72 results about "Climatology" patented technology

The invention relates to the field of ocean data buoy data quality control, and discloses a buoy meteorological data restoration method based on a space-time double-attention neural network, and the method comprises the following steps: data collection and preprocessing; establishing a space-time double-attention neural network model, wherein the model comprises a time coding link, a space coding link and a feature fusion layer; model training: inputting the time features containing the target elements to be predicted into a time coding link, inputting the meteorological elements into a space coding link, and outputting the target elements at the moment to be predicted by the model; after model training, evaluating the model by using the test set; and predicting a vacancy value or an abnormal value in the multi-dimensional meteorological element data acquired in real time by using the model which is qualified in evaluation, so as to realize data restoration. According to the method disclosed by the invention, time and space constraints are effectively combined, and abnormal values and vacant values in the meteorological data are predicted and replaced, so that the meteorological data are repaired.

The invention relates to the technical field of data processing, and discloses a numerical simulation method for a synergistic effect of an urban heat island and high-temperature heat waves. The method comprises the following steps: collecting urban building form data to construct a data set, and combining remote sensing data to carry out local climate zoning; extracting a high-temperature heat wave process and performing grading by utilizing machine learning; analyzing the urban heat island intensity time sequence change based on the remote sensing data; constructing an urban canopy mode coupling hydrology and an artificial heat source; and inputting different levels of heat wave data to simulate a synergistic effect. The technical problem that the urban heat island effect and high-temperature heat wave synergistic effect mechanism cannot be accurately simulated in the prior art is solved, and the numerical simulation method for quantitatively evaluating the urban heat island intensity amplification coefficient under the condition of different grades of high-temperature heat waves is established.

The invention relates to a multi-modal meteorological data downscaling generation method and device and computer equipment. The method comprises the following steps: acquiring topographic data and meteorological data in a to-be-measured area; inputting the topographic data and the meteorological data into a pre-trained deep learning model, carrying out feature coding on the topographic data and the meteorological data through the deep learning model to obtain a topographic feature vector and a meteorological feature vector, carrying out feature interaction on the topographic feature vector and the meteorological feature vector to obtain interaction features, and carrying out feature extraction on the interaction features; and carrying out downscaling decoding on the interaction features to obtain downscaling meteorological data. By adopting the method, the downscaling generation efficiency and the physical rationality of the meteorological data can be considered.

The invention provides a data model dual-drive-based water pollution prediction method and device, and relates to the technical field of water pollution monitoring, and the method comprises the steps: obtaining multi-source information reflecting an incidence relation between a pollution source position and water quality abnormity; training a preset random forest regression model by using the multi-source information and a particle swarm optimization algorithm to obtain a target random forest regression model, inputting real-time data of which the type is the same as that of the multi-source information into the target random forest regression model, and determining pollution source position information; constructing a one-dimensional pollutant diffusion model based on the spatial-temporal characteristic information, and expanding the one-dimensional pollutant diffusion model to a two-dimensional cellular model in combination with a cellular automaton simulation method; and inputting pollution source position information and environmental influence information into the two-dimensional cellular model to generate a water pollution diffusion prediction result. Through comprehensive application of the algorithm and the model, the accuracy and the real-time performance of water pollution prediction are improved.

The invention relates to a landslide meteorological early warning method coupling machine learning and a rainfall early warning index, which comprises the following steps: taking a frequency ratio of screened landslide evaluation factors in different grading intervals as input, taking a landslide occurrence state as output, adopting a machine learning model to carry out landslide susceptibility modeling, and establishing a landslide susceptibility partition map; modeling a quantitative relation between the rainfall scene and the rainfall early warning index; calculating early effective rainfall and induced event rainfall in different return periods by adopting Gumbel distribution based on historical rainfall statistical data of the to-be-researched area, determining a minimum rainfall early warning index and a maximum rainfall early warning index, and obtaining a rainfall early warning index distribution diagram of the to-be-researched area; and carrying out coupling superposition on the landslide susceptibility partition map and the rainfall early warning index distribution map to obtain a landslide risk meteorological early warning map of the to-be-researched area. According to the method, a scientific basis is provided for regional scale landslide early warning, and the problem of splitting of a traditional model in data utilization and mechanism interpretation is solved.

The invention discloses a method for analyzing influence of climate change and human activity on space-time evolution of water resources. The method comprises the following steps: acquiring meteorological information, hydrological information, land utilization information, soil information, social economic information and water resource information of a to-be-detected area; performing trend analysis on the water resource information to obtain a space-time evolution rule of the water resource information; performing attribution analysis on the time-space evolution rule to obtain influence factors of the time-space evolution of the water resource; obtaining the correlation degree of the influence factors and the space-time evolution rule, and completing the analysis of the climate change and human activity on the space-time evolution of the water resource. According to the method, the influence factors of water resource evolution of the to-be-detected area are researched through the multivariate statistical stepwise regression analysis model, the multicollinearity between the related influence factors of climate change and human activity is reduced through the characteristics of stepwise regression analysis, the calculation accuracy is improved, and the sustainable development of water resources is promoted.

The invention belongs to the technical field of point cloud data noise reduction, and particularly discloses a point cloud data noise reduction method and system, a terminal and a medium. Comprising the steps of obtaining original point cloud data of a target scene; for any point in the point cloud, calculating the local point cloud density based on the spatial distance from the point to a plurality of nearest neighbor points in the neighborhood of the point, and determining the neighborhood search radius of the point according to the local point cloud density; constructing a neighborhood point set according to the neighborhood search radius, and extracting local structure consistency features in the neighborhood point set; based on the local structure consistency feature, generating a judgment condition for judging a noise point, and judging whether the target point is the noise point or not according to the judgment condition; and filtering the points which are judged to be noise points from the point cloud data to obtain the point cloud data after noise reduction. Through adaptive neighborhood construction, local structure consistency feature modeling and dynamic generation of noise discrimination conditions, robust recognition of point cloud noise points under complex weather conditions such as rain and snow is realized, and improvement of the overall quality of point cloud data is facilitated.

The invention provides an atmospheric brown carbon aerosol light absorption characteristic determination method and electronic equipment, and the method comprises the steps: obtaining aerosol observation data and organic aerosol mass spectrum data; determining a brown carbon absorption coefficient corresponding to each wavelength according to the aerosol observation data; determining a plurality of organic aerosol sources and aerosol concentrations corresponding to the organic aerosol sources according to the organic aerosol mass spectrum data; according to the brown carbon absorption coefficient corresponding to each wavelength and the aerosol concentration corresponding to each organic aerosol source, training to obtain a plurality of brown carbon source decision models, and according to each brown carbon source decision model, determining at least one brown carbon source corresponding to each wavelength; and determining the absorption spectrum of each brown carbon source according to each brown carbon source corresponding to each wavelength. According to the method, accurate inversion of the absorption spectrum of each brown carbon source can be realized, cross-scale correlation from chemical components to climate effects is realized, and the accuracy and scientificity of brown carbon climate influence assessment are improved.

The embodiment of the invention provides a compressed air energy storage system and method based on goaf heat storage regulation and control. The system is applied to the technical field of compressed air energy storage and comprises a heat storage goaf module, an energy storage sub-module and an energy release sub-module. The method comprises the following steps: in a power consumption trough period, an energy storage sub-module operates to compress ambient air to a high-temperature and high-pressure state; in the power utilization peak period, the energy release sub-module operates, heat energy is transmitted to high-pressure air which is pumped out of the air storage shaft and flows through the energy storage heater, and high-temperature and high-pressure air is formed to drive the turbo expander to generate electricity. After the turbo expander completes power generation, exhausted low-temperature and low-pressure air is introduced into a multi-stage cold energy exchange pipe network buried in the goaf, and an energy closed loop is achieved. In this way, the technical problems that in the prior art, due to inherent intermittency and uncertainty of renewable energy sources, grid-connected consumption is difficult, wind and light abandoning is serious every year, and the peak-valley difference of a power grid tends to be gradually increased can be solved.

The invention discloses an accumulated snow depth inversion method and device based on multi-source data fusion, and the method comprises the steps: obtaining first snow depth data through a snow depth product, obtaining second snow depth data actually measured by a site, and obtaining independent variable data; the independent variable data comprises brightness temperature data, ground surface coverage data, forest coverage rate data, altitude data, latitude and longitude data, ground surface classification data and geographic coordinates; fusing the first snow depth data and the second snow depth data to obtain fused snow depth data; combining different independent variable combinations, and fusing the snow depth data as a data set to train a random forest model to obtain a plurality of snow depth prediction initial models; and evaluating the prediction precision of the plurality of snow depth prediction initial models, and taking the model with the highest prediction precision as a target snow depth prediction model. According to the method, the snow depth product and the site actually measured snow depth are fused, and the fused high-resolution snow depth data are obtained to serve as the target variable of the random forest algorithm, so that the model precision is improved.

The present application belongs to the technical field of urban meteorological data processing and spatial information calculation, and particularly relates to a method and device for constructing urban meteorological gridded data based on spatial interpolation. The method comprises meteorological data clustering, partition optimization by using a target function during clustering, partition interpolation, spatial division and processing of regions according to the clustering results of meteorological data, statistics of the number of base stations for each region, determination of the type of a region based on the spatial distribution density of the base stations, determination of a global variation function and a regional variation function for each region, calculation of the estimated value of an interpolation point by using a corresponding Kriging interpolation method based on the variation function for different region types, interpolation of points near the boundary lines of different regions by using the meteorological data of the base stations of the regions involved, and weighting to obtain the final result. Finally, the construction of urban meteorological gridded data based on spatial interpolation is realized.

The invention provides an atmospheric pollution driving factor decoupling attribution method and device. The method aims to solve the problems that in the prior art, atmospheric pollution prediction neglects a space process, consequently, precision is insufficient, and static background and dynamic meteorological driving factor contribution cannot be quantitatively decoupled. Comprising the following steps: training a prediction model with spatial information perception capability based on multi-modal input features, and learning a spatial dependency relationship of pollutant concentration and outputting a prediction value by extracting spatial feature data containing a target position and neighborhood information of the target position as input by the model; and calculating the contribution value of each input feature by applying an attribution algorithm, and grouping and aggregating the contribution values based on preset feature group division to obtain the aggregated contribution amount of the feature group, thereby realizing the quantitative decoupling of the driving factor. According to the method, contribution of driving force of different time scales is quantitatively distinguished, so that global high-resolution accurate prediction is realized, and mechanism analysis and decision support is provided for scientific pollution control.

1. Name of the product in this design: Weather Station. 2. Purpose of this design: For meteorological observation and the collection and transmission of meteorological data. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The utility model is applicable to the technical field of early-warning regulation and control devices, and provides an early-warning regulation and control device for preventing grapes from being frozen in early spring, which comprises a heat preservation bin and a fan, one end of the fan communicates with the heat preservation bin, and the other end of the fan communicates with a heat conduction main pipe. The monitoring mechanism is arranged beside the heat conduction main pipe; according to the utility model, the rapid transmission and wide distribution of heat are realized, and the environmental conditions in the greenhouse are monitored in real time, so that the utilization efficiency of the heat is obviously improved, and the heat utilization rate of the greenhouse is improved; the system ensures that grapes grow in a relatively warm and stable environment, effectively prevents freeze injury in early spring, can monitor temperature and humidity data in a greenhouse in real time, provides comprehensive environment information for planters, and gives an alarm in time to remind the planters to take necessary measures when abnormal conditions are monitored, so that the planting efficiency is improved. Therefore, healthy growth and stable yield of grapes are comprehensively guaranteed.

The invention discloses a sky radiation coupling water chilling unit high-proportion renewable cold supply system and a control method, and belongs to the technical field of building air conditioner cold source systems, and the sky radiation coupling water chilling unit high-proportion renewable cold supply system comprises a sky radiation refrigerator, a water-cooled water chilling unit, a cold storage water tank, a water pump, an electric valve, a controller and a radiation ceiling tail end. According to the system, five working modes are dynamically switched, and efficient coupling utilization of a sky radiation cold source in multiple links of cold storage, cold supply and condenser heat dissipation is achieved; at night, a radiation refrigerator is used for preparing cold energy and storing the cold energy in a cold storage water tank; when a cold load exists in the daytime room and the temperature of the water tank is lower than the designed water supply temperature of the radiation ceiling, the water tank directly supplies cold and continues to accumulate cold; when the refrigerating efficiency of the radiation refrigerator is reduced, only the water tank supplies cold; when the temperature of the water tank rises to be unable to supply cold, the water chilling unit is started to supply cold, and the radiation refrigerator is utilized to dissipate heat for the condenser; and when the refrigerating efficiency of the radiation refrigerator is reduced, the water tank is switched to dissipate heat of the condenser.

The application discloses a kind of short-acting rain prediction methods of fusing satellite cloud picture and radar echo, it is related to short-acting rain weather prediction field, the specific steps of this method are as follows: synchronous acquisition preprocessed satellite cloud picture and radar echo data, respectively with symmetric time series deep learning architecture extraction feature, generate dimension alignment's rainfall probability discrete distribution;Unified distribution is obtained by double mode confrontation fusion;Probability confidence calibration is carried out, and the distribution of confidence interval is generated;According to magnitude interval mapping, the output different magnitude rainfall probability and confidence interval are calculated, and the grid point prediction is completed;The application adopts symmetric time series deep learning architecture to process multi-modal data, realizes macroscopic and microscopic collaborative representation, improves the completeness and consistency of rainfall probability generation;Combined with historical sample calibration deviation, the original logic and features are retained, and the standardized grid point prediction results are output;Optimize each link in whole process, so that the prediction result is more in line with the actual, and the business adaptability and application value are improved.

This application pertains to a meteorological data processing method. Addressing the technical problems of existing generative adversarial networks (GANs) in downscaling applications, such as unstable training processes and overly smooth high-resolution data leading to vanishing or exploding gradients and an inability to accurately represent local meteorological conditions, this application provides a meteorological data downscaling method, system, electronic device, and readable storage medium. First, statistical distribution bias correction is performed on the original low-resolution meteorological data to be downscaled, resolving the issue of significant discrepancies between the original data and measured data, thus improving overall downscaling accuracy. This application utilizes a Wasserstein GAN to solve key problems such as unstable training, pattern collapse, and vanishing or exploding gradients. Furthermore, during training, the Wasserstein GAN in this application aims to minimize the overall loss, incorporating perceptual loss to address the problem of overly smooth output results that fail to reflect local meteorological conditions.

The application discloses a kind of river two-dimensional flow field drawing methods based on triangular mesh, comprising the following steps: first, the center point of each triangular net is reconstructed as vertex, so that each vertex has flow field data;Then calculate the length and width of the outer package rectangle of grid range, set grid side length, generate grid point set;Then generate trace with grid point as seed point, by calculating flow field vector, azimuth and predicted point position, dynamically adjust the trace direction and step length;Trace buffer zone is calculated using angle bisector method to avoid trace intersection;Repeat the above steps until all points complete trace generation.The application can make the trace density change with the grid density, evenly distributed while reflecting the key attention area flow field situation, and the trace does not intersect, node spacing dynamically adjusts, expresses flow field details with least data, effectively optimizes data volume and calculation accuracy, provides efficient tool for river flow field research.

The application discloses a water area division method and device of a map, an electronic device and a computer readable storage medium. The application obtains a water area grid map of a target map, the water area grid map comprising at least one water area region of the target map, the water area region being composed of a plurality of grids; determines an edge distance between a grid vertex of a grid and a region edge of the water area region; determines a vertex movement parameter of an edge grid vertex based on the edge distance between the grid vertex and the region edge; controls the edge grid vertex to move to the center of the water area region based on the vertex movement parameter of the edge grid vertex, until it is determined that the edge grid vertex is in the center range of the water area region, and determines the movement distance of the edge grid vertex; and determines the water area region type corresponding to the edge grid vertex based on the movement distance of the edge grid vertex, so that the accuracy of water area division in the map can be improved.

The invention relates to the technical field of three-dimensional modeling, in particular to a numerical analysis-based complex-form karst cave distribution simulation method, and solves the technical problem of inaccurate model construction caused by elimination of irregular boundary forms in a karst cave during dimensionality reduction of karst cave point cloud data in the prior art. The method comprises the following steps: acquiring point cloud data of a karst cave; dividing the point cloud data into a plurality of local space regions, and determining a complexity coefficient based on shape features and edge features of the point cloud data in each local space region; the complexity coefficient is used for representing the form complexity of the local space region; performing adaptive dimension reduction processing on each local space region according to the complexity coefficient to obtain point cloud data of each local space region after dimension reduction; and constructing a three-dimensional distribution model of the karst cave based on the point cloud data after dimension reduction of the plurality of local space regions.

A hydronic system includes a control unit configured to monitor a volume of water and an outlet temperature using flowmeters and temperature sensors, respectively. The control unit is configured to operate a heat pump to recharge a storage tank when a respective predetermined limit is reached for the volume of water or the outlet temperature. The control unit is configured to determine a time period based on the volume, the outlet temperature, and an operation cycle that may be on-peak or off-peak. The operation cycle is determined using day-ahead hourly prices, a temperature forecast, or a greenhouse gas emissions forecast. During an on-peak operation cycles, the control unit is configured to operate the heat pump unit instantaneously within the determined time-period. In an off-peak operation cycle, the control unit is configured to operate the heat pump unit selectively based on a cost and a schedule of a power source.

This invention relates to a method for urban multi-granularity catchment area delineation based on high-precision 3D data, comprising the following steps: acquiring high-precision 3D urban data using laser point cloud technology; classifying the point cloud data using a progressive triangulation filtering method to extract vector boundary lines of building, road, and overpass elements; performing hydrological analysis based on a high-precision DEM to extract catchment areas and merge them with boundary lines to construct a macroscopic boundary layer; dynamically dividing irregular grids using a quadtree grid subdivision and merging mechanism to construct a detailed grid layer; dividing the detailed grid layer into runoff generation, runoff confluence, and runoff-confluence raster layers; integrating the macroscopic boundary layer and the detailed grid layer, assigning hydrological parameters to form a multi-granularity 3D urban catchment area delineation; and achieving efficient storage and rapid retrieval through object-oriented spatial data organization and GeoJSON storage. This invention improves the precision of catchment area delineation and the accuracy of dynamic simulation in complex urban environments.

The application discloses a rocky desertification rapid identification method and system, and the method comprises the following steps: inputting a ground surface image into a lightweight semantic segmentation model, and outputting bare rock area pixels, vegetation area pixels and other area pixels from the lightweight semantic segmentation model; determining a base rock exposure rate and a vegetation coverage degree according to the bare rock area pixels, the vegetation area pixels and the other area pixels; determining an interference intensity grade according to selection information; inputting a soil layer thickness measurement value, slope data, the base rock exposure rate, the vegetation coverage degree and the interference intensity grade into a multi-factor comprehensive evaluation model to calculate a rocky desertification comprehensive index; and calculating a rocky desertification grade according to a preset grade determination threshold and the rocky desertification comprehensive index, and displaying a calculation result. The application solves the problem that a single index cannot comprehensively reflect the rocky desertification degree, and unifies different factors into a comprehensive index, so that the evaluation result is scientific, the work efficiency of ground investigation is improved, and the work intensity of workers is reduced.

The present application belongs to the technical field of geochemistry, and particularly relates to the estimation of the carbon flux of the earth system, and especially relates to a method and system for estimating the carbon flux of the deep-time earth system. The method for estimating the carbon flux of the deep-time earth system provided by the present application solves the four defects in the traditional technology caused by the fixed carbon pool assumption, the neglect of the atmospheric / biosphere carbon content, the isotopic error, and the failure to consider the fractionation effect through dynamic carbon pool segmentation, the inclusion of multi-sphere isotopic composition, and the correction of fractionation effect. The high-precision and verifiable model framework not only improves the scientificity of the deep-time carbon cycle research, but also provides a key tool for analyzing the climate evolution mechanism in the geological history period and predicting the future climate change trend, and has important theoretical innovation and practical application value.

This invention specifically discloses a wind-solar-hydro-pumped storage joint control method based on mixed integer programming, belonging to the field of power grid dispatching technology. The method comprises the following steps: the power grid dispatching center predicts the regional load curve for the next day and arranges the output of the consortium; wind and solar power plants within the consortium generate wind and solar output prediction curves for the next day's 96-hour period; the consortium comprehensively considers electricity prices, pumped storage operating costs, and performance penalties to optimize the output scheme and declare its proportion of system load; a joint optimization model is established, setting constraints such as reservoir capacity, pumping, and power generation inequalities and equality conditions for pumped storage units; and mixed integer linear programming (MILP) is used to solve for and generate the optimal dispatch scheme. This method can effectively mitigate the uncertainties of wind and solar power, improve energy utilization, increase system output stability and power quality, and maximize the economic benefits of the consortium.

The application discloses a lunar soil water ice drilling process sample temperature rise simulation prediction method and system, belongs to the moon water ice detection and temperature field simulation technical field, wherein the method comprises the following steps: matching lunar soil characteristic parameters according to the polar lunar soil properties, and establishing a lunar soil water ice particle system according to the lunar soil characteristic parameters; acquiring the inner diameter, the outer diameter and the wall thickness of a drill rod, and the heat output and the heating power input of an instantaneous heat source, and inputting the EDEM simulation software to establish a drill theoretical temperature rise model; performing a single-tooth cutting simulation test based on the water ice particle system and the drill theoretical temperature rise model, and determining a heat source point and a heat generation energy distribution ratio; and integrating the lunar soil water ice particle system, the drill theoretical temperature rise model and the heat generation energy distribution ratio to establish a moon-land interaction discrete element temperature rise model. The method increases the simulation of heat transfer forms such as convection and thermal radiation, the established simulation model is closer to the actual situation, and then the simulation model can predict the temperature rise of the drill and the lunar soil water ice in the drilling process.

According to the evaporative data center condensation air conditioning system based on natural cooling, the utilization rate of a natural cold source is remarkably increased through vertical layout of the three stages of evaporative cooling units and dynamic coupling of refrigerants in combination with fuzzy PID control driven by environmental parameters; specifically, through space-time complementation of soil pre-cooling and photovoltaic spraying, the annual PUE is reduced to 1.15 or below, and compared with a traditional system, energy is saved by 37%; the pipeline complexity of the graded plate exchange and shared refrigerant loop is reduced, and the operation and maintenance cost is reduced by 25%; a wind speed compensation model and wet bulb temperature correction ensure that the cooling capacity is stable in a dry / low-wind-speed environment; a closed loop is formed by cooling capacity prediction and parameter self-correction, and the cooling capacity distribution deviation is controlled within + / -5%.

The application provides an air source heat pump array cold and wet island effect evaluation method and system, and belongs to the field of air source heat pump operation performance evaluation; the method comprises the following steps: obtaining the environment temperature and relative humidity of an air source heat pump array area, and determining the heating indoor and outdoor design temperature; obtaining the air source heat pump array heating load rate according to the environment temperature, the heating indoor design temperature and the heating outdoor design temperature; determining the minimum starting rate of the air source heat pump array according to the air source heat pump array heating load rate; calculating the cold island effect intensity and the wet island effect intensity based on the environment temperature, the relative humidity and the array minimum starting rate; dividing the interaction relationship area between the cold island effect intensity and the wet island effect intensity according to the relative humidity; calculating the cold and wet island effect heating performance loss according to the cold island effect intensity and the wet island effect intensity for different interaction areas, so that the air source heat pump array cold and wet island effect intensity and the heating performance loss evaluation are realized.

The application relates to the field of karst basin runoff simulation calculation, and particularly discloses a karst SWAT model runoff simulation method coupled with an early-stage precipitation index, which comprises the following steps: step one, establishing a SWAT model with the characteristics of a karst area, generating a land use map with the characteristics of the karst area and hydrological response units (HRUs) with the distribution characteristics of the karst and non-karst; step two, modifying the source code of the SWAT model to construct a K-SWAT model with the function of karst runoff generation and concentration; step three, embedding a normalized early-stage precipitation index (MIWAPI) in the K-SWAT model to construct a K-W-D-SWAT model with the function of identifying the effect of dry and wet events on the karst runoff generation and concentration process; and step four, optimizing the parameters of the SWAT model, the K-SWAT model and the K-W-D-SWAT model by using the SUFI-2 algorithm in the SWAT-CUP software, and evaluating the runoff simulation level of each model in the karst area. The karst SWAT model runoff simulation method coupled with the early-stage precipitation index is suitable for the simulation of the runoff process in the karst area with complex climate change, and can improve the simulation accuracy and rationality of the hydrological process in the karst area.

The application provides a method for determining the light absorption characteristics of atmospheric brown carbon aerosols and an electronic device, wherein the method comprises: obtaining aerosol observation data and organic aerosol mass spectrum data; determining the brown carbon absorption coefficient corresponding to each wavelength according to the aerosol observation data; determining a plurality of organic aerosol sources and the aerosol concentration corresponding to each organic aerosol source according to the organic aerosol mass spectrum data; training a plurality of brown carbon source decision models according to the brown carbon absorption coefficient corresponding to each wavelength and the aerosol concentration corresponding to each organic aerosol source, and determining at least one brown carbon source corresponding to each wavelength according to each brown carbon source decision model; and determining the absorption spectrum of each brown carbon source according to each brown carbon source corresponding to each wavelength. The application can accurately retrieve the absorption spectrum of each brown carbon source, realize the cross-scale correlation from chemical composition to climate effect, and improve the accuracy and scientificity of the evaluation of the climate impact of brown carbon.