System and method for screening foggy weather process in North China

Abstract

The invention provides a system and a method for screening a heavy fog weather process in North China, and relates to the technical field of weather forecast, the system comprises a data fusion module, and a first data processing module, a second data processing module and an output module which are connected with the data fusion module; the first data processing module is used for acquiring sunflower-8 / 9 satellite inversion data and carrying out first quality control processing and inversion processing to obtain first output data, and the second data processing module is used for acquiring conventional meteorological data and carrying out second quality control to obtain second output data; the fusion data module is used for fusing the first output data and the second output data to obtain final fog area information, and the input module is used for outputting a fog correlation amount according to the final fog area information. The problems of low fog area forecasting accuracy and high weather forecasting cost in the prior art are solved.

Description

Technical Field

[0001] The invention relates to the technical field of meteorological forecasting, and in particular to a system and method for screening heavy fog weather processes in North China. Background Art

[0002] At present, weather forecasters need to rely on satellite images to judge foggy areas, which is a time-consuming and laborious task. They must carefully observe satellite images and determine the scope and intensity of foggy areas based on their own experience and judgment. However, this method has certain subjectivity and limitations. Different forecasters may come up with different results, and smaller or irregular foggy areas are easily overlooked or misjudged. In addition, the method of relying on manual judgment also requires a lot of human resources. Weather forecasters need to spend a lot of time and energy to analyze satellite images and issue relevant weather warning information in a timely manner. This not only increases the workload, but may also lead to delays in information transmission, affecting the decision-making and response capabilities of the public and relevant departments.

[0003] In order to solve these problems, an algorithm for automatically screening foggy weather processes in North China was developed, which can accurately determine the scope, intensity and duration of the foggy area. Compared with traditional manual judgment, the software has higher accuracy and reliability, improves the work efficiency of forecasters and reduces the consumption of human resources. Summary of the invention

[0004] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide a system and method for screening heavy fog weather processes in North China, which solves the problems of low accuracy in foggy area forecasting and high cost of meteorological forecasting in the prior art.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A system for screening heavy fog weather processes in North China, comprising:

[0007] A data fusion module and a first data processing module, a second data processing module and an output module all connected to the data fusion module;

[0008] The first data processing module is used to obtain the inversion data of the sunflower-8 / 9 satellite and perform the first quality control processing and inversion processing to obtain the first output data. The second data processing module is used to obtain conventional meteorological data and perform the second quality control to obtain the second output data. The fusion data module is used to fuse the first output data and the second output data to obtain the final fog area information. The input module is used to output fog-related quantities according to the final fog area information.

[0009] Preferably, the conventional meteorological data includes:

[0010] Visibility, relative humidity, precipitation, dust.

[0011] Preferably, the fog-related quantities include:

[0012] Temperature, wind speed, humidity.

[0013] Preferably, the second data processing module includes:

[0014] A first processing submodule, a second processing submodule and a third processing submodule;

[0015] The first processing submodule is used to perform a logical extreme value check to obtain extreme value data, the second processing submodule is used to perform time consistency processing on the extreme value data to obtain time consistent data, and the third processing submodule is used to perform space consistency processing on the time consistent data to obtain second output data.

[0016] A method for automatically screening heavy fog weather processes in North China, comprising:

[0017] Acquire the inversion data of the Sunflower-8 / 9 satellite and perform the first quality control processing and inversion processing to obtain the first output data;

[0018] Obtain conventional meteorological data and perform quality control to obtain second output data;

[0019] Fusing the first output data and the second output data to obtain final fog area information;

[0020] Output fog-related quantities according to the final fog area information.

[0021] The present invention discloses the following technical effects:

[0022] The present invention provides a system and method for screening foggy weather processes in North China, comprising: a data fusion module and a first data processing module, a second data processing module and an output module all connected to the data fusion module; the first data processing module is used to obtain the inversion data of the sunflower-8 / 9 satellite and perform a first quality control process and an inversion process to obtain the first output data, the second data processing module is used to obtain conventional meteorological data and perform a second quality control to obtain the second output data, the fusion data module is used to fuse the first output data and the second output data to obtain the final fog area information, and the input module is used to output fog-related quantities according to the final fog area information. The present invention performs quality control on the information in the sunflower-8 / 9 satellite inversion data and conventional materials and integrates the information obtained separately to obtain fog-related quantities for forecasting. The present invention has higher accuracy and reliability. Through comprehensive analysis of multi-source data, the system can accurately judge the scope, intensity and duration of the fog area, avoiding the subjectivity and errors in manual judgment. Secondly, the system realizes automatic monitoring and accurate early warning, greatly improving efficiency. Compared with traditional manual judgment, the system can complete monitoring and early warning work in a shorter time, providing more timely and effective support for responding to foggy weather events. In addition, the new system can also output relevant information about foggy weather in a timely manner, including the start and end time, area, number of stations and specific information of the foggy area, providing users with comprehensive foggy weather information and more accurate data support for disaster prevention and mitigation work. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 A schematic diagram of a system structure for screening heavy fog weather processes in North China provided by an embodiment of the present invention;

[0025] Figure 2 A framework diagram of a system for screening heavy fog weather processes in North China provided in an embodiment of the present invention.

[0026] Description of reference numerals:

[0027] 1-first data processing module, 2-second data processing module, 3-data fusion module, 4-output module. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] like Figure 1 As shown, the present invention provides a system for screening heavy fog weather processes in North China, comprising:

[0031] A data fusion module 3 and a first data processing module 1, a second data processing module 2 and an output module 4, all of which are connected to the data fusion module 3;

[0032] The first data processing module 1 is used to obtain the inversion data of the sunflower-8 / 9 satellite and perform the first quality control processing and inversion processing to obtain the first output data. The second data processing module 2 is used to obtain conventional meteorological data and perform the second quality control to obtain the second output data. The fusion data module is used to fuse the first output data and the second output data to obtain the final fog area information. The input module is used to output fog-related quantities according to the final fog area information.

[0033] Specifically, Figure 2 As shown in the figure, the algorithm for automatically screening the heavy fog weather process in North China includes four main modules. The first is the processing module of the inversion data of the sunflower-8 / 9 satellite (the first data processing module 1), which includes the quality control of the data and the implementation of the inversion technology. The second is the conventional data processing module of the ground station (the second data processing module 2), which reads the conventional meteorological data issued by the China Meteorological Administration and undergoes quality control processing. Next is the data fusion processing module, which is used to fuse the satellite inversion data and the conventional ground data to determine the final fog area range. Finally, there is the diagnosis result output module 4 (output module 4), which gives the key information such as the start and end time of foggy days in North China for many years, the area of ​​the foggy area, the number of foggy meteorological stations, and the station names, station numbers, and longitude and latitude geographical locations of these stations. At the same time, the meteorological quantities related to fog are saved, including temperature, wind speed, humidity and other data, to provide users with comprehensive foggy weather information.

[0034] Furthermore, the conventional meteorological data includes:

[0035] Visibility, relative humidity, precipitation, dust.

[0036] Furthermore, the fog-related quantities include:

[0037] Temperature, wind speed, humidity, fog start and end time, fog area, number of foggy stations and foggy station information.

[0038] Specifically, a processing module for the inversion data of the Sunflower-8 / 9 satellite was established, including data quality control and the implementation of inversion technology:

[0039] Data quality control includes: (1) Automated data verification of the raw data of Sunflower-8 / 9, that is, automatically detecting and marking outliers or errors in the raw data. Pixel values ​​that exceed the expected range or are obviously abnormal in brightness temperature data will be automatically marked as possible errors. (2) Cross-validation: Compare with other satellite or ground observation data such as GOES or Fengyun to identify and correct systematic errors. (3) Long-term consistency check: Check the consistency and trend changes of the data by analyzing long-term data sets. Any abnormal changes in long-term trends may indicate that the sensor calibration needs to be adjusted or there are other potential problems. (4) Noise removal: Apply filters to reduce or remove noise in the data. The noise removal process includes removing random noise, strip noise and other factors that may interfere with the data. (5) Radiation correction: Correct the radiation response of the sensor to ensure that the measured value reflects the actual physical radiation. Factors such as atmospheric conditions, viewing angle and solar radiation angle are considered in radiation correction. (6) Geometric correction: Adjust and correct the geometric distortion of the sensor so that the image and data are accurately located in the geographic coordinate system. This includes techniques such as terrain effect correction, projection transformation and image registration. (7) Quality marking: Adding quality markings to the data indicates its reliability and accuracy, helping users understand the credibility of the data and make appropriate decisions in further analysis and application. Through the above calibration and processing steps, the Sunflower-8 satellite is able to provide high-precision and reliable meteorological data, providing important support for weather forecasting, environmental monitoring and disaster management.

[0040] Satellite inversion technology: Satellite detection of fog combines the temperature, texture and noise detection steps commonly used in fog detection. The inversion of the fog top height at night is obtained by the correlation between the difference between the long-wave infrared (3.9μm) and medium-wave infrared (11.2μm) channels (Ellrod, 1995). During the day, due to the similar radiation characteristics of fog and stratus clouds, the stratus / stratocumulus cloud area is extracted from the cloud classification data of the sunflower-8 satellite as the fog / low cloud area. Finally, the sunflower-8 / 9 satellite inversion database is obtained.

[0041] Furthermore, the second data processing module includes:

[0042] A first processing submodule, a second processing submodule and a third processing submodule;

[0043] The first processing submodule is used to perform a logical extreme value check to obtain extreme value data, the second processing submodule is used to perform time consistency processing on the extreme value data to obtain time consistent data, and the third processing submodule is used to perform space consistency processing on the time consistent data to obtain second output data.

[0044] Specifically, step 2: establish a ground station routine data processing module, which mainly reads the visibility, relative humidity, precipitation, dust and other routine meteorological data issued by the China Meteorological Administration. The quality control includes logical extreme value check, time consistency check, spatial consistency check and other quality control. Among them, the data processing process of logical extreme value check is to identify and filter out those abnormal values ​​that exceed the reasonable range or data points that do not conform to physical laws. Through this check, abnormal data caused by sensor failure, data transmission error or other unexpected reasons can be effectively removed. Specifically, it includes (1) threshold detection: threshold detection is performed on the data. Any value that exceeds the preset range will be marked as abnormal and discarded. (2) physical consistency check: check whether the data conforms to known physical laws and rules. Data points that do not conform to physical laws are regarded as invalid data. For example, the near-ground temperature is set in the range of -50℃ to 60℃.

[0045] Temporal consistency checks are designed to ensure that the data collected over a period of time is consistent and reasonable, and to avoid sudden abnormal fluctuations or unreasonable changes. By checking the time series consistency of the data, temporal anomalies and errors can be detected and corrected. Specifically, they include: (1) Time series analysis: Analyze the data at consecutive time points at the same location to check the trend and amplitude of data changes. Sudden and unreasonable changes usually indicate that there is a problem with the data. (2) Trend and periodicity check: Check whether the data conforms to expected trends and periodic changes, such as daytime temperature changes, seasonal changes, etc. Data that does not conform to these expected patterns may be erroneous and require further verification. (3) Abnormal change detection: Set a change threshold, and any sudden change that exceeds the set threshold will be marked as a potential anomaly. For example, a sharp change in temperature in a short period of time may indicate a sensor failure or data processing error.

[0046] Spatial consistency check, that is, to ensure that the data collected at the same time have reasonable coherence in spatial distribution. By checking spatial consistency, spatial outliers or erroneous data points can be identified and corrected. Specifically, it includes (1) comparison of adjacent sites to detect whether there are significant unreasonable differences. In general, the attribute values ​​of spatially adjacent points (such as visibility, temperature, humidity, etc.) should have a relatively smooth transition. (2) Spatial smoothing: Use spatial smoothing algorithms (such as low-pass filters, Kriging interpolation, etc.) to process the data to remove spatial noise and anomalies. Through smoothing, the overall trend and structure of the data are maintained, while drastic fluctuations in a small range are eliminated. (3) Spatial terrain analysis: Check whether the data conforms to known spatial patterns or geographical features, such as the sea-land boundary, terrain influence, etc. The data should reflect these natural geographical features, and unreasonable spatial distribution may indicate data problems.

[0047] Finally, the ground fog database is obtained.

[0048] When there is no precipitation or dust, the relative humidity is greater than or equal to 90%, and the atmospheric visibility is less than 1km, it is judged to be a foggy area.

[0049] Step 3: Establish a data fusion processing module, and process the results of the inversion data of the sunflower-8 / 9 satellite into the sea fog area, and the processing results of the second data processing module into the land fog area.

[0050] Step 4: Establish the diagnostic result output module 4, and provide the key information such as the start and end time of foggy days in North China over the years, the area of ​​foggy areas, the number of foggy meteorological stations, and the station names, station numbers, and longitude and latitude geographical locations of these stations. The final output module uses the historical data from 2012 to 2024 combined with all the fog-related quantities output by the foggy area of ​​the current fusion module. At the same time, fog-related meteorological quantities, including temperature, wind speed, humidity and other data, are saved to provide users with comprehensive foggy meteorological information. In addition, the fog-related output quantities can be adjusted according to the needs of forecasters and different application scenarios to meet the needs of different users.

[0051] This embodiment also provides a method for automatically screening heavy fog weather processes in North China, including:

[0052] Acquire the inversion data of the Sunflower-8 / 9 satellite and perform the first quality control processing and inversion processing to obtain the first output data;

[0053] Obtain conventional meteorological data and perform quality control to obtain second output data;

[0054] Fusing the first output data and the second output data to obtain final fog area information;

[0055] Output fog-related quantities according to the final fog area information.

[0056] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0057] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A system for screening heavy fog weather processes in North China, characterized in that: include: A data fusion module and a first data processing module, a second data processing module and an output module all connected to the data fusion module; The first data processing module is used to obtain the inversion data of the sunflower-8 / 9 satellite and perform the first quality control processing and inversion processing to obtain the first output data. The second data processing module is used to obtain conventional meteorological data and perform the second quality control to obtain the second output data. The fusion data module is used to fuse the first output data and the second output data to obtain the final fog area information. The input module is used to output fog-related quantities according to the final fog area information.

2. A system for screening heavy fog weather processes in North China according to claim 1, characterized in that: The conventional meteorological data include: Visibility, relative humidity, precipitation, dust.

3. The system for screening heavy fog weather processes in North China according to claim 1, characterized in that: The fog related quantities include: Temperature, wind speed, humidity.

4. The system for screening heavy fog weather processes in North China according to claim 1, characterized in that: The second data processing module includes: A first processing submodule, a second processing submodule and a third processing submodule; The first processing submodule is used to perform a logical extreme value check to obtain extreme value data, the second processing submodule is used to perform time consistency processing on the extreme value data to obtain time consistent data, and the third processing submodule is used to perform space consistency processing on the time consistent data to obtain second output data.

5. A method for automatically screening foggy weather processes in North China, characterized in that: include: Acquire the inversion data of the Sunflower-8 / 9 satellite and perform the first quality control processing and inversion processing to obtain the first output data; Obtain conventional meteorological data and perform quality control to obtain second output data; Fusing the first output data and the second output data to obtain final fog area information; Output fog-related quantities according to the final fog area information.

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