27 results about "Shortwave radiation" patented technology

The invention provides a remote sensing estimation method for high spatial-temporal resolution crop evapotranspiration in an arid and semi-arid region, which comprises the following steps of: acquiring cloudless or less-cloudless high spatial resolution optical remote sensing data of a crop growing season in a research region, and calculating or inverting remote sensing earth surface parameters required by high spatial resolution evapotranspiration; comprising a vegetation index NDVI, a leaf area index LAI, a vegetation coverage FVC, a surface water index LSWI and a surface albedo; the method comprises the following steps: acquiring meteorological reanalysis data of daily scales ERA5-Land and GLADAS of a research area, wherein the meteorological reanalysis data comprises relative humidity RH, average temperature Ta, air pressure Pa, solar short-wave radiation # imgabs0 #, downward long-wave radiation # imgabs1 # and upward long-wave radiation # imgabs2 #; according to the technical scheme, multi-source remote sensing data, an evapotranspiration physical model and a space-time fusion technology based on evapotranspiration characteristics are utilized, and estimation of high space-time resolution evapotranspiration of the arid and semi-arid agricultural areas is achieved.

The embodiment of the invention provides a satellite-ground fusion radiation observation lattice point product fusion method, device and equipment, and is applied to the technical field of satellite-ground radiation observation data fusion. The method comprises the following steps: acquiring foundation radiation data, a first earth surface short-wave radiation product and a second earth surface short-wave radiation product; performing deviation correction on the first earth surface short-wave radiation product and the second earth surface short-wave radiation product; performing data fusion on the first earth surface short-wave radiation product and the second earth surface short-wave radiation product after deviation correction based on a maximum likelihood estimation algorithm to generate an earth surface short-wave radiation satellite data fusion product; and based on an optimal interpolation algorithm, carrying out data fusion by taking the earth surface short-wave radiation satellite data fusion product as a background field and taking the radiation data as a ground observation field to generate an earth surface short-wave radiation fusion grid point product. In this way, a high-precision earth surface short-wave radiation fusion lattice point product with a wide coverage range can be formed, so that the precision of a satellite product is improved.

The invention discloses an earth surface short-wave radiation product production method and device and a long-short-term memory network training method and device, and relates to the technical field of aerospace, and a specific implementation scheme is as follows: extracting a first short-wave radiation data set and a second short-wave radiation data set which are aligned in time from first earth surface short-wave radiation data collected by a satellite; acquiring a photovoltaic short-wave radiation data set which is acquired by a ground photovoltaic radiometer and is aligned with the first short-wave radiation data set in time; determining an albedo data set based on the satellite albedo product and the surface land cover product; obtaining an input short-wave radiation data sequence based on the first short-wave radiation data set, the second short-wave radiation data set, the albedo data set, the photovoltaic short-wave radiation data set and the ground photovoltaic radiometer coordinate vector point; inputting the input short-wave radiation data sequence into a pre-trained long short-term memory network to obtain an initial earth surface short-wave radiation product; and obtaining a target earth surface short-wave radiation product based on the initial earth surface short-wave radiation product.

The invention relates to the technical field of solar radiation prediction, in particular to a satellite-ground combined ultra-short-term solar radiation prediction method and system. Comprising the following steps: S1, collecting current state data and historical big data based on solar radiation; s2, preprocessing the ground-based cloud picture and the air-based cloud picture; and S3, identifying cloud layer state data based on the constructed cloud layer identification model. And S4, the solar radiation attenuation prediction model is adopted to identify the total solar radiation attenuation rate, and a radiation attenuation table is constructed. And S5, predicting cloud layer state change data and satellite observation total radiation change data by adopting an extrapolation method, and further calculating to obtain future short-term ground observation total radiation prediction data. According to the method, by combining observation of a stationary satellite and an all-sky imager, satellite-ground combined observation of cloud conditions of different height layers is realized, the influence of cloud in a whole atmospheric column on solar short-wave radiation is fully considered, the prediction precision is maintained, the operation process is optimized, and the precision and efficiency of solar radiation attenuation prediction are improved.

The application discloses a vegetation light protection trigger threshold estimation method and device, the method comprising: obtaining first reflectivity data and second reflectivity data at a first time, the first time being a unit time of a preset time period in a preset area, the first reflectivity data being MODIS 11th band reflectivity data, and the second reflectivity data being MODIS 13th band reflectivity data; determining a first Rchl value according to the first reflectivity data and the second reflectivity data, the first Rchl value being the value of Rchl at the first time; obtaining solar shortwave radiation SWR data corresponding to the first Rchl value at the first time to form an Rchl-SWR corresponding relationship; determining an integrated response curve according to the Rchl-SWR corresponding relationship; and determining the light protection trigger threshold of the vegetation in the preset area according to the integrated response curve. The application can determine the light protection trigger threshold of any type of vegetation in any region in the global range, and provide scientific and technological support for crop management, climate change response and land degradation warning.

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 present invention provides a method for inverting satellite solar shortwave radiation based on knowledge distillation, which relates to the field of solar shortwave radiation inversion, including: collecting polar-orbiting satellite data, geostationary satellite data, geographic information data, and ground observation data; preprocessing the data to obtain input features and labels for training teacher models and student models; using a random forest model to rank the importance of input features, select key features, and eliminate non-key features; using the key features to construct a deep learning model to generate a teacher model for solar shortwave radiation inversion; using the output of the teacher model as a soft label, introducing ground observation data as a hard label for knowledge distillation, and obtaining a student model for solar shortwave radiation inversion. The technical solution of the present invention overcomes the problems of data scarcity and high data acquisition costs faced by the prior art when building models based solely on ground observation data, while the inversion accuracy based entirely on satellite data is limited.

The present disclosure discloses a surface shortwave radiation product production method and device, and a long short-term memory network training method and device, which relate to the field of aerospace technology. A specific implementation scheme is as follows: extracting a first shortwave radiation data set and a second shortwave radiation data set that are time-aligned from first surface shortwave radiation data collected by a satellite; obtaining a photovoltaic shortwave radiation data set that is time-aligned with the first shortwave radiation data set collected by a ground photovoltaic radiometer; determining an albedo data set based on a satellite albedo product and a surface land cover product; obtaining an input shortwave radiation data sequence based on the first shortwave radiation data set, the second shortwave radiation data set, the albedo data set, the photovoltaic shortwave radiation data set, and the coordinate vector points of the ground photovoltaic radiometer; inputting the input shortwave radiation data sequence into a pre-trained long short-term memory network to obtain an initial surface shortwave radiation product; and obtaining a target surface shortwave radiation product based on the initial surface shortwave radiation product.

The application discloses a method for analyzing heat storage of a river-flooded lake based on dynamic parameterization, and relates to the technical field of water resources engineering. The method comprises the following steps: based on water level time series data and underwater topographic parameters of the lake, analyzing time-varying water area and average water depth; based on water quantity, water temperature data, precipitation, evaporation data and water level change rate of inflow and outflow, calculating horizontal heat advection term; based on wind speed data and average water depth, calculating dynamic vertical heat diffusion coefficient; based on average water depth and dynamic vertical heat diffusion coefficient, calculating effective memory time; based on dynamic vertical heat diffusion coefficient, effective memory time and water body extinction coefficient, calculating vertical heat conduction flux; based on average water depth, water body extinction coefficient, net shortwave radiation on water surface and sediment thermal physical property parameters, calculating lake bottom heat exchange term; and synthesizing the net shortwave radiation on water surface, the vertical heat conduction flux, the horizontal heat advection term and the lake bottom heat exchange term to obtain heat storage change rate.

The invention provides a long-time-sequence earth surface short wave cloud radiation forced effect estimation method and system. The method comprises the following steps: acquiring parameters of atmospheric roof incident solar radiation, atmospheric roof emergent short wave radiation under clear sky and all-sky conditions and earth surface short wave radiation under clear sky conditions; on the basis of a plane parallel hypothesis principle, constructing a correlation radiation transfer equation between the cloud coverage degree and parameters of atmospheric roof incident solar radiation, atmospheric roof emergent short-wave radiation under clear sky and all-sky conditions and earth surface short-wave radiation under the clear sky condition; according to a related radiation transfer equation, a long-time-sequence grid-by-grid cloud radiation nucleus of the whole-layer cloud coverage degree is calculated under a finite difference framework; and determining cloud coverage information, and multiplying the long-time-sequence grid-by-grid cloud radiation nucleus by the cloud coverage information to obtain an earth surface short wave radiation effect caused by the cloud coverage. According to the correlation between the TOA and the earth surface radiation parameter, the satellite observation data can be directly input for correlation calculation, and the calculation efficiency is greatly improved.

The present invention relates to a method for all-weather solar radiation remote sensing forecasting supported by deep learning, comprising the following steps: S1, acquiring time series multispectral remote sensing data; S2, performing data preprocessing on the acquired time series multispectral remote sensing data to obtain a preprocessed time series multispectral remote sensing dataset; S3, inputting the acquired preprocessed time series multispectral remote sensing dataset into a ConvLSTM network model to obtain instantaneous solar shortwave radiation forecast data or multi-timescale solar shortwave radiation forecast; the ConvLSTM network model is a deep learning network model oriented towards remote sensing images and incorporating a spatial attention mechanism. The forecasting method provided by the present invention fully considers the spatial and time series characteristics of solar radiation, and adds a spatial attention mechanism to the deep neural network to more effectively capture the sudden changes in solar radiation in nature.

The invention discloses a dynamic parameterization-based thermal reserve analysis method for a flood lake through river, and relates to the technical field of water resource engineering, and the method comprises the steps: analyzing a time-varying water area and an average water depth based on water level time sequence data and underwater topographic parameters of the lake; calculating a horizontal thermal advection item based on the inflow and outflow water quantity, the water temperature data, the rainfall and evaporation data and the water level change rate; calculating a dynamic vertical thermal diffusion coefficient based on the wind speed data and the average water depth; calculating effective memory time based on the average water depth and the dynamic vertical thermal diffusion coefficient; calculating vertical heat conduction flux based on the dynamic vertical heat diffusion coefficient, the effective memory time and the water extinction coefficient; calculating a lakebed heat exchange item based on the average water depth, the water extinction coefficient, the water surface net short wave radiation and the sediment thermophysical property parameters; the water surface net short wave radiation, the vertical heat conduction flux, the horizontal heat advection item and the lakebed heat exchange item are synthesized, and the heat reserve change rate is obtained.

The application discloses a kind of based on radiation form constraint active learning three-dimensional space-time solar radiation prediction method, first obtain long time sequence ground surface net solar shortwave radiation SSR spatial grid data, and construct space-time prediction sample;Subsequently, through radiation sequence representation learning extraction weather feature vector, and using clustering method identifies different radiation weather form;On this basis, construct three-dimensional convolutional neural network prediction model, and introduce active learning sample selection mechanism in model training process, through prediction residual evaluation sample information, simultaneously combined with weather type distribution constraint and K-center diversity screening strategy realizes new training sample selection, to form active learning iterative training process.The method can maintain higher prediction accuracy under the condition of reducing training sample size, improve the training efficiency and generalization ability of solar radiation grid prediction model, and can be applied to photovoltaic power prediction, power dispatching and new energy resource evaluation and other fields.

A radiation emitting semiconductor device (1) comprising a semiconductor body with a semiconductor layer sequence (2) is specified, wherein the semiconductor layer sequence (2) comprises an active region configured to emit radiation with a peak emission wavelength in the near-infrared spectral range, and wherein the semiconductor layer sequence (2) comprises an absorber (3) configured to at least partially absorb a shortwave radiation component, the absorber (3) having a cut-off wavelength that is shorter than the peak emission wavelength.

This invention provides a photosynthetic phenological inversion system combining meteorological suitability and vegetation indices, belonging to the field of remote sensing and ecological environment monitoring technology. The system includes a data input module, a growing season index calculation module, an improved phenological index synthesis module, a time-series reconstruction and phenological extraction module, and a result output and verification module, connected sequentially. It acquires and preprocesses multi-source data; calculates the diurnal growing season index based on temperature, precipitation, photoperiod, and shortwave radiation factor; normalizes the index and couples it with the remote-sensed vegetation index to generate an improved photosynthetic phenological index; extracts the photosynthetic start and end dates using curve fitting and a dynamic threshold method; and finally verifies and determines the optimal technical solution using ground observation data to generate the final product. This invention effectively solves the problems of inaccurate physiological process characterization, high susceptibility to noise interference, and lack of reliable verification in traditional remote-sensing phenological extraction, achieving higher accuracy and more physiologically meaningful large-scale vegetation photosynthetic phenological information extraction.

The present invention discloses a method and device for predicting a non-uniform temperature field within a three-dimensional urban street canyon. The method comprises: constructing a three-dimensional urban street canyon model and dividing it into several surface zones; calculating sky view parameters for each surface zone; generating a shadow distribution field for each surface zone; obtaining the solar shortwave radiation flux and ground longwave radiation flux for each surface zone based on the sky view parameters and shadow distribution field for each surface zone; calculating the sensible heat flux and latent heat flux for each surface zone; generating a non-uniform temperature field based on the sensible heat flux, latent heat flux, solar shortwave radiation flux, and ground longwave radiation flux for each surface zone; dividing the illuminated zone into a shadowed zone based on the shadow distribution field for each surface zone; and calculating the average temperature of the illuminated and shadowed zones based on the non-uniform temperature field. The present invention achieves real-time and accurate prediction of the non-uniform temperature field within a three-dimensional urban street canyon while reducing computing resource consumption.

This invention relates to the field of intelligent irrigation technology, and discloses an intelligent irrigation control system and method for landscaping, including a weather station, an infrared temperature sensor, a solenoid valve, and a controller. The controller establishes a global three-dimensional spatial coordinate system containing two-dimensional ground and facade grid cells, generates a shadow projection matrix based on global solar shortwave radiation, and calculates the effective cumulative radiation on the ground and facade respectively. The effective original canopy temperature is extracted based on the two-dimensional temperature matrix. The lateral longwave thermal radiation warming equivalent is calculated using the effective cumulative radiation on the facade and the equivalent thermal hysteresis coefficient, and this equivalent is subtracted from the original canopy temperature to obtain the corrected true canopy temperature. An adaptive judgment threshold is generated based on the effective cumulative radiation on the ground, the difference between the true canopy temperature and the ambient air temperature is calculated, and the difference is compared with the threshold to generate a command to drive the solenoid valve. This invention helps to eliminate interference from surrounding environmental thermal radiation and improves the accuracy of irrigation control.

The invention discloses a reflected radiation data interpolation method, system and application, and relates to the meteorological field, the reflected radiation data interpolation method comprises the following steps: obtaining observed radiation data and meteorological data; carrying out device difference correction on the incident short wave radiation data; calculating a clearness index; eliminating abnormal values of the reflected short-wave radiation data, the incident short-wave radiation data after the difference correction and the meteorological data; carrying out interpolation on the missing incident short wave radiation data; interpolating the missing reflection short wave radiation data; and systematically evaluating the interpolation result of the reflected short-wave radiation data. The invention provides a reflected radiation data processing method with an abnormal value elimination mechanism, a self-adaptive interpolation capability and a system evaluation function, which can systematically solve the problems of abnormity and missing in observation data, improve the accuracy of an interpolation result, data integrity and credibility, and improve the reliability of the observation data. And a solid data basis is provided for subsequent applications such as carbon-water flux calculation, ecological model simulation and remote sensing inversion.

The invention discloses a shortwave radiation parameterization method and device for a near-shore water body and electronic equipment, and relates to the technical field of water body monitoring. A proportion parameter of first wavelength light in short wave radiation, a proportion parameter of second wavelength light in short wave radiation, a parameter of the first wavelength light in a water body penetration process and a parameter of the second wavelength light in a water body penetration process are acquired, and a penetration parameter of the first wavelength light and a penetration parameter of the second wavelength light are determined by utilizing corresponding parameters; and then the penetration parameter of the first wavelength light and the penetration parameter of the second wavelength light are combined to obtain a short-wave radiation penetration parameter of the near-shore water body, so that the aim of parameterizing the short-wave radiation is fulfilled, and a solar short-wave radiation penetration process can be subsequently simulated according to the obtained short-wave radiation parameter. The method is used for optimizing analysis and research on the ocean thermal power process and the ocean ecosystem.

The utility model belongs to the field of photovoltaic park microhabitat sensing technical equipment, and discloses a photovoltaic energy flow logistics monitoring device for grassland in an arid area. Aiming at micro-ecological environments inside and outside the photovoltaic park, the device can quantitatively identify near-surface solar short-wave radiation, total radiation, net radiation, photosynthetically active radiation, air temperature and humidity, wind speed and wind direction, rainfall, evapotranspiration, soil temperature and humidity and carbon-water flux changes caused by construction and operation of the photovoltaic park; meanwhile, full-time high-precision vegetation monitoring is carried out in combination with a phenological camera, and adaptive succession characteristics of vegetation to the disturbed habitat of the photovoltaic park are quantified. According to the utility model, by observing organisms / meteorology, water vapor flux and vegetation phenology inside and outside the photovoltaic park in real time, the influence of the photovoltaic park on a local microhabitat and the adaptive succession of surface vegetation on a disturbed microhabitat are quantitatively explored, and the suitability of the photovoltaic park is objectively evaluated.

The application discloses a kind of reflected radiation data interpolation method, system and application, it is related to meteorological field, a kind of reflected radiation data interpolation method, comprising the following steps: obtaining observed radiation data and meteorological data;To incident shortwave radiation data is carried out instrument difference correction;Calculate clear sky index;To reflected shortwave radiation data, instrument difference correction after incident shortwave radiation data and meteorological data outlier rejection;To missing incident shortwave radiation data interpolation;To missing reflected shortwave radiation data interpolation;To reflected shortwave radiation data interpolation result system evaluation.The application provides a kind of reflected radiation data processing method with outlier rejection mechanism, adaptive interpolation capacity and system evaluation function, can systematically solve the problem of exception and missing in observation data, improve the accuracy of interpolation result, data integrity and reliability, provide solid data foundation for subsequent carbon flux calculation, ecological model simulation and remote sensing inversion etc.

The application discloses a photovoltaic power prediction method based on a stationary satellite neural network model, and belongs to the technical field of photovoltaic power prediction, and comprises the following steps: acquiring base station radiation historical observation data, satellite historical observation data and ground meteorological historical observation data, and performing space-time matching on the acquired data; and fusing and enhancing the satellite historical observation data and the ground meteorological historical observation data to obtain enhanced fusion features; constructing a ground shortwave radiation prediction model, taking the enhanced fusion features as input, and taking the base station radiation historical observation data as target output to perform training; acquiring future satellite parameters and inputting the same into the trained ground shortwave radiation prediction model, so that future ground shortwave radiation values can be predicted; and based on the obtained future ground shortwave radiation values, combined with the position information of a photovoltaic power station, photovoltaic module output power can be predicted. Therefore, the application can realize the prediction of photovoltaic module output power.

Disclosed is a device that will take radiometric images of the shortwave spectrum from 0.2-2 μm, which can then be processed into a spherical panoramic image. This single source of data can then be used to produce a wide range of functional outputs for radiative energy analysis, from architectural performance and thermal comfort analysis to replacing the array of sensors required to make specific biometeorological measurements, such as Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), Diffuse Horizontal Irradiance (DHI), Sky View Factor (SVF), and / or Global Tilted Irradiance (GTI). The data is also combined with a longwave array detector to produce full-spectrum radiative energy measurements.

The invention discloses an earth surface downward short wave radiation downscaling calculation method and device and a storage medium. The earth surface downward short wave radiation downscaling calculation method comprises the following steps: acquiring low spatial resolution data and high spatial resolution data; constructing a cloud layer shielding index based on the rainfall data; constructing a stacking model based on integration of various machine learning models, and training the stacking model by adopting low-spatial-resolution data; inputting the obtained high-spatial-resolution data as an input feature vector into the trained stack model to obtain an initial high-spatial-resolution earth surface downward short wave radiation value of high-spatial-resolution earth surface downward short wave radiation; and applying energy conservation constraint to the obtained initial high-spatial-resolution earth surface downward short wave radiation value to perform consistency correction. According to the method, an energy conservation constraint correction mechanism is introduced, and the spatial resolution, precision and physical consistency of the earth surface downward short wave radiation data under the complex terrain condition are effectively improved.

The invention provides an earth surface incident short wave radiation estimation method and system based on cloud coverage information, and the method comprises the steps: directly simulating a function relation between a TOA radiation parameter and an earth surface radiation parameter under a partial cloud condition through observation data, and converting the DSSR under the all-sky condition into a radiation transfer equation among a TOA observation value, a clear sky radiation parameter and a cloud coverage degree according to the function relationship, thereby estimating a more accurate DSSR. According to the invention, research is carried out by directly utilizing the correlation between the TOA radiation parameter and the earth surface radiation parameter, and cloud coverage information is embedded in the radiation transmission process; the method effectively avoids estimation difficulty caused by insufficient atmospheric parameters and estimation deviation caused by insufficient consideration of the influence of cloud coverage on radiation parameters in a traditional method which needs to take atmosphere or meteorological conditions as intermedia.

The invention relates to the technical field of data processing, and particularly discloses a thunderstorm and gale diagnostic analysis method and system based on radiation and cloud variables, and the method comprises the steps: carrying out the data matching of the product data on a FY-4 satellite and the simulation data of the thunderstorm and gale process; determining a spatial data set and a site data set of the thunderstorm gale process according to the matched data; and based on the steam furnace effect of solar short wave radiation, according to the spatial data set and the station data set, completing diagnostic analysis of the thunderstorm gale process. On the basis of the steam furnace effect of solar radiation and in combination with the physical process of thunderstorm and gale convection development, a diagnosis scheme for radiation energy, cloud variables and temperature and humidity profiles is designed. And the innovative application of satellite observation data such as secondary data products of a Chinese new generation of stationary satellites FY-4B and the like in diagnostic analysis is realized.