CN117975700A - Method and system for generating air ice accumulation early warning information based on digital earth - Google Patents
Method and system for generating air ice accumulation early warning information based on digital earth Download PDFInfo
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Abstract
The invention belongs to the technical field of weather forecast early warning air ice accumulation analysis processing, and provides an air ice accumulation early warning information generation method and system based on digital earth, wherein the method comprises the following steps: establishing an air ice accumulation historical case library; according to the sample data in the established air ice accumulation history case library, carrying out analysis and evaluation processing of various air ice accumulation diagnosis algorithms; according to analysis and evaluation processing data of various air ice accumulation diagnostic algorithms, determining a comprehensive weight coefficient and an air ice accumulation intensity index correction equation of each air ice accumulation diagnostic algorithm by adopting a hierarchical weight integration method; and receiving current user input, and generating air ice accumulation early warning information matched with the current user input by utilizing the ice accumulation intensity index correction equation of each determined air ice accumulation diagnosis algorithm. The invention effectively improves the automation of the development verification and correction processing of the air ice accumulation diagnosis algorithm, and improves the accuracy and reliability of determining the air ice accumulation grade or ice accumulation degree.
Description
Technical Field
The invention relates to the technical field of weather forecast early warning air ice accumulation analysis processing, in particular to an air ice accumulation early warning information generation method and system based on digital earth.
Background
At present, a common method is to utilize an aerial icing diagnosis algorithm to carry out icing potential forecasting and early warning based on a numerical weather forecasting product. However, the existing air ice accumulation diagnosis algorithm is an engineering empirical formula, and has a certain risk of missing report and empty report, and an algorithm development user is required to compare, check and correct. Currently, the comparison and verification of the air ice accumulation diagnosis algorithm are mostly completed manually, and the comparison and analysis are performed by manually collecting typical cases and writing calculation operations and manually processing calculation results by virtue of development users. This not only takes up a lot of time for the algorithm development user, severely affecting the working efficiency. Meanwhile, the aerial icing diagnosis algorithm is manually carried out, so that the number of comparison verification coverage cases is small, the comparison analysis result depends on manual experience and qualitative analysis, and automation, flow and accurate quantification of the comparison verification work cannot be realized. Moreover, a small amount of manually completed comparison verification case results are not easy to multiplex, the correction of the diagnosis algorithm results cannot be effectively supported, and a more efficient and automatic comparison verification process, parameter or result correction process cannot be realized.
Therefore, it is necessary to provide a new method for generating the early warning information of the ice accumulation in the air based on the digital earth, so as to solve the above-mentioned problems.
Disclosure of Invention
The invention aims to provide an aerial ice accumulation early warning information generation method and system based on digital earth, which are used for solving the technical problems that in the prior art, a comparison analysis result depends on manual experience and qualitative analysis, automation, flow and accurate quantification of comparison verification work cannot be realized, a small amount of manually completed comparison verification case results are not easy to multiplex, correction of diagnostic algorithm results cannot be effectively supported, a more efficient and automatic comparison verification process, parameter or result correction process and the like cannot be realized. The invention adopts the following technical proposal to solve the problems.
The first aspect of the invention provides a method for generating early warning information of ice accumulation in the air based on digital earth, which comprises the following steps: establishing an aerial icing historical case base based on a digital earth bottom database and multi-source meteorological data extracted by leading, wherein the multi-source meteorological data comprises an aviation aerial icing report, observation and detection data, a numerical forecasting product and analysis data; according to the sample data in the established air ice accumulation history case library, carrying out analysis and evaluation processing of various air ice accumulation diagnosis algorithms; according to analysis and evaluation processing data of various air ice accumulation diagnostic algorithms, a hierarchical weight integration method is adopted to determine the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm and an air ice accumulation intensity index correction equation, and the method specifically comprises the following steps of calculating the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm by adopting the following weight coefficients: accuracy rate weight coefficient, empty report rate weight coefficient, miss report rate weight coefficient;
and receiving current user input, and generating air ice accumulation early warning information matched with the current user input by utilizing the determined air ice accumulation intensity index correction equation.
According to an alternative embodiment, the calculating the comprehensive weight coefficient of the air ice accumulation diagnosis algorithm includes: the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm is obtained through calculation by adopting the following expression:
;
Wherein t i represents a comprehensive weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; y i represents an accuracy weight coefficient of an ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; z i represents the air report rate weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; w i represents a missing report rate weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; b represents a duty cycle corresponding to the accuracy weight coefficient y i; c represents a duty cycle corresponding to the null report rate weighting coefficient z i; d represents the duty ratio corresponding to the miss-report rate weight coefficient w i; b is in the range of 0.3 to 0.5, c is in the range of 0.3 to 0.5, d is in the range of 0.1 to 0.3, and b+c+d=1 is ensured.
According to an alternative embodiment, further comprising: according to the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm obtained through calculation, determining an air ice accumulation intensity index correction equation:
;
Wherein A represents the ice strength index after correction; t i represents the comprehensive weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2,3, and n; And the ice accumulation intensity indexes obtained by diagnosing by the ith air ice accumulation diagnosis algorithm are shown, each ice accumulation intensity index corresponds to one ice accumulation grade, and i is a positive integer, and specifically comprises 1,2, 3.
The second aspect of the present invention provides a system for generating early warning information of ice accumulation in the air based on digital earth, which adopts the method for generating early warning information of ice accumulation in the air based on digital earth according to the first aspect of the present invention, and the system for generating early warning information of ice accumulation in the air comprises: the system comprises a multisource meteorological data guiding and extracting module, an air icing historical case library management module, an air icing diagnosis algorithm verification and evaluation module, an air icing diagnosis algorithm intelligent correction module, a geographic information display service module and an air icing early warning information display module, wherein the air icing diagnosis algorithm verification and evaluation module realizes the comparative verification and the accuracy rate, the air reporting rate and the missing reporting rate statistical analysis and evaluation of an air icing diagnosis algorithm based on historical samples in an air icing historical case library; the intelligent correction module of the air ice accumulation diagnostic algorithm performs intelligent correction of the diagnostic result based on statistical analysis data of the air ice accumulation diagnostic algorithm, calculates and obtains comprehensive weight coefficients and an air ice accumulation intensity index correction equation of each air ice accumulation diagnostic algorithm, and generates updated air ice accumulation early warning information.
In a third aspect, the present invention provides an electronic device comprising: one or more processors; a storage means for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of the first aspect of the present invention.
In a fourth aspect, the invention provides a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the method according to the first aspect of the invention.
Compared with the prior art, the invention has the following advantages and beneficial effects:
The invention realizes data standardization, flow automation, correction intellectualization, result visualization and the like by leading and processing multi-source meteorological data, establishing an air icing historical case base, comparing and verifying various air icing algorithms, correcting and processing an air icing diagnosis algorithm, visually displaying air icing early warning information and the like, effectively improves the automation of developing and verifying the air icing diagnosis algorithm and correcting the air icing diagnosis algorithm, and improves the accuracy and reliability of determining the air icing grade or the icing degree.
In addition, when new air icing case samples exist, the samples can be automatically updated, namely, based on a large number of samples in a case library, the comparison verification of various air icing diagnosis algorithms is automatically carried out, and statistical analysis parameters such as accuracy, blank report rate, missing report rate and the like are provided, so that the method is convenient, quick and accurate, the problems that the existing manual algorithm is less in comparison verification coverage sample and low in working efficiency are effectively avoided, and the working efficiency of the development, debugging, optimization and verification of the air icing algorithm is greatly improved.
In addition, based on the comparison and verification results (including accuracy, empty report rate, missing report rate and the like) of the air ice accumulation diagnosis algorithm and statistical analysis data, a grading weight integration method is automatically adopted to realize the correction function of the diagnosis result, the correction equation of the comprehensive weight coefficient and the air ice accumulation intensity index of each air ice accumulation diagnosis algorithm is obtained through calculation, and corrected air ice accumulation early warning information is generated, so that the accuracy of the air ice accumulation potential diagnosis and the severity degree is effectively improved.
In addition, based on the digital earth frame, geographic data display information is superimposed on the generated air ice accumulation early warning information, meteorological environment elements and air ice accumulation diagnosis early warning information are displayed in a two-dimensional/three-dimensional visual environment, and clear, visual and immersive use experience is provided for users.
Drawings
FIG. 1 is a flow chart of an example of a digital earth-based overhead ice accumulation warning information generation method of the present invention;
FIG. 2 is a block diagram of an example application of the digital earth-based overhead ice accumulation warning information generation method of the present invention;
FIG. 3 is a schematic diagram of a middle partial flow of an embodiment of the method for generating overhead ice accumulation warning information based on digital earth according to the present invention;
FIG. 4 is a schematic diagram of a frame of an example of a digital earth-based overhead ice accumulation warning information generating system of the present invention;
FIG. 5 is a schematic diagram of an example of an application of the digital earth-based overhead ice accumulation warning information generating system of the present invention;
FIG. 6 is a schematic structural diagram of an embodiment of an electronic device according to the present invention;
Fig. 7 is a schematic diagram of an embodiment of a computer readable medium according to the present invention.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
In view of the above problems, the invention provides an air ice accumulation early warning information generation method based on digital earth, which realizes the comparison verification and correction processing of a multi-air ice accumulation diagnosis algorithm based on digital earth. The method is characterized in that an automatic, pipelining and intelligent operation flow is constructed based on a digital earth frame, and the method comprises multisource meteorological data guiding processing, establishment and management of an air icing history case base, contrast verification of various air icing algorithms, parameter correction and equation correction, visualization display of air icing early warning information and the like, so that the efficiency of air icing diagnosis algorithm development verification and correction use can be effectively improved. In addition, through covering a large number of historical samples of the aerial icing cases, the multi-parameter evaluation of various aerial icing diagnosis algorithms is carried out to realize automatic intelligent correction, and the accuracy and reliability of determining the aerial icing grade or the icing degree can be effectively improved.
It should be noted that the digital earth refers to an earth virtual system based on earth coordinates and having multiple resolutions of massive geographic, meteorological data and two-dimensional/three-dimensional display. The aerial icing refers to that when an aircraft flies in a cloud layer containing supercooled water drops, certain parts of the surface of the aircraft body are quickly condensed into ice, the shape and the surface characteristics of the aircraft body are changed, the aerodynamic characteristics of the aircraft are seriously affected, the resistance is increased, the lifting force is reduced, and the aircraft can lose control when serious, so that the aircraft is in a flight accident. The visualization is to use computer graphics and image processing technology to convert data into graphics or images to be displayed on a screen.
Example 1
The following describes the present invention in detail with reference to fig. 1,2, 3 and 4.
Fig. 1 is a flowchart illustrating steps of an example of a method for generating digital earth-based overhead ice accumulation warning information according to the present invention.
As shown in fig. 1, in step S101, an airborne icing history case base is established based on the digital earth ground layer database and the leading extracted multi-source weather data including airborne icing reports, observation and detection data, numerical forecast products and analysis data.
Fig. 2 is a frame diagram of an application scenario example to which the digital earth-based overhead ice accumulation early warning information generation method of the present invention is applied.
In the example of fig. 2, the system (corresponding to the "air ice accumulation early warning information generation system" in the figure) comprises a multi-source meteorological data leading and extracting module, an air ice accumulation historical case base management module, an air ice accumulation diagnosis algorithm packaging module, an air ice accumulation diagnosis algorithm verification and evaluation module, an air ice accumulation diagnosis algorithm intelligent correction module, a geographic information display service module and an air ice accumulation early warning information display module, wherein the air ice accumulation diagnosis algorithm verification and evaluation module realizes the comparison verification and the accuracy rate, the air report rate and the leakage report rate statistical analysis and evaluation of the air ice accumulation diagnosis algorithm based on historical samples in the air ice accumulation historical case base; the intelligent correction module of the air ice accumulation diagnostic algorithm performs intelligent correction of diagnostic results based on statistical analysis data (such as parameters of accuracy, blank report rate, missing report rate and the like) of the air ice accumulation diagnostic algorithm, obtains comprehensive weight coefficients and an air ice accumulation intensity index correction equation of each air ice accumulation diagnostic algorithm, and generates updated air ice accumulation early warning information. The detailed implementation process of the air ice accumulation early warning information generation method of the present invention will be described in detail with reference to an application example of fig. 2.
In one embodiment, an airborne icing history case base is established based on a digital earth underlying database (i.e., the digital earth underlying database) and the extracted multisource meteorological data, wherein the multisource meteorological data includes airborne icing reports, observation and detection data, numerical forecasting products and analysis data. The air icing history case library comprises air icing report cases corresponding to air icing reports, observation detection data, numerical forecasting products, analysis data and the like, such as air icing reports in a specific altitude range in a specified historical time period, wherein the air icing reports comprise air icing occurrence time, places/areas, altitude, icing intensity (no icing, mild icing, moderate icing, severe icing) and the like. Typical overhead ice accumulation reporting cases include time of occurrence, place/area of occurrence, severity (e.g., ice accumulation intensity), altitude of occurrence (e.g., altitude) of overhead ice accumulation in 1999-2002, see in particular table 1 below. In addition, related parameters such as temperature, humidity, etc. associated with ice accretion for a particular location/region are included.
TABLE 1
Table 1 is an example table showing sample data for the 1999-2002 air ice-accumulation history case library.
Optionally, the air ice accumulation historical case library is also corresponding to a historical case library server, and the server deploys an air ice accumulation historical case library management module for storing and managing historical samples and newly added samples in the air ice accumulation historical case database, so that the functions of adding, deleting, changing and searching can be realized.
In a specific embodiment, for example, the multi-source meteorological data extracted by the tapping is tapped by a server corresponding to the multi-source meteorological data from the overhead ice accumulation history case library, so that the tapping processing function is realized, and the meteorological data pushed from the server corresponding to the multi-source meteorological data can be received.
Specifically, the meteorological data comprises meteorological environment element data, and the meteorological environment element data comprises ground/high altitude temperature, humidity, wind speed/wind direction, pressure and the like.
For example, when the meteorological office data of a local department or a related department starts pushing, the guiding process of the server corresponding to the multi-source meteorological data is triggered. Specifically, the extraction of the lead connection is completed through the following steps:
step S201: push data is received.
After receiving the push data, the push data is automatically standardized.
Specifically, the pushing data comprise numerical weather forecast products, aviation air ice accumulation reports, ground detection data pushing data, high-altitude observation data pushing data and the like.
When the air ice accumulation history case base receives one or more meteorological pushing data, the rear end (such as a corresponding server) of the air ice accumulation history case base automatically performs standardized processing on the one or more meteorological pushing data, and specifically comprises decoding, classifying, storing and the like.
And extracting meteorological environment element data from the pushed ground detection data, high-altitude observation data, numerical forecasting products and analysis data. Specifically, the extraction of the meteorological environment element data comprises the steps of extracting meteorological environment element data such as wind field, humidity, precipitation, temperature, air pressure and the like, and pushing the extracted meteorological environment element data to an air ice accumulation diagnosis algorithm verification evaluation module or an air ice accumulation diagnosis algorithm intelligent correction module for subsequent data evaluation and analysis processing.
In step S202, it is determined whether the pushing data includes an airborne icing report (i.e. corresponds to "whether there is an airborne icing report" in fig. 3).
And pushing the air ice accumulation history case library to a corresponding server of the air ice accumulation history case library under the condition that the air ice accumulation history case library is judged to contain the aviation air ice accumulation report (namely, corresponding to 'yes' in fig. 3), so as to increase and update sample data in the air ice accumulation history case library.
And pushing the pushed aviation air ice accumulation report data to a corresponding server of an air ice accumulation historical case library according to the air ice accumulation occurrence time, occurrence place/area, occurrence altitude and ice accumulation intensity level so as to finish the increase and update of sample data in the air ice accumulation historical case library. Meanwhile, triggering an air ice accumulation diagnosis algorithm verification evaluation module, and calculating and updating air ice accumulation accuracy, air report rate and report missing rate statistical analysis data by combining the pushed meteorological environment element data. Further, an intelligent correction module of the air ice accumulation diagnostic algorithm is utilized, a hierarchical weight integration method is adopted to determine the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm, and an air ice accumulation intensity index correction equation, namely intelligent correction, is updated. In the example of fig. 3, the method further includes generating air ice accumulation early warning information by using the obtained updated air ice accumulation intensity index correction equation, and displaying the air ice accumulation early warning information in a visual manner.
And pushing the air ice accumulation diagnosis algorithm to a corresponding server of the air ice accumulation diagnosis algorithm intelligent correction module under the condition that the air ice accumulation report is not contained (namely, corresponding to 'no' in fig. 3). And then, generating the air ice accumulation early warning information by using a preset/existing correction equation so as to complete intelligent correction, and visually displaying the air ice accumulation early warning information.
It should be noted that the foregoing is merely illustrative of the present invention and is not to be construed as limiting thereof.
Next, in step S102, analysis and evaluation processing of various air ice accumulation diagnostic algorithms are performed according to the sample data in the established air ice accumulation history case library.
In a specific embodiment, according to the air ice accumulation history case library established in step S101, sample data of a specified history period (for example, 1999-2002) is selected, and analysis and evaluation processing of various air ice accumulation diagnostic algorithms are performed.
Specifically, the plurality of air ice accumulation diagnostic algorithms includes the following algorithms: IC index method, false frost point temperature empirical method, and ice accumulation index method.
For the IC index method, the ice accumulation index of the region of interest height H is calculated using the following expression.
;
Wherein IC H is the ice accretion index of the region of interest height H; RH H is the relative humidity in units of the region of interest height H; t H is the temperature of the region of interest height H in degrees Celsius; the subscript H denotes altitude or isobaric surface altitude.
Specifically, in this application example, for example, referring to the international civil aviation organization recommendation, when IC is equal to or less than 0, there is no ice accumulation; when 0< IC <40%, slight ice accumulation is caused; when the IC is more than or equal to 40% and less than 70%, the ice is accumulated moderately; when IC is more than or equal to 70%, the ice is seriously accumulated.
In this example, the ice strength index a 1 = [0,1,2,3] is defined, corresponding to no ice accumulation, mild ice accumulation, moderate ice accumulation, severe ice accumulation, respectively.
For the fake frost point temperature empirical method, the following expression is adopted to calculate the fake frost point temperature TF of the height H of the concerned area:
;
Wherein TF H is the false frost point temperature of the region of interest height H; v is the flying speed, the unit km/h; t H is the temperature of the region of interest height H in degrees Celsius; td H is the dew point temperature in degrees Celsius for the region of interest height H.
Specifically, in this application example, whenWhen the ice accumulation exists, the ice accumulation does not exist. When (when)When ice accumulation exists; /(I)And medium ice accumulation.
Further, according to the calculated value of the temperature of the false frost point and the above judgment rule, determining whether ice accumulation exists in a certain area and a certain height position and the ice accumulation degree (or ice accumulation grade). Specifically defined ice strength index a 2 = [0,1,2] corresponds to no ice accumulation, mild ice accumulation and moderate ice accumulation respectively.
For the ice accumulation index method, the liquid water content of a certain region of interest, height H, is calculated using the following expression.
;
Wherein I H represents the ice accretion index of the region of interest height H; LWC H is the liquid water content of the zone of interest height H, in g/kg;
specifically, in this application example, when I <1, there is no ice accumulation; when I is 1 to or less than 4.5, the ice is slightly accumulated; when I is more than or equal to 4.5 and less than or equal to 8, the ice is accumulated moderately; when I is more than or equal to 8, the ice is seriously accumulated.
Specifically defined ice strength indexes a 3 = [0,1,2,3] respectively correspond to no ice accumulation, slight ice accumulation, moderate ice accumulation and serious ice accumulation.
In a specific embodiment, the verification and evaluation module of the air ice accumulation diagnostic algorithm invokes the encapsulation module of the air ice accumulation algorithm based on the selected sample data from 1999 to 2002 to perform the comparison verification of the air ice accumulation diagnostic algorithm and the statistical analysis and evaluation of multiple parameters (such as accuracy, blank report rate, missing report rate and the like), thereby realizing the automatic comparison and verification function of multiple algorithms and the statistical analysis and evaluation function of multiple parameters.
Specifically, the verification evaluation statistical analysis parameters comprise an accuracy rate, an empty report rate and a missing report rate, wherein each parameter is defined, and a formula for calculating each parameter is determined. The method comprises the following steps:
accuracy refers to the fact that the forecast is correct in both cases with and without algorithmic diagnostics. The accuracy was calculated using the following expression: accuracy = forecast correct number of cases/total number of historical cases (e.g., total number of historical cases in a specified historical time period) ×100%.
The empty report rate refers to the condition that the algorithm diagnosis is available and the condition is not available, namely the empty report rate. The method is specifically calculated by adopting the following expression: empty report rate = empty report case number/algorithm diagnosing ice accumulation case number x 100%;
the missing report rate refers to no algorithm diagnosis and live condition, namely missing report. The method is specifically calculated by adopting the following expression: missing report rate = number of missing report cases/number of ice accumulation history cases x 100%.
Further, the intelligent correction module of the air ice accumulation diagnosis algorithm performs subsequent correction calculation or correction processing based on the statistical analysis data of the accuracy, the blank report rate and the missing report rate of the three air ice accumulation diagnosis algorithms.
It should be noted that the foregoing is merely illustrative of the present invention and is not to be construed as limiting thereof.
Next, in step S103, according to the analysis and evaluation processing data of the plurality of air ice accumulation diagnostic algorithms, a hierarchical weight integration method is adopted to determine the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm and the air ice accumulation intensity index correction equation, which specifically includes calculating the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm by adopting the following weight coefficients: accuracy weighting coefficient, null reporting rate weighting coefficient, miss reporting rate weighting coefficient.
In one embodiment, the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm is determined by adopting a hierarchical weight integration method according to analysis and evaluation processing data (such as the verification results shown in table 2) of a plurality of air ice accumulation diagnostic algorithms.
TABLE 2
Table 2 is an exemplary table of results of parameter comparison verification of 1999-2002 historical samples using the three above-described air ice accumulation diagnostic algorithms.
And particularly, calculating an accuracy weight coefficient, an empty report rate weight coefficient, a missing report rate weight coefficient and a comprehensive weight coefficient of each air ice accumulation diagnosis algorithm by adopting a hierarchical weight integration method.
More specifically, the first stage of the grading weight specifically calculates the accuracy weight coefficient of each air ice accumulation diagnosis algorithm，/>For the accuracy of each air icing diagnostic algorithm,/>The number of the air ice accumulation diagnostic algorithms;
Further, the air report rate weight coefficient of each air ice accumulation diagnosis algorithm is calculated respectively ，Air report rate for each air ice accumulation diagnostic algorithm,/>Is the number of the air ice accumulation diagnosis algorithms.
Further, the missing report rate weight coefficient of each air ice accumulation diagnosis algorithm is calculated respectively，Missing report rate for each air icing diagnosis algorithm,/>Is the number of the air ice accumulation diagnosis algorithms.
Then, the second stage of the grading weight calculates the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm according to different weight distribution:
;
Wherein t i represents a comprehensive weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; y i represents an accuracy weight coefficient of an ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; z i represents the air report rate weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; w i represents a missing report rate weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; b represents a duty cycle corresponding to the accuracy weight coefficient y i; c represents a duty cycle corresponding to the null report rate weighting coefficient z i; d represents the duty cycle corresponding to the miss-report rate weight coefficient w i.
Alternatively, b is in the range of 0.3 to 0.5, c is in the range of 0.3 to 0.5, d is in the range of 0.1 to 0.3, and b+c+d=1 is ensured.
In a specific application example, for example, b is 0.4, c is 0.4, and d is 0.2, the above formula is correspondingly modified as follows:
wherein t i represents the comprehensive weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1, 2 and 3; y i represents an accuracy weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1, 2 and 3; z i represents the empty report rate weight coefficient of the ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1, 2 and 3; w i represents a missing report rate weight coefficient of an ith air ice accumulation diagnosis algorithm, wherein i is a positive integer, and specifically comprises 1, 2 and 3; b represents a duty cycle corresponding to the accuracy weight coefficient y i; c represents a duty cycle corresponding to the null report rate weighting coefficient z i; d represents the duty cycle corresponding to the miss-report rate weight coefficient w i.
The specific numerical values of b, c and d can be flexibly configured according to application scenes so as to improve the accuracy of the diagnosis of ice accumulation in the air. In general, the fake frost point temperature empirical method considers the influences of the aircraft flight speed and the dynamic temperature rise, has higher ice accumulation prediction accuracy rate for certain concerned areas (such as eastern China) in spring, can effectively predict ice accumulation conditions of different heights, and has a missing report rate obviously smaller than that of an IC index method. The IC index method calculates the potential of ice accumulation based on the atmospheric temperature and relative humidity of certain regions of interest, and as a result, actually reflects the possibility of ice accumulation in the environmental background of the regions of interest, and the number of air reports in the high altitude region is less than that of the empirical method of the false frost point temperature, so that the IC index method is more reliable in the case of uncertain wind field conditions and aircraft airspeed. Therefore, for aircrafts such as large aircrafts or transport planes, the airspeed is slower, the acceleration is small, the accelerating and warming effects are poor, strong ice accumulation is easily encountered, caution is needed when ice accumulation prediction or prediction is carried out, the experimental calculation of the temperature of the false frost point is selected at the moment to be more proper, the ice accumulation area can be accurately predicted, the flight safety of the large aircrafts is effectively ensured, the weight of the large aircrafts can be properly increased, the weight increasing range can be determined according to the type of the aircrafts, the concerned area, the altitude and other parameters, and the weight increasing range is 0.3-0.5. For the aircraft with fast airspeed and large acceleration, if the aircraft suffers from ice accumulation at high altitude, the surface can be heated by acceleration to melt the ice accumulation, and the slight ice accumulation with smaller influence can be ignored, so that excessive air report is not suitable to occur, therefore, the selection of the IC exponential method prediction is more suitable, the task can be completed under the condition of ensuring safety, the weight of the aircraft can be properly increased, and the weight increasing range is determined according to the type of the aircraft, the area of interest, the altitude and other parameters, for example, the weight increasing range is 0.3-0.5.
For example, based on the above table 2, the comprehensive weight coefficient is calculated by using the hierarchical weight integration method, see in particular table 3.
TABLE 3 Table 3
Table 3 is an example table of integrated weight coefficients obtained by performing parameter comparison verification on 1999-2002 historical samples using the three above-described air ice accumulation diagnostic algorithms.
And then, constructing an intelligent correction equation for obtaining the air icing diagnosis algorithm based on the comprehensive weight coefficient at the third stage of the grading weight.
According to the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm obtained through calculation, determining an air ice accumulation intensity index correction equation as follows:
;
Wherein A represents the ice strength index after correction; t i represents the comprehensive weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2,3, and n; And the ice accumulation intensity indexes obtained by diagnosing by the ith air ice accumulation diagnosis algorithm are shown, each ice accumulation intensity index corresponds to one ice accumulation grade, and i is a positive integer, and specifically comprises 1,2, 3.
And (3) carrying out air ice accumulation intensity grading on the A value obtained after correction according to the threshold value of [0,1,2 and 3], wherein the air ice accumulation intensity grading comprises the following four ice accumulation grades: no ice accumulation (a=0), slight ice accumulation (0.ltoreq.a < 1), moderate ice accumulation (1.ltoreq.a < 2), severe ice accumulation (2.ltoreq.a) for judging the ice accumulation grade or ice accumulation degree.
Specifically, based on the comprehensive weight coefficients of table 3, the correction equation for updating the air ice accumulation diagnostic index for a specified period of time or in real time is:
。
Finally, by adopting a grading weight integration method (grading the ice accumulation degree calculated by different algorithms and integrating the ice accumulation degree into corresponding modules), the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm is obtained, and the intelligent correction equation of the air ice accumulation diagnosis result is realized.
In other embodiments, the equation may be corrected according to the air ice strength index such as the seasonal parameter, the regional parameter, the altitude parameter, and the like. The foregoing is illustrative only and is not to be construed as limiting the invention.
Next, in step S104, a current user input is received, and an air ice accumulation early warning information matched with the current user input is generated using the ice accumulation intensity index correction equation of the determined air ice accumulation diagnostic algorithm.
In a specific embodiment, the specified time, place and height input by the user is received, and the air ice accumulation early warning information matched with the current user input is generated, for example, visually displayed, by utilizing the ice accumulation intensity index correction equation of each air ice accumulation diagnosis algorithm, so that the user can view the matched air ice accumulation early warning information in real time, and more effective and accurate early warning information is provided for an airplane or other aviation application.
Specifically, the air ice accumulation early warning information comprises early warning level (corresponding to no ice accumulation, slight ice accumulation, medium ice accumulation and serious ice accumulation), altitude, early warning time and the like.
Optionally, the air ice accumulation pre-warning information further comprises diagnostic information, such as diagnostic information based on numerical weather forecast products and diagnostic information based on weather history.
It should be noted that the foregoing is merely illustrative of the present invention and is not to be construed as limiting thereof.
In another example, the method for generating the air ice accumulation early-warning information includes a step S301 of updating the air ice accumulation early-warning information.
In this example, the contents of steps S101, S102, S103, and S104 in the method for generating the ice accumulation in the air early warning information are substantially the same as those of steps S101, S102, S103, and S104 in the above example, and therefore, the description of the same portions is omitted and the limitation of the present invention is not to be interpreted.
In step S301, the over-the-air ice accumulation warning information is updated.
Specifically, when the correction equation of the air ice accumulation diagnosis algorithm is updated, the update processing of the air ice accumulation early warning information is triggered, diagnosis analysis is carried out on the air ice accumulation potential of the designated time, the designated location and the designated height input by a user by adopting the correction equation updated in real time or designated time, updated air ice accumulation early warning information is given, and two-dimensional/three-dimensional visual display is carried out.
Further, the air ice accumulation early warning information comprises early warning level (corresponding to no ice accumulation, slight ice accumulation, medium ice accumulation and serious ice accumulation), altitude, early warning time and the like.
For example, based on a digital earth frame, geographic data display information is superimposed on the generated air ice accumulation early warning information, meteorological environment elements and air ice accumulation diagnosis early warning information (including ice accumulation intensity indexes) are displayed in a two-dimensional/three-dimensional visual environment, and visual and clear air ice accumulation environment background fields and air ice accumulation severity quantitative classification can be provided for users.
In yet another example, when the multi-source meteorological data is extracted and no new aviation airborne icing report trigger is included, a preset/existing correction equation is adopted to perform diagnostic analysis on the airborne icing potential of the designated time, the designated location and the designated altitude input by the user, and the corrected airborne icing early warning information is given and displayed in a two-dimensional/three-dimensional visual mode.
For example, whether visual display of meteorological environment elements and visual display of air ice accumulation early warning information are carried out is determined according to parameter changes set by a user.
In a specific embodiment, the weather data in the weather data server and the geographical information in the geographical information server are obtained, and the classification is performed according to the threshold value of [0,1,2,3] according to the value of A determined by the three-level calculation in the step S103, and the classification corresponds to no ice accumulation (A=0), slight ice accumulation (0.ltoreq.A < 1), medium ice accumulation (1.ltoreq.A < 2) and serious ice accumulation (2.ltoreq.A) respectively.
And then generating air ice accumulation early warning information according to the early warning rule or the user-defined early warning rule.
Specifically, the air early warning rules can be selected according to application scenes, and the air early warning rules specifically comprise early warning information corresponding to airplane types and ice accumulation grades and are used for issuing air ice accumulation early warning information. For example, for a low-speed small aircraft, early warning is performed under the condition that slight ice accumulation is determined, and corresponding early warning information is to stop flying or change a route to avoid an aerial ice accumulation area. For example, for a high-speed large aircraft, when the medium ice accumulation is determined, early warning is carried out, and corresponding early warning information is that the aircraft stops flying or the route is changed to avoid the air ice accumulation area.
It should be noted that the foregoing is merely illustrative of the present invention and is not to be construed as limiting thereof.
Furthermore, the drawings are only schematic illustrations of processes involved in a method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It will be readily understood that the processes shown in the figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
Compared with the prior art, the method has the advantages that based on the digital earth frame, the data standardization, the flow automation, the correction intellectualization, the result visualization and the like are realized by carrying out the connection processing on multi-source meteorological data, establishing an air ice accumulation historical case base, carrying out the comparison and verification on various air ice accumulation algorithms, carrying out the correction processing on an air ice accumulation diagnosis algorithm, carrying out the visual display on air ice accumulation early warning information and the like, so that the automation of the development and verification and correction processing on the air ice accumulation diagnosis algorithm is effectively improved, and the accuracy and the reliability of determining the air ice accumulation grade or the ice accumulation degree are improved.
In addition, when new air icing case samples exist, the samples can be automatically updated, namely, based on a large number of samples in a case library, the comparison verification of various air icing diagnosis algorithms is automatically carried out, and statistical analysis parameters such as accuracy, blank report rate, missing report rate and the like are provided, so that the method is convenient, quick and accurate, the defects that the existing manual algorithm is less in comparison verification coverage sample and low in working efficiency are effectively overcome, and the working efficiency of air icing algorithm development, debugging, optimization and verification is greatly improved.
In addition, based on the comparison and verification results (including accuracy, blank report rate, missing report rate and the like) of the air ice accumulation diagnosis algorithm and statistical analysis data, a grading weight integration method is automatically adopted to realize the correction function of the diagnosis result, the correction equation of the comprehensive weight coefficient and the air ice accumulation intensity index of each air ice accumulation diagnosis algorithm is obtained through calculation, and corrected air ice accumulation early warning information is generated, so that the accuracy of the air ice accumulation potential diagnosis and the severity degree is effectively improved.
In addition, based on the digital earth frame, geographic data display information is superimposed on the generated air ice accumulation early warning information, meteorological environment elements and air ice accumulation diagnosis early warning information are displayed in a two-dimensional/three-dimensional visual environment, and clear, visual and immersive use experience is provided for users.
Example 2
The following are system embodiments of the present invention that may be used to perform method embodiments of the present invention. For details not disclosed in the system embodiments of the present invention, please refer to the method embodiments of the present invention.
Fig. 4 is a schematic structural view of an example of an overhead ice accumulation early warning information generation system based on digital earth according to the present invention.
Referring to fig. 4, a second aspect of the present disclosure provides an airborne ice accumulation early warning information generating system 600 based on digital earth, which adopts the airborne ice accumulation early warning information generating method based on digital earth according to the first aspect of the present invention.
Referring to fig. 2 and 4, the system 600 for generating early warning information of ice accumulation in the air includes a multi-source meteorological data extraction module, an air ice accumulation history case library management module, an air ice accumulation diagnosis algorithm verification and evaluation module, an air ice accumulation diagnosis algorithm intelligent correction module, a geographic information display service module, and an air ice accumulation early warning information display module, wherein the air ice accumulation diagnosis algorithm verification and evaluation module realizes the comparison verification and the accuracy, the air report rate and the leakage report rate statistical analysis and evaluation of the air ice accumulation diagnosis algorithm based on the history samples in the air ice accumulation history case library; the intelligent correction module of the air ice accumulation diagnostic algorithm performs intelligent correction of diagnostic results based on statistical analysis data (such as parameters of accuracy, blank report rate, missing report rate and the like) of the air ice accumulation diagnostic algorithm, obtains comprehensive weight coefficients and an air ice accumulation intensity index correction equation of each air ice accumulation diagnostic algorithm, and generates updated air ice accumulation early warning information. The air ice accumulation diagnosis algorithm verification and evaluation module comprises an air ice accumulation diagnosis algorithm packaging module.
Specifically, the multi-source meteorological data guiding and extracting module realizes multi-source meteorological data guiding and extracting functions of appointed time, geographic position and altitude based on a digital earth bottom database and meteorological data resources of a meteorological office, and specifically comprises multi-source data guiding and extracting, interpolation solving and the like of aviation air icing reports, observation detection data, numerical forecasting products, analysis data and the like. The meteorological environment elements which are connected and extracted comprise ground/high altitude temperature, humidity, wind speed/wind direction, pressure intensity and the like, and the acquired aviation air icing report comprises icing occurrence time, places/areas, altitude, icing strength (no icing, mild icing, moderate icing, severe icing) and the like.
The aerial ice accumulation history case library also comprises a management module, and the management module realizes the functions of establishing and managing the aerial ice accumulation history case library based on the digital earth bottom database and the guided aviation aerial ice accumulation report, and specifically comprises adding, reducing, deleting, inquiring, searching and the like.
In the example of fig. 2, the airborne ice accumulation diagnostic algorithm packaging module validates the evaluation module independent of the airborne ice accumulation diagnostic algorithm. The air ice accumulation diagnosis algorithm packaging module is designed based on a unified service model interface specification, realizes service packaging and port service calling of various diagnosis algorithms, and supports the addition and deletion of the diagnosis algorithms.
Specifically, the geographic information display service module is used for realizing the loading display service of two-dimensional/three-dimensional geographic information such as geographic high-definition satellite images, DEM digital elevations, administrative regions, landmarks and the like on a digital earth platform.
The air ice accumulation early warning display module realizes the text, two-dimensional/three-dimensional visual display of weather environment information and air ice accumulation early warning information. The meteorological environment information comprises ground/high altitude temperature, humidity, wind speed/wind direction, pressure intensity and the like. The aerial ice accumulation diagnosis information comprises diagnosis information based on a numerical weather forecast product and diagnosis information based on weather history data; the aerial ice accumulation early warning text is used for marking early warning grades (no ice accumulation, slight ice accumulation, moderate ice accumulation, serious ice accumulation), altitude, early warning time and other contents; and the visual display is to superimpose weather environment information or the air ice accumulation diagnosis information after intelligent correction on the numerical value earth two-dimensional/three-dimensional geographic information display.
The verification and evaluation module of the air ice accumulation diagnosis algorithm realizes the comparison verification and the accuracy rate, the air report rate and the report missing rate statistical analysis and evaluation of the air ice accumulation diagnosis algorithm based on the air ice accumulation history case library sample; the correction module of the air ice accumulation diagnostic algorithm performs correction processing of diagnostic results based on statistical analysis data (such as accuracy, blank report rate, missing report rate and the like) of the air ice accumulation diagnostic algorithm, and calculates and obtains a comprehensive weight coefficient of each air ice accumulation diagnostic algorithm and a correction equation of an air ice accumulation intensity index; the geographic information display service module realizes the loading display service of three-dimensional geographic information on the digital earth platform; the aerial ice accumulation early warning display module realizes the text and visual display of the two/three-dimensional meteorological environment information and the aerial ice accumulation early warning information based on the digital earth.
The digital earth is used as a basic software platform, functions of multi-source meteorological data connection, establishment of an air icing historical case library, encapsulation verification and correction processing of an air icing diagnosis algorithm and the like are integrated uniformly, an integrated, automatic and convenient diagnosis algorithm comparison verification/correction automation system is provided, accuracy of the air icing diagnosis algorithm is effectively improved, two-dimensional/three-dimensional visual release of air icing early warning information is carried out in a digital earth environment, influences possibly caused by air icing on an aircraft can be predicted/early-warned, and meteorological assurance is provided for aviation flight safety.
According to an alternative embodiment, the plurality of air ice accumulation diagnostic algorithms includes the following algorithms: IC index method, false frost point temperature empirical method, and ice accumulation index method.
For the IC index method, the ice accumulation index of the region of interest height H is calculated using the following expression:
;
Wherein IC H is the ice accretion index of the region of interest height H; RH H is the relative humidity in units of the region of interest height H; t H is the temperature of the region of interest height H in degrees Celsius; the subscript H denotes altitude or isobaric surface altitude.
When IC is less than or equal to 0, no ice accumulation exists; when 0< IC <40%, slight ice accumulation is caused; when the IC is more than or equal to 40% and less than 70%, the ice is accumulated moderately; when IC is more than or equal to 70%, the ice is seriously accumulated. And defining an ice strength index a 1 = [0,1,2 and 3] which respectively correspond to no ice accumulation, slight ice accumulation, medium ice accumulation and serious ice accumulation.
For the fake frost point temperature empirical method, the following expression is adopted to calculate the fake frost point temperature TF of the height H of the concerned area:
;
Wherein TF H is the false frost point temperature of the region of interest height H; v is the flying speed, the unit km/h; t H is the temperature of the region of interest height H in degrees Celsius; td H is the dew point temperature in degrees Celsius for the region of interest height H.
When (when)When the ice accumulation exists, the ice accumulation does not exist. When/>When ice accumulation exists; /(I)And medium ice accumulation. The ice strength index a 2 = [0,1,2] is defined to correspond to no ice accumulation, mild ice accumulation and moderate ice accumulation respectively.
For the ice accumulation index method, the liquid water content of a certain concerned area and a height H is calculated by adopting the following expression:
;
wherein I H represents the ice accretion index of the region of interest height H; LWC H is the liquid water content of the zone of interest height H in g/kg.
When I <1, no ice accumulation exists; when I is 1 to or less than 4.5, the ice is slightly accumulated; when I is more than or equal to 4.5 and less than or equal to 8, the ice is accumulated moderately; when I is more than or equal to 8, the ice is seriously accumulated. Specifically defined ice strength indexes a 3 = [0,1,2,3] respectively correspond to no ice accumulation, slight ice accumulation, moderate ice accumulation and serious ice accumulation.
According to an alternative embodiment, further comprising: the calculating the comprehensive weight coefficient of the air ice accumulation diagnosis algorithm comprises the following steps: the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm is obtained through calculation by adopting the following expression:
;
Wherein t i represents a comprehensive weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; y i represents an accuracy weight coefficient of an ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; z i represents the air report rate weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; w i represents a missing report rate weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1,2, 3, and n; b represents a duty cycle corresponding to the accuracy weight coefficient y i; c represents a duty cycle corresponding to the null report rate weighting coefficient z i; d represents the duty cycle corresponding to the miss-report rate weight coefficient w i.
Alternatively, b is in the range of 0.3 to 0.5, c is in the range of 0.3 to 0.5, d is in the range of 0.1 to 0.3, and b+c+d=1 is ensured.
And for the selection of specific values of b, c and d, the specific values can be flexibly configured according to application scenes so as to improve the accuracy of the diagnosis of ice accumulation in the air. In general, the fake frost point temperature empirical method considers the influences of the aircraft flight speed and the dynamic temperature rise, has higher ice accumulation prediction accuracy rate for certain concerned areas (such as eastern China) in spring, can effectively predict ice accumulation conditions of different heights, and has a missing report rate obviously smaller than an IC index method. The IC index method calculates the potential of ice accumulation based on the atmospheric temperature and relative humidity of certain regions of interest, and as a result, actually reflects the possibility of ice accumulation in the environmental background of the regions of interest, and the number of air reports in the high altitude region is less than that of the empirical method of the false frost point temperature, so that the IC index method is more reliable in the case of uncertain wind field conditions and aircraft airspeed. Therefore, for aircrafts such as large aircrafts or transport planes, the airspeed is slower, the acceleration is small, the accelerating and warming effects are poor, strong ice accumulation is easily encountered, caution is needed when ice accumulation prediction or prediction is carried out, the experimental calculation of the temperature of the false frost point is selected at the moment to be more proper, the ice accumulation area can be accurately predicted, the flight safety of the large aircrafts is effectively ensured, the weight of the large aircrafts can be properly increased, the weight increasing range can be determined according to the type of the aircrafts, the concerned area, the altitude and other parameters, and the weight increasing range is 0.3-0.5. For the aircraft with fast airspeed and large acceleration, if the aircraft suffers from ice accumulation at high altitude, the surface can be heated by acceleration to melt the ice accumulation, and the slight ice accumulation with smaller influence can be ignored, so that excessive air report is not suitable to occur, therefore, the selection of the IC exponential method prediction is more suitable, the task can be completed under the condition of ensuring safety, the weight of the aircraft can be properly increased, and the weight increasing range is determined according to the type of the aircraft, the area of interest, the altitude and other parameters, for example, the weight increasing range is 0.3-0.5.
According to an alternative embodiment, further comprising: according to the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm obtained through calculation, determining an air ice accumulation intensity index correction equation:
;
Wherein A represents the ice strength index after correction; t i represents the comprehensive weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2,3, and n; And the ice accumulation intensity indexes obtained by diagnosing by the ith air ice accumulation diagnosis algorithm are shown, each ice accumulation intensity index corresponds to one ice accumulation grade, and i is a positive integer, and specifically comprises 1,2, 3. And (3) carrying out air ice accumulation intensity grading on the A value obtained after correction according to the threshold value of [0,1,2 and 3], wherein the air ice accumulation intensity grading comprises the following four ice accumulation grades: no ice accumulation (a=0), slight ice accumulation (0.ltoreq.a < 1), moderate ice accumulation (1.ltoreq.a < 2), severe ice accumulation (2.ltoreq.a) for judging the ice accumulation grade or ice accumulation degree.
According to an alternative embodiment, further comprising: when the meteorological office data of the local or related departments begin to be pushed, triggering the connection processing of the server corresponding to the multi-source meteorological data.
Specifically, the leading process is completed through the following steps:
After receiving the push data, automatically carrying out standardized processing on the push data, wherein the push data comprises an aviation air ice accumulation report, meteorological environment element data, ground detection data, high-altitude observation data and numerical forecasting products;
When the pushing data is an aviation air ice accumulation report, pushing the data to a corresponding server of an air ice accumulation historical case library according to the air ice accumulation occurrence time, occurrence place/area, occurrence altitude and ice accumulation intensity level so as to finish the increase and update of sample data in the air ice accumulation historical case library; meanwhile, triggering and combining the pushed meteorological environment element data, calculating and updating statistical analysis data of the air ice accumulation accuracy, the air report rate and the missing report rate so as to further determine comprehensive weight coefficients of all air ice accumulation diagnosis algorithms and update an air ice accumulation intensity index correction equation;
And when the push data are ground detection data, high-altitude observation data, numerical forecasting products or analysis data, extracting meteorological environment element data.
According to an optional embodiment, the method further comprises the step of updating the air ice accumulation early warning information, and specifically comprises the following steps:
When the correction equation of the air ice accumulation diagnosis algorithm is updated, the update processing of the air ice accumulation early warning information is triggered, the updated correction equation is adopted to carry out diagnosis analysis on the air ice accumulation potential of the designated time, the designated location and the designated height input by a user, the updated air ice accumulation early warning information is given, and two-dimensional/three-dimensional visual display is carried out.
According to an optional embodiment, the method further comprises the step of updating the air ice accumulation early warning information, and specifically comprises the following steps:
When the multi-source meteorological data is extracted and does not contain new aviation air icing report trigger, a preset/existing correction equation is adopted to carry out diagnosis and analysis on the air icing potential of the designated time, the designated location and the designated height input by a user, and the corrected air icing early warning information is given and is displayed in a two-dimensional/three-dimensional visual mode.
According to an alternative embodiment, geographic data display information is superimposed on the generated airborne ice accumulation early warning information based on a digital earth frame to display meteorological environment elements and airborne ice accumulation diagnostic early warning information in a two-dimensional/three-dimensional visual environment.
In embodiment 2, the method for generating the air ice accumulation early-warning information by the digital earth is substantially the same as that in fig. 1, and therefore, the description of the same parts is omitted.
Fig. 5 is a schematic diagram illustrating an application scenario example of the digital earth-based overhead ice accumulation early warning information generating system of the present invention.
As shown in fig. 5, the system specifically comprises a digital earth client, an air ice accumulation history case library server interacted with the digital earth client, an air ice accumulation early warning information visual display server and an air ice accumulation diagnosis algorithm verification/correction calculation server. The air ice accumulation history case library service area, the air ice accumulation early warning information visual display server and the air ice accumulation diagnosis algorithm verification/correction calculation server can be interacted with the meteorological data server and the geographic data server, and the meteorological data server in the air ice accumulation early warning information generation system is connected with the meteorological data server in an external meteorological office (such as a router, a firewall and the like) for transmitting data.
Example 3
Fig. 6 is a schematic structural view of an embodiment of an electronic device according to the present invention.
As shown in fig. 6, the electronic device is in the form of a general purpose computing device. The processor may be one or a plurality of processors and work cooperatively. The invention does not exclude that the distributed processing is performed, i.e. the processor may be distributed among different physical devices. The electronic device of the present invention is not limited to a single entity, but may be a sum of a plurality of entity devices.
The memory stores a computer executable program, typically machine readable code. The computer readable program may be executable by the processor to enable an electronic device to perform the method, or at least some of the steps of the method, of the present invention.
The memory includes volatile memory, such as Random Access Memory (RAM) and/or cache memory, and may be non-volatile memory, such as Read Only Memory (ROM).
Optionally, in this embodiment, the electronic device further includes an I/O interface, which is used for exchanging data between the electronic device and an external device. The I/O interface may be a bus representing one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
It should be understood that the electronic device shown in fig. 6 is only one example of the present invention, and the electronic device of the present invention may further include elements or components not shown in the above examples. For example, some electronic devices further include a display unit such as a display screen, and some electronic devices further include a man-machine interaction element such as a button, a keyboard, and the like. The electronic device may be considered as covered by the invention as long as the electronic device is capable of executing a computer readable program in a memory for carrying out the method or at least part of the steps of the method.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, as shown in fig. 7, the technical solution according to the embodiment of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several commands to cause a computing device (may be a personal computer, a server, or a network device, etc.) to perform the above-described method according to the embodiment of the present invention.
The software product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. The readable storage medium can also be any readable medium that can communicate, propagate, or transport the program for use by or in connection with the command execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Python, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The computer-readable medium carries one or more programs (e.g., computer-executable programs) which, when executed by one of the devices, cause the computer-readable medium to implement the methods of the present disclosure.
Those skilled in the art will appreciate that the modules may be distributed throughout several devices as described in the embodiments, and that corresponding variations may be implemented in one or more devices that are unique to the embodiments. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present invention may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and which includes several commands to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The exemplary embodiments of the present invention have been particularly shown and described above. It is to be understood that this invention is not limited to the precise arrangements, instrumentalities and instrumentalities described herein; on the contrary, the invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. The method for generating the air ice accumulation early warning information based on the digital earth is characterized by comprising the following steps of:
Establishing an aerial icing historical case base based on a digital earth bottom database and multi-source meteorological data extracted by leading, wherein the multi-source meteorological data comprises an aviation aerial icing report, observation and detection data, a numerical forecasting product and analysis data;
According to the sample data in the established air ice accumulation history case library, carrying out analysis and evaluation processing of various air ice accumulation diagnosis algorithms;
According to analysis and evaluation processing data of various air ice accumulation diagnostic algorithms, a hierarchical weight integration method is adopted to determine the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm and an air ice accumulation intensity index correction equation, and the method specifically comprises the following steps of calculating the comprehensive weight coefficient of each air ice accumulation diagnostic algorithm by adopting the following weight coefficients: accuracy rate weight coefficient, empty report rate weight coefficient, miss report rate weight coefficient;
and receiving current user input, and generating air ice accumulation early warning information matched with the current user input by utilizing the determined air ice accumulation intensity index correction equation.
2. The method for generating the digital earth-based overhead ice accumulation early warning information according to claim 1, further comprising:
The plurality of air ice accumulation diagnostic algorithms includes the following algorithms: IC index method, false frost point temperature experience method, ice accumulation index method;
for the IC index method, the ice accumulation index of the region of interest height H is calculated using the following expression:
;
Wherein IC H is the ice accretion index of the region of interest height H; RH H is the relative humidity in units of the region of interest height H; t H is the temperature of the region of interest height H in degrees Celsius; subscript H represents altitude or isobaric surface altitude;
For the fake frost point temperature empirical method, the following expression is adopted to calculate the fake frost point temperature TF of the height H of the concerned area:
;
Wherein TF H is the false frost point temperature of the region of interest height H; v is the flying speed, the unit km/h; t H is the temperature of the region of interest height H in degrees Celsius; td H is the dew point temperature in degrees Celsius for the region of interest height H;
for the ice accumulation index method, the liquid water content of a certain concerned area and a height H is calculated by adopting the following expression:
;
Wherein I H represents the ice accretion index of the region of interest height H; LWC H is the liquid water content of the zone of interest height H in g/kg.
3. The method for generating the early warning information of the ice accumulation in the air based on the digital earth according to claim 1, wherein the calculating the comprehensive weight coefficient of each ice accumulation in the air diagnosis algorithm comprises:
The comprehensive weight coefficient of each air ice accumulation diagnosis algorithm is obtained through calculation by adopting the following expression:
;
Wherein t i represents a comprehensive weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; y i represents an accuracy weight coefficient of an ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; z i represents the air report rate weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; w i represents a missing report rate weight coefficient of an ith air ice accumulation diagnosis algorithm, i is a positive integer, and specifically comprises 1, 2,3, and n; b represents a duty cycle corresponding to the accuracy weight coefficient y i; c represents a duty cycle corresponding to the null report rate weighting coefficient z i; d represents the duty ratio corresponding to the miss-report rate weight coefficient w i;
b is in the range of 0.3 to 0.5, c is in the range of 0.3 to 0.5, d is in the range of 0.1 to 0.3, and b+c+d=1 is ensured.
4. The method for generating the digital earth-based overhead ice accumulation early warning information according to claim 1, further comprising:
According to the comprehensive weight coefficient of each air ice accumulation diagnosis algorithm obtained through calculation, determining an air ice accumulation intensity index correction equation:
;
Wherein A represents the ice strength index after correction; t i represents the comprehensive weight coefficient of the ith air ice accumulation diagnostic algorithm, i is a positive integer, and specifically comprises 1,2,3, and n; And the ice accumulation intensity indexes obtained by diagnosing by the ith air ice accumulation diagnosis algorithm are shown, each ice accumulation intensity index corresponds to one ice accumulation grade, and i is a positive integer, and specifically comprises 1,2, 3.
5. The method for generating the digital earth-based overhead ice accumulation early warning information according to claim 1, further comprising:
When the meteorological office data of the local or related departments begin to be pushed, triggering the connection processing of the server corresponding to the multi-source meteorological data.
6. The method for generating the digital earth-based overhead ice accumulation early warning information according to claim 4, wherein the guiding process is specifically completed by the following steps:
After receiving the push data, automatically carrying out standardized processing on the push data, wherein the push data comprises an aviation air ice accumulation report, meteorological environment element data, ground detection data, high-altitude observation data and numerical forecasting products;
When the pushing data is an aviation air ice accumulation report, pushing the data to a corresponding server of an air ice accumulation historical case library according to the air ice accumulation occurrence time, occurrence place/area, occurrence altitude and ice accumulation intensity level so as to finish the increase and update of sample data in the air ice accumulation historical case library; meanwhile, triggering and combining the pushed meteorological environment element data, calculating and updating statistical analysis data of the air ice accumulation accuracy, the air report rate and the missing report rate so as to further determine comprehensive weight coefficients of all air ice accumulation diagnosis algorithms and update an air ice accumulation intensity index correction equation;
And when the push data are ground detection data, high-altitude observation data, numerical forecasting products or analysis data, extracting meteorological environment element data.
7. The method for generating the early warning information of the ice accumulation in the air based on the digital earth according to claim 1, further comprising the step of updating the early warning information of the ice accumulation in the air, and specifically comprising the steps of:
When the correction equation of the air ice accumulation diagnosis algorithm is updated, the update processing of the air ice accumulation early warning information is triggered, the updated correction equation is adopted to carry out diagnosis analysis on the air ice accumulation potential of the designated time, the designated location and the designated height input by a user, the updated air ice accumulation early warning information is given, and two-dimensional/three-dimensional visual display is carried out.
8. The method for generating the early warning information of the ice accumulation in the air based on the digital earth according to claim 1, further comprising the step of updating the early warning information of the ice accumulation in the air, and specifically comprising the steps of:
When the multi-source meteorological data is extracted and does not contain new aviation air icing report trigger, a preset/existing correction equation is adopted to carry out diagnosis and analysis on the air icing potential of the designated time, the designated location and the designated height input by a user, and the corrected air icing early warning information is given and is displayed in a two-dimensional/three-dimensional visual mode.
9. The method for generating the digital earth-based overhead ice accumulation early warning information according to claim 1, comprising:
Based on the digital earth frame, geographic data display information is overlapped on the generated air ice accumulation early warning information so as to display meteorological environment elements and air ice accumulation diagnosis early warning information in a two-dimensional/three-dimensional visual environment.
10. An aerial ice accumulation early warning information generation system based on digital earth is characterized in that the aerial ice accumulation early warning information generation method based on digital earth is adopted, and the aerial ice accumulation early warning information generation system comprises:
The multi-source meteorological data is connected with an extraction module, an air ice accumulation historical case library management module, an air ice accumulation diagnosis algorithm verification and evaluation module, an air ice accumulation diagnosis algorithm intelligent correction module, a geographic information display service module and an air ice accumulation early warning information display module,
The verification and evaluation module of the air ice accumulation diagnosis algorithm realizes the comparison verification and the accuracy rate, the empty report rate and the missing report rate statistical analysis and evaluation of the air ice accumulation diagnosis algorithm based on the historical samples in the air ice accumulation historical case library; the intelligent correction module of the air ice accumulation diagnostic algorithm performs intelligent correction of the diagnostic result based on statistical analysis data of the air ice accumulation diagnostic algorithm, calculates and obtains comprehensive weight coefficients and an air ice accumulation intensity index correction equation of each air ice accumulation diagnostic algorithm, and generates updated air ice accumulation early warning information.
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