7 results about "Surface air temperature" patented technology

The invention discloses a remote sensing multi-parameter integrated inversion normal form method, system and equipment based on AI-Agent. According to the method, a deep learning neural network is dynamically driven through AI-Agent, a refining mechanism (RM)-Transformer-MoE size nested model, a physical method, a statistical method and expert knowledge are coupled, a DL-C-PSK normal form is constructed, a high-precision multi-source database is established based on the normal form, an appropriate radiation transfer equation is constructed through geophysical logical reasoning, and a high-precision multi-source database is established. And inversion of parameters such as surface temperature, surface emissivity, atmospheric water vapor content and near-surface air temperature is realized. According to a causal relationship between an input wave band and an output parameter, a direct synchronous inversion or iterative inversion mode is adopted to ensure multi-parameter high-precision synchronous inversion. Wherein the core of the deep learning neural network comprises RM logic derivation, SHAP model interpretation, Transform model architecture and a Transform-MoE size nested model, so that the interpretability, the adaptability and the precision of the model are improved. Through an AI-Agent driven RM-Transform-MoE nested model, deep coupling of physics-statistics-knowledge is realized, compared with a traditional SW method, the inversion precision is greatly improved, and verification shows that the technology is suitable for the fields of global climate observation, environment monitoring and the like.

The invention relates to an urban forest cooling function baseline construction and attenuation recovery evaluation method and system. The method comprises the following steps: acquiring day-by-day meteorological data of a research area to identify starting and ending dates of an extreme high temperature event; acquiring urban forest coverage distribution information in the research area and near-surface air temperature data or surface temperature data in a first date range, and calculating urban forest cooling efficiency data of each date in the first date range; calculating statistical characteristics of the urban forest cooling efficiency data of all dates of the beforehand reference period; determining the maximum attenuation value and date of the cooling efficiency during the extreme high-temperature event; and calculating the statistical characteristics of the urban forest cooling efficiency data of each sliding window by using the sliding windows, and calculating the recovery time and rate of urban forest cooling efficiency attenuation according to the baseline and a preset discrimination condition. It is ensured that attenuation is caused by the extreme high-temperature event, and the attenuation degree and the recovery process of the cooling function under the influence of the extreme high-temperature event are quantified.

The invention discloses a shipborne marine atmospheric boundary layer refractive index profile detection system and method, and relates to the technical field of marine atmospheric environment monitoring and electromagnetic wave propagation safeguard.The method comprises the steps that sea-air downlink infrared radiation spectrum data and sea surface air temperature, relative humidity and air pressure data are obtained; constructing a background atmosphere profile by using the reanalysis data, and correcting an initial profile bottom layer by using sea surface observation air temperature, relative humidity and air pressure data to form a prior state vector; constructing an inversion cost function including an observation residual term, a background prior term and a sea surface boundary constraint term, and performing inversion to obtain an atmospheric temperature profile and a relative humidity profile; and calculating an atmospheric refractive index profile according to the temperature profile, the relative humidity profile and the air pressure profile. According to the method, the marine atmospheric refractive index profile can be continuously obtained under the shipborne dynamic observation condition, and reliable data support is provided for marine electromagnetic propagation environment analysis and waveguide diagnosis.

The invention discloses a near-surface air temperature data downscaling method driven by multi-source collaborative variables, which relates to the technical field of air temperature data processing and comprises the steps of data preprocessing, sample division, downscaling model construction and air temperature data processing. The method comprises the following steps: firstly, introducing cloud cover, long / short wave radiation, display / latent heat flux and other elements as collaborative variables based on a mode output statistical thought, generating a multi-dimensional multi-source variable data set, and performing preprocessing such as resampling to form a complete data set; carrying out sample division and balance by adopting K-fold cross validation and a first-time adaptive decline algorithm to obtain a total training set and an independent validation set; stable and effective features are screened, and then three types of models including an elastic network, a Bayesian optimization random forest and a neural architecture search-based long and short term memory network are constructed; the to-be-processed data is input into the model to generate high-resolution air temperature data, the data precision is ensured through multi-dimensional verification, systematic deviation is effectively restrained, nonlinear correlation and extreme air temperature correction capacity are enhanced, the space-time stability is improved, and the method is suitable for climatic analysis, ecological environment evaluation and other scenes.

This invention discloses a high-resolution spatialization method for near-surface air temperature in glacial regions. This method integrates measured data from high-altitude meteorological stations, satellite remote sensing data, and machine learning-optimized spatial interpolation techniques to construct a continuous temperature field under complex terrain conditions. First, by fusing station-measured and satellite remote sensing data, a data complementarity method suitable for sparsely observed areas is established. Based on a machine learning optimization algorithm, spatialized glacial temperature records from meteorological station observations are used as training data, while satellite remote sensing data with broader coverage is employed. Surface temperature retrieved through a radiative transfer model is used as input features to correct the surface temperature of the study area, generating a spatial distribution of air temperature that better matches ground observations. Finally, by fusing altitude and vertical temperature lapse rate as core constraint variables and combining benchmark verification based on station observation data, the accuracy of near-surface air temperature spatialization calculations in high-altitude complex terrain areas is improved.

The application discloses a shipborne marine atmospheric boundary layer refractive index profile detection system and method, relates to the technical field of marine atmospheric environment monitoring and electromagnetic wave propagation guarantee, and comprises the following steps: acquiring sea-air downward infrared radiation spectrum data and sea surface air temperature, relative humidity and air pressure data; constructing a background atmospheric profile by using reanalysis data, and correcting the initial profile bottom layer by using the sea surface observation air temperature, relative humidity and air pressure data to form a prior state vector; constructing an inversion cost function containing an observation residual term, a background prior term and a sea surface boundary constraint term, and inverting to obtain an atmospheric temperature profile and a relative humidity profile; and calculating an atmospheric refractive index profile according to the temperature profile, the relative humidity profile and the air pressure profile. The application can continuously acquire the marine atmospheric refractive index profile under the shipborne dynamic observation condition, and provides reliable data support for marine electromagnetic propagation environment analysis and waveguide diagnosis.

The application discloses a kind of near-surface air temperature direct reduction rate generation method based on MODIS data, belong to remote sensing near-surface air temperature direct reduction rate generation technical field.The present application directly generates near-surface air temperature data using MODIS data, reduces the uncertainty brought by many auxiliary parameters in the generation process of near-surface air temperature;Using moving window convolution, strictly control the data in moving window, and then generate high temporal resolution, spatially continuous near-surface air temperature direct reduction rate product.The present application reduces the dependence on a variety of auxiliary ground variables and meteorological station measured values in the traditional near-surface air temperature direct reduction rate estimation method;The present application judges whether the field pixel of remote sensing data meets the requirements pixel by pixel, changes the size of moving window according to the judgment result, strictly controls the input data of model, to obtain credible daily spatially continuous SATLR;The near-surface air temperature direct reduction rate produced by the present application has the characteristics of high temporal resolution, spatially continuous, etc.