49 results about "Climate model" patented technology

Embodiments generally relate to methods of accurately predicting seasonal fluctuations in precipitation or other approximate functionals of a climate state space, such as the number of heating or cooling degree days in a season, maximum river flow rates, water table levels and the like. In one embodiment, a method for predicting climate comprises: deriving a climate attractor from a global climate model, wherein a tuning parameter for the climate attractor comprises a value of total energy for moving air and water on the earth's surface; estimating a predictive function for each of a plurality of computational cells within the global climate model; and predicting an approximate climate functional of interest for a given specific location utilizing a combination of the predictive functions from each of the plurality of computational cells geographically proximate the location, where at all stages, predictive functions are selected in part by comparison to historical data.

The invention discloses an analysis method of response of surface water quality to drought and flood events. The analysis method is characterized by comprising the following steps: step one, analyzing historical evolution and developing trend of drought and flood events; step two, building and calibrating an SWAT model; step three, calculating total nitrogen and total phosphorus; and step four, analyzing response of the surface water quality to the drought and flood events. Compared with the prior art, the analysis method is capable of screening typical representative months of drought events, flood events and drought and flood sudden turning events by combining indexes such as a standardized precipitation index, 24-hour precipitation amount and continuous non-rainy days and the like based on climate model forecasting results, the SWAT model and a statistic analysis method, comparing and analyzing the influence of drought and flood events to the water quality of the typical months and effectively analyzing a response relationship between the surface water quality change and the drought and flood events. The analysis method is especially applicable to analysis of the response of the surface water quality to the drought and flood events in the Hetao area.

The invention belongs to the technical field of water resource management, and particularly relates to a method for process adjustment and risk identification of operation of a water resource system of Internet of water. The method is characterized in that irrigation water demand information is provided for a regional multi-water-resource optimization allocation model based on real-time perceptual information, and real-time water demand is determined by a real-time water distribution decision-making model; a medium and long term runoff forecasting model is used for forecasting the runoff volume of a drainage basin in the future month by month; a downscaling climate model is used for providing input for a short and medium term hydrologic forecasting model; an underground water simulation forecasting model is used for regulating the level of underground water; a coupled forecasting multi-water-resource optimal dispatching model is combined with all the information to achieve combined dispatching of multiple water resources; a multi-water-resource dispatching model provides a day-by-day runoff water distribution decision, and water flow transportation is achieved through a water resource transportation automatic control unit so that precise distribution can be achieved. The method can be widely applied to drainage basin (region) water resource management, especially efficient utilization of water resources in irrigated areas. Implementation steps are clear, and projects are easy to realize.

The invention discloses a method for inverting boundary layer height based on coherent anemometric laser radar carrier-to-noise ratio. The basal principle is as follows: a coherent anemometric laser radar is used for acquiring a carrier-to-noise ratio vertical profile; after performing signal normalization, the signal is processed by utilizing wavelet covariance conversion; and the height corresponding to a maximum value after the wavelet conversion is used as the height of the top of the atmospheric boundary layer. Compared with the existing algorithm, the statics atmospheric boundary layer height with high time resolution can be acquired by using the coherent anemometric laser radar; the dynamics atmospheric boundary layer height acquired through wind field inversion is in favor of further improving the precision of a climate model, a weather forecast model, and the atmosphere pollution diffusion model.

Embodiments generally relate to methods of accurately predicting seasonal fluctuations in precipitation or other approximate functionals of a climate state space, such as the number of heating or cooling degree days in a season, maximum river flow rates, water table levels and the like. In one embodiment, a method for predicting climate comprises: deriving a climate attractor from a global climate model, wherein a tuning parameter for the climate attractor comprises a value of total energy for moving air and water on the earth's surface; estimating a predictive function for each of a plurality of computational cells within the global climate model; and predicting an approximate climate functional of interest for a given specific location utilizing a combination of the predictive functions from each of the plurality of computational cells geographically proximate the location, where at all stages, predictive functions are selected in part by comparison to historical data.

The invention discloses a method for evaluating grape climate regionalization in a Chinese continental monsoon climate region. The method comprises the following steps: collecting data, analyzing thedata, establishing a digital elevation model, establishing a climate model and establishing a damp-heat index. Based on the digital elevation model, space calculation combining multivariate linear stepwise regression and residual interpolation is adopted, simulation errors are reduced to a great extent, it is found that the matching degree of a zoning scheme and actual cultivation conditions of all counties is extremely high through comparison with climate zoning results, the important factor of air humidity is added into the zoning scheme, the index of the damp-heat index is provided by referring to the hot index for evaluating the comfort degree of people, and the index quite conforms to the climate characteristics of China.

A system and method for providing multivariate climate change forecasting are provided that obtain, from one or more climate model datasets, simulated historical and future climate model data, and from one or more climate observational datasets, historical observed climate data. A statistical distribution, using a Bayesian model, is provided of extremes or climate indices for one or more variable climate features using the simulated climate model data and the observed climate data. One or more metrics are determined, including a prediction of a future climate variable for a determined future time period, a confidence bound of the prediction of the future climate variable for the determined future time period, and a prediction bound for the future climate variable for the determined future time period. The metrics can be transmitted to a variety of applications in a variety of formats.

The invention relates to a statistical downscaling method based on non-stationary time series decomposition. The method comprises the specific steps of S1, downscaling data preparation; S2, decomposing a non-stationary time sequence; S3, selecting an optimal time sequence decomposition result; S4, training a random forest model; S5, synthesizing decomposition components of the time sequence aftertraining; S6, performing model evaluation; and S7, downscaling a future scene. According to the method, a statistical relationship is searched among steady-state components; therefore, the problem ofrelated statistical relationship consistency hypothesis in statistical downscaling is solved, the problem of scale mismatching always existing between a climate model and a hydrological model is solved, and a more reliable way is provided for basin response in a series of researches such as future climate change by utilizing the hydrological model.

The invention discloses a health-care climate evaluation method combining climate data and social perception data. The method comprises the following steps: S1, collecting historical climate information and latitude and longitude information of different positions in an evaluation area; s2, calculating a temperature and humidity index IH, a wind-cold index IWC and a holiday index IHC of all positions in the set area in each day within a set year number; s3, constructing a health-care climate model; s4, constructing a health-care climate social perception model; s5, according to the health-care climate model and the health-care climate social perception model, a final health-care climate evaluation model is constructed; s6, performing classification and grading evaluation on the result by using a natural breakpoint method through reclassification; and finally, a result D is obtained, D is a geographic space distribution map layer, the file is raster data and is composed of pixels organized according to rows and columns, and each pixel comprises latitude and longitude information of the point and a D value. According to the method, historical data information, social perception data and multi-source data fusion evaluation are combined, and the evaluation model of the health and maintenance climate can be accurately obtained.

The present invention relates to a radiation transfer calculation method suitable for cloud micro-physical properties continuous variations, based on a two-stream approximation scheme, the method comprising the following steps of 1) representing radiation flux of the cloud micro-physical properties continuous variations as a sum of constant terms and disturbance terms; 2) calculating and obtainingfirst radiation flux according to a traditional two-stream radiation transfer equation, and setting the first radiation flux as the constant terms; 3) substituting an asymmetry factor g and a singlescattering albedo [omega] into a traditional two-stream radiation transfer strength equation in a parameterized form by a perturbation method and forming a heterogeneity caused disturbance term equation set, and solving the heterogeneity caused disturbance term equation set and obtaining second radiation flux represented by two perturbation factors epsilon<omega> and epsilon<g>; and 4) summing thefirst radiation flux and the second radiation flux and solving the radiation flux of the cloud micro-physical properties continuous variations. The vertical nonuniform problem of intra-cloud opticalproperties in a climate model is effectively solved by the method, thereby improving accuracy of radiation calculation.

The invention discloses an early warning method of an extreme climate and composite extreme climate comprehensive early warning system, and belongs to the technical field of climate prediction. The system comprises a data preprocessing system, a global climate model optimization system, a regional climate model dynamic downscaling and parameterization scheme optimization system, a statistical downscaling system, a set prediction system, an extreme climate index and composite extreme climate index system, a relationship establishment system and a classification system. Future climate change scenes as many as possible are obtained through global climate model optimization, RCM regional climate model dynamic downscaling and parameterization scheme optimization in combination with a coupling dynamic-statistical downscaling mode and a set prediction mode; by calculating extreme climate indexes and composite extreme climate indexes under different scenes, the relationship between the indexes and agricultural activities is established based on a multivariate statistical method or a correlation analysis method. According to the invention, favorable support is provided for agriculture to cope with future extreme and composite extreme climate changes.

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 atmospheric boundary layer detection method based on a hybrid laser radar. The basic principle is: using a hybrid lidar, integrating the direct detection aerosol lidar system and the coherent wind measurement lidar system, simultaneously detecting the vertical profile of aerosol optical properties and turbulence intensity, and inverting the height of the atmospheric boundary layer respectively , using the comparison of the difference between the two and the selected threshold to determine different types of atmospheric boundary layers. This method can quantitatively classify the atmospheric boundary layer with only one device, and carry out quantitative and parametric description of various types of boundary layers, which is helpful for improving the accuracy of atmospheric models such as climate models, weather forecast models, and atmospheric pollution diffusion models. Further improve.

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.