50 results about "Heat wave" patented technology

The invention relates to the field of disaster prediction, and particularly discloses a prediction system and method for high-temperature heat wave drought composite disasters, and the system comprises a multi-source data collection module which is used for collecting meteorological data, topographic data, vegetation and soil data and human activity data, and constructing a multi-dimensional input feature set; the data processing module is used for carrying out space-time alignment, normalization processing and abnormal value elimination on the acquired meteorological data, topographic data, vegetation and soil data and human activity data, and carrying out dimensionality reduction through a principal component analysis method to extract key features; the deep learning model training module adopts a CNN-RNN fusion architecture; and the prediction output module is used for generating a composite disaster prediction result through the trained deep learning model training module. By adopting the technical scheme of the invention, multi-dimensional data can be considered, a multi-element coupling model is constructed, and prediction of spatial and temporal distribution, evolution rate and coupling strength of high-temperature heat wave drought composite disasters in complex geographic units and ecologically fragile areas is realized.

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 provides a lightning fire occurrence probability prediction method fusing extreme climate factors, and relates to the technical field of forest fire prediction and risk assessment. The method comprises the following steps: collecting multi-source data such as thunder and lightning, extreme climate, weather, vegetation, soil and terrain, and constructing a balanced sample set; training an ignition probability model by adopting a random forest, XGBoost, a convolutional neural network and other models, and evaluating the performance difference before and after the extreme climate index is included; explaining variable contribution by using an SHAP method, and identifying a key driving factor; a risk grading grid map is generated according to the prediction probability, and the fire danger grade is automatically improved under the composite condition of heat waves and drought. The method has high precision and strong interpretability, and is suitable for fine prediction and prevention and control decision support of the occurrence probability of the lightning fire under the extreme climate background.

The invention relates to an ocean heat wave prediction method, and the method comprises the steps: obtaining the physical variable historical time series data of each region of a target sea area, generating a physical variable prediction sequence containing the physical variable prediction value of a future time point through a composite model obtained through training, and carrying out the mining to obtain the physical variable relation data. Then, the physical variable prediction sequence, the physical variable relation data and the preset task instruction are input into a heat wave analysis module, the input data are accurately analyzed through the heat wave analysis module, and conclusion deviation caused by non-uniform standards during manual interpretation is avoided. Through automatic analysis, direct manual participation is reduced, and the analysis efficiency and the standardization degree are improved. And finally, obtaining ocean heat wave information output by the heat wave analysis module and obtaining a prediction result.

The application provides a city surface area classification method and related equipment. The city surface area classification method comprises: obtaining a first target parameter of a to-be-determined city surface area, the first target parameter comprising a characteristic building height, an average building height, a building height standard deviation, a building coverage rate, an impervious surface ratio, a characteristic vegetation canopy height, an average vegetation canopy height, and a vegetation coverage rate of the to-be-determined city surface area; inputting an electronic map corresponding to the to-be-determined city surface area and the first target parameter into a city surface area classification model to obtain a city surface area type corresponding to the to-be-determined city surface area output by the city surface area classification model, the city surface area type being used for analysis or simulation of heat waves, air quality, and extreme weather of the to-be-determined city surface area. In the application, the fineness and determination accuracy of the city surface area type are improved.

This invention discloses a camera with defogging function, including a mounting housing. A rotating block is fixedly connected to one side of the mounting housing, and a mounting base connected to a wall is rotatably connected to the surface of the rotating block. A camera lens is mounted on the other side of the mounting housing. In low-temperature weather, the cooling fan inside the mounting housing is tilted towards the camera lens, so that when the cooling fan rotates, the heat generated by the circuit board is carried out through the ventilation holes and blown onto the surface of the camera lens through the end face of the protective cover, thereby heating the surface of the lens and preventing a large amount of fog from forming on the lens surface, which would affect the image captured by the camera lens. In hot weather, the cooling fan is tilted to the other side, thereby preventing the hot air generated by heat dissipation in high-temperature weather from blowing onto the surface of the camera lens and forming a heat wave, which would affect the image captured by the camera lens.

To create more coolness and shade, we offer an eco-friendly double fan made by screwing two fans together and unfolding them for use. [Solution] The device includes two overlapping fans: an upper fan 1, a lower fan 2, a small screw rod 3, a wing nut 4 for fastening fan 1 and the screw rod 3, a wing nut for tightening fan 1 and fan 2, a gasket, and a plastic pocket attached to the back of fan 2 for inserting and securing fan 1. By fastening the two overlapping fans together using the screw rod and wing nut and then spreading them out for use, more coolness and shade can be obtained, and it can greatly contribute to countermeasures against the recent heat waves in terms of ease of use and eco-friendliness.

The application discloses an extreme weather prediction and identification method based on multi-model integration and machine learning coupling, and belongs to the field of climate-adaptive building design and building environment engineering. The technical scheme comprises the following steps: taking the GCM data set of CMIP6 and the RCM data set of CORDEX as original data, combining ERA5 reanalysis data to perform deviation correction and time downscaling processing; constructing a prediction model integrating random forest algorithm and SSP-RCP multi-scenario framework, dividing training set and test set according to time sequence, and realizing multi-scale prediction after standardization and super parameter optimization; constructing an extreme weather identification system based on quantile threshold method, dividing heat wave and cold wave threshold, and quantifying the duration, intensity and severity thereof; and finally generating a high-granularity regional future extreme weather data set for 2024-2034. The application can provide high-precision and high-temporal and spatial resolution meteorological data, provide support for building simulation and climate-adaptive building design, and has good regional adaptability and promotion potential.

The invention discloses an electrical load prediction model construction method for a summer high-temperature heat wave scene, and relates to the technical field of artificial intelligence and intelligent power utilization. The method comprises the following steps: acquiring summer electrical load data and meteorological characteristic data of a to-be-predicted area; carrying out data expansion by utilizing a T imeGAN network; training an electrical load prediction model by using the expanded data set, and executing the following operations in the model: inputting a time sequence formed by electrical load data and a plurality of meteorological feature data into a feature attention layer, learning attention weights among input features in the time sequence, and correcting the time sequence by using the attention weights; inputting the corrected time sequence into a Bi LSTM network and a time sequence attention layer, learning attention weights among time steps, and obtaining context features; and predicting the electrical load of the next time step of the time sequence by using the context features.

Disclosed in the present invention is a method for studying the interannual variability of marine heatwaves in the Southern Indian Ocean. The method includes: on the basis of acquired data, exploring the spatial distribution characteristics and linear variation trend characteristics of marine heatwaves in the Southern Indian Ocean; analyzing the relationship between the intensity of marine heatwaves in the Southern Indian Ocean and an El Niño-Southern Oscillation (ENSO) process; analyzing the spatial evolution of marine heatwaves and sea surface temperature anomalies in the Southern Indian Ocean during El Niño events; analyzing the energy contributions of the ocean and atmosphere to marine heatwave events during El Niño events, and exploring the physical mechanism of marine heatwaves in the Southern Indian Ocean; and determining whether marine heatwaves in the Southern Indian Ocean are affected by shortwave radiation and latent heat modulated by the ENSO process. The present invention discovers that during El Niño events, within a study area, low cloud cover decreases while high cloud cover increases, the mixed-layer depth reduces, and shortwave radiation penetrates the sea surface; moreover, northwesterly winds anomalously intensify while climatological southeasterly winds are suppressed, thereby reducing evaporation, decreasing latent heat energy loss, and thus promoting warming.

The application provides a kind of heat wave influence on global navigation satellite system positioning accuracy evaluation method and system, determine the research area and research year of target heat wave event, according to the corresponding climate state of research year;Obtain the temperature data of each meteorological station in the research area, interpolate and supplement the missing data among them;According to the data after interpolation and supplement, determine the research period of heat wave;Analyze the abnormal value spatial distribution of two-meter temperature above ground and daily average soil moisture in the research period of research area;Analyze the change of abnormal value of air temperature and atmospheric precipitable water per hour, and explain the reason of atmospheric precipitable water anomaly through the corresponding relationship of factors;Analyze the abnormal value change of ionospheric total electron content and air temperature per hour;Compare the difference of global navigation satellite system positioning accuracy in heat wave period and non-heat wave period in research period.The application provides a reference for users to carry out high-precision GNSS positioning during heat wave.

This invention provides a method and system for detecting community structure in spatially concurrent extreme climate events, comprising: collecting gridded temperature and precipitation data of the study area, extracting binary time series of heat waves and extreme precipitation events, and performing event synchronization determination calculations and significance tests; constructing a two-layer coupled heat wave-extreme precipitation network based on the inter-layer adjacency matrix; obtaining stable community classification results based on the two-layer coupled network using a community detection method combining the Leiden algorithm and consensus clustering; performing lead-lag correlation analysis on all community pairs to identify key community pairs with strong correlations and their lag times, and further exploring the spatiotemporal propagation characteristics of climate events. This invention fully utilizes the advantages of two-layer coupled climate network analysis, combining the Leiden algorithm and consensus clustering method to improve the accuracy and stability of community detection, and can effectively reveal the spatial concurrency characteristics and spatiotemporal propagation patterns of global extreme climate events.

This invention discloses a method for the quantification and unified identification of joint stress in daily-scale combined drought-heat wave events, comprising: acquiring daily-scale temperature data and land surface moisture data and performing time alignment and spatial consistency preprocessing; then standardizing and determining extreme stresses in the daily temperature data and land surface moisture data to obtain daily-scale single stress intensity indices; constructing daily-scale joint stress intensity indices based on the single stress intensity indices; performing multi-class discrete coding of daily stress states based on the single stress intensity indices; identifying combined drought-heat wave events and single stress events using a continuous run-length scan method; and integrating each identified combined drought-heat wave event and single stress event to construct a structured event record set. Based on this, this invention achieves fine differentiation between concurrent combined drought-heat wave events, continuous combined drought-heat wave events, and single stress events.

The invention relates to a composite heat wave dynamic risk prediction method, system and device and a medium. The method comprises the steps of obtaining time sequence observation data and prediction time lag of a target area, and performing preprocessing to obtain standardized grid point time sequence meteorological data; performing change feature extraction according to the standardized grid point time sequence meteorological data, and determining a dry and wet partition label of the target area according to the dryness index; performing feature splicing on the obtained dry and wet partition labels, daily potential evapotranspiration, daily standardized rainfall evapotranspiration indexes, threshold temperature, a multivariable change feature matrix and grid point static features to obtain feature tensors; inputting the feature tensor into a pre-trained composite heat wave risk prediction model to obtain a prediction result; and on the basis of the physical constraint base line, probability calibration, physical consistency filtering and risk grading are sequentially carried out on the prediction result to obtain a risk probability thermodynamic diagram. By adopting the method, a more accurate dynamic risk prediction result can be generated according to the composite heat wave evolution difference of different dry and wet zones.

Methods and systems for determining the AccuWeather HeatWave Counter and Severity Index are discussed. The AccuWeather HeatWave Counter and Severity Index is intended to be used to understand, present, and predict the severity of HeatWaves, issue public safety announcements, and support policy decisions related to climate change. In particular, the methods and systems of the invention are effective for monitoring periods of excessive heat and generating warnings and recommendations during the HeatWaves to reduce temperature-related health risks to people and domestic animals and impacts on temperature-sensitive products.

The invention provides a causal analysis method and system for ocean heat wave events and chlorophyll changes, which are applied to the technical field of ocean environment monitoring, and are characterized in that a multi-dimensional causal feature matrix is constructed through multi-source long-time sequence environmental data in combination with time-space identifiers and abnormal change sequences of the heat wave events, and the causal analysis result of the heat wave events and chlorophyll changes is obtained through joint probability distribution expression. And performing decomposition calculation on the causal information of the heat wave accumulated intensity characteristic and the dynamic environment element characteristic relative to the chlorophyll abnormal change to obtain multiple types of causal information components, judging the dominant action type of the chlorophyll change according to the proportion of the multiple types of causal information components, and outputting a corresponding causal attribution result. According to the causal analysis method and system for the ocean heat wave event and the chlorophyll change, the causal relationship of the ocean heat wave event to the chlorophyll concentration change of the phytoplankton is analyzed through construction of a multi-dimensional causal feature matrix, joint probability distribution mapping and causal information decoupling.

This invention relates to the field of industrial measurement and control, and more particularly to a wireless sensing system for the temperature field of a roasting furnace. The system includes a wireless sensing node module, an adaptive sampling control module, and a temperature field reconstruction module. The wireless sensing node module acquires real-time temperature data with spatial location information; the adaptive sampling control module calculates a heat wave sensitivity factor based on the real-time temperature, determines the adaptive sampling period by combining the heat wave propagation tendency of neighboring nodes, and collects key temperature data according to the adaptive sampling period; the reconstruction module receives the data and generates an isothermal surface cloud map through three-dimensional inverse distance weighted interpolation, completing the three-dimensional visualization of the temperature field and anomaly early warning. This invention adaptively adjusts the sampling period by using the heat wave sensitivity factor and heat wave propagation tendency, and accurately reconstructs the temperature field using a three-dimensional mesh and high-density interpolation, avoiding the distortion and high power consumption problems of fixed sampling, and improving the accuracy of temperature field reconstruction.

This invention relates to the field of ecology and environmental technology, and particularly to a method and apparatus for assessing the impact of drought and heatwave events on total primary productivity (TPP) of vegetation. The method includes: constructing original driving data and typical meteorological year data based on meteorological and underlying surface data to establish a Noah-MP land surface model to simulate TTP and various ecosystem variables under original and typical meteorological year scenarios, and calculating meteorological drought, agricultural drought, and heatwave thresholds under the original scenarios to identify drought and heatwave events; constructing time-varying most probable functions of TTP and various ecosystem variables based on drought and heatwave events to compare the differences in TTP and various ecosystem variables under original and typical meteorological year scenarios, thereby analyzing the impact of drought and heatwave events on TTP under different driving factors. This solves the problems of existing technologies that do not fully consider the interaction of multiple variables and lack physical mechanisms.

The application relates to the technical field of high-temperature heat wave detection, in particular to a high-temperature heat wave detection method based on day and night time, which comprises the following steps: acquiring an hourly day and night distribution map of a target region in a target time period; constructing an hourly day and night judgment matrix of the target region in the target time period according to day and night information corresponding to a plurality of grids in the hourly day and night distribution map; acquiring hourly apparent temperature data of the target region in the target time period; acquiring hourly daytime apparent temperature data and hourly nighttime apparent temperature data of the target region in the target time period according to the hourly apparent temperature data of the target region in the target time period and the hourly day and night judgment matrix; acquiring temperature threshold data; and obtaining day and night high-temperature heat wave detection data of the target region in the target time period according to the hourly daytime apparent temperature data, the hourly nighttime apparent temperature data and the temperature threshold data.

Device and method for mitigating, adapting to and combating climate change based on the efficient and massive evaporation of water, which cools and humidifies the environment, helping to mitigate heat waves, droughts and fire 5 risks and promoting plant growth and soil health. By placing a vertical wall (2) perpendicular to an incident wind (1), an upward air current (4) is generated. Once the velocity of this upward current (4) has been measured, the maximum diameter of the water droplets arranged in the upward current (4) that will rise in it is calculated, and a nebulization of droplets (5) with diameters smaller than the 10 calculated diameter is produced by means of a pumping system (6) and a nebulization system (7).

The invention relates to the technical field of climate event analysis, in particular to a regional composite thermal wave population exposure risk analysis method based on multi-source data. The method comprises the following steps: acquiring day-by-day temperature observation data, month-by-month reanalysis data of various meteorological elements and population distribution data in a target area; judging a composite heat wave event by adopting a percentile threshold method, and counting the composite heat wave frequency; on the basis of an inverse algorithm, calculating a whole-layer atmospheric heat source according to monthly meteorological reanalysis data; analyzing the correlation between the composite heat wave frequency in the target area and an atmospheric heat source, and establishing a linear regression equation; and calculating the population exposure degree of the composite heat wave in the target area caused by the abnormal change of the atmospheric heat source, and quantitatively evaluating the population exposure risk level. The method disclosed by the invention reveals the formation mechanism of the composite heat wave event from a new perspective, assists in improving the prediction capability, provides a solid scientific basis for accurately identifying the distribution of related high-risk crowds, and has important scientific significance and application prospects.

The present application relates to the technical field of household appliances, in particular to an inner shell assembly of a cooking appliance and a cooking appliance with the same. The present application aims to solve the technical problem of slow heating of the existing cooking appliance. To this end, the present application provides an inner shell assembly of a cooking appliance, the inner wall of the inner shell assembly surrounds a heating cavity of the cooking appliance, the inner wall is made of a high reflectivity material and / or the inner wall is coated with a high reflectivity coating, and the inner wall protrudes into the heating cavity with a plurality of heat dissipation protrusions, the inner shell assembly further comprises a heating element for emitting heat waves into the heating cavity, the heat waves emitted by the heating element are uniformly scattered into the heating cavity after being reflected by the plurality of heat dissipation protrusions. The cooking appliance of the present application can improve the reflection effect of heat waves by using high reflectivity material and / or high reflectivity coating, at the same time, the plurality of heat dissipation protrusions can improve the scattering effect of heat waves, so as to improve the heating rate of the cooking appliance.

The application provides an atmospheric data assimilation method, device, equipment and storage medium. It relates to the technical field of computer science and atmospheric science. The method comprises the following steps: adding a cost function, a prior estimate and a gradient of the cost function into a gradient-based descent algorithm, adding a posterior estimate, and constructing a four-dimensional variational and ensemble Kalman filter combination model based on Bayesian prior information; and based on the four-dimensional variational and ensemble Kalman filter combination model, data assimilation is performed on atmospheric data. The application combines artificial intelligence technology, especially deep learning and Bayesian optimization adaptive algorithm, enhances and optimizes the traditional data assimilation algorithm, and can be widely applied to the prediction of extreme weather events such as high temperature and heat wave. Through the assimilation of historical data and real-time observation data, the prediction accuracy of future climate change trends is significantly improved, providing stronger support for extreme weather warning and decision making.

The invention discloses a wind power time sequence stochastic simulation method considering a high-temperature heat wave event, and the method comprises the following steps: 1), defining a weather state type, and obtaining a historical typical weather state sequence; 2) based on the weather state type, establishing an upper-layer day-by-day weather state sequence; 3) establishing joint distribution for meteorological factors in each weather state in the historical typical weather state sequence by adopting an R-vine copula function, and constructing a meteorological factor joint probability density function; and 4) integrating the upper-layer day-by-day weather state sequence and the meteorological factor joint probability density function to generate a weather scene sequence, and inputting the weather scene sequence into the wind power generation physical model to generate a wind power time sequence. The wind power generated by the method can effectively capture the random change characteristics of weather and the duration of the heat wave event, and accurately reflect the heat wave events of different time scales.

The invention relates to the field of climate change, and discloses a vertical three-dimensional quantitative tracking and tracing method for heat of a heat wave event, and the method comprises the steps: collecting data; identifying the space-time range of the high-temperature heat wave event; heat sources with abnormal temperature during the high-temperature heat wave event are tracked; contribution quantification of a heat source driving factor during a high-temperature heat wave event; analyzing vertical characteristics of atmospheric heat transfer; according to the method, the heat abnormality of the heat wave event is traced, and the thermodynamic structure characteristics of the atmospheric temperature abnormality of the whole troposphere and the multi-scale driving mechanism of the heat abnormality are disclosed in combination with the vertical section analysis, so that the understanding of the extreme high-temperature event is deepened; and a scientific basis is provided for formulating a more accurate disaster prevention and reduction strategy for regional climate abnormity caused by global climate change.

The present application relates to the field of carbon neutralization, and discloses a method and equipment for tracking and future risk estimation of interland-sea migration heat wave life process, the method comprising: data downloading; identifying marine source type landing heat wave and land source type entering sea heat wave event; quantifying the spatial and temporal attribute characteristics of marine source type landing heat wave and land source type entering sea heat wave; detecting the influence of different human activities on marine source type landing heat wave and land source type entering sea heat wave; weather scale and interdecadal scale physical mechanism of marine source type landing heat wave and land source type entering sea heat wave migration and landing or entering sea; estimating the risk of marine source type landing heat wave and land source type entering sea heat wave under future high emission scenario; the present application analyzes the response situation under human-induced climate change, clarifies the physical mechanism of landing and entering sea, helps to deepen the understanding of the life cycle process of the two types of interland-sea migration heat wave, and provides a scientific basis for coping with the natural challenges brought by the two types of interland-sea migration heat wave under climate change.

A method for automatically controlling the heatwave closure of a non-solar shutter driven by an electric motor, each motor being connected to a control unit equipped with telecommunications means and controllable by means of an individual remote control programmable by the user between an automated and a non-automated operating mode of the shutter, an additional remote control being associated with each shutter, said additional remote control including means for measuring the ambient temperature, a method characterized in that it comprises: - the determination of conditions defined as being heatwave-like, - the determination that the current season presents high temperatures, - if the conditions are determined to be heatwave-like and if the current season is determined to present high temperatures, the transmission to the motor by the control unit of a heatwave-related closure sequence. (See abstract figure: Fig. 1)

This invention belongs to the field of integrated climate change assessment modeling technology, specifically involving a heat wave simulation method based on an integrated climate change assessment model. This method, based on climatological techniques, combines the Integrated Climate Change Assessment (IAM) model with features from multiple complex Earth system models and historical observed temperature characteristics. It first simulates the global annual mean temperature, then transforms it into monthly, daily, and intraday global geographic grid temperatures. During the transformation process, it simulates the monthly seasonal effects and daily mean characteristics of the Earth system model, capturing historically observed intraday temperature anomalies and diurnal temperature range characteristics. Finally, by superimposing mean and wave dynamic characteristics, it simulates daily extreme temperatures, thereby simulating regional short-term heat wave characteristics consistent with long-term global climate change trends. This invention achieves simplified simulation of regional extreme temperatures using IAM, improves the ability and efficiency of IAM in assessing extreme climate risks, and facilitates efficient climate policy analysis.

The invention discloses a regional high-temperature heat wave meteorological disaster thematic resource library system and a construction method. The system comprises a basic resource layer module, an algorithm layer module, a product layer module and a management application layer module. The method comprises the steps of data acquisition, characteristic quantity calculation, data reorganization and fusion, product production, system application service providing and the like. According to the construction method and system of the resource library, a set of high-temperature heat wave disaster multi-source data automatic acquisition and fusion method is adopted. Meanwhile, the invention provides a set of regional high-temperature heat wave dynamic identification and evaluation algorithm, the regional high-heat wave weather process can be rapidly identified, process disaster-inducing factors are automatically extracted, the process level is evaluated, disaster information is collected and fused, and data support is rapidly provided for dynamic monitoring of high-temperature heat wave disaster events. On the basis, a high-temperature heat wave disaster sequence product is provided, a high-temperature heat wave meteorological data rapid sharing service is provided through the system, and cross-department and cross-region safety service sharing of high-temperature heat wave disaster data resources is achieved. According to the construction method and system of the regional high-temperature hot-wave meteorological disaster thematic resource library, a generalizable mode is provided for fine management and utilization of disaster event data resources of different regions and different disaster types.

The invention provides a method and a device for evaluating abnormal weather data, which can be applied to the technical field of machine learning and weather prediction. The evaluation method comprises the following steps: processing initial to-be-evaluated data based on reference data and a resolution processing strategy to obtain processed to-be-evaluated data; performing fusion and conversion processing on the to-be-assessed data to obtain processing features and difference data corresponding to the to-be-assessed data, the difference data representing a difference value between the resolution of the to-be-assessed data and the resolution of the processing features; on the basis of the processing features, the difference data and the meteorological candidate data set, meteorological processing data meeting a preset resolution is determined, and the preset resolution comprises a preset spatial resolution and a preset duration resolution; the meteorological processing data is evaluated based on preset evaluation strategies, an abnormal weather evaluation result corresponding to the to-be-evaluated data is obtained, and the preset evaluation strategies comprise a thermal wave evaluation strategy and a cold wave evaluation strategy based on quantiles.