Lightning-strike-danger-level derivation device and lightning-strike-danger-level display system

Abstract

A lightning-strike-danger-level derivation device according to the present invention derives a lightning-strike danger level for each of a plurality of regions defined in the form of a mesh on the basis of latitudes and longitudes. The lightning-strike-danger-level derivation device is provided with: an echo-intensity derivation unit that derives an altitude distribution of echo intensities for each of the plurality of regions by using observation data acquired from a meteorological radar; a temperature derivation unit that derives an altitude distribution of temperatures for each of the plurality of regions by using observation data acquired from a meteorological observation device; a feature derivation unit that derives features used to derive the lightning-strike danger level; and a lightning-strike-danger-level derivation unit that derives the lightning-strike danger level by using the features. The feature derivation unit derives a cumulative echo intensity for each of the plurality of regions, the cumulative echo intensity being a partial or entire cumulative value of echo intensities along the vertical direction. The lightning-strike-danger-level derivation unit derives an altitude distribution of lightning-strike danger levels for each of the plurality of regions by using the cumulative echo intensity and the altitude distribution of temperatures.

Description

Lightning risk deriving device and lightning risk display system

[0001] The present invention relates to a lightning risk deriving device and a lightning risk display system.

[0002] Many aircraft are struck by lightning throughout the year. While the likelihood of a lightning strike directly leading to a serious accident is extremely low, it can damage the aircraft's exterior skin, and repairing this damage is said to cost hundreds of millions of yen annually. Furthermore, inspections and emergency repairs of struck aircraft take time, affecting flight schedules regardless of the scale of the damage. Therefore, in addition to the costs associated with repairing the damage caused by lightning, there are also indirect costs.

[0003] Aircraft operations are broadly divided into a takeoff and landing phase and a cruising phase. At flight altitudes during the cruising phase, lightning strikes are unlikely to occur and evasive action is easy, so lightning strikes are rare during the cruising phase. On the other hand, at flight altitudes during the takeoff and landing phase, lightning strikes are likely to occur, so lightning avoidance is required. To address this issue, information obtained from a lightning monitoring system called LIDEN (Lightning Detection Network system) operated by the Japan Meteorological Agency is widely used. One method for assessing lightning strike risk (lightning strike risk) uses weather radar observation data and lightning strike data (see Patent Document 1).

[0004] Japanese Patent Application Laid-Open No. 2022-651

[0005] However, while this conventional technology can evaluate the planar (two-dimensional) risk of lightning strike, and although it allows for horizontal evasive action, it is difficult to utilize during the takeoff and landing phases, where evasive action itself is difficult. Therefore, there is a need for a method to derive three-dimensional lightning strike risk that allows for evasive action in both the horizontal and vertical directions.

[0006] The present invention has been made in consideration of the above-mentioned problems, and provides a lightning risk deriving device and a lightning risk display system that can derive a three-dimensional lightning risk.

[0007] The present invention provides a lightning risk derivation device that derives a lightning risk for each of a plurality of regions separated into a mesh-like structure by latitude and longitude, and includes an echo intensity derivation unit that derives an altitude distribution of echo intensity for each of the plurality of regions using observation data obtained from a weather radar, a temperature derivation unit that derives an altitude distribution of air temperature for each of the plurality of regions using observation data obtained from a meteorological observation device, a feature value derivation unit that derives feature values ​​used in deriving the lightning risk, and a lightning risk derivation unit that derives the lightning risk using the feature values, wherein the feature value derivation unit derives an integrated echo intensity, which is an integrated value of the echo intensity in some or all of the vertical direction, for each of the plurality of regions, and the lightning risk derivation unit derives the altitude distribution of lightning risk for each of the plurality of regions using the integrated echo intensity and the altitude distribution of air temperature.

[0008] According to the present invention, it is possible to provide a lightning risk deriving device and a lightning risk display system that are capable of deriving a three-dimensional lightning risk.

[0009] FIG. 1 is a functional block diagram showing the configuration of a lightning risk deriving device according to this embodiment. FIG. 2 is a flow chart showing a process for deriving an echo intensity distribution. FIG. 3 is a flow chart showing a process for deriving each feature value. FIG. 4 is a flow chart showing a process for deriving an air temperature distribution. FIG. 5(a) is a diagram showing the altitude difference between adjacent isobaric surfaces derived using an altimetry formula and the data required to derive the altitude difference, and FIG. 5(b) is a diagram showing the altimetry formula. FIG. 6 is a flow chart showing a process for deriving a lightning risk level, which is two-dimensional information, using each feature value. FIG. 7 is a flow chart showing a process for deriving an altitude distribution of lightning risk level using two-dimensional information on the lightning risk level and the air temperature distribution.

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same components are denoted by the same reference numerals, and the description thereof will be omitted as appropriate.

[0011] <Overview of the lightning risk deriving device according to this embodiment> First, an overview of the lightning risk deriving device according to this embodiment will be described using Fig. 1. Fig. 1 is a functional block diagram showing the configuration of the lightning risk deriving device according to this embodiment. As shown in Fig. 1, the lightning risk deriving device 1 according to this embodiment is composed of an echo intensity deriving unit 10, a feature amount deriving unit 20, an air temperature deriving unit 30, and a lightning risk deriving unit 40.

[0012] The echo intensity derivation unit 10 derives an elevation distribution of echo intensity (in this embodiment, in 100-m intervals, for example) for each of multiple regions divided into a mesh-like pattern by latitude and longitude (in this embodiment, both latitude and longitude are divided into 0.005-degree intervals) from observation data acquired from multiple weather radars. In this embodiment, the weather radar uses a C-band radar under the jurisdiction of the Japan Meteorological Agency, which emits a single C-band radio wave into the atmosphere and observes the intensity of the reflected wave (hereinafter, "echo intensity"). Furthermore, the echo intensity, which is the observation data acquired from each weather radar, is a distribution of echo intensity in a spherical coordinate system centered on each weather radar. This distribution is acquired as echo intensity for each space specified by the elevation angle, azimuth angle, and linear distance. Therefore, to derive the elevation distribution of echo intensity for each of the multiple regions, the echo intensity acquired from each weather radar must be processed. Details of the processing performed by the echo intensity derivation unit 10, including this processing, will be described later using FIG. 2 . In the following description, the elevation distribution of echo intensity for each of the multiple regions will simply be referred to as the "echo intensity distribution." Furthermore, each of the multiple regions is referred to as a "unit surface," and the space divided into 100-meter intervals within each unit surface is referred to as a "unit space." Furthermore, unless otherwise specified, echo intensity refers to the echo intensity corresponding to one unit space. Furthermore, while the size of the multiple regions is not particularly limited in the present invention, in this embodiment, the multiple regions are assumed to have a horizontal extent sufficient to cover the entire territory of Japan, including the waters off Japan. Furthermore, the top surface altitude of the unit space located at the highest altitude among the unit spaces provided on each unit surface is also not particularly limited. In this embodiment, the top surface altitude is set to 15,000 m, taking into account the detectable range of weather radar. This top surface altitude corresponds to the upper limit of the "predetermined altitude range" in the present invention, and the altitude (elevation) of the earth's surface is the lower limit of the "predetermined altitude range." Furthermore, in the description of this embodiment, unless otherwise specified, "altitude distribution" refers to the altitude distribution within the "predetermined altitude range." Furthermore, in the present invention, "altitude" refers to the height relative to the mean sea level of Tokyo Bay.

[0013] Echo intensity (an example of so-called precipitation intensity) is an index used to evaluate the amount of raindrops present in a space corresponding to the echo intensity, and is expressed in dBZ. Generally, there is a positive correlation between echo intensity and the risk of lightning strike. Furthermore, some or all of the multiple weather radars may be a C-band multi-parameter radar (C-band MP radar) that emits two types of C-band radio waves (horizontal polarization and vertical polarization) and observes their echo intensities, an X-band radar that emits a single X-band radio wave, an X-band multi-parameter radar (X-band MP radar) that emits X-band horizontal and vertical polarization waves, or a combination of these.

[0014] The feature deriving unit 20 derives feature values ​​for each unit surface, which are used to derive the lightning risk level, using the echo intensity distribution derived by the echo intensity deriving unit 10 and the temperature distribution derived by the temperature deriving unit 30 (details of which will be described later). In this embodiment, the feature values ​​include an integrated value of echo intensity in the vertical direction (over the entire predetermined altitude range) (hereinafter referred to as "VIR") and an integrated value of echo intensity in the vertical direction for a unit space where the temperature within the predetermined altitude range falls within a specific temperature range (hereinafter referred to as "MTR"). Because these feature values ​​are vertical integrated values, they are two-dimensional information (hereinafter simply referred to as "two-dimensional information") that does not contain altitude information. Details of the process for deriving these feature values ​​will be described later with reference to FIG. 3. Here, the specific temperature range is a temperature range in which cloud charging is considered likely to occur based on past cases of lightning strikes on aircraft. In this embodiment, the specific temperature range is a range from -9°C to -11°C. Furthermore, the lightning risk deriving unit 40 may derive the lightning risk using the VIR of these feature quantities without using the MTR, in which case there is no need to derive the MTR. Similarly, the lightning risk may derive the lightning risk using the MTR of these feature quantities without using the VIR, in which case there is no need to derive the VIR. In other words, the lightning risk deriving unit 40 may derive the lightning risk using at least either the VIR or the MTR.

[0015] The temperature derivation unit 30 derives the altitude distribution of temperature for each unit surface from the observation data acquired from multiple meteorological observation devices and the results of hourly atmospheric analysis provided by the Japan Meteorological Agency. The division interval of the altitude distribution of temperature can be the same as the division interval of echo intensity. This prevents a decrease in the accuracy of lightning strike risk estimation while reducing the amount of calculation. Specifically, in this embodiment, the division interval is 100 m, as with echo intensity. In this embodiment, the multiple meteorological observation devices are meteorological observation devices used for ground-based meteorological observation by meteorological offices, and the observation data acquired from each meteorological observation device includes temperature and air pressure. In addition, the altitude at which each meteorological observation device is installed is also referenced when deriving the altitude distribution of temperature. Furthermore, from the results of the hourly atmospheric analysis, temperatures corresponding to each of multiple isobaric surfaces (in this embodiment, 1000 hPa, 975 hPa, 950 hPa, etc., are not particularly limited as long as they cover the range of 15,000 m, the upper surface altitude of the unit space) are derived for each unit surface. Details of the process for deriving the altitude distribution of temperature will be described later using Figures 4 and 5. Note that some or all of the multiple weather observation devices may be different from the weather observation devices described above, as long as they are capable of acquiring temperature, barometric pressure, and altitude. Similarly, the hourly atmospheric analysis may be replaced with another atmospheric analysis, such as a 30-minute atmospheric analysis, as long as it is capable of deriving temperatures corresponding to each of multiple isobaric surfaces for each unit surface. In addition, in the description of this embodiment, the altitude distribution of temperature for each unit surface will simply be referred to as the "temperature distribution."

[0016] The lightning risk deriving unit 40 derives a height distribution of lightning risk for each unit surface using the feature quantities (VIR, MTR) derived by the feature quantity deriving unit 20, which are two-dimensional information, and the temperature distribution derived by the temperature deriving unit 30. In this embodiment, the lightning risk evaluation is based on three levels: "high," "medium," and "low," in descending order of lightning risk. Details of the derivation process will be described later with reference to FIGS. 6 and 7 . However, the number of levels for the lightning risk evaluation is not limited to three, and any number of levels equal to or greater than two can be used. As will be described later, this embodiment employs a method of deriving a height distribution of lightning risk by masking the lightning risk, which is two-dimensional information, with a mask temperature band. However, this is not limiting. That is, any method may be employed as long as it reevaluates the lightning risk, which is two-dimensional information, using the temperature distribution to convert the lightning risk into three-dimensional information (height distribution of lightning risk). Furthermore, as will be described later, in this embodiment, the lightning risk level is first derived using the feature values, which are two-dimensional information, and then the altitude distribution of the lightning risk level is derived using the temperature distribution, but this is not limited to this. For example, the feature values, which are two-dimensional information, and the temperature distribution may be used in combination to directly derive the altitude distribution of the lightning risk level without deriving the lightning risk level, which is two-dimensional information.

[0017] In this way, the lightning risk derivation device 1, by having the above-mentioned functional configuration, is able to derive an unprecedented altitude distribution of lightning risk (three-dimensional lightning risk), and utilizing the altitude distribution of lightning risk contributes to preventing lightning strikes on aircraft.

[0018] As shown in FIG. 1 , the present invention may also provide a lightning risk display system 100 including the lightning risk derivation device 1 described above and a lightning risk display device 50 that displays the altitude distribution of lightning risk derived by the lightning risk derivation unit 40 in three dimensions. The lightning risk display device 50 may be any device capable of displaying the altitude distribution of lightning risk in three dimensions, such as a tablet terminal or a desktop terminal. This allows aircraft pilots and air traffic controllers to visually recognize the altitude distribution of lightning risk and encourages them to determine routes (particularly takeoff and landing routes) that take the altitude distribution of lightning risk into account. Other examples of utilizing the altitude distribution of lightning risk include systems that automatically determine routes or candidate routes for aircraft and other flying objects by referring to the altitude distribution of lightning risk, and are not limited to the lightning risk display system 100 described above.

[0019] <Process for deriving echo intensity distribution> Next, details of the process for deriving the altitude distribution of echo intensity for each unit surface (echo intensity distribution) from the echo intensities acquired from each weather radar will be described with reference to Fig. 2. Fig. 2 is a flow chart showing the process for deriving the echo intensity distribution, and this process is executed by the echo intensity derivation unit 10.

[0020] 2, in the first step, step S10, the echo intensity acquired within the detection range of each C-band radar is converted into an altitude distribution of echo intensity for each unit surface. Specifically, the echo intensity distribution in the spherical coordinate system centered on the C-band radar is first converted into an echo intensity distribution in a Cartesian coordinate system centered on the Earth using the latitude and longitude at which the C-band radar is installed, and the result of this conversion is then converted into an altitude distribution of echo intensity for each unit surface (echo intensity distribution).

[0021] In step S11, a simple average of the conversion results of each C-band radar derived in step S10 is derived. Specifically, a simple average of the conversion results of each C-band radar is derived for each unit space.

[0022] In step S12, the simple average of the echo intensities for each unit space calculated in step S11 is smoothed. Specifically, the simple average of the echo intensities for 500 unit spaces, defined as 10 unit spaces in the latitude direction, 10 unit spaces in the longitude direction, and 5 unit spaces in the altitude direction, including the target unit space, is taken as the echo intensity for the target unit space. This allows for smoothing of changes in the echo intensities for the unit spaces. This also contributes to smoothing of changes in each feature quantity for the unit spaces. Note that, to achieve this effect, the range of unit spaces (including the target unit space) used to smooth the simple average of the echo intensities is not particularly limited, and may be any range that is composed of a plurality of unit spaces in each of the latitude direction, longitude direction, and altitude direction.

[0023] <Process for deriving each feature amount> Next, the process for deriving each feature amount (VIR, MTR) from the echo intensity distribution and the temperature distribution will be described in detail with reference to Fig. 3. Fig. 3 is a flow chart showing the process for deriving each feature amount, and this process is executed by the feature amount deriving unit 20.

[0024] As shown in Figure 3, in the first step, step S20, an integrated value (VIR) of echo intensity in the vertical direction (over the entire predetermined altitude range) is derived for each unit surface. In step S21, an integrated value of echo intensity in the vertical direction for unit spaces in the predetermined altitude range where the air temperature falls within a specific temperature range (first temperature range) is derived for each unit surface. Specifically, the first temperature range is -9°C to -11°C. Note that in step S21, there may be cases where the unit spaces falling within the specific temperature range are discontinuous in the vertical direction. In such cases, all of the echo intensities corresponding to the discontinuous unit spaces are integrated.

[0025] <Process for Deriving Air Temperature Distribution> Next, the process for deriving the altitude distribution of air temperature (air temperature distribution) for each unit surface from the observation data acquired from each meteorological observation device and the results of hourly atmospheric analysis will be described in detail with reference to Figures 4 and 5. Figure 4 is a flow chart showing the process for deriving the air temperature distribution, which is executed by the air temperature derivation unit 30. Figure 5(a) is a diagram showing the altitude difference between adjacent isobaric surfaces derived using the altimetry formula and the data required to derive the altitude difference, and Figure 5(b) is a diagram showing the altimetry formula.

[0026] 4, in the first step, step S30, Voronoi division is performed using the installation points of multiple meteorological observation devices. Specifically, while ignoring the elevation difference between the installation points of multiple meteorological observation devices, a perpendicular bisector is drawn to the line connecting adjacent kernel points (installation points of meteorological observation devices) to derive the nearest area (hereinafter referred to as "divided area") for each kernel point.

[0027] In step S31, the result of the Voronoi division in step S30 is used to calculate the ground data (altitude Z ０ , temperature T ０ , atmospheric pressure P ０ Specifically, for each unit surface, the ground data of the meteorological observation device corresponding to the divided area including the center of the unit surface is set as the ground data of the unit surface.

[0028] In step S32, the analysis results of the hourly atmospheric analysis (temperatures corresponding to each of the multiple isobaric surfaces) are converted into data for each unit surface. Specifically, for each unit surface, the analysis results of the unit area (area bounded by 0.0625 degrees longitude and 0.05 degrees latitude) related to the hourly atmospheric analysis that includes the center of the unit surface are set as the data for that unit surface.

[0029] In step S33, the altitude distribution of temperature for each unit surface is derived using the ground data, the conversion results of the hourly atmospheric analysis (temperatures corresponding to each of the multiple isobaric surfaces corresponding to each unit surface), and the altitude formula.

[0030] Specifically, the altitude formula shown in FIG. 5(b) is used to calculate the average temperature T (K) of two adjacent isobaric surfaces and the atmospheric pressure (P ｍ , P ｎ (both in units of hPa), and enter the thickness h of the two isopressure surfaces. ｍ，ｎ (m) is derived. Then, the altitude Z of the ground data is calculated. ０ Thickness h ｍ，ｎ By sequentially adding these, the altitude Z for the unit surface being targeted this time is ｎ and temperature T ｎ In the altitude measurement formula, R is the gas constant of dry air, and g is the gravitational acceleration (m / s ２ ) For example, the thickness of the isobaric surface h １，２ When deriving the altitude formula, the average temperature T = (temperature T １ +Temperature T ２ ) / 2, atmospheric pressure P ｍ = atmospheric pressure P １ (1000 hPa), atmospheric pressure P ｎ = atmospheric pressure P ２ (975 hPa). In particular, the thickness h from the ground to the nearest isobaric surface ０，１ When deriving the ０ , atmospheric pressure P ０ ) and use the altitude formula to get the average temperature T = (temperature T ０ +Temperature T １ ) / 2, atmospheric pressure P ｍ = atmospheric pressure P ０ , atmospheric pressure P ｎ = atmospheric pressure P １ (1000hPa). Then, enter altitude Z ０ The thickness h derived from ０，１ By adding this, the altitude Z for the unit surface being targeted this time is １ Furthermore, the altitude Z １ Thickness h １，２ By adding ２The height of each isobaric surface is derived by adding the thicknesses of the isobaric surfaces derived in sequence. As described above, the altitude distribution of air temperature in this embodiment is the temperature of a unit space divided into 100-meter intervals for each unit surface. Therefore, in this embodiment, the temperature of the unit space is derived by linear interpolation using the altitude and temperature associated with each isobaric surface derived using the altimetry formula.

[0031] In this embodiment, when deriving the altitude distribution of temperature for each unit surface using the altimetry formula, ground data corresponding to each unit surface is determined by Voronoi tessellation using the installation locations of multiple meteorological observation devices (used for ground-based meteorological observation by meteorological stations). This allows the ground data of the nearest meteorological observation device to be associated with each unit surface, improving the accuracy of the altitude distribution of temperature for each unit surface. This improvement in accuracy contributes to improving the accuracy of the altitude distribution of lightning risk.

[0032] In this embodiment, the temperature derivation unit 30 performs a process of determining ground data corresponding to each unit surface by Voronoi tessellation using the installation locations of multiple meteorological observation devices, but the meteorological observation devices corresponding to each unit surface may be determined in advance by Voronoi tessellation using the installation locations of multiple meteorological observation devices. In other words, the temperature derivation unit 30 does not have to perform a process of determining ground data corresponding to each unit surface by Voronoi tessellation using the installation locations of multiple meteorological observation devices.

[0033] Furthermore, when multiple meteorological observation devices have an abnormality (when the acquired ground data is abnormal, when the ground data itself cannot be acquired, etc.), the temperature derivation unit 30 may execute a process to determine ground data corresponding to each unit surface by Voronoi tessellation using the installation locations of multiple meteorological observation devices excluding the abnormal meteorological observation device. However, when such a meteorological observation device has an abnormality, the ground data corresponding to each unit surface may be determined as usual by Voronoi tessellation using the installation locations of multiple meteorological observation devices including the abnormal meteorological observation device, and the ground data of the unit surface corresponding to the abnormal meteorological observation device may be replaced with past ground data of that unit surface (especially the most recent normal ground data).

[0034] <Process for deriving altitude distribution of lightning risk> Next, details of the process for deriving the altitude distribution of lightning risk using the feature amounts (VIR, MTR) and the distribution of temperature will be described with reference to Figures 6 and 7. Figure 6 is a flow chart showing the process for deriving the lightning risk, which is two-dimensional information, using the feature amounts, and Figure 7 is a flow chart showing the process for deriving the altitude distribution of lightning risk using the two-dimensional information of the lightning risk and the distribution of temperature. Both of these processes are executed by lightning risk deriving unit 40.

[0035] As shown in Fig. 6, in the first step, step S40, the next unit surface is set as the target surface. Here, the target surface refers to the unit surface that will be referenced in subsequent processing. The next unit surface refers to the next unit surface in the order in which all unit surfaces that make up the above-mentioned multiple regions are set as target surfaces, and when step S40 is executed for the first time, the first unit surface in that order is set as the target surface. The same applies to Fig. 7.

[0036] In step S41, it is determined whether the target surface is within 10 km of a unit surface having an MTR of 15 dBZ or more. If the condition is met, the process proceeds to step S42. If the condition is not met, the process proceeds to step S44. In step S42, it is determined whether the target surface is within 10 km of a unit surface having a VIR of 25 dBZ or more. If the condition is met, the process proceeds to step S43. If the condition is not met, the process proceeds to step S44. In step S43, the lightning risk level (two-dimensional information) of the target surface is set to "high." Note that each "distance from the unit surface" described above is the distance from the center of the unit surface, and the distance is derived by referring to the latitude and longitude of the center of the unit surface and the latitude and longitude of the center of the corresponding target surface.

[0037] In step S44, it is determined whether the target surface is within 10 km of a unit surface having an MTR of 15 dBZ or more. If the condition is met, the process proceeds to step S45. If the condition is not met, the process proceeds to step S46. In step S45, the lightning risk of the target surface is set to "medium." In step S46, the lightning risk of the target surface is set to "low." In step S47, it is determined whether processing for all unit surfaces has been completed. If the condition is met, the process shown in FIG. 6 is terminated. If the condition is not met, the process returns to step S40. Note that the above-described processing (steps S41 to S45) includes the same determination process (steps S41 and S44), but the determination process may be executed only once. This can be achieved, for example, by setting the lightning risk of the target surface to "medium" when the conditions for the same determination process are satisfied, then executing the determination process of step S42 for the target surface with a "medium" lightning risk, and updating the lightning risk of the target surface for which the conditions for the determination process are satisfied to "high." Alternatively, as a method for performing the same determination process only once in the above-described processes (steps S41 to S45), a method may be employed in which, in the process shown in FIG. 6, step S45 is executed when the conditions for step S42 are not satisfied, and step S46 is executed when the conditions for step S41 are not satisfied.

[0038] Next, as shown in FIG. 7 , in the first step, step S50, the next unit surface is set as the target surface. In step S51, a mask temperature band is set according to the season. The lightning strike risk deriving unit 40 stores information indicating multiple seasons and the mask temperature bands associated with each season in a storage unit (not shown). The temperature ranges of the mask temperature bands for each season are different, but some overlap is permitted. Specifically, the mask temperature band for winter (October to March) is set to -10°C to 0°C, and for summer (April to September), the mask temperature band is set to -10°C to +5°C. These mask temperature bands are derived from past lightning strike cases. When the lightning strike risk deriving unit 40 receives an input specifying a date or season, it references the storage unit to obtain and set information indicating the corresponding mask temperature band.

[0039] In step S52, the lightning risk of the target surface (two-dimensional information) is set as the lightning risk of the unit space corresponding to the temperature within the mask temperature band set in step S51. In step S53, the lightning risk of the unit space corresponding to the temperature outside the mask temperature band set in step S51 is set to "low." As a result, the lightning risk of the corresponding unit space is masked by the mask temperature band (second temperature range). In step S54, it is determined whether the processing for all unit surfaces has been completed. If the condition is met, the processing shown in FIG. 7 is terminated. If the condition is not met, the processing returns to step S50. Note that in this embodiment, as described above, for each unit surface, the lightning risk of the unit space is set by referencing the temperature of the unit space and determining whether the temperature is within or outside the mask temperature band. However, the present invention is not limited to this. For example, a unit space corresponding to the lower limit of the mask temperature band (if there are multiple, the one with the lowest altitude, hereinafter referred to as the "lower limit unit space") and a unit space corresponding to the upper limit of the mask temperature band (if there are multiple, the one with the highest altitude, hereinafter referred to as the "upper limit unit space") may be derived, and the lightning risk of the target surface may be set to these unit spaces and all unit spaces sandwiched between them. This is because, taking into account the temperature lapse rate, the temperature of the unit space between the lower limit unit space and the upper limit unit space corresponds to the temperature range (mask temperature band) determined by the temperatures of the lower limit unit space and the upper limit unit space.

[0040] In this manner, in this embodiment, the lightning risk level, which is two-dimensional information, is first derived using the feature quantities (VIR, MTR), which are two-dimensional information, and then the altitude distribution of the lightning risk level (three-dimensional information of the lightning risk level) is derived using the temperature distribution. In particular, the thresholds used to derive the two-dimensional lightning risk level (thresholds related to steps S41, S42, and S44) are thresholds derived using past cases of aircraft being struck by lightning (combinations of the routes of aircraft struck by lightning and the meteorological conditions at the time). This reduces the number of samples of past aircraft strikes required to determine the thresholds for deriving the two-dimensional lightning risk level, and also improves the accuracy of the thresholds. The thresholds may be changed as needed based on future collections of lightning strike cases, or may be changed as needed to take into account meteorological parameters other than echo intensity.

[0041] As described above, when deriving the lightning risk level from the two-dimensional information, either VIR or MTR may be used, but the other may not be used. Specifically, when deriving the lightning risk level from the two-dimensional information using VIR and not MTR, steps S41, S44, and S45 may be deleted from the process shown in FIG. 6 , step S42 may be executed after step S40, and step S46 may be executed if the determination condition for step S42 is not satisfied. In this modification, step S43 may be executed if the determination condition for step S42 is satisfied. On the other hand, when deriving the lightning risk level from the two-dimensional information using MTR and not VIR, steps S42, S44, and S45 may be deleted from the process shown in FIG. 6 , and step S43 may be executed if the determination condition for step S41 is satisfied, and step S46 may be executed if the determination condition for step S41 is not satisfied. In these modified examples, the lightning risk level of the two-dimensional information is divided into two levels: "high" and "low." However, by adding another threshold to the current single-level threshold for the feature value used (either VIR or MTR), the two-dimensional lightning risk level may be divided into three levels: "high," "medium," and "low," as in the present embodiment.

[0042] As described above, in this embodiment, when deriving the altitude distribution of lightning risk, the mask temperature zone referenced is a temperature zone according to the season. This can improve the accuracy of the altitude distribution of lightning risk. Note that the mask temperature zone in this embodiment may be switched by referring to meteorological conditions such as air temperature and atmospheric pressure trends. Furthermore, the mask temperature zone is not limited to being switched between two seasons, winter and summer, but may be switched between four seasons. Furthermore, the mask temperature zone may be determined according to the latitude, climate, and topography of the area for which the altitude distribution of lightning risk is to be derived.

[0043] As mentioned above, the mask temperature range may vary depending on the parameters (e.g., season), but any temperature range is allowed to partially overlap with the specific temperature range (-9°C to -11°C). In particular, the lower limit of the mask temperature range (-10°C, which is constant regardless of season) is included in the specific temperature range. This increases the influence of the temperature range around -10°C, where clouds are likely to become charged, when deriving the altitude distribution of lightning risk using MTR in addition to VIR.

[0044] The lightning risk deriving device according to the present embodiment has been described above with reference to the drawings, but these are merely examples of the present invention, and various other configurations may be adopted. In particular, the input data to the echo intensity deriving unit 10 and the air temperature deriving unit 30 may be predicted data. Furthermore, the above-described embodiments may be combined as appropriate within the scope of the present invention.

[0045] <Modifications of the Process for Deriving the Altitude Distribution of Lightning Risk> The following modifications may be adopted for the process for deriving the altitude distribution of lightning risk described above. First, in the first modification, immediately before step S47 in the process shown in FIG. 6 , a process is added to determine whether the altitude (the altitude of the vertical center of the unit space) of a unit space on the target surface where the temperature falls within the specific temperature range (-9°C to -11°C) described above is less than 1000 m. If this condition is met, the lightning risk of the target surface is overwritten to "low." If this condition is not met, the lightning risk of the target surface previously set (set in steps S41 to S46) is maintained. This is because, in natural lightning statistics, lightning strikes are rare when the specific temperature range exists below an altitude of 1000 m. This improves the accuracy of the altitude distribution of lightning risk. The execution location and content of the processing added in the description of the first modification are not limited to those described above, as long as the lightning risk for all unit spaces (unit spaces above the unit surfaces) corresponding to each unit surface where the altitude of the unit surface is less than 1000 m and the temperature of the unit surface falls within the specific temperature range is set to "low." Furthermore, the threshold value (altitude 1000 m) in the first modification may be changed as appropriate based on future collected cases of aircraft lightning strikes. Furthermore, when adopting the first modification, the type of feature referenced in deriving the lightning risk from the two-dimensional information is not important. That is, the first modification can be adopted regardless of whether both VIR and MTR are used as features, whether only VIR is used, or whether only MTR is used. This also applies to the second modification described below.

[0046] Next, in the second modification, a process is added immediately before step S54 in the process shown in FIG. 7 to set the lightning risk for unit spaces located below the cloud base to "low." This is also due to the fact that past lightning strikes on aircraft have been rare at altitudes lower than the cloud base. Note that the cloud base refers to the lowest altitude within the vertical range where clouds exist. In this modification, it is derived using information (e.g., cloud cover, altitude, relative humidity, and temperature) obtained from numerical weather forecasting models such as the Mesoscale Model (MSM) and Localized Model (LFM) provided by the Japan Meteorological Agency. In this modification, "clouds" refer to collections of water droplets or ice crystals in the atmosphere, with no particular size restrictions, for example, referring to those approximately 0.001 mm to 0.02 mm. This also improves the accuracy of the altitude distribution of lightning risk. Note that the execution location and content of the process added in the second modification are not limited to those described above, as long as the lightning risk for all unit spaces located below the cloud base is set to "low."

[0047] This embodiment encompasses the following technical idea: (1) A lightning risk deriving device that derives a lightning risk for each of a plurality of regions separated into a mesh of latitude and longitude, comprising: an echo intensity deriving unit that derives an altitude distribution of echo intensity within a predetermined altitude range for each of the plurality of regions using observation data acquired from a weather radar; an air temperature deriving unit that derives an altitude distribution of air temperature within the predetermined altitude range for each of the plurality of regions using observation data acquired from a meteorological observation device; a feature amount deriving unit that derives feature amounts used in deriving the lightning risk; and a lightning risk deriving unit that derives the lightning risk using the feature amounts, wherein the feature amount deriving unit derives an integrated echo intensity, which is an integrated value of the echo intensity within at least a part of the predetermined altitude range for each of the plurality of regions, and the lightning risk deriving unit derives the altitude distribution of lightning risk for each of the plurality of regions using the integrated echo intensity and the altitude distribution of air temperature. (2) The lightning risk deriving device according to (1), wherein the feature amount deriving unit derives, for each of the plurality of regions, a specific temperature band integrated echo intensity which is an integrated value of the echo intensities corresponding to a first temperature range within the predetermined altitude range, using the altitude distribution of the air temperature, and the lightning risk deriving unit derives the altitude distribution of the lightning risk for each of the plurality of regions using at least the specific temperature band integrated echo intensity. (3) The lightning risk deriving device according to (1) or (2), wherein the feature amount deriving unit derives, for each of the plurality of regions, a vertical integrated echo intensity which is an integrated value of the echo intensities over the entire predetermined altitude range, and the lightning risk deriving unit derives the altitude distribution of the lightning risk for each of the plurality of regions using at least the vertical integrated echo intensity.(4) The lightning risk deriving device according to any one of (1) to (3), wherein the lightning risk deriving unit derives a lightning risk that does not include altitude information for each of the plurality of regions using the feature amounts derived by the feature amount deriving unit, and derives an altitude distribution of the lightning risk for each of the plurality of regions using the derived lightning risk and the altitude distribution of the air temperature, and the lightning risk deriving unit uses an algorithm derived using past lightning strike cases when deriving the lightning risk that does not include altitude information for each of the plurality of regions. (5) The lightning risk deriving device according to (4), wherein the lightning risk deriving unit masks the derived lightning risk for each of the plurality of regions with a second temperature range when deriving the altitude distribution of the lightning risk for each of the plurality of regions. (6) The lightning risk deriving device according to (5), wherein the second temperature range is determined according to the season. (7) The lightning risk deriving device according to any one of (1) to (6), wherein a plurality of the meteorological observation devices are present in an area consisting of the plurality of regions, the temperature deriving unit derives the temperature, pressure, and altitude corresponding to each of the plurality of regions from the meteorological observation devices, and derives a height distribution of the temperature for each of the plurality of regions using an altimetry formula that uses the derived temperature, pressure, and altitude as well as temperatures on a plurality of isobaric surfaces derived from the results of atmospheric analysis, the temperature, pressure, and altitude corresponding to an arbitrary region among the plurality of regions are determined by the meteorological observation devices corresponding to the arbitrary region, and the meteorological observation devices corresponding to the arbitrary region are determined by Voronoi tessellation using installation points of the meteorological observation devices. (8) A lightning risk display system comprising: the lightning risk deriving device according to any one of (1) to (7), and an image display device, wherein the image display device three-dimensionally displays the altitude distribution of the lightning risk for each of the plurality of regions derived by the lightning risk deriving device.

[0048] This application claims priority based on Japanese Patent Application No. 2022-106893, filed on July 1, 2022, the disclosure of which is incorporated herein in its entirety.

[0049] REFERENCE SIGNS LIST 1 Lightning strike risk deriving device 10 Echo intensity deriving unit 20 Feature amount deriving unit 30 Air temperature deriving unit 40 Lightning strike risk deriving unit 50 Lightning strike risk display device 100 Lightning strike risk display system

Claims

1. A lightning risk deriving device that derives a lightning risk for each of a plurality of regions divided into a mesh shape by latitude and longitude, an echo intensity deriving unit that derives an altitude distribution of echo intensity in a predetermined altitude range for each of the plurality of regions using observation data acquired from a weather radar; a temperature deriving unit that derives an altitude distribution of air temperature in the predetermined altitude range for each of the plurality of regions using observation data acquired from a meteorological observation device; A feature derivation unit that derives a feature used to derive a lightning risk level; a lightning risk deriving unit that derives a lightning risk using the feature amount; Equipped with the feature amount deriving unit derives, for each of the plurality of regions, an integrated echo intensity that is an integrated value of the echo intensity in at least a part of the predetermined altitude range; The lightning risk deriving unit derives a height distribution of a lightning risk for each of the plurality of regions using the integrated echo intensity and the height distribution of the air temperature. A lightning strike risk deriving device characterized by the above.

2. the feature amount deriving unit derives, for each of the plurality of regions, a specific temperature zone integrated echo intensity, which is an integrated value of the echo intensities corresponding to a first temperature range within the predetermined altitude range, using the altitude distribution of the air temperature; The lightning risk deriving unit derives an altitude distribution of a lightning risk for each of the plurality of regions by using at least the specific temperature zone integrated echo intensity.

2. The lightning risk deriving device according to claim 1.

3. the feature amount deriving unit derives a vertical integrated echo intensity, which is an integrated value of the echo intensity over the entire predetermined altitude range, for each of the plurality of regions; The lightning risk deriving unit derives an altitude distribution of a lightning risk for each of the plurality of regions using at least the vertical integrated echo intensity.

3. The lightning risk deriving device according to claim 2.

4. the lightning risk derivation unit derives a lightning risk for each of the plurality of regions that does not include altitude information by using the feature amount derived by the feature amount derivation unit, and derives an altitude distribution of the lightning risk for each of the plurality of regions by using the derived lightning risk and the altitude distribution of the air temperature; In the lightning risk deriving unit, an algorithm derived using past lightning strike cases is used to derive the lightning risk not including altitude information for each of the plurality of regions.

4. The lightning risk deriving device according to claim 1, wherein the lightning risk deriving device is a device for deriving a lightning risk.

5. When deriving the altitude distribution of the lightning risk for each of the plurality of regions, the lightning risk deriving unit masks the derived lightning risk for each of the plurality of regions with a second temperature range.

5. The lightning risk deriving device according to claim 4.

6. The second temperature range is determined according to a season.

6. The lightning risk deriving device according to claim 5.

7. a plurality of the meteorological observation devices are present within an area constituted by the plurality of regions; The air temperature derivation unit is Deriving temperature, pressure, and altitude corresponding to each of the plurality of regions from the meteorological observation device; deriving an altitude distribution of temperature for each of the plurality of regions using an altimetry formula that uses the derived temperature, pressure, and altitude as well as temperatures at a plurality of isobaric surfaces derived from the results of the atmospheric analysis; The temperature, pressure, and altitude corresponding to any one of the plurality of regions are determined by the meteorological observation device corresponding to the arbitrary region, and the meteorological observation device corresponding to the arbitrary region is determined by Voronoi division using an installation point of the meteorological observation device.

4. The lightning risk deriving device according to claim 1, wherein the lightning risk deriving device is a device for deriving a lightning risk.

8. The lightning risk deriving device according to claim 1 ; An image display device; Equipped with The image display device three-dimensionally displays the altitude distribution of the lightning risk for each of the plurality of regions derived by the lightning risk deriving device. A lightning strike danger indication system.