9 results about "Cloud base height" patented technology

The invention provides a FY-4 offshore cloud bottom height correction method considering a buoy ceilometer, and belongs to the technical field of offshore cloud bottom height correction.According to the method, the cloud bottom height data of a buoy ceilometer and a FY-4 satellite are collected, sea surface reflection pollution correction is carried out on the satellite data, and a cloud layer structure is identified by using K-means clustering; extracting multi-scale fractal dimension features of buoy and satellite data and calculating a difference parameter, organizing correction data into a four-dimensional correction tensor, decomposing and extracting a low-rank structure by adopting CANDECOMP, and inputting a decomposition result and the fractal dimension difference parameter into a cloud base height bidirectional optimization model; dynamic balance between precision improvement and space-time stability maintenance is realized through a game mechanism of a precision optimization sub-model and a stability optimization sub-model in the model, and the technical problem that the marine cloud bottom height precision and the space-time stability of satellite inversion are difficult to consider at the same time is solved.

1. Name of the product in this design: Cloud Gauge. 2. Purpose of this design: This design is used to measure data such as cloud base height, cloud thickness, and number of cloud layers. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

This application provides a cloud measurement system and method based on a wave glider. By integrating a laser cloud-measuring radar with a marine meteorological observation instrument onto a wave glider platform with ultra-long endurance, autonomous navigation, and virtual mooring capabilities, a sea-based mobile cloud observation system is constructed. This system overcomes the inherent shortcomings of existing satellite remote sensing observations, such as discontinuity and lack of vertical structure information, as well as the high cost, poor maneuverability, and limited coverage of ship and buoy observations. It achieves long-term, continuous, and mobile observation of cloud systems over vast ocean areas and can acquire high-precision cloud base height, vertical structure, and conventional meteorological elements from the sea surface, significantly improving the spatiotemporal continuity and data quality of marine meteorological observation.

The application provides a cloud bottom height inversion method, and belongs to the technical field of cloud bottom height inversion, and comprises the following steps: obtaining a cloud echo signal; segmenting the cloud echo signal, and setting a threshold value for each segment; dividing an inversion interval, and obtaining a forward difference echo signal sequence by differentiating the cloud echo signal in the inversion interval; selecting points from positive to negative and from negative to positive in the sequence to form a difference mutation sequence; selecting a local increasing interval from the difference mutation sequence, and judging whether the maximum slope in the local increasing interval exceeds a noise difference standard deviation threshold value; if yes, the point is determined to be a non-noise wave peak point; for each segment of the cloud echo signal, if the wave bottom, the wave top and the wave peak of the cloud echo signal all exceed the threshold value, and the extinction coefficient is greater than 0, the cloud echo signal is determined to be a final cloud echo signal; and the cloud bottom height is inverted by using the final cloud echo signal. The method can invert the cloud bottom height.

The invention provides an accurate ceilometer comparison and measurement method, and belongs to the technical field of ceilometers, the method comprises the steps: building an aerosol scattering feature discrimination matrix, removing an aerosol layer, reserving a real cloud layer signal, employing a cloud layer boundary Bayesian inference algorithm based on maximum likelihood estimation to obtain the posterior probability distribution of cloud base height, and carrying out the comparison and measurement of the cloud base height. Constructing a double-layer game optimization model to improve the cloud layer recognition precision and minimize the data registration error, calculating the cloud layer movement speed by adopting a cloud layer motion vector estimation algorithm, carrying out space-time interpolation correction, and calculating a correlation coefficient and a linear regression slope to judge the comparison qualification. And increment deviation analysis is carried out on all maximum cloud height values to judge full-scale performance, so that the technical problem that the comparison accuracy is reduced due to space-time mismatching of observation data of a reference instrument and a tested instrument caused by dynamic movement of the cloud layer is solved.

The application provides a domestic passive meteorological satellite cloud bottom height high-precision inversion method and system, and belongs to the field of atmospheric cloud parameter remote sensing inversion and quantitative remote sensing mechanism. The application fuses satellite multi-channel atmospheric top reflectivity observation, brightness temperature observation and atmospheric temperature profile reanalysis data, develops a complex nonlinear feature extraction and modeling method, improves the nonlinear mapping capability among the atmospheric top reflectivity, the brightness temperature and the cloud bottom height, combines the whole period infrared channel characteristics and the stratification information, enhances the night and all-time inversion capability, improves the generalization adaptability of the model through the multi-source sample expansion and the stacking learning strategy, designs the sample expansion and the auxiliary training mechanism, effectively alleviates the problem of insufficient high-quality training data, and finally realizes the high-precision inversion of the all-time cloud bottom height suitable for the domestic stationary or polar orbit meteorological satellite.

This invention provides an accurate cloud height comparison method, belonging to the field of cloud height technology. The invention establishes an aerosol scattering feature discrimination matrix to eliminate the aerosol layer and retain the true cloud signal. It employs a maximum likelihood estimation-based Bayesian inference algorithm for cloud boundaries to obtain the posterior probability distribution of cloud base height. A two-layer game optimization model is constructed to improve cloud identification accuracy and minimize data registration errors. A cloud motion vector estimation algorithm is used to calculate cloud movement speed and perform spatiotemporal interpolation correction. Correlation coefficients and linear regression slopes are calculated to determine the pass / failability of the comparison. Incremental deviation analysis is performed on all maximum cloud height values ​​to determine full-range performance. This invention solves the technical problem of decreased comparison accuracy caused by spatiotemporal mismatch between the observation data of the reference instrument and the tested instrument due to dynamic cloud movement.

The application provides a FY-4 sea cloud base height correction method considering a buoy cloud height instrument, and belongs to the technical field of sea cloud base height correction. The application collects the buoy cloud height instrument and FY-4 satellite cloud base height data, performs sea surface reflection pollution correction on the satellite data, identifies the cloud layer structure by using K-means clustering, extracts the multi-scale fractal dimension features of the buoy and satellite data and calculates the difference parameters, organizes the correction data into a four-dimensional correction tensor, extracts the low-rank structure by using CANDECOMP decomposition, inputs the decomposition result and the fractal dimension difference parameters into a cloud base height bidirectional optimization model, and realizes the dynamic balance between the accuracy improvement and the spatiotemporal stability maintenance in the model by the game mechanism of the accuracy optimization sub-model and the stability optimization sub-model, so that the technical problem that the sea cloud base height precision and the spatiotemporal stability of the satellite inversion are difficult to be considered is solved.

The invention discloses a cloud base height forecasting method based on multi-factor dynamic analysis, relates to the technical field of meteorological numerical forecasting and atmospheric boundary layer analysis, and aims to predict the height of a cloud base by identifying the structural feature that the internal humidity of a mixed layer changes along with the height instead of only depending on the average relative humidity of the mixed layer in the cloud base height forecasting process. A continuous humidity increasing section is extracted, and the position of a potential condensation layer is determined, so that the initial condition of air block lifting calculation can more accurately reflect the actual water vapor distribution condition in the mixing layer. Under the condition that a local wet layer or a local high-humidity area exists, a wet layer structure closer to an actual condensation occurrence position can still be identified, so that the cloud base height calculation process is closer to a real atmospheric state; by calculating the thickness of the mixed layer, the vertical range of the mixed layer can be definitely limited, and the subsequent humidity structure analysis can be carried out aiming at the important region where the low cloud is formed, so that the cloud bottom height analysis process corresponds to the actual atmospheric boundary layer structure.