32 results about "Climate pattern" patented technology

The invention discloses a cloud condensation nucleus number concentration vertical profile inversion method based on a multi-wavelength laser radar. The method comprises the steps: adopting the multi-wavelength laser radar to detect aerosol optical parameters; correcting the influence of the relative humidity on aerosol optical parameters by utilizing sounding; selecting an aerosol model with bimodal logarithmic normal distribution, and establishing a T-matrix scattering model considering the shape of aerosol particles; establishing a lookup table associated between aerosol optical parametersand spectral distribution parameters of different types of aerosols; based on aerosol optical parameters detected by a laser radar, obtaining corresponding spectral distribution parameter values through a lookup table, and obtaining the result of the cloud condensation tuberculosis number concentration vertical profile through critical activation radius calculation. The method has the advantages that the inversion accuracy of the cloud condensation tuberculosis number concentration vertical profile under different types of aerosols and different relative humidity conditions is improved, the automatic inversion of the cloud condensation tuberculosis number concentration vertical profile is realized, and more accurate observation data is provided for improving a parameterization scheme of the cloud condensation tuberculosis number concentration in a climate mode.

The invention discloses an evaluation method for evaluating water-induced landslide disaster loss caused by climate change decline, and belongs to the technical field of geological disaster prevention and control. According to the method, a physical process model is utilized, spatial heterogeneity of surface features of all grid points on a region is considered, and rainfall threshold values corresponding to all space grid points in a region range with spatial heterogeneity are obtained; the method comprises the following steps of: selecting a landslide model, optimizing a climate mode by combining historical and climate mode data, simulating an easily-occurring area and a possibly-rushing-out and influence area of the landslide by utilizing a model, and better matching an influence range simulated by utilizing the method with disaster loss lattice point data. The problem that the climate change scene and the landslide influence in landslide disaster assessment are difficult to assess is solved.

The invention discloses a method for calculating an optimal climate mode to simulate tropical cyclone activity performance. The method comprises the following steps: collecting related information, and calculating two-dimensional field distribution of tropical cyclone path density, a path density simulation value, a path type simulation value, a monthly change simulation value, a comprehensive simulation performance value and global comprehensive simulation performance values of a plurality of climate modes; sorting the comprehensive simulation performance values, and finally obtaining an optimal mode for simulating tropical cyclone activity in multiple climate modes. According to the invention, the tropical cyclonic activity simulation capabilities of a plurality of climate modes are quantitatively compared; based on the multi-aspect characteristics of the path and the frequency of the tropical cyclone, the influence of the simulation capability of the mode in different sea areas on the total simulation capability in the global range is combined, and the sorting of quantitative values can be given, so the performance value result is more objective and real, and the advantages anddisadvantages of the weather mode on the tropical cyclone activity simulation performance can be more intuitively expressed.

The invention provides a flood disaster social economic exposure degree evaluation method based on a climate mode set. The method comprises the steps: collecting hydrological, meteorological and underlying surface data of a research region, calibrating a watershed distributed hydrological model, and extracting the output data of a global climate mode; performing deviation correction on the output data of the global climate mode by adopting a multivariable deviation correction method to obtain a corrected global climate mode meteorological series; using the corrected global climate mode meteorological series to drive the distributed hydrological model and the hydrodynamic model to simulate the river submerging depth under the climate change scene; and evaluating the population and GDP exposure degree of the flood disaster under the influence of the climate change based on the simulation result of the step 3 by considering the dynamic population sharing the social economic path and the GDP scene. According to the method, the influence of the flood events on the social economic system under various climate change scenes is evaluated, and the method has important scientific significance on flood risk prediction and loss evaluation in the future.

The invention discloses a power grid galloping long-term prediction method and system based on climate dynamic downscaling. The power grid galloping long-term prediction method comprises the steps: selecting a global climate mode, carrying out the prediction of a monthly average meteorological field of N months in the future, and outputting meteorological data; selecting a regional climate mode, dividing a to-be-predicted region into grids, carrying out integration with a meteorological field of meteorological data at the prediction starting moment as an initial field, wherein the integrationduration is N months; outputting the integrated meteorological elements day by day in the regional climate mode, judging whether the meteorological elements output day by day of the grid meet a dancing day model or not, and judging the date meeting the dancing day model as the dancing day of the grid; and counting the to-be-predicted time within N months to obtain the total number of dancing dayson each grid, and drawing a contour map on the to-be-predicted area. The power grid galloping long-term prediction method is good in universality and can be suitable for calculation of long-term prediction of power grid galloping in different regions.

Embodiments relate to a method including assigning a relative or absolute per output unit weighting factor using a mathematical formulas based on individual and/or total sample population carbon sourcing.

The invention relates to a North Pacific Ocean sea surface salinity interannual modal identification method and system. The method comprises the following steps: acquiring CMIP6 climate mode data of a plurality of modes; obtaining an ORAS4 reanalysis data set of the European mid-term weather forecast center as comparison reference data; two empirical orthogonal function modes EOF1 and EOF2 of the NPSDV are calculated by comparing reference data, the EOF1 is a dipole mode, and the EOF2 is a monopole mode; two empirical orthogonal function modes EOF1'and EOF2 'of the NPSDV are calculated through the CMIP6 climate mode data of all modes, and the modes of the EOF1' and the EOF2 'are recognized according to the space correlation coefficient of the EOF1 and the EOF1', the space correlation coefficient R12 of the EOF1 and the EOF2 ', the space correlation coefficient R21 of the EOF2 and the EOF1' and the space correlation coefficient R22 of the EOF2 and the EOF2 '.

The invention provides a lake water-gas interface carbon dioxide exchange capacity assessment method and system, and the method comprises the steps: obtaining lakebed elevation data and a plurality of driving data, inputting the lakebed elevation data and the plurality of driving data into a preset surface water-underground water coupling simulation model, and carrying out the calculation to obtain a lake water surface area; acquiring multiple groups of climate mode data, inputting the multiple groups of climate mode data into a flux block formula, and calculating to obtain water-gas interface carbon dioxide flux; and according to the lake water surface area and the water-gas interface carbon dioxide flux, calculating to obtain the lake water-gas interface carbon dioxide exchange capacity. According to the method, the physical distributed simulation and description of the lake are realized, each water balance item of the lake is comprehensively considered, the exchange capacity of the carbon dioxide on the water-gas interface of the lake is quantitatively evaluated through coupling with the climate mode, and compared with the traditional method, the method has the characteristics of low investment, high precision and strong physical mechanism.

The invention discloses a method for correcting rainfall deviation based on the idea of ​​segmentation, aiming at improving the rainfall simulation accuracy of a series of rainfall models such as climate model, downscale model and rainfall generation model. The method includes: 1) dividing the measured rainfall sequence into three parts: minimum value, normal value and maximum value based on the quantile of the measured rainfall sequence; 2) dividing the simulated rainfall sequence into three parts based on the quantile of the simulated rainfall sequence It is also divided into three parts: minimum value, normal value and maximum value; 3) based on the three-segment data of the measured rainfall sequence, the deviation correction is performed on the three-segment data of the simulated rainfall sequence; 4) a newly proposed evaluation index is adopted , to effectively evaluate the effect of rainfall bias correction. The beneficial effects of the present invention are: effectively eliminating the error between the simulated rainfall of the rainfall model and the actual measured rainfall, improving the rainfall simulation accuracy of the rainfall model; laying a solid foundation for the correction of the deviation of the rainfall model's future prediction of rainfall, and improving the reliability of its prediction sex.

The invention provides an air-land-reservoir-water four-dimensional coupled medium and long-term runoff forecasting method. A drainage basin air-land-reservoir-water calculation scheme based on a climate mode, a series-connection two-parameter water balance model, a storage capacity difference model and an incoming water synthesis model is established; a gas-land coupler, a land-reservoir coupler and a reservoir water coupler are established respectively, and through intelligent correction, a state judgment machine, uniform distribution and other methods, climate mode grid point output is converted into partition input of two parameter models, flow output of the two parameter models is converted into water level input of a reservoir model, and water storage output of the reservoir model is converted into influence flow input of an incoming water model; and coupling the models by utilizing a coupler, and establishing a medium-and-long-term runoff coupling forecasting model to obtain an actual flow forecast value. By means of the method, ten-day-month-season scale runoff forecasting can be achieved, the influence of reservoir regulation and storage on runoff forecasting is considered, the method is high in precision compared with a common method, and water balance can be guaranteed.

The invention discloses a climate mode evaluation and deviation correction method based on information entropy, and the method comprises the following steps: selecting a climate evaluation result anda climate measurement result of each climate model according to the actual demands; calculating information entropy and mutual information of each climate model and the measurement result; obtaining aVI image and an RVI image; evaluating the advantages and disadvantages of the climate model; n climate evaluation models with good evaluation results are selected to construct a multi-mode ensemble forecasting system; and performing result correction by using a least square method. According to the method, the output data of the multiple climate modes are used as independent variables, the deviation correction model of the output data of the multiple climate modes is constructed, evaluation results are further corrected while climate mode evaluation is achieved, and accurate prediction of future climate scenes is facilitated.

The invention discloses a quantitative detection and attribution method for the influence of artificial carbon emission on water circulation key variables, which comprises the following steps of: performing deviation correction on the water circulation key variables (evapotranspiration and rainfall) simulated by a CMIP6 climate mode by adopting a quantile increment mapping method so as to reduce the uncertainty of climate mode simulation; on the basis of observation constraints, multi-mode weighted average is adopted to integrate multi-mode simulation results, so that the simulation precision of the climate mode on water circulation is improved; based on the processed climate mode simulation result and an optimal fingerprint method, multivariable detection and attribution are carried out, and fingerprint signals of the influence of artificial greenhouse gas emission and aerosol emission on water circulation key variables are quantitatively identified; and finally, estimating a future water circulation space-time evolution rule by using the established deviation correction and multi-mode weighting relationship, and reducing uncertainty and errors of future estimation. According to the method, the influence of artificial carbon emission on key variables of water circulation can be quantitatively identified, and theoretical reference can be provided for double-carbon targets and climate change coping.

The invention discloses a sub-season-season-interannual scale integrated climate mode set prediction system. The system comprises an initialization module, a high-resolution climate mode module, a set prediction module and a prediction post-processing module. The initialization module is used for downloading, extracting and processing multi-source data including atmosphere, land surface, ocean and sea ice, and using external parameters for controlling and achieving preprocessing such as data selection, checking and horizontal and vertical interpolation of meteorological elements, and the initialization module is suitable for data preprocessing of operation in all climate modes. The high-resolution climate mode module is used for carrying out objective quantitative prediction on multi-circle coupling collaborative change of atmosphere, land surface, ocean and sea ice; the set prediction module is used for generating any number of set prediction sample members combined by physical parameter tendency random disturbance and an initial value time lag method. The invention provides the climate prediction with high resolution, high prediction accuracy and good controllability, and provides multi-time-scale and multi-space-scale climate prediction of atmosphere, land surface, ocean and sea ice.

The invention relates to a method, a storage medium and equipment for detecting a climatic mode index sequence mutation point. And reading observation sequence data, determining cut-off lengths and probability levels of climate modes, and calculating statistically significant difference values among different modes. And starting to cyclically search a sudden change point, if the value of a certain point is remarkably different from that of the previous climate mode, considering the point as a candidate point of climate mode sudden change, otherwise, moving to the next point. And after the candidate point is determined, calculating the mode conversion index of the point, if the index has a negative value, indicating that the mode mutation fails, and if the index has a positive value, indicating that the mutation succeeds, and formally determining the point as a mode mutation point. And taking the new mode as a reference mode, continuing the operation until the end of the observation sequence, and detecting all mode mutation points. The method solves the problem that the detection performance of the existing method is sharply reduced at the tail end of the sequence, and the climate mode transfer can be detected as early as possible and then the change of the amplitude along with time is monitored. The method is easy to operate, and a user can change input parameters according to requirements.