained by direct measurements and values calculated by dispersion models.

A power transmission and transformation equipment ice coating disaster monitoring and forecasting method based on meteorological and topographic factors comprises the following steps of: S1, collecting meteorological and topographic data comprising geographic information such as a sea level elevation, river network information, a slope, an exposure, slope variability, exposure variability, a waviness, a roughness, a surface illumination degree and the like; S2, establishing an ice coating thickness estimation meteorological model, wherein the meteorological model is as follows: Y=-0.11x1-0.49x2-0.34x3-0.335x4+0.00x5-0.013x6+0.27x7+1.75x8; S3, carrying out topographic correction of the ice coating thickness estimation meteorological model and carrying out contrastive analysis on an ice coating thickness increment and a difference value of an actually measured value and a meteorological model estimated value, which are obtained by utilizing the formulas, wherein a topographic correction model is as follows: delta Y'=0.19+0.0014x1-0.0035x2+0.045x3; S4, adding the meteorological model in the step 2 with a topographic correction model in the step 3 to obtain a final ice coating thickness comprehensive correction model, completing monitoring on ice coating thickness distribution and carrying out forecasting on the basis of an obtained result. The method considers influence of microtopography and micrometeorology on monitoring of a power transmission and transformation equipment ice coating disaster and has the advantages of high accuracy, high practicality, high reliability and the like.

The invention provides a method and a device for early warning the spread of mountain fires in a power network. The method comprises the following steps: determining a prediction area; The fire risk factors in the prediction area are obtained, and the fire risk index is calculated according to the fire risk factors, and the fire risk level is determined. The meteorological forecast values of the forecasted area are obtained by WRF meteorological model, and the fire spread velocity, fire line intensity and regional combustion temperature are calculated according to the meteorological forecast values. Output and display Fire Hazard Index, Fire Hazard Grade, Fire Spread Speed, Fire Line Intensity and Zone Burning Temperature. The invention constructs a fire hazard index, The fire danger grade, fire spread speed, fire line intensity and regional combustion temperature are output as the mountain fire spread warning model, in which the fire spread speed, fire line intensity and regional combustion temperature are statistically analyzed by the WRF meteorological model data, which makes the whole model more optimized and can accurately realize the mountain fire forecast.

The invention discloses a random production simulation method used for a wind energy-solar photovoltaic energy-stored energy combined power generating system. The random production simulation method is characterized in that 1, meteorological model division is carried out by adopting a K-Means algorithm; 2, wind energy-solar photovoltaic energy-stored energy probabilistic modeling is carried out; 3, a wind energy power generating module, a photovoltaic power generating module, an energy storage device, and a load are serialized; 4, random production simulation is realized based on a sequence operation theory. The random production simulation method is advantageous in that a wind energy-solar photovoltaic energy complementation characteristic is better described, and the random production simulation of the wind energy-solar photovoltaic energy-stored energy combined power generating system is carried out, and therefore references are provided for the operation and the scheduling of the wind energy-solar photovoltaic energy-stored energy combined power generating system.

The invention, which belongs to the technical field of air quality prediction, relates to a forecasting method for village and town-level atmospheric pollution traceability. The method comprises the following steps: obtaining regional topographic data; manufacturing a town district and county geographic information file according to the regional topographic data; gridding the regional topographicdata and assimilating the regional topographic data to a mesoscale meteorological model; obtaining meteorological data and performing numerical simulation through a mesoscale meteorological model to obtain a meteorological field; then selecting a traceability point location, and calculating to obtain a pollution gas mass corresponding to the traceability point location according to the meteorological field and a Lagrange model; and carrying out traceability prediction on the polluted gas mass at the traceability point location according to the town district and county geographic information file. The method overcomes a defect that the village and town atmospheric pollution traceability cannot be effectively forecasted in time in the prior art, the forecasting method of the village and town-level atmospheric pollution traceability is provided, the forecasting of the atmospheric pollution traceability can be timely and effectively realized, and accuracy of the atmospheric pollution traceability forecasting can be improved.

The invention discloses a regional carbon flux estimation method based on remote sensing data. A mesoscale meteorological model (WRF) is used to output results, to provide spatial information within atarget region range and required meteorological field data for a vegetation photosynthetic respiration model (VPRM). High-precision vegetation type data (SYNMAP with a resolution of 1 km) is extracted, to classify land use types in a target area; an enhanced vegetation index (EVI) and a land surface water index (LSWI) are obtained by inversion of medium-high-resolution remote sensing data (MODIS09A1); parameters such as the EVI and the LSWI are placed in a target area grid by a spatial difference method; for different regional characteristics, more than one year of historical observation datais used, and these parameters are optimized by using a light response equation (Michaelis-Menten); and finally, based on the data, the carbon flux calculation is performed on the target area using the VPRM model.

The invention relates to a method for calculating high-precision Chinese offshore sea wave characteristic distribution. According to the method, a meteorological model WRF, a large-area sea wave modelwavewatch 3 and a sea wave model swan used in the offshore area of China are combined, and a multi-year historical sea wave characteristic data product with the spatial resolution of 0.04 degree * 0.04 degree can be calculated. As the China offshore area is divided into the East China sea area and the South China sea area by considering the monsoon influence area and the wave propagation characteristics during model establishment. The western pacific ocean is prevented from being brought into a mode range, and computing resources are prevented from being consumed. Due to the fact that the twosea areas have the overlapping area, the overlapping area has two calculation results, a weighted average method is used, the calculation results of the two overlapping areas are integrated, and thewhole set of data has spatial continuity.

The present invention relates to a middle micro-scale power grid wind damage early warning method through combination of remote sensing landform information. The method takes a forecast field formed by WRF as an initial condition, employs a CALMET meteorological model to perform refinement diagnosis of the wind field and downscaling calculation, and leads in remote sensing landform information data with higher resolution to obtain the forecast with higher resolution.

The invention discloses a resource scheduling method of a power distribution system in extreme natural disaster weather, the power distribution system comprises a power distribution network and a producer and eliminator cluster, the power distribution network comprises a plurality of nodes, the producer and eliminator cluster is connected with the power distribution network through at least one node, and a mobile power generation vehicle is also arranged in the power distribution system. The method comprises the following steps: generating an objective function for the operation cost of the power distribution system in extreme natural disaster weather; constructing a meteorological model about extreme natural disaster weather; based on the meteorological model, constructing a damage modelof the extreme natural disaster weather to the power distribution system; in combination with the damage model, constructing an uncertainty model of faults of the power distribution system under the influence of extreme natural disaster weather; setting constraint conditions for the mobile power generation vehicle and loads of lines and nodes in the power distribution network; based on the constraint condition and the uncertainty model, solving the target function to obtain a solving result; and scheduling resources in the power distribution system according to a solving result.

The invention discloses a method and a system for predicting environmental meteorological data of a power transmission line. The invention relates to the technical field of meteorological model prediction. The technical problems that a traditional weather prediction method is poor in anti-noise capability and prone to data interference are solved. The method comprises steps of collecting environmental meteorological data of a power transmission line and weather forecast data of corresponding time; dividing the data into a training set and a test set; putting the training set into a TCN model combined with a weighted channel for training to obtain a weather prediction model; and then testing the meteorological prediction model by using the test set so as to adjust the hyper-parameter thetaof the meteorological prediction model, and then repeating model training until the meteorological prediction model converges or reaches the maximum number of iterations to obtain a final prediction model. The final prediction model obtained through the method is high in anti-noise capacity and not prone to being interfered by abnormal data, and finally obtained prediction data are more accurate compared with an existing model.

The invention discloses a medium-scale atmospheric photochemical pollution simulation prediction algorithm increasing a meteorological model interface. A meteorological model interface module is addedbased on a CALGRID chemical model, MM5 and WRF level Arakawa B and C grid point meteorological data are interpolated into an Arakawa A grid point of a CALGRID, meteorological data of MM5 and WRF vertical sigma terrain following coordinate systems are interpolated into a Z terrain following coordinate system of the CALGRID, characteristic parameters of an underlying surface are acquired from an external data set according to the type of the underlying surface outputted by a meteorological model, and boundary layer meteorological parameters such as PGT (page table) stability classification, friction velocity, convection rate scale and Monin-Obukhov length needed by the CALGRID model are acquired by prediction field diagnosis in the meteorological model. The CALGRID model is successfully connected with MM5, WRF and TAPM output meteorological fields.

The invention discloses a flood control scheduling method based on digital twin and the method comprises the following steps: S1, constructing a digital twin body of a flood control scheduling system; S2, tracking and updating the digital twin body of the flood control dispatching system to obtain the real-time and synchronous digital twin body of the flood control dispatching system; and S3, based on the digital twin body of the real-time synchronous flood control scheduling system, carrying out meteorological and hydrological ensemble forecasting by using the meteorological model and the hydrological models, predicting the flood control scheduling process of the target reservoir in the next week, analyzing, studying and judging the flood control situation according to the prediction result, and providing an adjustment scheme of the current reservoir scheduling rule. The invention has the advantages that the defects that an existing flood control dispatching method cannot comprehensively reflect real-time information of flood control dispatching, the effective forecasting period of meteorological and hydrological forecasting is short and forecasting precision is not high are overcome, flood control dispatching process information can be accurately provided, flood control risks can be dynamically evaluated, and flood disaster defense work can be smoothly carried out.

The invention belongs to the technical field of atmospheric particulate collection and analysis, and discloses an atmospheric particulate collection and analysis device and a collection and analysis method thereof. The collection and analysis method of the atmospheric particulate collection and analysis device comprises the steps: atmospheric particulate concentration data and images are collected, and atmospheric particulate images are recognized; the collected concentration data are corrected, compared and analyzed; and the source of atmospheric particulates is traced, and atmospheric particulate data are stored and displayed. By establishing the correction model, the data of the monitoring station can be directly corrected, so that the accuracy of the atmospheric particulate mass concentration data is improved; a source list-meteorological model-particle diffusion model technology is adopted to analyze atmospheric particulate pollution sources, and a pollution source area identification model is established; historical and future particulate matter pollution sources can be traced, the traceability result is accurate, the targeting performance is high, and the supporting performance specified by the prevention and control policy is particularly high.

The invention discloses a wind power plant extended photovoltaic multi-objective optimization method by considering boost main transformer capacity, which improves an independent wind-solar meteorological model, considers the correlation between wind speed and solar radiation intensity changes, and converts meteorological data into power generation output data. A multi-objective optimization modelby taking the field area and the boost main transformer capacity as constraint conditions is constructed, and a multi-objective optimization model by taking the maximum boost main transformer utilization rate, the minimum power variable coefficient and the minimum clean energy waste rate as objective functions is constructed; and, long-term meteorological data of a researched area is obtained through simulation by taking hours as a time scale based on a Monte Carlo method, a Pareto optimal solution set is solved by adopting a multi-target particle swarm algorithm, and the influence of expansion of the boost main transformer capacity on a final scheme is considered.

The invention discloses a wind power forecasting method considering the operation condition of a wind turbine generator system, which comprises the following steps of: acquiring wind farm basic data,historical data and forecasting day data; normalizing the historical meteorological data of the wind farm to form a meteorological model vector initial training sample library; the meteorological model vector Ek of the wind farm at the kth time of the forecast day being normalized and recorded as Fk; the initial training sample library of meteorological model vector being screened; constructing BPNeural Network Power Forecasting Model Final Training Sample lambda k; training a BP Neural Network Power Forecasting Model with a Final Training Sample; Fk being inputted to the trained model, and the power prediction value Pk at the kth time of the prediction day being obtained. The problems of inaccurate wind power prediction and low precision caused by different geo-meteorological conditionsof wind turbines in mountainous wind farms on the plateau are solved.

The invention discloses a power transmission channel control method. The method comprises the following steps that laser point cloud data and cruise image data of a power transmission channel and video data shot by video equipment installed on the power transmission tower of the power transmission channel are collected, the three-dimensional model of the power transmission channel is modeled on the basis of a laser point cloud data line, and the three-dimensional model comprises a meteorological model established on the basis of meteorological data, operation and check data is input to the three-dimensional model for data storage, fusion, computing and analysis, wherein the three-dimensional model achieves transmission video image active early warning based on cruise image data and video data, and the three-dimensional model dynamically analyzes and calculates sag, windage yaw and tower stress based on laser point cloud data and the cruise image data.