Method and System for Controlling Quality Mark of Offshore Multi-Band Cloud and Fog Observation Data

Abstract

The present invention relates to the technical field of cloud and fog observation, and more specifically, to a method and system for controlling the quality marking of multi-band cloud and fog observation data at sea. The solution includes setting two quality control codes, namely the QC method control code and the application quality control code; setting a process for comprehensively analyzing the sea cloud and fog observation data by using a variety of quality control methods, and the comprehensive analysis process is used to form the final application quality control code according to the quality control codes of a variety of QC methods; forming an application quality control identification code according to the laser fog measurement quality control data; forming an application quality control identification code according to the millimeter wave cloud and fog measurement quality control data; obtaining the original observation image to extract the all-sky application quality control identification code; and the quality control identification code of the weather and hydrological observation data. Through reasonable quality control, the solution forms quality and application quality identification codes for multi-band cloud and fog observation data, facilitating users to conduct analysis and prediction.

Description

Technical Field

[0001] The present invention relates to the technical field of cloud and fog observation, and more specifically, to a method and system for controlling the quality marking of multi-band cloud and fog observation data at sea. Background Art

[0002] The importance of quality control of meteorological observation data has been recognized by all scientists who use meteorological data. Ground meteorological observation records must be representative, accurate, and comparable. All kinds of observed values can be regarded as random variables in a statistical sense. Errors usually occur when observed values are collected. According to the nature and causes of errors, there may be three types of errors with completely different natures in meteorological observation data: random errors, systematic errors, and gross errors (accidental errors). The purpose of quality control is to ensure that the data provided for application meets various requirements (including uncertainty, resolution, continuity, homogeneity, representativeness, time limit, format, etc.). Good data does not need to be particularly excellent. What matters is that its quality should be known and verifiable.

[0003] Before the technology of the present invention, it was difficult to effectively control the quality of multi-band cloud and fog observation data, which led to the inability to effectively analyze multi-band clouds and fog at sea. In particular, it was impossible to determine which data were abnormal and which might be incorrect. Summary of the Invention

[0004] In view of the above problems, the present invention provides a method and system for controlling the quality marking of multi-band cloud and fog observation data at sea. Through reasonable quality control, quality identification codes for quality and application are formed for multi-band cloud and fog observation data, facilitating users to conduct analysis and prediction.

[0005] According to the first aspect of the embodiments of the present invention, a method for controlling the quality marking of multi-band cloud and fog observation data at sea is provided.

[0006] In one or more embodiments, preferably, the method for controlling the quality marking of multi-band cloud and fog observation data at sea includes:

[0007] Set two quality control codes, namely the QC method control code and the application quality control code;

[0008] Set a process for comprehensively analyzing sea cloud and fog observation data using multiple quality control methods. The comprehensive analysis process is used to form a final application quality control code based on multiple QC method quality control codes;

[0009] Form an application quality control identification code according to the laser fog measurement quality control data;

[0010] Form an application quality control identification code according to the millimeter wave cloud and fog measurement quality control data;

[0011] Obtain the original observation image to extract the quality control identification code for the all-sky application;

[0012] The quality control identification code for weather and hydrological observation data.

[0013] In one or more embodiments, preferably, the two quality control codes are respectively set as the QC method control code and the application quality control code, which specifically include:

[0014] Set a 4-level QC method quality control code for each quality control method. Among them, the value range of the QC method quality control code is 0-3, where 0 indicates correct, 1 indicates suspicious, 2 indicates warning, and 3 indicates data error;

[0015] Determine the application quality control code for each data. The value range of the application quality control code is 0-9. Among them, 0 means the data is correct, 1 means the data is suspicious, 2 means the data is warning, 3 means the data is error, 4-6 are reserved, 7 means no observation task, 8 means the data is missing, and 9 means the format check fails.

[0016] In one or more embodiments, preferably, the process of using multiple quality control methods to comprehensively analyze the marine cloud and fog observation data is set. The comprehensive analysis process is used to form the final application quality control code according to multiple QC method quality control codes, which specifically include:

[0017] Read the observation data before quality control and form four types of quality control data: laser fog measurement, millimeter wave cloud and fog, meteorological and hydrological load, and all-sky imaging;

[0018] Calculate the QC quality control code for the four types of quality control data;

[0019] Fuse the QC quality control codes of the four types of quality control data into the application quality control code of a single device and output the observation data after quality control.

[0020] In one or more embodiments, preferably, the formation of the application quality control identification code according to the laser fog measurement quality control data specifically includes:

[0021] After the dead time correction process, add the first laser fog measurement quality control identification code;

[0022] After the geometric overlap factor correction process, add the second laser fog measurement quality control identification code;

[0023] After the background noise subtraction process, add the third laser fog measurement quality control identification code;

[0024] After the data smoothing process, add the fourth laser fog measurement quality control identification code;

[0025] Perform cloud and aerosol algorithm classification and data quality identification;

[0026] Based on the first laser fog measurement quality control identification code, the second laser fog measurement quality control identification code, the third laser fog measurement quality control identification code, and the fourth laser fog measurement quality control identification code, combined with the data quality identification, a laser fog measurement application quality control identification code is formed using the first calculation formula;

[0027] The first calculation formula is:

[0028]

[0029] Wherein, M1 is the laser fog measurement application quality control identification code, Cx1 is the number of times that QC1, QC2, QC3, and QC4 are 1, Cx2 is the number of times that QC1, QC2, QC3, and QC4 are 2, Cx3 is the number of times that QC1, QC2, QC3, and QC4 are 3, QC1 is the first laser fog measurement quality control identification code, QC2 is the second laser fog measurement quality control identification code, QC3 is the third laser fog measurement quality control identification code, QC4 is the fourth laser fog measurement quality control identification code, L1 is the laser fog measurement data quality identification. When there is cloud data, L1 = 1, f() is a fitting function, and when the condition inside () is satisfied, the output of the fitting function is 0; otherwise, the output of the fitting function is 1.

[0030] In one or more embodiments, preferably, forming the application quality control identification code based on the millimeter-wave cloud and fog measurement quality control data specifically includes:

[0031] After spectral quality control, the first millimeter-wave cloud and fog measurement quality control identification code is added;

[0032] After noise elimination processing, the second millimeter-wave cloud and fog measurement quality control identification code is added;

[0033] After spectral moment extraction processing, the third millimeter-wave cloud and fog measurement quality control identification code is added;

[0034] After isolated echo processing, the fourth millimeter-wave cloud and fog measurement quality control identification code is added;

[0035] Perform velocity ambiguity processing to identify whether there is cloud data, and label it as the millimeter-wave cloud and fog measurement data quality identification;

[0036] Based on the first millimeter-wave cloud and fog measurement quality control identification code, the second millimeter-wave cloud and fog measurement quality control identification code, the third millimeter-wave cloud and fog measurement quality control identification code, and the fourth millimeter-wave cloud and fog measurement quality control identification code, combined with the millimeter-wave cloud and fog measurement data quality identification, a millimeter-wave cloud and fog measurement application quality control identification code is formed using the second calculation formula;

[0037] The second calculation formula is:

[0038]

[0039] Among them, M2 is the quality control identification code for millimeter-wave cloud and fog measurement applications, Dx1 is the number of times QD1, QD2, QD3, and QD4 are 1, Dx2 is the number of times QD1, QD2, QD3, and QD4 are 2, Dx3 is the number of times QD1, QD2, QD3, and QD4 are 3, QD1 is the first laser fog measurement quality control identification code, QD2 is the second laser fog measurement quality control identification code, QD3 is the third laser fog measurement quality control identification code, QD4 is the fourth laser fog measurement quality control identification code, L2 is the laser fog measurement data quality identification. When there is cloud data, L2 = 1, f() is a fitting function. When the condition inside () is satisfied, the output of the fitting function is 0; otherwise, the output of the fitting function is 1.

[0040] In one or more embodiments, preferably, the extraction of the all-sky application quality control identification code from the obtained original observation image specifically includes:

[0041] Obtain the original observation image, determine whether it is visible light channel data. If it is visible light channel data, perform brightness equalization correction and add the first all-sky quality control identification code. On this basis, perform white balance correction and add the second all-sky quality control identification code;

[0042] If it is not visible light channel data, it is considered to be infrared channel data, perform brightness temperature value correction, and add the third all-sky quality control identification code;

[0043] Form the all-sky application quality control identification code according to the first all-sky quality control identification code, the second all-sky quality control identification code, and the third all-sky quality control identification code using the third calculation formula;

[0044] The third calculation formula is:

[0045]

[0046] Among them, M2 is the all-sky application quality control identification code, Ex1 is the number of times QE1, QE2, QE3, and QE4 are 1, Ex2 is the number of times QE1, QE2, QE3, and QE4 are 2, Ex3 is the number of times QE1, QE2, QE3, and QE4 are 3, QE1 is the first all-sky quality control identification code, QE2 is the second all-sky quality control identification code, QE3 is the third all-sky quality control identification code, f() is a fitting function. When the condition inside () is satisfied, the output of the fitting function is 0; otherwise, the output of the fitting function is 1.

[0047] In one or more embodiments, preferably, the quality control identification code for the weather and hydrological observation data specifically includes:

[0048] When the observation data fails the format check, mark the comprehensive quality control code as 2;

[0049] When it fails the missing measurement check, no further subsequent checks are performed;

[0050] There is no observation task, and the marked application quality control code is 7;

[0051] There is an observation task, and the applied quality control code is 8;

[0052] When the limit value check fails, no further subsequent checks are performed, and the applied quality control code is 2;

[0053] For the observed data that passes the limit value check, the change range value check, internal consistency check, time consistency check, spatial consistency check, and comprehensive check are completed in sequence, and the corresponding applied quality control codes are marked.

[0054] According to the second aspect of the embodiments of the present invention, a quality marking control system for maritime multi-band cloud and fog observation data is provided.

[0055] In one or more embodiments, preferably, the quality marking control system for maritime multi-band cloud and fog observation data includes:

[0056] An applied quality control code setting module for setting two quality control codes as the QC method control code and the applied quality control code respectively;

[0057] A process quality control module for setting a process of comprehensively analyzing maritime cloud and fog observation data using multiple quality control methods, and the comprehensive analysis process is used to form the final applied quality control code according to multiple QC method quality control codes;

[0058] A laser fog measurement module for forming an applied quality control identification code according to laser fog measurement quality control data;

[0059] When the cloud amount recognized from the original image of the all-sky imager is 0, it is considered that the current weather is clear sky. If the forward scattering visibility obtained by laser fog measurement is less than 5 km, it is considered that the laser radar quality control identification is suspicious.

[0060] A millimeter wave cloud and fog measurement module for forming an applied quality control identification code according to millimeter wave cloud and fog measurement quality control data;

[0061] When the cloud amount recognized from the original image of the all-sky imager is 10, it is considered that the current weather is cloudy. If the reflectivity factor obtained by millimeter wave cloud and fog measurement is empty, it is considered that the millimeter wave cloud and fog data quality control identification is suspicious.

[0062] When the forward scattering recognized by the laser fog measurement module is less than 5 km, if the reflectivity factor obtained by millimeter wave cloud and fog measurement is empty, it is considered that the millimeter wave cloud and fog data quality control identification is suspicious.

[0063] An all-sky imaging module for obtaining the original observation image to extract the all-sky applied quality control identification code;

[0064] When a portrait or other foreign object is recognized from the original image of the all-sky imager, it is considered that there is an error in the original image, and it is considered that the data quality control flag of the all-sky imaging module is in error.

[0065] The meteorological and hydrological module is used for the quality control identification code of weather and hydrological observation data.

[0066] When the current navigation speed is greater than 3 km / h, it is considered that there is suspicion in the meteorological and hydrological observation data, and it is considered that the data quality control flag of the all-sky imaging module is suspicious.

[0067] According to the third aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the method described in any one of the first aspects of the embodiments of the present invention is implemented.

[0068] According to the fourth aspect of the embodiments of the present invention, there is provided an electronic device, including a memory and a processor, where the memory is used to store one or more computer program instructions, and wherein the one or more computer program instructions are executed by the processor to implement the method described in any one of the first aspects of the embodiments of the present invention.

[0069] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0070] In the solution of the present invention, quality analysis is performed on a single type of device to form a quality control code.

[0071] In the solution of the present invention, through the joint analysis of multi-type quality control, an application quality control code is formed.

[0072] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in the written specification, claims, and drawings.

[0073] Next, through the drawings and embodiments, the technical solutions of the present invention will be further described in detail. Description of the Drawings

[0074] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained without creative efforts based on these drawings.

[0075] Figure 1 It is a flowchart of a method for controlling the quality marking of multi-band cloud and fog observation data at sea according to an embodiment of the present invention.

[0076] Figure 2 It is a flowchart for setting two quality control codes, namely the QC method control code and the application quality control code, in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention.

[0077] Figure 3 It is a flowchart for setting the process of comprehensively analyzing marine cloud and fog observation data by using multiple quality control methods in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention. The process of the comprehensive analysis is used to form the final application quality control code according to multiple QC method quality control codes.

[0078] Figure 4 It is a flowchart for forming an application quality control identification code according to the laser fog measurement quality control data in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention.

[0079] Figure 5 It is a flowchart for forming an application quality control identification code according to the millimeter wave cloud and fog measurement quality control data in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention.

[0080] Figure 6 It is a flowchart for obtaining the original observation image and extracting the all-sky application quality control identification code in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention.

[0081] Figure 7 It is a flowchart for the quality control identification code of weather and hydrological observation data in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention.

[0082] Figure 8 It is a structure diagram of a marine multi-band cloud and fog observation data quality marking control system according to an embodiment of the present invention.

[0083] Figure 9 It is a structure diagram of an electronic device according to an embodiment of the present invention. Detailed implementation manners

[0084] In some of the processes described in the specification, claims, and above-mentioned drawings of the present invention, a plurality of operations appear in a specific order. However, it should be clearly understood that these operations can be executed not in the order in which they appear herein or in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. Additionally, these processes can include more or fewer operations, and these operations can be executed sequentially or in parallel. It should be noted that the descriptions such as "first" and "second" in this article are used to distinguish different messages, devices, modules, etc., do not represent a sequence, and do not limit that "first" and "second" are of different types.

[0085] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present invention.

[0086] The importance of quality control of meteorological observation data has been recognized by all scientists who use meteorological data. Ground meteorological observation records must be representative, accurate, and comparable. All kinds of observed values can be regarded as random variables in a statistical sense. Errors usually occur when observed values are collected. According to the nature and cause of the errors, there may be three types of errors with completely different natures in meteorological observation data: random errors, systematic errors, and gross errors (accidental errors). The purpose of quality control is to ensure that the data provided for application meets various requirements (including uncertainty, resolution, continuity, homogeneity, representativeness, time limit, format, etc.). Good data does not need to be particularly excellent. What is important is that its quality should be known and verifiable.

[0087] Before the technology of the present invention, it was difficult to effectively perform quality control on multi-band cloud and fog observation data, which led to the inability to effectively analyze multi-band clouds and fog at sea. In particular, it was impossible to determine which data were abnormal and which might be incorrect.

[0088] In an embodiment of the present invention, a method and system for quality marking control of multi-band cloud and fog observation data at sea are provided. Through reasonable quality control, this solution forms quality identification codes for quality and application of multi-band cloud and fog observation data, facilitating users to perform analysis and prediction.

[0089] According to the first aspect of the embodiments of the present invention, a method for quality marking control of multi-band cloud and fog observation data at sea is provided.

[0090] Figure 1It is a flowchart of a method for controlling the quality marking of maritime multi - band cloud and fog observation data according to an embodiment of the present invention.

[0091] In one or more embodiments, preferably, the method for controlling the quality marking of maritime multi - band cloud and fog observation data includes:

[0092] S101. Set two quality control codes, namely the QC method control code and the application quality control code respectively;

[0093] S102. Set a process for comprehensively analyzing maritime cloud and fog observation data using multiple quality control methods, and the comprehensive analysis process is used to form the final application quality control code according to multiple QC method quality control codes;

[0094] S103. Form an application quality control identification code according to the laser fog measurement quality control data;

[0095] S104. Form an application quality control identification code according to the millimeter - wave cloud and fog measurement quality control data;

[0096] S105. Obtain the original observation image and extract the all - sky application quality control identification code;

[0097] S106. Quality control identification code for weather and hydrological observation data.

[0098] In the embodiment of the present invention, by combining data quality and application quality, the effectiveness of the observation data of the current cloud and fog observation system is realized.

[0099] Figure 2 It is a flowchart of setting two quality control codes, namely the QC method control code and the application quality control code respectively, in the method for controlling the quality marking of maritime multi - band cloud and fog observation data according to an embodiment of the present invention.

[0100] As Figure 2 shown, in one or more embodiments, preferably, setting two quality control codes, namely the QC method control code and the application quality control code respectively, specifically includes:

[0101] S201. Set 4 - level QC method quality control codes for each quality control method. Among them, the value range of the QC method quality control code is 0 - 3, where 0 represents correct, 1 represents suspicious, 2 represents warning, and 3 represents data error;

[0102] S202. Determine the application quality control code for each data. The value range of the application quality control code is 0 - 9. Among them, 0 means the data is correct, 1 means the data is suspicious, 2 means the data is warning, 3 means the data is error, 4 - 6 are reserved, 7 means no observation task, 8 means data missing, and 9 means failed format check.

[0103] In the embodiments of the present invention, the QC method control code: This control code is usually used to indicate whether the adopted quality control method is appropriate or effective. Four levels of QC method quality control codes are set, with a value range from 0 to 3: 0 indicates that the QC method used is correct. 1 indicates that there may be problems with the QC method and the results are suspicious. 2 indicates a warning, and the QC method may be imperfect or need adjustment. 3 indicates that there is an error in the QC method and the quality inspection cannot be correctly performed. Application quality control code: The application quality control code more specifically marks the quality status of each data point. The value range is from 0 to 9, and the specific meanings are as follows: 0 indicates that the data is completely correct. 1 indicates that the data is in doubt and may need further verification. 2 is a data warning, indicating that there may be problems with the data but it has not been confirmed. 3 clearly indicates that there are errors in the data. 4 to 6 are reserved as spare codes and can be used for future expansion or other specific purposes. 7 indicates that there is no observation task, that is, there is no valid observation at this data point. 8 indicates that the data is missing, that is, there should be data at this moment but it cannot be collected. 9 indicates that the data fails the format check, that is, the format of the data does not conform to the predetermined standard.

[0104] Figure 3 It is a process for setting and utilizing multiple quality control methods to comprehensively analyze marine cloud and fog observation data in a method for controlling the quality marking of marine multi-band cloud and fog observation data according to an embodiment of the present invention. The comprehensive analysis process is a flowchart for forming the final application quality control code according to multiple QC method quality control codes.

[0105] As Figure 3 shown, in one or more embodiments, preferably, the process for setting and utilizing multiple quality control methods to comprehensively analyze marine cloud and fog observation data, and the comprehensive analysis process for forming the final application quality control code according to multiple QC method quality control codes specifically includes:

[0106] S301. Read the observation data before quality control and form four types of quality control data: fog measurement by laser, millimeter-wave cloud and fog, meteorological and hydrological load, and all-sky imaging.

[0107] S302. Calculate the QC quality control code for the four types of quality control data.

[0108] S303. Integrate the QC quality control codes of the four types of quality control data into the application quality control code for a single type of device and output the observation data after quality control.

[0109] In the embodiments of the present invention, reading the original data: The original data needs to be read from the observation equipment first. These data may include the outputs of devices such as fog measurement by laser, millimeter-wave cloud and fog radar, meteorological and hydrological load, and all-sky imager. These data are usually unprocessed original signals, such as echo power values, backscattered light intensities, etc.

[0110] Form quality control data: After obtaining the original data, the next step is to perform preliminary processing on this data to form quality control data for further analysis. This may include steps such as decoding the signal, unit conversion, time synchronization, etc. At this stage, some basic quality control methods may be applied, such as checking the integrity and consistency of the data.

[0111] Calculate the QC quality control code: For the four types of quality control data formed, the corresponding QC quality control code needs to be calculated next. This step involves the evaluation of data quality and assigns a QC quality control code to each data point according to preset standards or algorithms. For example, if the echo power value of a certain data point is abnormally high, it may be marked as "suspicious" or "error".

[0112] Fuse and apply the quality control code: According to the calculated QC quality control code, this information is fused into the application quality control code for a single type of device. This step may need to comprehensively consider the characteristics of different devices and the observation objectives, as well as the specific meaning of the QC quality control code. For example, if the data of both the laser fog monitor and the millimeter-wave cloud and fog radar show "correct", the final application quality control code may also be "correct".

[0113] Output the quality-controlled data: After determining the application quality control code, the last step is to output the quality-controlled observation data. These data now contain information about their quality and can be used by scientific researchers or business systems. In practical applications, these data may be stored in a database or directly used in real-time monitoring and warning systems.

[0114] Figure 4 It is a flowchart of forming an application quality control identification code according to the laser fog quality control data in the method for controlling the quality marking of marine multi-band cloud and fog observation data in an embodiment of the present invention.

[0115] As Figure 4 shown, in one or more embodiments, preferably, forming the application quality control identification code according to the laser fog quality control data specifically includes:

[0116] S401. After dead time correction processing, add the first laser fog quality control identification code;

[0117] S402. After geometric overlap factor correction processing, add the second laser fog quality control identification code;

[0118] S403. After background noise subtraction processing, add the third laser fog quality control identification code;

[0119] S404. After data smoothing processing, add the fourth laser fog quality control identification code;

[0120] S405. Perform cloud and aerosol algorithm classification and data quality identification;

[0121] S406. Form a quality control identification code for laser fog measurement application by using a first calculation formula in combination with the data quality identification based on the first laser fog measurement quality control identification code, the second laser fog measurement quality control identification code, the third laser fog measurement quality control identification code, and the fourth laser fog measurement quality control identification code;

[0122] The first calculation formula is as follows:

[0123]

[0124] Wherein, M1 is the quality control identification code for laser fog measurement application, Cx1 is the number of times that QC1, QC2, QC3, and QC4 are 1, Cx2 is the number of times that QC1, QC2, QC3, and QC4 are 2, Cx3 is the number of times that QC1, QC2, QC3, and QC4 are 3, QC1 is the first laser fog measurement quality control identification code, QC2 is the second laser fog measurement quality control identification code, QC3 is the third laser fog measurement quality control identification code, QC4 is the fourth laser fog measurement quality control identification code, L1 is the laser fog measurement data quality identification. When there is cloud data, L1 = 1, f() is a fitting function, and when the condition inside () is satisfied, the output of the fitting function is 0; otherwise, the output of the fitting function is 1.

[0125] In the embodiment of the present invention, data distortion is avoided: Dead time correction is necessary because it can prevent sensor data distortion in the case of high count rates. Increase the quality control identification code: After the dead time correction process is completed, the first laser fog measurement quality control identification code will be increased, indicating that the data has undergone this correction. Improve the data acquisition accuracy: Geometric overlap factor correction helps to improve the accuracy of data acquisition when the laser beams overlap. Increase the quality control identification code: After the geometric overlap factor correction process, the second laser fog measurement quality control identification code will be increased. Enhance the signal clarity: Subtracting background noise helps to enhance the signal clarity, thereby obtaining more accurate measurement results. Increase the quality control identification code: After the background noise subtraction process, the third laser fog measurement quality control identification code will be increased. Reduce data fluctuations: Data smoothing processing helps to reduce data fluctuations and make the trend more obvious. Increase the quality control identification code: After the data smoothing processing, the fourth laser fog measurement quality control identification code will be increased. Conduct data classification: Conducting cloud and aerosol algorithm classification is to better identify and distinguish the effects of different components on laser transmission. Data quality identification: Combining the data quality identification helps with subsequent data analysis and interpretation. Calculation formula: Through the first calculation formula, in combination with the four laser fog measurement quality control identification codes and the data quality identification, the quality control identification code for laser fog measurement application is calculated. Significance of the identification code: This application quality control identification code represents the data quality state after a series of correction processes and is crucial for subsequent data use and trustworthiness.

[0126] Figure 5It is a flowchart of forming an application quality control identification code based on millimeter-wave cloud and fog quality control data in the method for controlling the quality mark of marine multi-band cloud and fog observation data according to an embodiment of the present invention.

[0127] As Figure 5 shown, in one or more embodiments, preferably, forming the application quality control identification code according to the millimeter-wave cloud and fog quality control data specifically includes:

[0128] S501. After spectral quality control, add the first millimeter-wave cloud and fog quality control identification code;

[0129] S502. After noise elimination processing, add the second millimeter-wave cloud and fog quality control identification code;

[0130] S503. After spectral moment extraction processing, add the third millimeter-wave cloud and fog quality control identification code;

[0131] S504. After isolated echo processing, add the fourth millimeter-wave cloud and fog quality control identification code;

[0132] S505. Perform velocity ambiguity processing, identify whether there is cloud data, and mark it as the millimeter-wave cloud and fog data quality mark;

[0133] S506. According to the first millimeter-wave cloud and fog quality control identification code, the second millimeter-wave cloud and fog quality control identification code, the third millimeter-wave cloud and fog quality control identification code, and the fourth millimeter-wave cloud and fog quality control identification code, combine the millimeter-wave cloud and fog data quality mark and use the second calculation formula to form the millimeter-wave cloud and fog application quality control identification code;

[0134] The second calculation formula is:

[0135]

[0136] where M2 is the millimeter-wave cloud and fog application quality control identification code, Dx1 is the number of times when QD1, QD2, QD3, and QD4 are 1, Dx2 is the number of times when QD1, QD2, QD3, and QD4 are 2, Dx3 is the number of times when QD1, QD2, QD3, and QD4 are 3, QD1 is the first laser fog quality control identification code, QD2 is the second laser fog quality control identification code, QD3 is the third laser fog quality control identification code, QD4 is the fourth laser fog quality control identification code, L2 is the laser fog data quality mark, when there is cloud data, L2 = 1, f() is a fitting function, and when the condition inside () is satisfied, the fitting function outputs 0, otherwise, the fitting function outputs 1.

[0137] In the embodiments of the present invention, spectral quality control helps to ensure that the data obtained from the millimeter-wave cloud radar accurately reflects the actual meteorological conditions. After completing the spectral quality control, the first millimeter-wave cloud and fog quality control identification code will be added, indicating that the data has undergone this correction. Noise cancellation helps to improve the overall clarity of the data and make the useful signals more prominent. After the noise cancellation process, the second millimeter-wave cloud and fog quality control identification code will be added. Spectral moment extraction processing helps to enhance the interpretability of the data and make the information extracted from the data more reliable. After the spectral moment extraction processing, the third millimeter-wave cloud and fog quality control identification code will be added. Isolated echo processing helps to improve data coherence and reduce the impact caused by outliers. After the isolated echo processing, the fourth millimeter-wave cloud and fog quality control identification code will be added. Velocity ambiguity processing helps to identify whether there is cloud data, which is particularly important for meteorological analysis. After the velocity ambiguity processing, it will be marked as the millimeter-wave cloud and fog data quality identification, which is crucial for subsequent data analysis and interpretation. Through the second calculation formula, combining the four millimeter-wave cloud and fog quality control identification codes and the data quality identification, the millimeter-wave cloud and fog application quality control identification code is calculated.

[0138] Figure 6 It is a flowchart of extracting the all-sky application quality control identification code from the obtained original observation image in the method for controlling the quality mark of marine multi-band cloud and fog observation data in an embodiment of the present invention.

[0139] As Figure 6 shown, in one or more embodiments, preferably, the extracting the all-sky application quality control identification code from the obtained original observation image specifically includes:

[0140] S601. Obtain the original observation image, determine whether it is visible light channel data. If it is visible light channel data, perform brightness equalization correction and add the first all-sky quality control identification code. On this basis, perform white balance correction and add the second all-sky quality control identification code;

[0141] S602. If it is not visible light channel data, it is considered to be infrared channel data, perform brightness temperature value correction, and add the third all-sky quality control identification code;

[0142] S603. Use the third calculation formula to form the all-sky application quality control identification code according to the first all-sky quality control identification code, the second all-sky quality control identification code, and the third all-sky quality control identification code;

[0143] The third calculation formula is:

[0144]

[0145] Among them, M2 is the quality control identification code for all-sky applications, Ex1 is the number of times QE1, QE2, QE3, and QE4 are 1, Ex2 is the number of times QE1, QE2, QE3, and QE4 are 2, Ex3 is the number of times QE1, QE2, QE3, and QE4 are 3, QE1 is the first all-sky quality control identification code, QE2 is the second all-sky quality control identification code, QE3 is the third all-sky quality control identification code, f() is a fitting function, and when the condition inside () is satisfied, the fitting function outputs 0; otherwise, the fitting function outputs 1.

[0146] In an embodiment of the present invention, first, it is determined whether the acquired original observation image is visible light channel data. Visible light channel data usually requires brightness equalization correction to adjust the overall brightness of the image to make it more natural and balanced. If it is not visible light channel data, it is considered infrared channel data. This type of data usually requires brightness temperature value correction to accurately reflect the temperature distribution on the object surface. After performing brightness equalization correction, the first all-sky quality control identification code is added, indicating that the data has undergone this correction process. On the basis of brightness equalization correction, white balance correction is performed to further adjust the color balance of the image, and then the second all-sky quality control identification code is added. For infrared channel data, after performing brightness temperature value correction, the third all-sky quality control identification code is added, indicating that the data has undergone this correction process. According to the first all-sky quality control identification code, the second all-sky quality control identification code, and the third all-sky quality control identification code, the all-sky application quality control identification code is formed using the third calculation formula. Fitting function: In the third calculation formula, f() is a fitting function, and when the condition inside () is satisfied, the fitting function outputs 0; otherwise, the fitting function outputs 1. The role of this function is to adjust the value of the application quality control identification code according to the occurrence times of the quality control identification code.

[0147] Figure 7 It is a flowchart of the quality control identification code for weather and hydrological observation data in the method for marking and controlling the quality of maritime multi-band cloud and fog observation data according to an embodiment of the present invention.

[0148] As Figure 7 shown, in one or more embodiments, preferably, the quality control identification code for the weather and hydrological observation data specifically includes:

[0149] S701: When the observation data fails the format check, mark the comprehensive quality control code as 2;

[0150] S702: When it fails the missing measurement check, no subsequent checks are performed;

[0151] S703: When there is no observation task, mark the application quality control code as 7;

[0152] S704: When there is an observation task, the application quality control code is 8;

[0153] When the boundary value check fails, no further checks are performed, and the application quality control code is 2.

[0154] For the observed data that passes the boundary value check, perform the range of change value check, internal consistency check, time consistency check, spatial consistency check, and comprehensive check in sequence, and mark the corresponding application quality control code.

[0155] In the embodiment of the present invention, when the observed data fails the format check, no other checks are performed, and the comprehensive quality control code is marked as 2 (data error). When the missing measurement check fails, no further checks are performed. If there is no observation task, the application quality control code is marked as 7; if there is an observation task, the application quality control code is 8. When the boundary value check fails, no further checks are performed, and the application quality control code is 2 (data error). For the observed data that passes the boundary value check, perform the main range of change value check, internal consistency check, time consistency check, spatial consistency check, and comprehensive check in sequence, and mark the corresponding application quality control code.

[0156] According to the second aspect of the embodiment of the present invention, a quality marking control system for maritime multi-band cloud and fog observation data is provided.

[0157] Figure 8 It is a structural diagram of a quality marking control system for maritime multi-band cloud and fog observation data according to an embodiment of the present invention.

[0158] In one or more embodiments, preferably, the quality marking control system for maritime multi-band cloud and fog observation data includes:

[0159] An application quality control code setting module 801 for setting two quality control codes as the QC method control code and the application quality control code respectively.

[0160] A process quality control module 802 for setting a process of comprehensively analyzing maritime cloud and fog observation data using multiple quality control methods, and the comprehensive analysis process is used to form the final application quality control code according to multiple QC method quality control codes.

[0161] A laser fog measurement module 803 for forming an application quality control identification code according to laser fog measurement quality control data.

[0162] When the cloud amount identified from the original image of the all-sky imager is 0, it is considered that the current weather is clear sky. If the forward scattering visibility obtained by laser fog measurement is less than 5 km, it is considered that the laser radar quality control mark is suspicious.

[0163] A millimeter wave cloud and fog measurement module 804 for forming an application quality control identification code according to millimeter wave cloud and fog measurement quality control data.

[0164] When the cloud cover identified from the original image of the all-sky imager is 10 oktas, the current weather is considered cloudy. If the reflectivity factor obtained from the millimeter-wave cloud and fog measurement is empty, the quality control flag for the millimeter-wave cloud and fog measurement data is considered suspicious.

[0165] When the forward scatter identified by the laser fog measurement module is less than 5 km, if the reflectivity factor obtained from the millimeter-wave cloud and fog measurement is empty, the quality control flag for the millimeter-wave cloud and fog measurement data is considered suspicious.

[0166] The all-sky imaging module 805 is used to obtain the original observation image for extracting the quality control identification code for all-sky applications;

[0167] When a person image or other foreign object is identified from the original image of the all-sky imager, it is considered that there is an error in the original image, and the quality control flag for the all-sky imaging module data is considered incorrect.

[0168] The meteorological and hydrological module 806 is used for the quality control identification code of weather and hydrological observation data.

[0169] When the current sailing speed is greater than 3 km / h, it is considered that there is suspicion in the meteorological and hydrological observation data, and the quality control flag for the all-sky imaging module data is considered suspicious.

[0170] In the embodiment of the present invention, through a series of modular designs, a system applicable to different structures is realized. This system can achieve closed-loop, reliable, and efficient execution through collection, analysis, and control. When the missing measurement check fails, no subsequent checks are performed. When there is no observation task, the application quality control code is marked as 7; when there is an observation task, the application quality control code is 8. When the limit value check fails, no subsequent checks are performed, and the application quality control code is 2 (data error). For the observation data that passes the limit value check, the main change range value check, internal consistency check, time consistency check, spatial consistency check, and comprehensive check are completed in sequence, and the corresponding application quality control code is marked.

[0171] According to the third aspect of the embodiment of the present invention, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the method described in any one of the first aspects of the embodiment of the present invention is realized.

[0172] According to the fourth aspect of the embodiment of the present invention, an electronic device is provided. Figure 9 It is the structure diagram of an electronic device in an embodiment of the present invention. Figure 9The electronic device shown is a general maritime multi - band cloud and fog observation data quality marking control device. The electronic device can be a device such as a smart phone or a tablet computer. As shown, the electronic device 900 includes a processor 901 and a memory 902. Among them, the processor 901 is electrically connected to the memory 902. The processor 901 is the control center of the terminal 900, connecting various parts of the entire terminal using various interfaces and lines. By running or calling the computer programs stored in the memory 902 and calling the data stored in the memory 902, it executes various functions of the terminal and processes data, thereby monitoring the terminal as a whole.

[0173] In this embodiment, the processor 901 in the electronic device 900 will load the instructions corresponding to the processes of one or more computer programs into the memory 902 according to the following steps, and the processor 901 will run the computer programs stored in the memory 902 to implement various functions: Set two quality control codes as the QC method control code and the application quality control code respectively; Set a process for comprehensively analyzing maritime cloud and fog observation data using multiple quality control methods, and the comprehensive analysis process is used to form a final application quality control code based on multiple QC method quality control codes; Form an application quality control identification code based on laser fog measurement quality control data; Form an application quality control identification code based on millimeter - wave cloud and fog measurement quality control data; Obtain the original observation image to extract the all - sky application quality control identification code; The quality control identification code of weather and hydrological observation data.

[0174] The memory 902 can be used to store computer programs and data. The computer programs stored in the memory 902 contain instructions that can be executed in the processor. The computer programs can form various functional modules. The processor 901 executes various functional applications and data processing by calling the computer programs stored in the memory 902.

[0175] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0176] In the solution of the present invention, quality analysis is performed on a single - type device to form a quality control code.

[0177] In the solution of the present invention, an application quality control code is formed through the joint analysis of multiple - type quality controls.

[0178] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer - usable storage media (including but not limited to disk memories and optical memories, etc.) containing computer - usable program code.

[0179] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate means for realizing the functions specified in one or more of the flows Figure 1 one or more flows and / or blocks Figure 1 or means for realizing the functions specified in one or more of the blocks.

[0180] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that realize the functions specified in one or more of the flows Figure 1 one or more flows and / or blocks Figure 1 or means for realizing the functions specified in one or more of the blocks.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one or more of the flows Figure 1 one or more flows and / or blocks Figure 1 or means for realizing the functions specified in one or more of the blocks.

[0182] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling the quality marking of multi - band cloud and fog observation data at sea, characterized in that, The method includes: Setting two types of quality control codes, namely the QC method control code and the application quality control code; Setting a process for comprehensively analyzing marine cloud and fog observation data using quality control methods, and the comprehensive analysis process is used to form the final application quality control code according to the QC method quality control code; Forming an application quality control identification code based on the laser fog measurement quality control data; Forming an application quality control identification code based on the millimeter wave cloud and fog measurement quality control data; Obtaining the original observation image and extracting the all-sky application quality control identification code; Marking the quality control identification code of the weather and hydrological observation data; Among them, the setting of the two types of quality control codes as the QC method control code and the application quality control code specifically includes: Setting 4-level QC method quality control codes for each quality control method. Among them, the value range of the QC method quality control code is 0 to 3, where 0 represents correct, 1 represents suspicious, 2 represents warning, and 3 represents data error; Determining the application quality control code for each data, and the value range of the application quality control code is 0 to 9. Among them, 0 means the data is correct, 1 means the data is suspicious, 2 means the data is warning, 3 means the data is error, 4 to 6 are reserved, 7 means no observation task, 8 means data missing, and 9 means failed format check; Among them, the setting of the process for comprehensively analyzing marine cloud and fog observation data using quality control methods, and the comprehensive analysis process is used to form the final application quality control code according to the QC method quality control code, specifically includes: Reading the observation data before quality control and forming four types of quality control data: laser fog measurement, millimeter wave cloud and fog, meteorological and hydrological load, and all-sky imaging; Calculating the QC quality control code for the four types of quality control data; Fusing the QC quality control codes of the four types of quality control data into the application quality control code of a single type of device and outputting the observation data after quality control.

2. The method for controlling the quality marking of offshore multi-band cloud and fog observation data according to claim 1, wherein, The forming of the application quality control identification code based on the laser fog measurement quality control data specifically includes: After dead time correction processing, adding the first laser fog measurement quality control identification code; After geometric overlap factor correction processing, adding the second laser fog measurement quality control identification code; After background noise subtraction processing, adding the third laser fog measurement quality control identification code; After data smoothing processing, adding the fourth laser fog measurement quality control identification code; Performing cloud and aerosol algorithm classification and data quality identification; According to the first laser fog measurement quality control identification code, the second laser fog measurement quality control identification code, the third laser fog measurement quality control identification code, and the fourth laser fog measurement quality control identification code, and combining the data quality identification to form the laser fog measurement application quality control identification code using the first calculation formula; The first calculation formula is: ； Among them, M1 is the laser fog measurement application quality control identification code, Cx1 is the number of times when QC1, QC2, QC3, and QC4 are 1, Cx2 is the number of times when QC1, QC2, QC3, and QC4 are 2, Cx3 is the number of times when QC1, QC2, QC3, and QC4 are 3, QC1 is the first laser fog measurement quality control identification code, QC2 is the second laser fog measurement quality control identification code, QC3 is the third laser fog measurement quality control identification code, QC4 is the fourth laser fog measurement quality control identification code, L1 is the laser fog measurement data quality identification. When there is cloud data, L1 = 1, f() is a fitting function, and when the condition in () is satisfied, the fitting function outputs 0, otherwise, the fitting function outputs 1.

3. The method for controlling the quality marking of marine multi-band cloud and fog observation data according to claim 1, wherein Forming an application quality control identification code based on millimeter-wave cloud and fog measurement quality control data specifically includes: After spectral quality control, add the first millimeter-wave cloud and fog measurement quality control identification code; After noise elimination processing, add the second millimeter-wave cloud and fog measurement quality control identification code; After spectral moment extraction processing, add the third millimeter-wave cloud and fog measurement quality control identification code; After isolated echo processing, add the fourth millimeter-wave cloud and fog measurement quality control identification code; Perform velocity ambiguity processing to identify whether there is cloud data and label it as the millimeter-wave cloud and fog data quality label; According to the first millimeter-wave cloud and fog measurement quality control identification code, the second millimeter-wave cloud and fog measurement quality control identification code, the third millimeter-wave cloud and fog measurement quality control identification code, and the fourth millimeter-wave cloud and fog measurement quality control identification code, combine with the millimeter-wave cloud and fog data quality label to form the millimeter-wave cloud and fog application quality control identification code using the second calculation formula; The second calculation formula is: ； Wherein, M2 is the millimeter-wave cloud and fog application quality control identification code, Dx1 is the number of times QD1, QD2, QD3, and QD4 are 1, Dx2 is the number of times QD1, QD2, QD3, and QD4 are 2, Dx3 is the number of times QD1, QD2, QD3, and QD4 are 3, QD1 is the first millimeter-wave fog measurement quality control identification code, QD2 is the second millimeter-wave fog measurement quality control identification code, QD3 is the third millimeter-wave fog measurement quality control identification code, QD4 is the fourth millimeter-wave fog measurement quality control identification code, L is the millimeter-wave fog data quality label. When there is cloud data, L = 1, f() is a fitting function, and when the condition in () is satisfied, the fitting function outputs 0, otherwise, the fitting function outputs 1.

4. The method for controlling the quality marking of marine multi-band cloud and fog observation data according to claim 1, characterized in that, Obtaining the original observation image and extracting the all-sky application quality control identification code specifically includes: Obtain the original observation image, determine whether it is visible light channel data. If it is visible light channel data, perform brightness equalization correction and add the first all-sky quality control identification code. On this basis, perform white balance correction and add the second all-sky quality control identification code; If it is not visible light channel data, it is considered to be infrared channel data, perform brightness temperature value correction, and add the third all-sky quality control identification code; According to the first all-sky quality control identification code, the second all-sky quality control identification code, and the third all-sky quality control identification code, form the all-sky application quality control identification code using the third calculation formula; The third calculation formula is: ； Wherein, M2 is the all-sky application quality control identification code, Ex1 is the number of times QE1, QE2, QE3, and QE4 are 1, Ex2 is the number of times QE1, QE2, QE3, and QE4 are 2, Ex3 is the number of times QE1, QE2, QE3, and QE4 are 3, QE1 is the first all-sky quality control identification code, QE2 is the second all-sky quality control identification code, QE3 is the third all-sky quality control identification code, f() is a fitting function, and when the condition in () is satisfied, the fitting function outputs 0, otherwise, the fitting function outputs 1.

5. The method for controlling the quality marking of offshore multi-band cloud and fog observation data according to claim 1, characterized in that, Labeling the quality control identification code of weather and hydrological observation data specifically includes: When the observation data fails the format check, label the comprehensive quality control code as 2; When it fails the missing measurement check, no further subsequent checks are performed; When there is no observation task, label the application quality control code as 7; When there is an observation task, the application quality control code is 8; When the boundary value check fails, no subsequent checks are performed, and the application quality control code is 2; For the observed data that pass the boundary value check, perform the range of change value check, internal consistency check, time consistency check, spatial consistency check, and comprehensive check in sequence, and label the corresponding application quality control code.

6. The quality marking control system for multi-band cloud and fog observation data at sea, characterized in that The system is used to implement the method described in any one of claims 1-5, and the system includes: An application quality control code setting module for setting two quality control codes as the QC method control code and the application quality control code respectively; A process quality control module for setting a process for comprehensively analyzing the marine cloud and fog observation data using quality control methods, and the comprehensive analysis process is used to form the final application quality control code according to the QC method quality control code; A laser fog measurement module for forming an application quality control identification code according to the laser fog measurement quality control data; A millimeter wave cloud and fog measurement module for forming an application quality control identification code according to the millimeter wave cloud and fog measurement quality control data; A full sky imaging module for obtaining the original observation image and extracting the full sky application quality control identification code; A meteorological and hydrological module for labeling the quality control identification code of the weather and hydrological observation data.

7. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, The computer program instructions, when executed by the processor, implement the method described in any one of claims 1-5.

8. An electronic device, comprising a memory and a processor, characterized in that The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method described in any one of claims 1-5.

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