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A Boundary Layer Height Extraction Algorithm Based on Random Sampling Fitting

A technology of boundary layer height and random sampling, which is applied in the field of atmospheric detection to achieve good feasibility and stability.

Active Publication Date: 2022-02-08
CENT SOUTH UNIV
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Problems solved by technology

These algorithms have their applicable conditions, and currently there is no method that can be fully applied to automatically extract BLH

Method used

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  • A Boundary Layer Height Extraction Algorithm Based on Random Sampling Fitting
  • A Boundary Layer Height Extraction Algorithm Based on Random Sampling Fitting
  • A Boundary Layer Height Extraction Algorithm Based on Random Sampling Fitting

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Embodiment Construction

[0036] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in various ways defined and covered by the claims.

[0037] see Figure 1a and Figure 1b The boundary layer height extraction algorithm based on random sampling fitting includes the following steps 1 to 3:

[0038] Step 1) Initial data selection: The ASR data from the Level 1 product of CALIOP of the CALIPSO satellite is used as the input data of the algorithm. A threshold value is introduced, which is: surface ASR>1, to reflect the change of aerosol load from the surface to the top of the troposphere, and complete the selection of initial data.

[0039] Specifically, the CALIPSO satellite consists of three instruments: Orthogonal Polarization Cloud Aerosol Lidar (CALIOP), Imaging Infrared Radiometer (IIR) and Wide Field Camera (WFC). CALIOP is a dual-wavelength polarization-sensitive lidar that provides hi...

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Abstract

The present invention provides a boundary layer height extraction algorithm based on random sampling fitting, including three main steps of signal selection, random sample fitting, and self-diagnosis, using the total attenuation-scattering ratio data of level 1 products of the spaceborne laser radar CALIPSO, The present invention combines the ideal profile fitting method and the principle of random sampling consistency to develop a BLH algorithm for automatically extracting laser radar data. The algorithm of the present invention performs at least 200 random sampling and fitting of the data, and performs sample analysis according to the fitting results. Perform optimization screening, select the sample with the largest number of updated samples for re-fitting to obtain the coefficient of determination and BLH value, the result at this time is the best, and finally verify whether the optimal BLH value obtained is reasonable based on the coefficient of determination, and output the result if it is reasonable. The algorithm of the invention can accurately determine the BLH under the condition of low signal-to-noise ratio or the existence of clouds where other existing algorithms are not applicable, and has good feasibility and stability.

Description

technical field [0001] The invention relates to the technical field of atmospheric detection, in particular to a boundary layer height extraction algorithm based on random sampling fitting. Background technique [0002] The atmospheric boundary layer is the lowest part of the atmosphere, which is directly affected by the surface, and is an air layer where matter, energy and water vapor are exchanged between the earth's surface and the free atmosphere. Changes in the boundary layer have enormous implications for climate, the environment, and human health. BLH (Boundary Layer Height, refers to the height of the atmospheric boundary layer, referred to as the boundary layer height in this application) is an important parameter to describe the vertical distribution of pollutants and the study of the boundary layer, and is also a basic input parameter for weather and climate models. The higher the height of the boundary layer, the more conducive to the diffusion and dilution of p...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/48G01S17/95G06V10/771G06K9/62
CPCG01S7/4802G01S17/95G06F18/2113Y02A90/10
Inventor 王威潘雅妮
Owner CENT SOUTH UNIV
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