32 results about "Climate pattern" patented technology

The present invention discloses a climate change prediction method and system for fitting various climate modes based on a modified BP neural network. The method comprises the following steps: collecting rainfall data that characterizes a climate change feature; performing downscaling processing on climate mode prediction grid data, so as to obtain a long series of data with the same resolution as measured data; performing average correction on a downscaled climate mode prediction series; establishing a modified BP neural network model and determining a network model structure; training and inspecting the established BP neural network model; and predicting a future climate spatial-temporal change using a model output. According to the method and system disclosed by the present invention, output / input data processing of the BP neural network is modified, and various climate modes are fit to predict the future climate change, so that reliability of the prediction result is increased, and the defects that the deviation of a single mode is relatively large during an assessment and that basin space nonuniformity is not considered during a multi-mode collection assessment and the like are made up.

The invention discloses an evaluation method for evaluating landslide disaster loss induced by climate change and falling water, and belongs to the technical field of geological disaster prevention and control. This method uses the physical process model, considers the spatial heterogeneity of the surface characteristics of each grid point in the region, and obtains the precipitation threshold corresponding to each spatial grid point in the region with spatial heterogeneity; combined with historical and climate model data, the optimal The climate model was established, and then the landslide-prone area and the possible rush-out and impact area were simulated by the model. The impact range simulated by this method can better match the disaster loss grid data, which solves the problem of climate in landslide disaster assessment. Change scenarios and landslide impacts are difficult to assess.

The invention discloses a staged design flood calculation method under the integrated climate model. By establishing the coupling model of GCM and VIC, the runoff process of the reservoir under the future climate change scenario is predicted, and the average value under the climate change scenario is obtained through the arithmetic mean method. The runoff process is analyzed by the probability change point method, and the main flood season and the non-main flood season are divided into main and non-main flood seasons. The calculation model of the most probable combination method for reservoir design flood peak volume is constructed through the Copula function, and the predicted runoff data of the reservoir under the future climate change scenario is used as Design the input of the flood peak combination method to calculate the model, and consider the combination of multi-variables with the same frequency and the most likely combination at the same time, and calculate the joint design value of the reservoir at different return period levels. The invention has a strong statistical basis and provides a new approach for the staged design flood calculation under the climate change scenario.

The present invention relates to a radiative transfer calculation method suitable for continuous changes in cloud microphysical properties. Based on a second-flow approximation scheme, the method includes the following steps: Step 1) Expressing the radiant flux with continuous changes in cloud microphysical properties as a constant term and a disturbance term and; step 2) calculate the first radiant flux according to the traditional second-flow radiative transfer equation, and set the first radiant flux as the constant item; step 3) use the perturbation method to combine the asymmetry factor g and the unit Substituting the parameterized form of the scattering albedo ω into the traditional two-flow radiation transfer intensity equation to form a non-uniformity-induced disturbance term equation group, and by solving the non-uniformity-induced disturbance term equation group, two micro-disturbance factors and the expression The second radiant flux; step 4) summing the first radiant flux and the second radiant flux to complete the solution of the radiant flux with continuously changing microphysical properties of the cloud. This method effectively solves the vertical inhomogeneity of optical properties inside clouds in climate models, thereby improving the accuracy of radiation calculations.

The invention discloses a subseasonal-seasonal-interannual scale integrated climate model ensemble prediction system, including an initialization module, a high-resolution climate model module, an ensemble prediction module and a post-prediction processing module. The initialization module is used for downloading, extracting and processing the included Multi-source data of the atmosphere, land surface, ocean, and sea ice, using external parameters to control and realize data selection, inspection, horizontal and vertical interpolation of meteorological elements and other pre-processing, suitable for data pre-processing of all climate model operations, high resolution The climate model module is used to objectively and quantitatively predict the coupled and coordinated changes of the atmosphere, land surface, ocean, and sea ice. The ensemble prediction module is used to generate any number of ensembles that combine random disturbances of physical parameters and initial value time lag methods. Predict sample membership. The invention provides a multi-time-scale and multi-space-scale climate prediction of the atmosphere, land surface, ocean and sea ice with high resolution, high prediction accuracy and good maneuverability.

The invention discloses a multi-climate model output result set correction method, and proposes a classification method of the climate model: for example, according to longitude and latitude, according to landform type, and the like. According to the grids divided into the research area, it is judged which one belongs to the classification; combined with the proposed multi-climate model output result set calculation formula, the parameters of the formula are obtained by fitting with the measured values, and finally the corrected predicted values ​​are obtained. This correction method makes full use of data information and comprehensively considers the combination of different classification climate models. Compared with the simulation results of the previous single-optimized climate model for grids, the simulated value is closer to the measured value and more in line with the actual situation.

The invention discloses a dimension reduction and correction model based on a spacial multi-correlation solution set algorithm. The processing method of the model comprises the steps of (1) obtainingdata, wherein the data includes a climate pattern grid data series Xt = (x1, t, x2, t, ..., xm, t) and actual measurement data series Yt= (y1, t, y2, t, ..., yn, t) of each site, m refers to the number of the grids, t refers to time and n refers to the number of the sites; (2) constructing the dimension reduction and correction model based on the spacial multi-correlation solution set algorithm: Y= B + AX + epsilon (epsilon - N (0, sigma 2)), wherein A and B are used for reflecting a related structural relationship between the grid data and the actual measurement data of the sites, and the sigma is a standardized independent random vector; (3) adopting a particle swarm optimization algorithm to figure out the solutions to the coefficient matrix A and the coefficient matrix B in an equation(1). The dimension reduction and correction model based on the spacial multi-correlation solution set algorithm has the advantage of increasing the simulation precision.

The invention discloses a short-term climate prediction method based on statistical downscaling technology, which includes performing singular value decomposition on my country's monthly average precipitation and large-scale predictors within the modeling fitting period, and extracting my country's monthly average precipitation and large-scale forecasting factors respectively. The main modes of the scale predictors are typically coupled with spatially heterogeneous correlation distribution spatial patterns and the corresponding principal component time series pairs; using stepwise regression analysis, the adaptive main modes of the monthly mean precipitation and large-scale predictors suitable for the forecast period are obtained. Modal typical coupled spatially heterogeneous correlation profiles and principal component time series pairs. The advantages are: integrated climate model and previous key factors, based on multiple processing methods such as EOF, SVD and multiple linear regression to extract the optimal coupling variation among multiple factors, developed multi-source information dynamic processing and extraction technology, and constructed optimal information Integrating self-adaptive downscaling technology to realize the gridded prediction of the monthly average precipitation in different regions of the country under the climatic conditions.

The present application discloses a method and system for simulating the growth process of ice clouds, including: constructing an ice cloud particle spectrum distribution database and a non-spherical ice cloud particle scattering database, the ice cloud particle spectrum distribution database contains ice cloud particle observation data, the non-spherical ice cloud particle The spherical ice cloud particle scattering database includes ice cloud particle scattering characteristic parameters; according to the ice cloud particle spectral distribution database and the non-spherical ice cloud particle scattering database, calculate the fitting relationship between the ice cloud optical characteristic parameters and the ice cloud macroscopic physical quantities, And determine the fitting coefficient, the ice cloud optical characteristic parameters include ice cloud extinction efficiency, ice cloud asymmetry factor and ice cloud single scattering albedo, the ice cloud macroscopic physical quantity includes ice cloud ice water content and ice cloud average effective Radius; applying the fitting coefficients to a radiative transfer model to simulate the growth process of the ice cloud. This application improves the accuracy of the expression of ice cloud optical characteristics in existing climate models, and can effectively invert the microphysical parameters of ice clouds on a global scale.

The present invention provides a method and system for assessing the amount of carbon dioxide exchange at the lake water-air interface, the method comprising: obtaining lake bottom elevation data and multiple driving data, and inputting the lake bottom elevation data and multiple driving data into preset surface water-ground water In the coupled simulation model, the water surface area of ​​the lake is calculated; multiple sets of climate model data are obtained, and multiple sets of climate model data are input into the flux block formula to calculate the carbon dioxide flux at the water-air interface; according to the lake water surface area and the water-air interface The carbon dioxide flux was calculated to obtain the carbon dioxide exchange volume at the lake water-air interface. This method realizes the simulation and description of the physical distribution of the lake, fully considers the water balance items of the lake, and through the coupling with the climate model, quantitatively evaluates the exchange of carbon dioxide at the water-air interface of the lake. Compared with the traditional method, it has more advantages It has the characteristics of low investment, high precision and strong physical mechanism.

The invention particularly relates to a distributed collaborative analysis system and method of massive climate pattern model output data. The system comprises a central server, a plurality of node servers, and at least one piece of Web front-end service equipment. The central server is used for storing global data information and node server information; the node servers are used for storing and managing node data information, performing task analysis scheduling management and data analysis processing; the Web front-end service equipment is used for user information maintenance, data information retrieval, task submission, analysis task status query and analysis result query and downloading. The data analysis work is finished at each node server, so that the data redundancy is reduced. The plurality of node servers are capable of collaboratively working, the contrastive analysis of the massive climate pattern model output data can be executed in a distributed manner, and an analysis result can be acquired on-line. Finally, the efficiency of the research work is greatly improved.