Step-by-step active and passive sea surface wind field combination method based on polarization combination

Abstract

The application relates to a step-by-step active and passive sea surface wind field combined calculation method based on polarization combination, belonging to the field of space microwave remote sensing, and comprising the following steps: obtaining measurement data of a microwave radiometer and measurement data of a microwave scatterometer, determining a sea surface wind speed; constructing a cost function, and solving the cost function according to the measurement data of the microwave radiometer and the measurement data of the microwave scatterometer, and determining a sea surface wind direction when the cost function reaches a minimum value, that is, a finally determined sea surface wind direction. The application combines the measurement data of the microwave radiometer and the measurement data of the microwave scatterometer to perform combined calculation of a sea surface wind field, improves the calculation precision of the sea surface wind field, adopts a polarization combination mode to construct a new brightness temperature parameter, suppresses atmospheric influence and improves wind direction sensitivity, and enables the radiometer to have wind direction measurement capability.

Description

Technical Field

[0001] This application relates to the field of space microwave remote sensing, specifically to a step-by-step method for joint calculation of active and passive sea surface wind fields based on polarization combination. Background Technology

[0002] Sea surface wind is an important parameter in the ocean-atmosphere system. Measuring sea surface wind is crucial for understanding global climate change, ocean-atmosphere interactions, and improving extreme weather forecasting.

[0003] Currently, spaceborne microwave scatterometers and fully polarimetric radiometers are the main methods for measuring global sea surface wind fields. A microwave scatterometer is an active sensor that emits microwave signals and measures the backscattered signal (normalized radar cross section) from the sea surface. The backscattered signal is mainly modulated by sea surface roughness, which is directly related to sea surface wind. Therefore, sea surface wind field information can be obtained through the sea surface backscattering coefficient measured by the scatterometer. Similar to the principle of scatterometers measuring wind vectors, the sea surface microwave radiation energy measured by fully polarimetric radiometers is also modulated by sea surface roughness. Fully polarimetric radiometers measure four parameters of the Stokes vector. The first two parameters, characterizing horizontal and vertical polarization, are less sensitive to wind direction, while the third and fourth Stokes parameters are very sensitive. Therefore, fully polarimetric radiometers can simultaneously measure wind speed and wind direction information. Currently, there are relatively few spaceborne fully polarimetric radiometers, and the measured brightness temperature data is difficult to obtain.

[0004] Most spaceborne microwave radiometers are linearly polarized microwave radiometers, meaning they only measure horizontal and vertical polarization brightness temperature information. Because horizontal and vertical polarization brightness temperatures are less sensitive to wind direction, making it difficult to obtain wind direction information, linearly polarized radiometers typically only measure sea surface wind speed data.

[0005] Based on the current state of research, existing technologies have the following problems: 1. Spaceborne linearly polarized microwave radiometers typically only measure horizontal and vertical polarization brightness temperatures, which are less sensitive to wind direction, and usually only measure sea surface wind speed, making it difficult to obtain sea surface wind direction information.

[0006] 2. Both spaceborne microwave radiometers and microwave scatterometers can acquire sea surface wind information, but currently both payloads generate their own operational sea surface wind data independently, with limited joint applications, making it difficult to leverage their respective advantages. Summary of the Invention

[0007] To overcome at least one deficiency in the prior art, this application provides a stepwise active and passive sea surface wind field joint calculation method based on polarization combination.

[0008] In one embodiment, a step-by-step method for joint calculation of active and passive sea surface wind fields based on polarization combination includes: The sea surface wind speed is determined by acquiring measurement data from the microwave radiometer and the microwave scatterometer using the following formula:

[0009] in, For sea surface wind speed, For microwave radiometer Brightness temperature measured by each measurement channel. This is the brightness-temperature conversion function. For microwave scattering meter The backscattering coefficient measured by each measurement channel. , , All are coefficients; A cost function is constructed, and based on the measurement data from the microwave radiometer and the microwave scatterometer, the cost function is solved to determine the sea surface wind direction at which the cost function reaches its minimum value; this is the final determined sea surface wind direction. The cost function is:

[0010]

[0011]

[0012] in, The cost function value, For microwave radiometer Brightness temperature parameters at a measurement frequency For microwave radiometer Brightness temperature parameter mode value at a measurement frequency Let V be the variance of the brightness temperature parameter of the microwave radiometer. For microwave scattering meter The backscattering coefficient measured by each measurement channel. Backscattering coefficient data calculated for the model. Let V be the variance of the backscattering coefficient of the microwave scatterer; This represents the number of measurement frequencies of the microwave radiometer. This refers to the number of measurement channels of the microwave scatterometer; For microwave radiometer Vertical polarization brightness temperature at each measurement frequency For microwave radiometer Horizontal polarization brightness temperature at a measurement frequency For coefficients; , , All are microwave radiometers. Sea surface wind speed at various measurement frequencies Sea surface temperature coefficient, This is the angle between the azimuth angle observed by the microwave radiometer and the wind direction over the sea surface.

[0013] In one embodiment, the coefficient The following formula is used for calculation:

[0014] in, For microwave radiometer Vertical polarization brightness temperature at each measurement frequency For microwave radiometer Horizontal polarization brightness temperature at a measurement frequency This refers to the sea surface temperature.

[0015] In one embodiment, the method further includes: The measurement data from the microwave radiometer and the microwave scatterometer are matched with sea surface temperature, sea surface wind speed, and sea surface wind direction to obtain a matched dataset. Determining coefficients based on the matching dataset , , With sea surface wind speed Sea surface temperature The relationship between the coefficients , , .

[0016] In one embodiment, coefficients are determined based on the matching dataset. , , With sea surface wind speed Sea surface temperature The relationships between them include: Calculate the first based on the measurement data of the microwave radiometer. Brightness temperature parameters at various measurement frequencies were obtained using the least squares method, combined with a matching dataset, for different sea surface wind speeds and sea surface temperatures. , , The polynomial fitting method is used to obtain , , With sea surface wind speed Sea surface temperature The relationship between them.

[0017] In one embodiment, when The corresponding measurement frequency is 10.7 GHz. ;when The corresponding measurement frequencies are 18.7 GHz or 37 GHz. .

[0018] Compared with the prior art, this application has the following beneficial effects: This application combines measurement data from microwave radiometers and microwave scatterometers to perform joint calculations of sea surface wind fields, thereby improving the accuracy of sea surface wind field calculations. It also employs a polarization combination method to construct new brightness temperature parameters, suppressing atmospheric influences while enhancing wind direction sensitivity, thus enabling the radiometer to measure wind direction. Attached Figure Description

[0019] This application can be better understood by referring to the description given below in conjunction with the accompanying drawings, which, together with the detailed description below, are incorporated in and form part of this specification. In the drawings: Figure 1 A flowchart of a step-by-step method for joint calculation of active and passive sea surface wind fields based on polarization combination is shown. Detailed Implementation

[0020] Exemplary embodiments of the present application will be described below with reference to the accompanying drawings. For clarity and brevity, not all features of the actual embodiments are described in the specification. However, it should be understood that many embodiment-specific decisions can be made in the development of any such actual embodiment to achieve the developer’s specific objectives, and these decisions may vary as the embodiments differ.

[0021] It should also be noted that, in order to avoid obscuring this application with unnecessary details, only the device structure closely related to the solution of this application is shown in the accompanying drawings, while other details that are not closely related to this application are omitted.

[0022] It should be understood that this application is not limited to the described embodiments by virtue of the following description with reference to the accompanying drawings. In this document, embodiments may be combined with each other, features may be substituted or borrowed between different embodiments, and one or more features may be omitted in one embodiment, where feasible.

[0023] This application provides a step-by-step method for joint calculation of active and passive sea surface wind fields based on polarization combination. Figure 1 A flowchart of a stepwise method for joint calculation of active and passive sea surface wind fields based on polarization combination is shown. See [link / reference]. Figure 1 The methods mainly include: Step S1: Obtain measurement data from the microwave radiometer and the microwave scatterometer to determine the sea surface wind speed using the following formula:

[0024] in, For sea surface wind speed, For microwave radiometer Brightness temperature measured by each measurement channel. This is the brightness-temperature conversion function. For microwave scattering meter The backscattering coefficient measured by each measurement channel. , , All are coefficients.

[0025] here, This indicates the measurement channel of the microwave radiometer. This indicates a vertical polarization measurement at 10.7 GHz. This indicates a horizontal polarization measurement at 10.7 GHz. This indicates a vertical polarization measurement at 18.7 GHz. This indicates the horizontal polarization measurement at 18.7 GHz. This indicates a vertical polarization measurement at 37 GHz. This indicates a horizontal polarization measurement at 37 GHz; This indicates the measurement channel of the microwave scatterometer. This indicates the vertical polarization measurement in the Ku band. This indicates the horizontal polarization measurement in the Ku band.

[0026] when The corresponding measurement frequency is 10.7 GHz. ;when The corresponding measurement frequencies are 18.7 GHz or 37 GHz. .

[0027] After acquiring measurement data from the microwave radiometer and microwave scatterometer, the measurement data were first quasi-synchronously matched spatiotemporally with sea surface temperature, wind speed, and wind direction using thresholding and interpolation methods, and then gridded to obtain a matched dataset. The spatial matching window was 25 km, and the temporal matching window was 30 minutes. Then, based on the matched dataset, the coefficients were determined using the least squares method. , , Here, the matching dataset includes the correspondence between brightness temperature and sea surface wind speed measured by each measurement channel of the microwave radiometer, and the correspondence between backscattering coefficient and sea surface wind speed measured by each measurement channel of the microwave scatterometer. The coefficients can be determined using the least squares method. , , .

[0028] Step S2: Construct the cost function, and solve the cost function based on the measurement data of the microwave radiometer and the microwave scatterometer to determine the sea surface wind direction when the cost function reaches its minimum value, which is the final determined sea surface wind direction.

[0029] The cost function is:

[0030]

[0031]

[0032] in, The cost function value, For microwave radiometer Brightness temperature parameters at a measurement frequency For microwave radiometer Brightness temperature parameter mode value at a measurement frequency Let V be the variance of the brightness temperature parameter of the microwave radiometer. For microwave scattering meter The backscattering coefficient measured by each measurement channel. The backscattering coefficient data for model calculation can be obtained using the existing NSCAT-4 model. Let V be the variance of the backscattering coefficient of the microwave scatterer; This represents the number of measurement frequencies of the microwave radiometer. This refers to the number of measurement channels of the microwave scatterometer; For microwave radiometer Vertical polarization brightness temperature at each measurement frequency For microwave radiometer Horizontal polarization brightness temperature at a measurement frequency For coefficients; , , All are microwave radiometers. Sea surface wind speed at various measurement frequencies Sea surface temperature coefficient, This is the angle between the azimuth angle observed by the microwave radiometer and the wind direction over the sea surface.

[0033] It should be noted that each measurement frequency of the microwave radiometer corresponds to two measurement channels. For example, the measurement frequency of 10.7 GHz corresponds to... and These are the two measurement channels.

[0034] Specifically, The variance of the brightness temperature parameter of the microwave radiometer is given by the measurement frequency of the microwave radiometer. It is obtained through the variance calculation formula. The variance of the backscattering coefficient of the microwave scatterer is obtained by using the variance calculation formula based on the backscattering coefficients measured by each measurement channel of the microwave scatterer.

[0035] Specifically, optimization methods such as the least squares method can be used to solve for the cost function, and the minimum value of the cost function can be obtained. , The angle between the azimuth of the microwave radiometer and the wind direction over the sea surface is used to determine the wind direction over the sea surface, given the azimuth of the microwave radiometer.

[0036] The construction process of the cost function is described below.

[0037] First, based on geophysical radiation characteristics, the atmospheric top brightness temperature measured by a radiometer mainly consists of the upward atmospheric brightness temperature, the sea surface radiation brightness temperature after atmospheric attenuation, and the downward atmospheric brightness temperature reflected from the sea surface after atmospheric attenuation. It can be approximately expressed as follows:

[0038] In the formula, The brightness temperature of the top of the atmosphere as observed by the microwave radiometer is indicated by the subscript. The symbols represent the polarization mode, where H represents horizontal polarization and V represents vertical polarization. Sea surface reflectance, Atmospheric transmittance, Sea surface temperature, The effective temperature of the atmosphere.

[0039] Define brightness temperature parameters :

[0040] in, This is an empirical coefficient.

[0041] To reduce the impact of the atmosphere, it is necessary to select appropriate parameters to suppress it. Sensitivity to atmospheric parameters (atmospheric water vapor content and liquid water content), let:

[0042] We can obtain:

[0043] in, To match the sea surface temperature with the brightness temperature of the top of the atmosphere observed by the microwave radiometer.

[0044] Then, It can effectively suppress the influence of the atmosphere in the CK band. It is mainly related to sea surface wind speed, wind direction, and sea surface temperature, and can be expressed as a function in the following form:

[0045] Coefficients can be determined based on the matching dataset. , , With sea surface wind speed Sea surface temperature The relationships between them. Specifically, they include: Calculate the first based on the measurement data of the microwave radiometer. Brightness temperature parameters at each measurement frequency By combining the matching dataset, the least squares method was used to obtain the sea surface wind speed and sea surface temperature under different conditions. , , The polynomial fitting method is used to obtain , , With sea surface wind speed Sea surface temperature The relationship between them.

[0046] Here, the matching dataset includes the matching relationship between microwave radiometer measurement data and sea surface wind speed and sea surface temperature. Further, the matching relationship between brightness temperature parameter and sea surface wind speed and sea surface temperature can be obtained. Combining this with the least squares method, the brightness temperature parameter can be obtained under different sea surface wind speeds and sea surface temperatures. , , .

[0047] The proposed method for joint calculation of active and passive sea surface wind fields based on polarization combination was validated using HY-2B on-orbit data. The results show that the calculation accuracy of sea surface wind speed and wind direction is improved compared with the calculation results of the scatterometer alone. The method of this application improves the calculation accuracy of wind speed from 1.2 m / s to 1.0 m / s and the calculation accuracy of wind direction from 15° to 12.5°.

[0048] In summary, this application combines measurement data from a microwave radiometer and a microwave scatterometer to perform joint calculations of the sea surface wind field, thereby improving the calculation accuracy. A new brightness temperature parameter is constructed using a polarization combination method, which suppresses atmospheric influences while improving wind direction sensitivity, enabling the radiometer to measure wind direction.

[0049] The above descriptions are merely various embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A step-by-step method for joint calculation of active and passive sea surface wind fields based on polarization combination, characterized in that, include: The sea surface wind speed is determined by acquiring measurement data from the microwave radiometer and the microwave scatterometer using the following formula: in, For sea surface wind speed, For microwave radiometer Brightness temperature measured by each measurement channel. This is the brightness-temperature conversion function. For microwave scattering meter The backscattering coefficient measured by each measurement channel. , , All are coefficients; A cost function is constructed, and based on the measurement data from the microwave radiometer and the microwave scatterometer, the cost function is solved to determine the sea surface wind direction at which the cost function reaches its minimum value; this is the final determined sea surface wind direction. The cost function is: in, The cost function value, For microwave radiometer Brightness temperature parameters at a measurement frequency For microwave radiometer Brightness temperature parameter mode value at a measurement frequency Let V be the variance of the brightness temperature parameter of the microwave radiometer. For microwave scattering meter The backscattering coefficient measured by each measurement channel. Backscattering coefficient data calculated for the model. Let V be the variance of the backscattering coefficient of the microwave scatterer; This represents the number of measurement frequencies of the microwave radiometer. This refers to the number of measurement channels of the microwave scatterometer; For microwave radiometer Vertical polarization brightness temperature at each measurement frequency For microwave radiometer Horizontal polarization brightness temperature at a measurement frequency For coefficients; , , All are microwave radiometers. Sea surface wind speed at various measurement frequencies Sea surface temperature coefficient, This is the angle between the azimuth angle observed by the microwave radiometer and the wind direction over the sea surface.

2. The method as described in claim 1, characterized in that, coefficient The following formula is used for calculation: in, For microwave radiometer Vertical polarization brightness temperature at each measurement frequency For microwave radiometer Horizontal polarization brightness temperature at a measurement frequency This refers to the sea surface temperature.

3. The method as described in claim 1, characterized in that, The method further includes: The measurement data from the microwave radiometer and the microwave scatterometer are matched with sea surface temperature, sea surface wind speed, and sea surface wind direction to obtain a matched dataset. Determine the coefficients based on the matching dataset. , , With sea surface wind speed Sea surface temperature The relationship between the coefficients , , .

4. The method as described in claim 3, characterized in that, Determine the coefficients based on the matching dataset. , , With sea surface wind speed Sea surface temperature The relationships between them include: Calculate the first based on the measurement data of the microwave radiometer. Brightness temperature parameters at various measurement frequencies, combined with the matching dataset, were obtained using the least squares method for different sea surface wind speeds and sea surface temperatures. , , The polynomial fitting method is used to obtain , , With sea surface wind speed Sea surface temperature The relationship between them.

5. The method as described in claim 1, characterized in that, when The corresponding measurement frequency is 10.7 GHz. ;when The corresponding measurement frequencies are 18.7 GHz or 37 GHz. .

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