153 results about "Microwave radiometer" patented technology

The invention belongs to the technical field of ocean remote sensing, and relates to a spaceborne microwave radiometer tropical cyclone wind speed inversion method based on physical constraint deep learning, comprising the following steps: acquiring tropical cyclone parameter information; extracting multi-band brightness temperature data of the satellite-borne microwave radiometer in a corresponding space-time range, and constructing a sample data set; a deep learning inversion algorithm model with physical constraints is loaded and trained; the physical constraint deep learning inversion algorithm model comprises an input layer, a network layer, a physical layer and an output layer; the network layer is composed of a residual neural network, the physical layer is composed of a D matrix remote sensing statistical formula and provides physical constraints for the whole model, and the D matrix is a nonlinear D matrix; and outputting the tropical cyclone wind speed in the current space-time range. According to the method, the brightness temperature information of the satellite-borne microwave radiometer is obtained by utilizing the tropical cyclone trajectory information, and the network model with physical information is constructed by utilizing the combination of the D matrix equation and the neural network, so that more accurate and high-precision tropical cyclone wind speed information is obtained.

The invention provides an HY-2A ocean water vapor inversion method based on machine learning, and the method comprises the steps: constructing a high-quality HY-2A scanning microwave radiometer data set through the data preprocessing, matching, feature extraction and normalization processing of HY-2A satellite scanning microwave radiometer data and ERA5 reanalysis data. A plurality of machine learning models are used for training and testing, Bayesian optimization is used for realizing hyper-parameter automatic adjustment, an optimal solution in finite time is obtained, an SHAP method is used for explaining the models, contribution of each characteristic variable is clear, interpretability of the used machine learning models is improved, and finally high-precision inversion of the water vapor over the sea is realized. The method has efficient calculation performance, can realize rapid processing of large-scale marine meteorological data, and improves the interpretability of a machine learning model. The method has important application value in numerical weather forecast, ocean extreme weather forecast, climate monitoring and other geophysical and meteorological fields.

The invention belongs to the technical field of ocean remote sensing detection, and relates to a sea temperature inversion method based on K-Ka band microwave radiometer weak signal enhancement deep learning. Parameters of measured data of the microwave radiometer and reanalysis sea gas parameter data are selected; determining the size of a space-time window based on the brightness temperature characteristics of K and Ka wavebands, and carrying out space-time matching to establish a modeling data set; performing quality control on the modeling data set based on indexes such as quality identification, offshore distance, brightness temperature abnormity and air-sea parameter abnormity; normalizing the modeling data set and splitting the modeling data set into a training set, a verification set and a test set; and constructing a weak signal enhancement DNN model based on the K-Ka band microwave radiometer by using the training set and the verification set, and performing inversion by using the test set to obtain a sea surface temperature product. According to the method, the precision of performing sea surface temperature inversion by using the K and Ka wave band brightness temperatures of the microwave radiometer is improved, the problem of insufficient precision is solved, and a new possibility is provided for inversion of SST on a finer scale.

The invention discloses an airplane ice accretion monitoring method fusing millimeter wave cloud radar and ground-based microwave radiometer data, which comprises the following steps: step 1, taking temperature profile and relative humidity profile data monitored by a ground-based microwave radiometer in a test area in real time as input quantities to obtain airplane ice accretion index values corresponding to all profile data; step 2, obtaining a reflectivity Z profile of liquid water particles in a test area and a total liquid water value LWP on an observation path; step 3, carrying out inversion to obtain a liquid water content LWC profile in the cloud on the observation path; step 4, taking an overlapped area of an area of which the temperature profile data of the foundation microwave radiometer is less than 0 DEG C and an area of which the inverted liquid water content data of the cloud is greater than 0, a supercooled water area in the cloud is formed; and step 5, analyzing whether the ice accumulation area in the step 1 and the supercooled water area in the step 4 are overlapped or not, if yes, representing that ice accumulation occurs in the air, and if not, representing that no ice accumulation occurs in the air. According to the method disclosed by the invention, a millimeter wave cloud radar and ground-based microwave radiometer active and passive combined detection technology is adopted, the total amount of liquid water and a water vapor profile in the airport airspace are detected, the distribution of supercooled liquid water in cloud in the airport airspace is inverted, and the distribution of a potential icing area of an aircraft is monitored in real time.

The invention discloses a microwave cold noise source fusing TEC temperature control and noise temperature compensation technologies, and belongs to the technical field of microwave radiometer calibration. The device comprises a cold source module, a noise compensation module and a constant-temperature control module, wherein the cold source module generates a low-temperature noise signal through a field-effect tube and a terminal resistor; the noise compensation module detects environment temperature change in real time based on a thermistor and a Wheatstone bridge, drives a noise diode to generate a compensation signal, couples the compensation signal with a cold source noise signal after attenuation, and counteracts noise temperature deviation caused by the environment temperature. The constant temperature control module adopts a platinum resistance sensor and a PID algorithm to control a Peltier element in a closed-loop mode, and accurate adjustment (+ / -0.1 DEG C) is achieved. According to the invention, noise compensation and TEC negative feedback temperature control technologies are combined, so that the noise temperature of the system is stabilized in a range of + / -0.1 K for a long time, the measurement precision and reliability of the microwave radiometer in an outdoor complex environment are remarkably improved, and the method is suitable for scenes of remote sensing detection, unmanned aerial vehicle monitoring and the like.

The invention discloses a satellite-borne synthetic aperture microwave radiometer multi-angle brightness temperature noise suppression method, which belongs to the technical field of microwave remote sensing, and comprises the following steps: acquiring historical marine physical parameters, and calculating to obtain multi-angle brightness temperature according to the historical marine physical parameters; fitting the multi-angle brightness temperature, and establishing a relational expression of the brightness temperature and the observation angle under different physical parameters; and calculating the slope of the fitting curve, calculating the deviation between the brightness temperature of the multiple angles and the brightness temperature of any single angle, and establishing a deviation lookup table of the brightness temperature of the multiple angles and the brightness temperature of the specific angle under different physical parameters. The brightness temperature correction value of the corresponding angle is searched in the lookup table, and the brightness temperature of SMOS multi-angle observation is mapped to a single angle; and averaging the mapped single-angle brightness temperature to obtain the noise-suppressed single-angle brightness temperature.

The invention provides an active and passive combined microwave remote sensing detection method for earth surface air pressure and air pressure profile, which comprises the following steps: by combining a satellite-borne / airborne millimeter wave differential absorption radar and a satellite-borne / airborne microwave radiometer and utilizing oxygen differential absorption measurement, obtaining accurate land / ocean surface air pressure data; and the air pressure profile is further obtained by combining temperature and humidity profile data measured by a satellite-borne / airborne microwave radiometer. Compared with the prior art, the method has the advantages that active and passive microwaves are adopted for combined detection, detection information obtained by a microwave radiometer is complemented, calculation of the surface pressure is enhanced, and the surface pressure inversion precision is improved; according to the method, the surface pressure value can be obtained, and the atmospheric pressure profile can also be obtained. According to the method, accurate surface pressure detection can be realized, and the atmospheric pressure profile can be further deduced by combining the temperature profile and the humidity profile observed by the microwave radiometer.

The invention provides a novel broadband simulation multiple correlation type microwave radiometer, and relates to the technical field of passive remote sensing detection. The system comprises a double-path correlation radio frequency front-end unit, an intermediate-frequency filtering and amplifying unit and an analog multiple correlation unit, wherein the analog multiple correlation unit comprises two analog multiple correlation channels, each analog multiple correlation channel comprises a broadband multiplication unit and an active differential filtering unit, and the broadband multiplication units are used for carrying out differential conversion on input same signals and orthogonal signals and carrying out correlation operation; and performing active differential filtering processing on the signal after the correlation operation through an active differential filtering unit, and outputting two paths of orthogonal differential parameters. The analog multiple correlation unit designed by the invention adopts a full-link differential design, including differential passive / active filtering, amplification and transmission, the design can provide amplitude twice as large as that of a single-ended signal and better linearity under the same power supply voltage, and meanwhile, the problems of direct-current drift and common-mode interference suppression are solved.

The invention provides an intelligent quality control and inversion method for electric power meteorological multi-source data, and relates to the field of data processing. In the method, a multi-view polarized brightness temperature vector structure is constructed by using original brightness temperature observation data acquired by a plurality of satellite-borne microwave radiometers in a near-synchronous orbit intersection area, and a multi-dimensional radiation transmission equation set driven by an earth ellipsoid path integral model is input to generate a brightness temperature prediction result; an inversion optimization model is constructed based on view angle invariant residual constraint, initialization is carried out based on historical data and ground data, and variational inversion solving is carried out to obtain a joint inversion result; and evaluating the credibility through a profile quality vector, and finally supporting stability early warning and load correction in electric power meteorology. By implementing the technical scheme provided by the invention, the quality control and inversion precision of the power meteorological multi-source data profile can be improved.

The invention discloses a direct assimilation method for a ground-based microwave radiometer, and relates to the technical field of meteorological observation, and the method comprises the steps: calling an RTTOF-gb rapid radiation transmission mode, enabling a derivation type in a WRFDA system to correspond to an RTTOF-gb derivation type, enabling RTTOV, RTTOF-gb and the WRFDA system to be coupled at the same time, and converting a background field of a numerical weather forecast mode into simulated brightness temperature data; the source of the deviation and the nonlinear relation between the source and the deviation are considered, a deviation correction forecast factor is calculated according to the original observation brightness temperature and the background field, deviation correction is conducted on the original observation brightness temperature, and the corrected observation brightness temperature is obtained; and based on the corrected observation brightness temperature data, performing three-dimensional variation assimilation processing on the background field to obtain an analysis field, and outputting a diagnosis file. According to the method, a good deviation correction effect can be achieved, adjustment can be conveniently carried out according to actual application requirements, RTTOF-gb and RTTOV can be used at the same time, and combined direct assimilation of various foundation microwave radiometers and satellite-borne microwave radiometers can be achieved.

The invention relates to a satellite-borne microwave radiometer cold air calibration attitude planning method based on multi-objective optimization, and belongs to the field of satellite microwave remote sensing, and the method comprises the steps: building a satellite attitude kinematics model and an attitude dynamics model through a geocentric equator inertial coordinate system, an orbital coordinate system and a satellite body coordinate system; establishing a brightness temperature sum model received by the microwave radiometer in the cold air calibration process; according to the method, a microwave radiometer receiving brightness temperature sum, brightness temperature fluctuation, platform maneuvering capability, energy and a satellite sensor field of view are comprehensively considered, a multi-target optimization model of microwave radiometer cold air calibration consideration constraints is established, solving is performed, constraint conditions are established, and a solution or a solution set is obtained. According to the method, the brightness temperature sum and the brightness temperature fluctuation in the observation area of the microwave radiometer in the cold air calibration process are optimized by adopting multi-objective optimization, and the on-orbit cold air calibration effect and the system reliability of the satellite-borne microwave radiometer are improved.

The invention discloses a construction and inversion method of a sea surface wind speed inversion model based on a dual-frequency wind field radar, the sea surface wind speed inversion model comprises a sea surface wind speed inversion model and a geophysical model function, and scattering measurement data, microwave radiometer data and sea surface wind field data are acquired; taking latitude and longitude and time information of the scattering measurement data as a reference, and respectively carrying out quasi-synchronous matching on the microwave radiometer data and the sea surface wind field data with the scattering measurement data by adopting a space-time matching threshold method to obtain an active and passive data set; on the basis of sea surface radiation and scattering characteristics, a geophysical model function for wind direction inversion and a sea surface wind speed inversion model capable of inhibiting rainfall influence are constructed by utilizing the characteristic that different frequencies have different penetrating power and adopting an active and passive spectrum gradient ratio, and the sea surface wind speed and the sea surface wind direction of a high-wind-speed sea surface can be obtained at the same time; the technical problem that it is difficult to quantitatively measure the sea surface wind speed and the sea surface wind direction of the high-wind-speed sea surface wind field at the same time in the prior art is solved.

The invention discloses a space-time matching comparison and uniformity evaluation method for a three-dimensional atmosphere live field fusion product. The method comprises the steps of constructing a multi-source data verification framework, implementing refined space-time matching, executing multi-level quality control, comprehensively inspecting and analyzing and outputting a product specification. By constructing a multi-source collaborative verification framework, integrating sounding, microwave radiometer, satellite and foundation observation data, and establishing a refined space-time matching model and a multi-level quality control system, the error condition of a live product can be quantitatively given. The method is suitable for space-time matching comparison and homogeneity inspection of air temperature, humidity and horizontal wind speed / wind direction elements, and supports meteorological model optimization and low-altitude economic application.

The invention discloses a differential measurement-based satellite-borne synthetic aperture microwave radiometer imaging correction method, which comprises the following steps of: respectively selecting a reference area and a correction area in a global range, and respectively intercepting scientific data and auxiliary data in a specific time period in the reference area and the correction area based on load normal earth observation data; averaging the visibility functions intercepted in the reference area to obtain a reference visibility function; generating a reference brightness temperature and a correction brightness temperature through a simulation model by using the auxiliary data intercepted in the reference area and the correction area respectively; performing difference and inversion processing on the normal earth observation visibility function to be subjected to imaging processing by using the reference visibility function to obtain a difference inversion brightness temperature; calculating a correction coefficient by using the reference visibility function, the reference brightness temperature, the visibility function intercepted in the correction area and the correction brightness temperature; and correcting and compensating the differential inversion brightness temperature by using the correction coefficient and the reference brightness temperature to obtain the final inversion brightness temperature.

The invention relates to an atmospheric boundary layer height inversion method based on a UNet + + network and a SimAM attention mechanism, and the method comprises the steps: firstly, making an image segmentation data set according to the obtained micro-pulse laser radar data and microwave radiometer data, in the data set, enabling an original image to be a gray-scale map of a normalized relative back scattering signal, and enabling the original image to be a gray-scale map of a normalized relative back scattering signal; the annotation image is a binary image of the height of the atmospheric boundary layer obtained through inversion according to data of the microwave radiometer, and meanwhile, the original image and the annotation image need to be matched in time and space; then, taking UNet + + as a basic framework, introducing a SimAM attention mechanism into jump connection in the basic framework, constructing a deep learning model SimAM-UNet + +, and training the deep learning model by using a data set; and finally, the predicted atmospheric boundary layer height can be obtained through the trained deep learning model. According to the method, the SimAM attention mechanism is introduced into UNet + +, and effective inversion of the atmospheric boundary layer height under the complex weather condition is realized.

The invention relates to a system deviation correction method for improving the salinity inversion precision of an interference type microwave radiometer, and relates to the technical field of satellite ocean remote sensing data processing. The method comprises the following steps of: acquiring an area, strictly purifying and screening observed brightness temperature data of a preset time window in the area to eliminate the influence of radio frequency interference, sun and moon pollution and the like, acquiring high-purity original data, calculating simulated brightness temperature by utilizing a radiation transmission model, and subtracting the simulated brightness temperature from the purified observed brightness temperature to obtain a brightness temperature deviation sample; and then a robust statistical method based on a sliding window and a median is adopted to carry out statistical calculation on the deviation sample to obtain a stable and reliable deviation correction value, and finally a two-dimensional lookup table is generated and applied to sea surface salinity inversion. According to the method, the observation brightness temperature for salinity inversion can be efficiently and accurately corrected from the source, and the contradiction between stability and adaptability in the prior art is solved.

The invention belongs to the technical field of atmospheric microwave remote sensing and monitoring, and relates to a rapid temperature and humidity profile inversion method for a multi-frequency atmospheric microwave radiometer. Acquiring a brightness temperature data set of the multi-frequency atmospheric microwave radiometer, performing space-time matching on the brightness temperature data set and corresponding ERA5 reanalysis or sounding balloon temperature and humidity profile data, constructing a matched data set, and dividing the matched data set into a test set, a training set and a verification set; establishing an atmosphere temperature and humidity profile inversion model based on a CNN-LSTM combined neural network; and training the model by using the training set, guiding the model optimization process by using the verification set, finally inputting multi-frequency brightness temperature data measured by the multi-frequency microwave radiometer into the trained model, and carrying out inversion to obtain an atmosphere temperature and humidity profile. According to observation data of the multi-frequency atmosphere microwave radiometer, regional atmosphere temperature and humidity profile data are rapidly and accurately obtained, and efficient inversion of the temperature and humidity profile is achieved; the vertical detection advantage of the multi-frequency microwave radiometer is exerted, the inversion efficiency is improved, and the method has a wide application prospect.

The invention provides an atmospheric temperature and humidity profile inversion method, device and equipment, a medium and a program product, and relates to the technical field of atmospheric remote sensing, and the method comprises the steps: collecting the brightness temperature data of the atmosphere, the cloud feature data of the atmosphere and the ground temperature, humidity and pressure data; inputting the brightness temperature data, the cloud feature data and the ground temperature, humidity and pressure data into a meteorological profile inversion model to obtain an atmospheric temperature and humidity profile output by the meteorological profile inversion model; wherein the meteorological profile inversion model comprises a multi-modal feature extraction layer, a double-flow collaborative network layer and a physical-data hybrid constraint layer. According to the method, cloud feature data and ground temperature, humidity and pressure data are introduced into atmosphere temperature and humidity profile inversion of the microwave radiometer, and an artificial intelligence algorithm is introduced to realize multi-modal feature fusion and automatically adapt to different weather conditions, so that the inversion precision of the atmosphere temperature and humidity profile is improved.

The invention is directed to a method for detecting moisture in a roof structure comprising measuring microwave emission of the roof structure, particularly by using a passive microwave radiometer. The invention is also directed to use of a passive microwave radiometer for detecting leakages in a roof structure.

The invention discloses a microwave radiometer stripe elimination preprocessing method based on moving median smoothing, and the method comprises the following steps: 1, carrying out the circular scanning through a microwave radiometer, and obtaining a heat source count value Cw, a cold source count value Cc, an observation target count value Ce, a heat source brightness temperature Tw, and a cold source brightness temperature Tc; step 2, performing noise smoothing on moving medians between scanning lines on the heat source observation count value Cw and the cold source count value Cc to obtain a smoothed heat source observation count value and a smoothed cold source count value; and step 3, performing two-point calibration by using the heat source brightness temperature Tw and the cold source brightness temperature Tc obtained in the step 1 and the smoothed heat source observation count value and the smoothed cold source count value obtained in the step 2 to obtain the stripe-eliminated observation target brightness temperature Te. The method provided by the invention can effectively solve the problem of influence of stripe noise on the data quality of the microwave radiometer in the existing stripe elimination method.

The present invention discloses a method for determining an on-orbit calibration nonlinear coefficient of a satellite-borne microwave radiometer before launch. The method comprises: sequentially observing three calibration blackbodies by the satellite-borne microwave radiometer to be measured within a scanning cycle to obtain observation voltages and brightness temperatures corresponding to three different temperatures; the three calibration blackbodies comprise: a cold calibration blackbody at the boiling point of liquid nitrogen, a hot calibration blackbody at ambient temperature, and a calibration blackbody at an intermediate temperature between the cold and ambient temperatures; obtaining a secondary calibration curve from the observation voltages and brightness temperatures at the three different temperatures; determining virtual cold space data from the secondary calibration curve through virtual cold space observation; if observation data at an intermediate value between the virtual cold space data and the hot calibration blackbody data can be determined from the virtual cold space data and the hot calibration blackbody data, calculating the nonlinear coefficient from the virtual cold space data and the hot calibration blackbody data; otherwise, calculating the nonlinear coefficient from the virtual cold space data, the hot calibration blackbody data, and the intermediate temperature blackbody data.

This application provides a method, device, and computer-readable storage medium for evaluating the on-orbit calibration error of a microwave radiometer calibration system used in geostationary orbit. The application evaluates the on-orbit calibration error of the microwave radiometer calibration system by determining the errors of the calibration cold source, calibration heat source, Earth observation radiation brightness temperature, and Earth target brightness temperature. By separately evaluating the errors of the calibration cold source, calibration heat source, Earth observation radiation brightness temperature, and Earth target brightness temperature in the microwave radiometer calibration system used in geostationary orbit, each error is quantified, thus quantifying the on-orbit calibration error of the microwave radiometer calibration system. Furthermore, the different radiation transmission paths are considered during the evaluation of each error, making the evaluation of the sources of on-orbit calibration error of the microwave radiometer calibration system used in geostationary orbit not only effective and accurate but also highly implementable.

The application relates to a reconfigurable metasurface for electrically-controlled scanning of a real-aperture microwave radiometer, which comprises a plurality of array-distributed basic units, the basic unit comprising a top metal patch, a first dielectric layer, a metal reflection layer, a second dielectric layer and a bottom metal layer which are sequentially stacked from top to bottom; the top metal patch comprises two cross-connected I-shaped patches and a triangular metal branch located in the cross region and having a certain gap with the I-shaped patch; the I-shaped patch comprises a straight arm and end arms located at both ends of the straight arm and having a certain gap with the straight arm; a PIN diode is connected between the straight arm and the end arms; the end arms are connected with each other through a metal feed line, and an isolation resistor is arranged on the metal feed line; the application dynamically controls the reflection phase according to the working state of the diode combination, and has high reflectivity and reflection bandwidth and small loss.

The utility model provides a multichannel millimeter wave radiometer signal intensifier. Relates to the technical field of microwave radiometers. The multi-channel millimeter wave radiometer comprises a mounting plate, a multi-channel millimeter wave radiometer and a fixing mechanism, a multi-channel millimeter wave radiometer and a signal intensifier are fixedly installed on the installation plate, a plurality of jacks are formed in one side of the multi-channel millimeter wave radiometer, second connecting terminals are arranged in the jacks, a wire is connected to the signal intensifier, and one end of the wire is connected with a first connecting terminal. The multichannel millimeter wave radiometer signal enhancer provided by the utility model has the following advantages: through cooperation of the components, the multichannel millimeter wave radiometer and the signal enhancer can be rapidly assembled and disassembled; in addition, the effect of avoiding poor connection between the first connecting terminal and the second connecting terminal can be achieved, and the effect of protecting the jacks can be achieved while the first connecting terminal is pulled out.

The present invention discloses a test device and a test method for the backward leakage of an antenna reflector of a spaceborne microwave radiometer, which includes an antenna reflector, a moving component, a metal bucket, a horn antenna, a standard radiometer, a rotating device, an angle measuring device, and a data acquisition device. The present invention measures the backward leakage of the antenna reflector directly by establishing a low brightness temperature test environment, changing the backward leakage brightness temperature of the antenna reflector, and output change of the standard radiometer. In the present invention, the standard radiometer is used to directly test the backward leakage of the antenna reflector, so the test accuracy is higher; in the present invention, the rotating device is used to simulate the on-orbit movement trajectory of the horn antenna of the spaceborne microwave radiometer, and the backward leakage of the antenna reflector at multiple positions of the horn antenna can be tested, and the test time is short; in the present invention, the rotating device can move multiple horn antennas simultaneously, and multiple frequency points can be tested simultaneously; it has good popularization and application value.

[PROBLEM] Provided are a weather observation device, a weather observation system, an estimation method, and a computer program. [SOLUTION] A weather observation device comprises: an acquisition unit for acquiring observation data based on received radio waves of a microwave radiometer and an environmental temperature of an environment in which the microwave radiometer is installed; a conversion unit for converting the observation data into first luminance temperature data having luminance temperature as a physical dimension; an estimation unit for estimating second luminance temperature data which serves as a base when calculating the luminance temperature data in the sky above the microwave radiometer from the environmental temperature; and a calculation unit for calculating the luminance temperature data in the sky above the microwave radiometer from the first luminance temperature data and the second luminance temperature data.

The invention discloses an in-orbit calibration method for correcting self-radiation of a heat mirror of a microwave imager based on reference radiation. The method comprises the following steps: calculating an included angle between the heat mirror of the microwave imager and the sun; calculating the earth observation brightness temperature of the microwave imager; calculating the observed brightness temperature of the reference microwave radiometer; simulation brightness temperature of the reference microwave radiometer and the microwave imager is obtained based on radiation transmission model simulation; calculating an observation brightness temperature deviation and a simulation brightness temperature deviation, and calculating a system error between the reference microwave radiometer and the microwave imager; based on the system error, the included angle between the microwave imager heat mirror and the sun is adopted for function relation fitting, and the heat mirror self-radiation brightness temperature of the reference microwave radiometer is calculated; the included angle between the microwave imager heat mirror and the sun is calculated on orbit in real time, and the earth observation brightness temperature of the microwave imager is corrected based on the self-radiation brightness temperature of the heat mirror. The self-radiation of the heat mirror is solved in real time by taking double deviations of observation brightness temperature and simulation brightness temperature as constraints, and the problem that the temperature of the heat mirror of the microwave imager cannot be actually measured in orbit is solved.

The invention discloses a method for inverting warm cloud microphysical parameters based on a ground-based millimeter wave cloud radar and a microwave radiometer, and the method comprises the steps: 1, obtaining the observation data of the millimeter wave cloud radar, and obtaining a whole-layer liquid water path and a temperature gallery line through the microwave radiometer; 2, identifying warm cloud in millimeter wave cloud radar observation by using a temperature gallery line T; 3, constructing an initial liquid water content profile based on the reflectivity factor and the particle concentration in the warm cloud layer, and calculating an initial liquid water path of the warm cloud layer; 4, the whole-layer liquid water path obtained by the microwave radiometer is used as whole-layer constraint, the initial particle concentration and the initial liquid water content at the vertical height in the warm cloud layer are calibrated according to the proportion, the adjusted warm cloud layer liquid water content and the adjusted warm cloud layer inner particle concentration are obtained, and a physical boundary constraint interval is applied to the particle concentration; and 5, calculating the effective radius of the particles in the warm cloud layer according to the adjusted liquid water content of the warm cloud layer and the particle concentration in the warm cloud layer. According to the method, high-precision warm cloud microphysical parameter vertical distribution can be obtained.

The present application relates to a kind of sea ice surface snow depth combined estimation method, based on the characteristics that microwave radiometer brightness temperature decreases with the increase of sea ice surface snow depth, FY brightness temperature data is used to calculate the brightness temperature of open water at different frequencies, then the brightness temperature of sea ice surface of 10 sub-channels and 20 polarization gradient rate characteristics are calculated using open water brightness temperature and FY brightness temperature data.The OIB airborne data is gridded, and the daily average OIB snow depth of 12.5 km resolution is obtained.The correlation between 30 brightness temperature characteristics and OIB snow depth is calculated, and the linear regression model and machine learning model of one-year ice and multi-year ice surface snow depth estimation are established by selecting 5 sub-features with high correlation, thereby developing the combined estimation model of snow depth.The above is the sea ice surface snow depth combined estimation method proposed by the present application, which improves the estimation accuracy of polar sea ice surface snow depth.

The application discloses a kind of methods and systems for calculating the rotation angle of spaceborne L-band microwave radiometer, method includes: obtaining the satellite orbit parameters and the brightness temperature data of ocean time of spaceborne L-band microwave radiometer;Simulate horizontal polarization, vertical polarization and cross-polarization radiation brightness temperature data;The stokes radiation brightness temperature data obtained by simulation is converted into the brightness temperature data under antenna coordinate system using rotation matrix;Using joint cost function, the above-mentioned simulation and conversion are carried out using nonlinear iteration until the rotation angle change is less than the first set threshold and the sea surface salinity change is less than the second set threshold, solve the rotation angle and sea surface salinity;According to the rotation angle, recalculate the rotation matrix;According to the new rotation matrix, the obtained brightness temperature data is converted into corresponding horizontal polarization TH, vertical polarization TV, cross-polarization T3 and T4, complete the accurate conversion of spaceborne L-band microwave radiometer brightness temperature.