Program for generating display data for assisting in aircraft route determination and display system for assisting in aircraft route determination

Abstract

The present invention executes: a first lightning strike danger level derivation process for using rain cloud information that has been acquired from a weather radar to derive a current lightning strike danger level for each of a plurality of regions which are defined in a mesh-like pattern by latitudes and longitudes; a second lightning strike danger level derivation process for using a history of the rain cloud information that has been acquired from the weather radar without using a numerical forecast model to derive a lightning strike danger level for each of a plurality of regions up to a first later time; a third lightning strike danger level derivation process for using at least rain cloud information that has been derived by using the numerical forecast model to derive the lightning strike danger level for each of the plurality of regions up to a second later time which is later than the first later time; and a display data generation process for generating display data for displaying, in time series, the lightning strike danger levels that have been derived by the first lightning strike danger level derivation process, the second lightning strike danger level derivation process, and the third lightning strike danger level derivation process.

Description

Display data generation program for assisting aircraft in determining route, and display system for assisting aircraft in determining route

[0001] The present invention relates to a display data generation program for assisting in aircraft route determination, and a display system for assisting in aircraft route determination.

[0002] Weather has a significant impact on aircraft operations in terms of safety, fuel efficiency, and other costs. For example, lightning strikes occur frequently throughout the year. While lightning strikes on aircraft themselves are unlikely to directly lead to serious accidents, they can damage the aircraft's exterior skin, and repairing this damage is said to cost hundreds of millions of yen annually. In addition, inspections and emergency repairs of lightning-struck aircraft take time, affecting flight schedules regardless of the scale of the damage. As a result, in addition to the costs associated with repairing lightning damage, indirect costs also increase.

[0003] In response to this, there is a method for predicting the risk of lightning strikes up to several tens of minutes in advance using observation data from weather radar and lightning data (Patent Document 1).

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

[0005] However, even for aircraft flying within Japan, flight times are rarely shorter than a few tens of minutes, and flight times must be estimated to be around six hours. Therefore, even if such conventional technology is used, it is highly likely that it will not be possible to predict the risk of lightning strikes during landing before takeoff, and therefore it will not be possible to determine a route that takes the risk of lightning strikes into account.

[0006] On the other hand, if a numerical weather forecasting model is used to predict the risk of lightning strikes at the time of landing at the time of takeoff, the prediction accuracy will be low. Therefore, when the lightning risk is displayed on a display or other device to determine route, a large gap will occur between the current lightning risk and the lightning risk predicted using a numerical weather forecasting model, which will hinder route decisions.

[0007] The present invention has been made in consideration of the above-mentioned problems, and provides a display data generation program for supporting aircraft route determination, and a display system for supporting aircraft route determination, which reduces the gap between the current lightning risk and the predicted lightning risk using a numerical forecast model when displaying these lightning risks.

[0008] The present invention is a display data generation program for supporting aircraft route determination, which executes: a first lightning risk derivation process that uses rain cloud information acquired from a weather radar to derive a current lightning risk for each of a plurality of regions separated into a mesh pattern by latitude and longitude; a second lightning risk derivation process that derives a lightning risk for each of the plurality of regions up to a first hour ahead using a history of rain cloud information acquired from the weather radar without using a numerical forecast model; a third lightning risk derivation process that derives a lightning risk for each of the plurality of regions up to a second hour ahead, after the first hour ahead, using rain cloud information derived using at least the numerical forecast model; and a display data generation process that generates display data for chronologically displaying the lightning risks derived by the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process.

[0009] According to the present invention, it is possible to provide a display data generation program that supports aircraft route determination, and a display system that supports aircraft route determination, which reduces the gap between the current lightning risk and the predicted lightning risk using a numerical forecast model when displaying these lightning risks.

[0010] FIG. 1 is a flow chart showing an overview of a display data generation program for supporting aircraft route determination according to this embodiment. FIG. 2 is a flow chart showing a process for deriving an altitude distribution of echo intensity. FIG. 3 is a flow chart showing a process for deriving an altitude distribution of air temperature. FIG. 4(a) is a diagram showing the altitude difference between adjacent isobaric surfaces derived using an altimetry formula and data required to derive the altitude difference, and FIG. 4(b) is a diagram showing the altimetry formula. FIG. 5 is a flow chart showing a process for deriving each feature value. FIG. 6 is a flow chart showing a process for deriving a two-dimensional lightning risk. FIG. 7 is a flow chart showing a process for deriving an altitude distribution of lightning risk. FIG. 8 is a flow chart showing a process for predicting two-dimensional lightning risk for every 10 minutes up to 60 minutes into the future. FIG. 9 is a conceptual diagram illustrating a prediction method using optical flow. FIG. 10 is a flow chart showing a process for predicting two-dimensional lightning risk for every hour up to six hours into the future. FIG. 11 is a flow chart showing a process for predicting echo intensity for every 10 minutes up to 60 minutes into the future. Fig. 12(a) is a flow diagram showing a lightning risk display process, and Fig. 12(b) is a flow diagram showing a cross-section update process. Fig. 13 is a diagram showing an example of an image when the current lightning risk is displayed. Fig. 14 is a diagram showing an example of an image when a forecast of lightning risk up to 60 minutes into the future is displayed. Fig. 15 is a diagram showing an example of an image when a forecast of lightning risk up to 6 hours into the future is displayed. Fig. 16 is a timing chart showing the transition of the lightning risk displayed in the lower display area. Fig. 17 is a block diagram showing an overview of the display system according to this embodiment.

[0011] 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 where appropriate.

[0012] <Outline of a program for generating display data to support aircraft route determination> First, an outline of a program for generating display data to support aircraft route determination according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a flow chart showing an outline of a program for generating display data to support aircraft route determination according to this embodiment.

[0013] As shown in FIG. 1, the display data generation program for supporting aircraft route determination in this embodiment derives the current lightning risk level, a predicted lightning risk level for the next 60 minutes, and a predicted lightning risk level for the next 6 hours, and generates display data for displaying these lightning risk levels. These processes are executed by a display data generation device, which will be described later.

[0014] Specifically, in step S1, the first step of a program for generating display data to assist aircraft route determination, meteorological observation data is acquired from multiple weather radars and multiple meteorological observation devices. In this embodiment, the multiple weather radars are C-band radars under the jurisdiction of the Japan Meteorological Agency, which emit a single C-band radio wave toward the atmosphere and observe the intensity of the reflected wave (hereinafter referred to as "echo intensity"). However, some or all of the multiple weather radars may be C-band multiparameter radars (C-band MP radars) that emit two types of C-band radio waves (horizontally polarized and vertically polarized) and observe their echo intensities, X-band radars that emit a single X-band radio wave, X-band multiparameter radars (X-band MP radars) that emit both horizontally and vertically polarized X-band waves, or a combination thereof. Regardless of which weather radar is used, its horizontal resolution is smaller than the unit surface (described below) and its vertical resolution is smaller than the unit altitude (described below). Furthermore, in this embodiment, echo intensity is an index used to evaluate the amount of raindrops contained in the target space, and its unit is dBZ. Generally, there is a positive correlation between echo intensity and the risk of lightning strike. Echo intensity is an example of rain cloud information in the present invention. Furthermore, the multiple meteorological observation devices in this embodiment are meteorological observation devices used for ground-based meteorological observation by meteorological offices, and the meteorological observation data acquired from these meteorological observation devices includes temperature and barometric pressure. Furthermore, as will be described in detail later, the altitude at which each meteorological observation device is installed and the results of hourly atmospheric analysis are also referenced when deriving the current altitude distribution of temperature. Note that 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.

[0015] In step S2, a first lightning risk derivation process (described in detail below) is executed to derive the current lightning risk using meteorological observation data. In step S3, a second lightning risk derivation process (described in detail below) is executed to derive a lightning risk prediction for the next 60 minutes in 10-minute intervals (shorter than the time intervals in the third lightning risk derivation process described later) using meteorological observation data.

[0016] In step S4, weather forecast data is obtained from a numerical prediction model. Here, the numerical prediction model in this embodiment is the Japan Meteorological Agency's numerical prediction model (MSM) that covers the atmosphere in Japan and its surrounding seas. However, other numerical prediction models such as the Japan Meteorological Agency's local numerical prediction model (LFM) may also be used as the numerical prediction model, or a combination of these numerical prediction models may also be used. In this embodiment, the weather forecast data acquired from the numerical weather forecast model includes, for each unit area (a region divided by 0.0625 degrees longitude and 0.05 degrees latitude), hourly precipitation (kg / m^2), ground pressure, temperature (K) at the ground and at each of multiple isobaric surfaces (1000 hPa, 975 hPa, 950 hPa, 925 hPa, 900 hPa, 850 hPa, 800 hPa, 700 hPa, 600 hPa, 500 hPa, 400 hPa, and 300 hPa), and altitude at each of the multiple isobaric surfaces. When the weather forecast data is acquired, the altitude distribution of temperature is derived based on a method similar to the method using the altimetry formula and linear interpolation described below. In particular, in this embodiment, data related to the unit area including the center of the unit surface is set as data for the unit surface.

[0017] In step S5, a third lightning risk derivation process (details described later) is executed, which uses weather forecast data to derive a lightning risk prediction for each hour (larger than the time increment of the second lightning risk derivation process) from one hour ahead (60 minutes ahead) to six hours ahead.

[0018] In step S6, display data for displaying the lightning risk derived in steps S2, S3, and S5 is generated, and then the program for generating display data to support aircraft route determination is terminated. In this embodiment, the display data for displaying the lightning risk is data consisting of the current data, data in 10-minute increments from the current data (excluding the current data) up to 60 minutes from now (including 60 minutes from now), and data in 1-hour increments from 60 minutes from now (including 60 minutes from now) up to 6 hours from now (including 6 hours from now), and data in which an altitude distribution of lightning risk is associated with each of the unit surfaces described below. However, the display data generated by the program for generating display data to support aircraft route determination according to this embodiment can take any format as long as it is data that can identify the altitude distribution of lightning risk for each unit surface.

[0019] Thus, the display data generation program for assisting aircraft route determination in this embodiment includes a first lightning risk derivation process for deriving the current lightning risk, a second lightning risk derivation process for deriving the lightning risk for the next 60 minutes from the present, and a third lightning risk derivation process for deriving the lightning risk for the next 1 to 6 hours, as well as a process for generating display data for displaying the lightning risk derived by these lightning risk derivation processes. This enables aircraft route determination based on a visual understanding of the lightning risk. The lightning risk derivation processes are described in detail below.

[0020] <First Lightning Risk Derivation Process> First, the first lightning risk derivation process will be described in detail using Figures 2 to 7. The first lightning risk derivation process, which derives the current height distribution of lightning risk, includes a process for deriving the height distribution of echo intensity, a process for deriving the height distribution of temperature, a process for deriving each feature (VIR and MTR, described below), a process for deriving a two-dimensional lightning risk, and a process for deriving the height distribution of lightning risk, and these processes are executed in the indicated order. Figure 2 is a flow chart showing the process for deriving the height distribution of echo intensity. Figure 3 is a flow chart showing the process for deriving the height distribution of temperature. Figure 4(a) is a diagram showing the height difference between adjacent isobaric surfaces derived using an altimetry formula and the data required to derive the height difference, and Figure 4(b) is a diagram showing the altimetry formula. Figure 5 is a flow chart showing the process for deriving each feature. Figure 6 is a flow chart showing the process for deriving a two-dimensional lightning risk. FIG. 7 is a flow chart showing a process for deriving the altitude distribution of the lightning risk.

[0021] As shown in FIG. 2 , in step S210, the first step in the process of deriving the altitude distribution of echo intensity, the echo intensity acquired within the detection range of each C-band radar is converted into an altitude distribution of echo intensity. Specifically, the echo intensity distribution in a 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 of the C-band radar, and the converted result is then converted into an altitude distribution of echo intensity. Here, a “unit surface” refers to each surface divided into a mesh-like shape by latitude and longitude (in this embodiment, both latitude and longitude are divided into 0.005-degree increments). Furthermore, an “altitude distribution” refers to the distribution when viewed in 100-meter vertical intervals, and unless otherwise specified, refers collectively to the distribution derived for each unit surface. Furthermore, in the following description, each altitude divided into 100-meter vertical intervals will be referred to as a “unit altitude,” and each space divided by the unit surface and unit altitude will be referred to as a “unit space.” In the present invention, the size of the area in which the unit surface is defined is not particularly limited, but in this embodiment, the area in which the unit surface is defined is an area with a horizontal size sufficient to cover the entire territory of Japan, including the waters off Japan. Similarly, the upper limit altitude for defining the unit altitude is not particularly limited, but in this embodiment, the upper surface altitude is set to 15,000 m, taking into account the range detectable by weather radar. This upper surface altitude corresponds to the upper limit of the "predetermined altitude range" described below, and the altitude (elevation) of the earth's surface corresponds to the lower limit of the "predetermined altitude range."

[0022] In step S211, a simple average of the conversion results of each C-band radar derived in step S210 is derived. Specifically, for each unit space, a simple average of the conversion results of each C-band radar is derived.

[0023] In step S212, the simple average of the echo intensities for each unit space calculated in step S211 is smoothed, and then the process shown in FIG. 2 is terminated. 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 used as the echo intensity for the target unit space. This allows smoothing of horizontal and vertical changes in the echo intensity for the unit space. This also contributes to smoothing of horizontal and vertical changes for each feature quantity described below. Note that, to achieve this effect, the range of unit spaces used to smooth the simple average of the echo intensities is not particularly limited, and it is sufficient if the range includes the target unit space and is composed of a plurality of unit spaces in each of the latitude direction, longitude direction, and altitude direction.

[0024] Next, as shown in Figure 3, in step S220, which is the first step in the process of deriving the altitude distribution of temperature (current), Voronoi division is performed using the installation points of multiple meteorological observation devices. Specifically, while ignoring the elevation differences 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), and the nearest area (hereinafter referred to as "divided area") to each kernel point is derived.

[0025] In step S221, the result of the Voronoi division in step S220 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. In particular, the altitude Z ０ refers to altitude (elevation), i.e., height relative to the mean sea level of Tokyo Bay.

[0026] In step S222, 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.

[0027] In step S223, the altitude distribution of temperature 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 altimetry formula (see Figure 4(b)), and then the process shown in Figure 3 is terminated.

[0028] Specifically, as shown in Figures 4(a) and 4(b), the altitude formula uses the mean 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 Pｎ = 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 ２ The 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.

[0029] In this embodiment, when deriving the altitude distribution of temperature for each unit surface using the altitude formula, ground data corresponding to each unit surface is determined by Voronoi tessellation using the installation locations of multiple meteorological observation devices (used for surface 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 the current temperature. This improvement in accuracy also contributes to improving the accuracy of the altitude distribution of lightning risk derived using the altitude distribution of the current temperature.

[0030] Next, as shown in Fig. 5, in step S230, which is the first step in the process of deriving each feature, 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 S231, an integrated value (MTR) of echo intensity in the vertical direction for each unit space within the predetermined altitude range where the air temperature falls within a specific temperature range (in this embodiment, -9°C to -11°C) is derived for each unit surface, and then the process shown in Fig. 5 is terminated. In step S231, it is possible that the unit spaces where the air temperature falls 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.

[0031] Next, as shown in Figure 6, in step S240, which is the first step in the process of deriving a two-dimensional lightning risk, the next unit plane is set as the target plane. Here, the target plane refers to the unit plane that will be referenced in the subsequent process of deriving a two-dimensional lightning risk. The next unit plane refers to the next unit plane in the order in which all unit planes that make up the region in which the above-mentioned unit plane is defined are set as target planes. When step S240 is executed for the first time, the first unit plane in the order is set as the target plane. This also applies to the processes shown in Figures 7 and 9, which will be described later.

[0032] In step S241, 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 S242. If the condition is not met, the process proceeds to step S245. Note that being within 10 km of a unit surface having an MTR of 15 dBZ or more includes the unit surface itself having an MTR of 15 dBZ or more. In step S242, 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 S243. If the condition is not met, the process proceeds to step S244. Note that, as in step S245, being within 10 km of a unit surface having a VIR of 25 dBZ or more includes the unit surface itself having a VIR of 15 dBZ or more. In step S243, the lightning risk (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 this 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. This also applies to the processing shown in Figure 9, which will be described later.

[0033] In step S244, the lightning risk level (two-dimensional information) of the target surface is set to "medium." In step S245, the lightning risk level (two-dimensional information) of the target surface is set to "low." In step S246, it is determined whether processing for all unit surfaces has been completed. If the condition is met, the processing shown in FIG. 6 is terminated. If the condition is not met, the processing returns to step S240.

[0034] 7, in step S250, which is the first step in the process of deriving the altitude distribution of lightning strike risk, the next unit plane is set as the target plane. In step S251, a mask temperature range is set according to the season. Specifically, the mask temperature range is set to -10°C to 0°C in winter (October to March), and -10°C to +5°C in summer (April to September). These mask temperature ranges are derived from past lightning strike cases.

[0035] In step S252, the altitude distribution of air temperature for each unit surface derived in the process shown in FIG. 3 (hereinafter referred to as the "altitude distribution of current air temperature") is referenced, and the same lightning risk level as the lightning risk level (two-dimensional information) of the target surface is set for all unit spaces (within the currently set target surface, and this also applies to step S253 described later) corresponding to temperatures within the mask temperature band set in step S251. In step S253, the altitude distribution of current air temperature is referenced, and the lightning risk level for unit spaces corresponding to temperatures outside the mask temperature band set in step S251 is set to "low." This masks the lightning risk of the corresponding unit space by the mask temperature band. In step S254, it is determined whether the process for all unit surfaces has been completed. If the condition is met, the process shown in FIG. 7 is terminated. If the condition is not met, the process returns to step S250.

[0036] In this embodiment, as described above, the lightning risk level for each unit space is determined by referencing the temperature of the unit space and determining whether the temperature is within or outside the mask temperature band. However, this is not limited to this. For example, a unit space corresponding to the lower limit of the mask temperature band (if there are multiple units, 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 units, the one with the highest altitude, hereinafter referred to as the "upper limit unit space") may be determined, and the lightning risk level for the target surface may be set based on the lightning risk levels of these unit spaces and all unit spaces between them. This is because, taking into account the temperature lapse rate, the temperatures of the unit spaces between the lower limit unit space and the upper limit unit space fall within the temperature range (mask temperature band) defined by the temperatures of the lower limit unit space and the upper limit unit space.

[0037] As described above, in the first lightning risk derivation process of this embodiment, to derive the altitude distribution of the current lightning risk, two-dimensional information, i.e., feature quantities (VIR and MTR), are derived using the altitude distribution of echo intensity acquired from the weather radar and the altitude distribution of current air temperature. After the derived feature quantities are used to derive the two-dimensional lightning risk, the altitude distribution of the current lightning risk is derived using the altitude distribution of the current air temperature. In particular, the thresholds for the feature quantities used to derive the two-dimensional lightning risk (thresholds for steps S241 and S242 shown in FIG. 6 ) are thresholds derived using past aircraft lightning strike cases (combinations of the routes of aircraft that have been struck by lightning and the weather conditions at the time). This reduces the number of samples of past aircraft lightning strike cases required to determine the thresholds for deriving the altitude distribution of the lightning risk (two-dimensional information), and also improves the accuracy of the thresholds themselves. These thresholds may be changed as appropriate based on future collected cases of aircraft being struck by lightning, or may be changed as appropriate taking into account meteorological parameters other than echo intensity.

[0038] Furthermore, when deriving the current lightning risk elevation distribution, either VIR or MTR may be used, without the other being used. Specifically, when VIR is used but MTR is not used when deriving the lightning risk from the two-dimensional information, steps S241 and S244 may be deleted from the process shown in Figure 6, and step S242 may be executed after step S240, and step S243 may be executed if the determination condition for step S242 is satisfied, and step S245 may be executed if the determination condition for step S242 is not satisfied. On the other hand, when MTR is used but VIR is not used when deriving the lightning risk from the two-dimensional information, steps S242 and S244 may be deleted from the process shown in Figure 6, and step S243 may be executed if the determination condition for step S241 is satisfied, and step S245 may be executed if the determination condition for step S241 is not satisfied. In these modified examples, the lightning risk level of the two-dimensional information is divided into two levels, "high" and "low," but by setting the threshold value for the feature amount (VIR or MTR) to two levels, the two-dimensional lightning risk level may be divided into three levels, "high," "medium," and "low," as in the present embodiment. Note that when these modified examples are adopted, it is desirable to adopt similar modified examples in the second lightning risk derivation process described below.

[0039] As described above, in this embodiment, when deriving the altitude distribution of lightning risk, the mask temperature zone referenced is a temperature zone corresponding 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 all four seasons. Furthermore, the mask temperature zone may be determined according to the latitude, climate, and topography of the region for which the altitude distribution of lightning risk is to be derived, or may be changed as appropriate based on future collected cases of aircraft being struck by lightning.

[0040] 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.

[0041] <Regarding the Second Lightning Risk Derivation Process> Next, the second lightning risk derivation process for deriving the lightning risk from the present to the next 60 minutes will be described in detail using Figures 8 and 9. In addition to these figures, the process shown in Figure 7, which has already been described, will be used to explain the details of this process. Figure 8 is a flow chart showing the process of predicting a two-dimensional lightning risk every 10 minutes up to the next 60 minutes, and this process is executed first in the second lightning risk derivation process. Figure 9 is a conceptual diagram explaining a prediction method using optical flow.

[0042] As shown in FIG. 8 , in step S310, the first step of the process for predicting two-dimensional lightning risk every 10 minutes up to 60 minutes into the future (hereinafter referred to as the "short-term lightning risk prediction process"), the two-dimensional lightning risk distribution at time N-1 is visualized in grayscale. In step S311, the two-dimensional lightning risk distribution at time N at the target altitude is visualized in grayscale. Here, time N-1 and time N refer to the two times compared when deriving the optical flow, which will be described later. More specifically, when step S310 is first executed in the short-term lightning risk prediction process, time N corresponds to the present, and time N-1 corresponds to 10 minutes before the present. Incrementing N by 1 corresponds to moving each time (time N-1, time N) 10 minutes into the future. This also applies to the modified example shown in FIG. 11, which will be described later. In this embodiment, "imaging the two-dimensional lightning risk distribution in grayscale" refers to representing each unit surface as an image with a shade of gray corresponding to the level of the two-dimensional lightning risk corresponding to that unit surface. More specifically, "low" two-dimensional lightning risk corresponds to "white," "medium" two-dimensional lightning risk corresponds to "gray," and "high" two-dimensional lightning risk corresponds to "black." Furthermore, in steps S310 to S313, if steps S310 and S311 are performed for the second or subsequent time, grayscale images of the two-dimensional lightning risk distribution have already been generated for both time N-1 and time N. Therefore, the processing of steps S310 and S311 for the second or subsequent time may be omitted.

[0043] In step S312, an optical flow (motion vector field) between time N-1 and time N is derived using the grayscale image representing the two-dimensional distribution of lightning risk at time N-1 and the grayscale image representing the two-dimensional distribution of lightning risk at time N. In subsequent step S313, the grayscale image at time N and the derived optical flow are used to generate a grayscale image representing the two-dimensional distribution of lightning risk at time N+1. Specifically, as shown in FIG. 9 , the optical flow (middle left of FIG. 9 ) between time N-1 and time N is estimated, assuming that the shades of corresponding pixels (unit surfaces) before and after movement between the grayscale image at time N-1 (top left of FIG. 9 ) and the grayscale image at time N (top right of FIG. 9 ) remain unchanged. Then, a grayscale image at time N+1 is generated by moving each dark-colored (gray or black) pixel in the grayscale image at time N (middle right of FIG. 9 ) by the motion vector corresponding to that pixel. This is based on the assumption that the derived optical flow continues between time N and time N+1. Note that this method of generating a grayscale image using optical flow is also the same in the modified example shown in FIG.

[0044] In step S314, it is determined whether generation of a grayscale image representing the two-dimensional distribution of lightning risk for the next 60 minutes has been completed. If the condition is met, the process proceeds to step S316. If the condition is not met, the process returns to step S310 via step S315. Note that in step S315, time N is set to time N+1. As a result, in subsequent processing, a grayscale image representing the two-dimensional distribution of lightning risk for the next 10 minutes is generated.

[0045] In step S316, each of the generated grayscale images is converted into a two-dimensional lightning risk distribution, and the short-term lightning risk prediction process is then terminated. Specifically, using the relationship between the two-dimensional lightning risk level used in steps S310 and S311 and the shading in the grayscale images, each of the grayscale images generated up to that point for every 10 minutes up to the next 60 minutes is converted into a two-dimensional lightning risk distribution.

[0046] Next, the second lightning risk derivation process further executes the process shown in Fig. 7 using the two-dimensional lightning risk distribution for every 10 minutes up to 60 minutes into the future derived in the short-term lightning risk prediction process. This allows the altitude distribution of lightning risk for every 10 minutes up to 60 minutes into the future to be predicted. In particular, in this embodiment, the process shown in Fig. 7 executed in the second lightning risk derivation process references the altitude distribution of the current air temperature, just as in the process shown in Fig. 7 executed in the first lightning risk derivation process.

[0047] In this way, the second lightning risk derivation process in this embodiment is configured to derive a two-dimensional lightning risk distribution for every 10 minutes up to 60 minutes into the future using the two-dimensional lightning risk distribution for 10 minutes from now and the current two-dimensional lightning risk distribution (history related to the two-dimensional lightning risk distribution), and then derive a height distribution of lightning risk for every 10 minutes up to 60 minutes into the future using the height distribution of the current air temperature. Note that the process of predicting the two-dimensional lightning risk for every 10 minutes up to 60 minutes into the future, which is executed in the second lightning risk derivation process, derives optical flows from grayscale images at two adjacent times, and uses the optical flows and a grayscale image at the later of the two adjacent times to generate (estimate) a grayscale image at the time immediately following the later time, but this is not limited to this. Specifically, when deriving the optical flow, in addition to grayscale images at two adjacent times, a grayscale image at a time (e.g., time N-2) earlier than the two adjacent times (time N, time N-1) may be used. This allows the optical flow to take into account acceleration and deceleration between these times, and also improves the accuracy of the movement vectors themselves that make up the optical flow. This also applies to the derivation of the optical flow described using FIG. 11.

[0048] <Third Lightning Risk Derivation Process> Next, details of the third lightning risk derivation process for deriving the lightning risk from one hour to six hours ahead will be described with reference to Fig. 10. Note that the process shown in Fig. 7, which has already been described, will be used in addition to Fig. 10 to explain the details of this process. Fig. 10 is a flow chart showing the process for predicting a two-dimensional lightning risk for each hour up to six hours ahead, and this process is executed first in the third lightning risk derivation process.

[0049] As shown in FIG. 10 , in step S510, the first step of the process for predicting two-dimensional lightning risk for each hour up to six hours into the future (hereinafter referred to as the “short-term lightning risk prediction process”), the next time is set as the target time. Here, the target time refers to the time to be predicted. In particular, when the process of step S510 is first executed, the target time is set to one hour into the future. Thereafter, each time the process is executed, the target time is set to one hour after the previous target time. In step S511, the next unit surface is set as the target surface. In step S512, it is determined whether the hourly precipitation rate on the target surface at the target time is 5 kg / m^2 or greater. If this condition is met, the process proceeds to step S513. If this condition is not met, the process proceeds to step S514. Here, the hourly precipitation rate refers to the hourly precipitation rate for the target time acquired from the numerical forecast model in step S4. This also applies to the hourly precipitation rate described below. This hourly precipitation rate is an example of rain cloud information in the present invention. In step S513, the lightning risk (two-dimensional information) of the target surface is set to "high."

[0050] In step S514, it is determined whether the hourly precipitation rate on the target surface is 3 kg / m^2 or more. If this condition is met, the process proceeds to step S515. If this condition is not met, the process proceeds to step S516. In step S515, the lightning risk level (two-dimensional information) for the target surface is set to "medium." In step S516, the lightning risk level (two-dimensional information) for the target surface is set to "low." In step S517, it is determined whether processing for all unit surfaces has been completed. If this condition is met, the process proceeds to step S518. If this condition is not met, the process returns to step S511.

[0051] In step S518, it is determined whether the two-dimensional lightning risk prediction for the next six hours has been completed. If the condition is not met, the process returns to step S510; if the condition is met, the short-term lightning risk prediction process is terminated.

[0052] Next, the third lightning risk derivation process further executes the process shown in Fig. 7 using the two-dimensional lightning risk for each hour up to six hours into the future derived in the short-term lightning risk prediction process. Note that in this embodiment, the process shown in Fig. 7 executed in the third lightning risk derivation process uses the altitude distribution of temperature derived using weather forecast data obtained from a numerical weather forecast model, unlike the first lightning risk derivation process and the second lightning risk derivation process, which use the altitude distribution of current air temperature.

[0053] In this way, the third lightning risk derivation process in this embodiment is configured to derive a two-dimensional hourly lightning risk distribution from one hour to six hours ahead from the hourly precipitation obtained from the numerical forecast model, and then derive an hourly height distribution of lightning risk from one hour to six hours ahead using the height distribution of temperature derived using the numerical forecast model.

[0054] <Regarding a Modified Example of the Second Lightning Risk Derivation Process> Next, a modified example of the second lightning risk derivation process will be described with reference to Fig. 11. Note that in describing this modified example, the processes shown in Figs. 5 to 7, which have already been described, will be used in addition to Fig. 11. Fig. 11 is a flow chart showing the process of predicting echo intensity every 10 minutes up to 60 minutes into the future, and this process is executed first in the modified example of the second lightning risk derivation process.

[0055] As shown in Figure 11, in step S320, which is the first step of the process for predicting echo intensity every 10 minutes up to 60 minutes in advance (hereinafter referred to as "short-term echo intensity prediction process"), the next unit altitude is set as the target altitude. Here, the target altitude refers to the unit altitude that will be referenced in the subsequent short-term echo intensity prediction process. Furthermore, the next unit altitude refers to the next unit altitude in the order in which all unit altitudes viewed in the vertical direction are set as target altitudes, and when step S320 is executed for the first time, the first unit altitude in the order is set as the target altitude.

[0056] In step S321, the echo intensity distribution at time N-1 at the target altitude is imaged in grayscale. In step S322, the echo intensity distribution at time N at the target altitude is imaged in grayscale. Here, the echo intensity distribution refers to the horizontal echo intensity distribution determined for each target altitude. In this modification, imaging the echo intensity distribution in grayscale refers to imaging each unit surface with a shade corresponding to the echo intensity value corresponding to that unit surface (the greater the echo intensity value, the darker the image), and this imaging is performed for each target altitude. Furthermore, in steps S320 to S324, if the processing related to steps S321 and S322 is performed for the second or subsequent time, grayscale images of the echo intensity distribution have already been generated for both time N-1 and time N. Therefore, the processing related to steps S321 and S322 from the second or subsequent time may not be performed.

[0057] In step S323, an optical flow corresponding to each unit surface is derived using the grayscale image of the echo intensity distribution at time N-1 and the grayscale image of the echo intensity distribution at time N. In step S324, a grayscale image of the echo intensity distribution at time N+1 is generated using the grayscale image at time N and the derived optical flow. In step S325, it is determined whether generation of grayscale images of the echo intensity distribution up to 60 minutes into the future has been completed. If this condition is met, the process proceeds to step S327. If this condition is not met, the process returns to step S321 via step S326. In step S326, time N is set to time N+1, and a grayscale image of the echo intensity distribution 10 minutes into the future is generated by subsequent processing.

[0058] In step S327, each of the generated grayscale images is converted into an echo intensity distribution. Specifically, using the relationship between the echo intensity values ​​used in the processes in steps S321 and S322 and the shading of the grayscale images, each of the grayscale images generated up to that point, every 10 minutes up to the next 60 minutes, is converted into an echo intensity distribution.

[0059] In step S328, it is determined whether or not processing has been completed for all target altitudes, and if the condition is met, the short-term echo intensity prediction process is terminated, but if the condition is not met, the process returns to step S320. As a result, in the short-term echo intensity prediction process, an altitude distribution of echo intensity for every 10 minutes up to 60 minutes ahead is derived.

[0060] Next, in a modified example of the second lightning risk derivation process, the process shown in Fig. 5 is performed using the altitude distribution of echo intensity every 10 minutes up to 60 minutes into the future derived by the process shown in Fig. 11, and VIR and MTR are derived every 10 minutes up to 60 minutes into the future. Then, using these derived feature quantities, the processes shown in Fig. 6 and Fig. 7 are performed, thereby predicting the altitude distribution of lightning risk every 10 minutes up to 60 minutes into the future in this modified example of the second lightning risk derivation process as well. The process shown in Fig. 7, which is performed in this modified example, references the altitude distribution of the current air temperature.

[0061] In the process shown in Fig. 11, since the prediction target is three-dimensional information (altitude distribution of echo intensity), the optical flow is derived as described above and the echo intensity prediction using the optical flow is performed for each unit altitude, but this is not limited to this. For example, a unit vertical plane having a unit surface width along the latitudinal direction may be defined, and echo intensity prediction may be performed for each unit vertical plane using a method in which the unit altitude in the method shown in Fig. 11 is replaced with the unit vertical plane. This also makes it possible to derive the altitude distribution of echo intensity every 10 minutes up to 60 minutes in advance.

[0062] Furthermore, these prediction methods may be combined. Specifically, a three-dimensional motion vector field is generated for each unit space by combining the horizontal optical flow for each unit altitude derived by the method shown in Figure 11 with the vertical optical flow for each unit vertical plane. The altitude distribution of the echo intensity for the rear side used to derive these optical flows is then shifted by the amount of the generated three-dimensional motion vector field to derive the altitude distribution of the echo intensity 10 minutes later. This method allows for consideration of three-dimensional changes in echo intensity, thereby improving the prediction accuracy of the altitude distribution of the echo intensity in the modified example of the second lightning strike risk derivation process described above.

[0063] As described above, the display data generation program for assisting aircraft route determination in the present invention can be said to execute the following processes: a first lightning risk derivation process that uses rain cloud information (echo intensity) obtained from a weather radar to derive the current lightning risk for each of multiple regions (unit surfaces) divided into a mesh pattern by latitude and longitude; a second lightning risk derivation process that uses a history of rain cloud information obtained from the weather radar to derive the lightning risk for each of multiple regions up to the first hour ahead (60 minutes ahead) without using a numerical forecast model; a third lightning risk derivation process that uses rain cloud information (hourly precipitation) derived using at least a numerical forecast model to derive the lightning risk for each of multiple regions up to the second hour ahead (6 hours ahead) after the first hour ahead; and a display data generation process that generates display data for displaying the lightning risk derived by the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process in chronological order. According to this method, by sandwiching a lightning risk predicted using historical rain cloud information without using a numerical forecast model between the lightning risk derived from current rain cloud information and the lightning risk predicted from rain cloud information derived using a numerical forecast model, it is possible to ensure the accuracy of the lightning risk prediction while smoothing the transition of the lightning risk over time. This leads to easier route decisions while watching the transition of the lightning risk during briefings, etc.

[0064] In the above-described embodiment and modified examples, the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process all derive a height distribution of lightning risk. However, some or all of these lightning risk derivation processes may derive a two-dimensional lightning risk distribution. That is, some or all of the above-described "lightning risk for each of multiple regions" may be two-dimensional lightning risk. Regarding the rain cloud information, the first lightning risk derivation process and the second lightning risk derivation process use echo intensity as the rain cloud information, and the third lightning risk derivation process uses hourly precipitation as the rain cloud information. However, any information that can evaluate the amount of raindrops may be used as the rain cloud information. Furthermore, the above "deriving a lightning risk for each of multiple regions up to the first hour ahead using the history of rain cloud information" is not limited to the optical flow method described above, and may also include machine learning methods such as deep learning. Furthermore, with regard to the above phrase "using rain cloud information derived using at least a numerical forecast model," in the above-described embodiment and variant examples, all of the rain cloud information (hourly precipitation) used in the third lightning strike risk derivation process is obtained from a numerical forecast model, but some of the rain cloud information may also be obtained from forecast information other than a numerical forecast model.

[0065] In addition, in the present embodiment and the modified examples, as described above, in each of the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process, the altitude distribution of air temperature is used to convert the two-dimensional lightning risk into an altitude distribution of lightning risk, which allows for smooth transitions in the three-dimensional lightning risk over time.

[0066] In particular, in this embodiment and the modified example, the second lightning risk derivation process converts the two-dimensional lightning risk into an altitude distribution of lightning risk using the altitude distribution of the current air temperature, as in the first lightning risk derivation process, which allows for a smooth transition of the three-dimensional lightning risk from the present to the first time ahead.

[0067] 11, the modified second lightning risk deriving process uses the history of the echo intensity altitude distribution to derive the echo intensity altitude distribution for every 10 minutes up to 60 minutes into the future, and then uses the derived echo intensity altitude distribution to derive the lightning risk for every 10 minutes up to 60 minutes into the future. This improves the accuracy of the lightning risk prediction for every 10 minutes up to 60 minutes into the future. This is due to the need to predict upstream information used to derive the lightning risk and the fact that the horizontal resolution of the echo intensity obtained from the weather radar is smaller than the unit surface.

[0068] On the other hand, in the second lightning risk derivation process of this embodiment, as described with reference to Figure 8, the lightning risk is derived every 10 minutes up to 60 minutes into the future using the history of derived lightning risk. This reduces the processing load of the second lightning risk derivation process compared to the modified example of the second lightning risk derivation process. Note that this effect becomes more pronounced as the interval at which the lightning risk is derived by the second lightning risk derivation process becomes shorter.

[0069] <Display of Lightning Risk> In this embodiment, a display device (described later) displays the lightning risk using display data generated by the display data generation program for assisting aircraft route determination. Details of the lightning risk display according to this embodiment are described below with reference to FIGS. 12 to 15 . The processes shown in FIGS. 12(a) and 12(b) are executed by a display device (described later). FIG. 12(a) is a flow chart illustrating the lightning risk display process, and FIG. 12(b) is a flow chart illustrating the view update process. In particular, the lightning risk display process is executed when the takeoff and landing airports are determined, and the view update process is executed when the selected route is changed. FIGS. 13 to 15 are diagrams showing examples of images displayed in the display area (display) of the display device. FIG. 13 shows an example of an image displaying the current lightning risk, FIG. 14 shows an example of an image displaying a lightning risk forecast for the next 60 minutes, and FIG. 15 shows an example of an image displaying a lightning risk forecast for the next 6 hours.

[0070] As shown in FIG. 12A, the first step of the lightning strike risk display process, step S70, involves acquiring candidate routes. Here, candidate routes are routes determined when the takeoff and landing airports are determined. Although there are generally multiple candidate routes, depending on the determined takeoff and landing airports, in this embodiment, the takeoff and landing airports are determined by input operations on the display device (selecting an airport on a map). However, these airports may also be acquired from a device other than the display device, such as a display data generating device (described later). Furthermore, once the takeoff and landing airports are determined by these methods, a route connecting these airports may be drawn by input operations on the display device, or the route may be acquired from a device other than the display device.

[0071] In step S71, display data is acquired. The display data is generated by the display data generation program for assisting aircraft route determination, and is data in which the altitude distribution of lightning risk is associated with each unit surface for the present, every 10 minutes up to 60 minutes from the present, and every hour from 60 minutes to 6 hours.

[0072] In step S72, a default route from among the acquired candidate routes is set as the selected route. The default route may be any of the candidate routes, but is preferably the route with the shortest cruising distance among the candidate routes.

[0073] In step S73, the lightning risk and the candidate routes are displayed on a 3D map. As a result, the lightning risk (three-dimensional) and multiple candidate routes are displayed together on the 3D map in the lower display area. Specifically, as shown in Figures 13 to 15, the candidate routes and the lightning risk are displayed together on the 3D map displayed in the lower display area 501 of the display device. In particular, unit spaces with a lightning risk level of "medium" or "high" are displayed on the 3D map so that the level can be identified, and unit spaces with the lowest lightning risk level of "low" are not displayed. This also applies to the cross-sectional view described below.

[0074] The lightning risk level for a given time displayed on the 3D map is determined by operating the scroll bar sb displayed in the lower display area 501. Specifically, by sliding a slider sb1, which has a scale indicating the time, left or right, the lightning risk level for the time corresponding to the position of marker sb2 is displayed on the 3D map. For example, if the current time is 02:30 (2:30 AM) in Coordinated Universal Time (UTC) and marker sb2 is associated with 02:30 on the slider sb1, the current lightning risk level is displayed on the 3D map. If the slider sb1 is then slid to the right and marker sb2 is associated with 02:50 on the slider sb1, the lightning risk level for 20 minutes from now is displayed on the 3D map. If the slider sb1 is then slid to the right and marker sb2 is associated with 03:40 on the slider sb1, the lightning risk level for 1 hour and 10 minutes from now will be displayed on the 3D map. The displayed lightning risk level is updated each time the lightning risk level is updated, and the previously updated lightning risk level is maintained until the update. Specifically, the lightning risk level derived by the first lightning risk derivation process is maintained until 10 minutes have passed, at which point the display switches from the lightning risk level derived by the first lightning risk derivation process to the lightning risk level derived by the second lightning risk derivation process. Thereafter, the display of the lightning risk level derived by the second lightning risk derivation process is updated every 10 minutes until 60 minutes have passed. Furthermore, after 60 minutes, the display of the lightning risk level derived by the third lightning risk derivation process begins, and the display of the lightning risk level is updated every hour. In particular, in this embodiment, the lightning risk level 60 minutes from now derived by the second lightning risk derivation process is displayed until 70 minutes from now. Therefore, from 60 minutes to 70 minutes from now, the display period of the lightning risk level derived by the second lightning risk derivation process and the display period of the lightning risk level derived by the third lightning risk derivation process overlap. Furthermore, at any time, the candidate routes are displayed together with the lightning risk level.In particular, the selected route among the candidate routes is displayed with a thicker line than the other routes, making it possible to identify which candidate route has been selected. In this embodiment, although the slider sb1 corresponds to a period from the present to six hours in the future, only a portion of the period (in the example shown in Figure 13, the period from 02:05 to 02:55) is displayed in one scene displayed in the lower display area 501, but the portion corresponding to the entire period from the present to six hours in the future may also be displayed in the lower display area 501 at one time.

[0075] In step S74, the selected route and the lightning risk present in the cross section are displayed on a cross section obtained by cutting the 3D map vertically along the selected route, and then the lightning risk display process is terminated. As a result, the selected route and the lightning risk present in the cross section are displayed together on the cross section displayed in the upper display area. Specifically, this is as shown in the upper display area 502 in Figures 13 to 15. Note that the unit of the left vertical axis in the upper display area 502 is FL (Flight Level), and 1 FL corresponds to 100 feet.

[0076] Next, as shown in Figure 12(b), in step S80, which is the first step in the cross-section update process executed when the selected route is updated, the selected route is updated. In this embodiment, the selected route is updated by tapping on a candidate route other than the currently selected route on the screen. In step S81, the selected route and the lightning risk present in the cross-section are displayed on a cross-section obtained by cutting the 3D map vertically along the updated selected route, and then the cross-section update process is terminated. As a result, the display content in the upper display area 502 is updated to correspond to the updated selected route.

[0077] In this embodiment, the lightning risk level is displayed in the display area (display) of the display device using display data generated by the above-described program for generating display data for assisting aircraft route determination. This allows for a smooth transition of the lightning risk level over time to be displayed, thereby improving the visibility of the lightning risk level itself and facilitating route determination. To achieve this effect, the displayed lightning risk level may be two-dimensional. This also applies to the display in the lower display area 501 in the following inventions. In this embodiment, the lightning risk level is displayed in the display area of ​​the display device together with the route, but the route does not necessarily have to be displayed.

[0078] However, smoothing the transition of the lightning risk level over time can make it difficult to recognize which lightning risk level was derived from the displayed lightning risk level. This is particularly noticeable between the second lightning risk level derivation process and the third lightning risk level derivation process, which have a large difference in prediction accuracy. Below, we will explain in detail the function that solves this problem.

[0079] First, in this embodiment, as shown in Fig. 14, a unit space whose lightning risk level derived in the second lightning risk derivation process is "medium" or "high" is displayed in a cube shape with a clear outline. On the other hand, as shown in Fig. 15, a unit space whose lightning risk level derived in the third lightning risk derivation process is "medium" or "high" is displayed in a cloud-like display mode with an unclear outline. This makes it easy to recognize whether the lightning risk level being displayed is the one derived in the second lightning risk derivation process or the one derived in the third lightning risk derivation process. In order to achieve this effect, the difference between the display mode of a unit space whose lightning risk level derived in the second lightning risk derivation process is "medium" or "high" and the display mode of a unit space whose lightning risk level derived in the third lightning risk derivation process is "medium" or "high" is not limited to a difference in shape as in this embodiment, but may be any difference in color or a combination thereof, as long as it is a difference in display mode that can be visually distinguished. This also applies to the difference in display mode in the following explanation.

[0080] 13 , in this embodiment, a unit space for which the lightning risk derived in the first lightning risk derivation process is "medium" or "high" is displayed in the same display mode as a unit space for which the lightning risk derived in the second lightning risk derivation process is "medium" or "high." This allows a user to intuitively recognize that the lightning risk derived in the first lightning risk derivation process and the lightning risk derived in the second lightning risk derivation process are of the same type. Here, "lightning risk of the same type" refers to the use of common information (echo intensity and current lightning risk) used to derive the lightning risk, the use of common logic for deriving the lightning risk (the use of the above-mentioned feature values), and the like, which means that the accuracy of both lightning risk levels is similar.

[0081] 15 , in this embodiment, the display mode of the portion of the slider sb1 (an example of a first image in the present invention) corresponding to the period in which the lightning risk derived in the second lightning risk derivation process is displayed (in this example, the portion before 03:30) is different from the display mode of the portion of the slider sb1 corresponding to the period up to the period in which the lightning risk derived in the third lightning risk derivation process is displayed (in this example, the portion after 03:30). This makes it easy to recognize whether the lightning risk being displayed was derived in the third lightning risk derivation process. Note that, including the following modifications, a different display mode of the slider sb1 refers to a different display mode in the portion excluding the characters indicating the time.

[0082] Furthermore, although different from the present embodiment, the display mode of the entire slider sb1 when the lightning risk derived in the second lightning risk derivation process is displayed may be different from the display mode of the entire slider sb1 when the lightning risk derived in the third lightning risk derivation process is displayed. This makes it easier to recognize whether the lightning risk being displayed is the one derived in the second lightning risk derivation process or the one derived in the third lightning risk derivation process. To achieve this effect, the display mode of the marker sb2 when the lightning risk derived in the second lightning risk derivation process is displayed may be different from the display mode of the marker sb2 when the lightning risk derived in the third lightning risk derivation process is displayed, or the display modes of both the slider sb1 and the marker sb2 may be different between these cases. In these modified examples, when the display mode of the slider sb1 is changed, the display mode of the entire slider sb1 may be changed, or the display mode of a part of the slider sb1 may be changed. This also applies to when the display mode of the marker sb2 is changed.

[0083] Furthermore, in this modification, it is preferable that the display mode of the slider sb1 when the lightning risk derived in the first lightning risk derivation process is displayed be the same as the display mode of the slider sb1 when the lightning risk derived in the second lightning risk derivation process is displayed. The same applies to the marker sb2. This allows the user to intuitively recognize that the lightning risk derived in the first lightning risk derivation process and the lightning risk derived in the second lightning risk derivation process are the same type of lightning risk.

[0084] 13 to 15, in the present embodiment, the lightning risk levels derived in the first, second, and third lightning risk derivation processes are all displayed in the same manner in the cross section taken along the vertical direction of the selected route displayed in the upper display area 502. This allows the lightning risk level ("high" or "medium") to be easily recognized even if the lightning risk levels displayed in the lower display area 501 are changed in different display modes.

[0085] <Display of lightning risk level 60 minutes from now> Next, the display of the lightning risk level 60 minutes from now in the lower display area 501 will be described in detail with reference to Fig. 16. Fig. 16 is a timing chart showing the transition of the lightning risk level displayed in the lower display area 501.

[0086] As shown in FIG. 16 , when the lightning risk level 60 minutes after the slider sb1 is operated is displayed, the lightning risk level derived by the second lightning risk derivation process and the lightning risk level derived by the third lightning risk derivation process are displayed superimposed on each other. This allows the user to intuitively recognize that the lightning risk levels have been switched to different types. Here, "the lightning risk levels are not the same" refers to the fact that, as opposed to the above-described lightning risk levels being the same, the information used to derive the lightning risk levels is different, or the logic for deriving the lightning risk levels is the same, which means that there is a difference in the accuracy of the two lightning risk levels. To achieve this effect, the period during which the lightning risk levels derived by the second lightning risk derivation process and the lightning risk levels derived by the third lightning risk derivation process are superimposed is not important. However, it is preferable that this period be the interval for deriving the lightning risk level in the second lightning risk derivation process (10 minutes in this embodiment). Furthermore, as shown in Figure 16, during this period, it is preferable to gradually increase the transparency of the lightning risk derived by the second lightning risk derivation process and fade it out as the display time during that period progresses.

[0087] When the lightning risk level 10 minutes after the slider sb1 is operated is displayed, the lightning risk level derived by the first lightning risk level derivation process that had been displayed up until then is hidden, and only the lightning risk level derived by the second lightning risk level derivation process is displayed. Although not shown in the figure, the lightning risk level is also displayed in the upper display area 502 in the same manner as in the lower display area 501.

[0088] Furthermore, although not shown, when the tap button sb3 on the scroll bar sb is operated, the displayed time progresses toward the future at a constant speed from the displayed time at the time of the tap button sb3 operation without operating the slider sb1, and a lightning risk simulation is executed in which the displayed lightning risk changes in accordance with the progress of the displayed time. This allows the user to visually grasp the speed at which the lightning risk moves. It is also possible to move an image resembling an aircraft on the selected route in accordance with the progress of the lightning risk simulation (progression of the displayed time). This allows the user to visually evaluate the lightning risk on the selected route.

[0089] <Overview of Display System for Assisting in Determining Aircraft Routes> Next, an overview of a display system for assisting in determining aircraft routes according to this embodiment will be described with reference to Fig. 17. Fig. 17 is a block diagram showing an overview of the display system according to this embodiment.

[0090] As shown in Figure 17, display system 100, which is a display system that assists in aircraft route determination, is made up of a generation program execution device 1 that executes the above-mentioned program for generating display data that assists in aircraft route determination, and a display device 50 that has a display and executes the processing related to the display of lightning risk described using Figures 12 to 15. Furthermore, generation program execution device 1 includes a first lightning risk derivation unit 10 that executes the above-mentioned first lightning risk derivation processing, a second lightning risk derivation unit 20 that executes the second lightning risk derivation processing, a third lightning risk derivation unit 30 that executes the third lightning risk derivation processing, and a display data generation unit 40 that executes the display data generation processing.

[0091] In the display system 100 of this embodiment, the generation program execution device 1 and the display device 50 are configured as separate devices, but this is not limiting. For example, the display device 50 may include a generation program execution unit including all of the functional units of the generation program execution device 1, thereby configuring the display system 100 as a single device. The number of devices that configure the display system 100 and the allocation of the functional units of the display system 100 to the devices do not matter.

[0092] The above description is an example of the present invention, and various other configurations may be adopted. Furthermore, the above-described configurations may be combined as appropriate within the scope of the gist of the present invention.

[0093] This embodiment encompasses the following technical ideas: (1) A display data generation program for supporting aircraft route determination, which executes: a first lightning risk derivation process that uses rain cloud information acquired from a weather radar to derive a current lightning risk for each of a plurality of regions separated into a mesh of latitude and longitude; a second lightning risk derivation process that uses a history of rain cloud information acquired from the weather radar to derive a lightning risk for each of the plurality of regions up to a first hour ahead without using a numerical forecast model; a third lightning risk derivation process that uses rain cloud information derived using at least the numerical forecast model to derive a lightning risk for each of the plurality of regions up to a second hour ahead, which is after the first hour ahead; and a display data generation process that generates display data for chronologically displaying the lightning risks derived by the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process. (2) The program for generating display data to assist in aircraft route determination described in (1) above, wherein the first lightning risk derivation process derives a current altitude distribution of temperature for each of the multiple regions using observation data acquired from a meteorological observation device, and derives a current altitude distribution of lightning risk for each of the multiple regions using the derived current altitude distribution of temperature in addition to rain cloud information acquired from the weather radar; the second lightning risk derivation process derives a altitude distribution of lightning risk for each of the multiple regions up to the first hour ahead using the altitude distribution of temperature for each of the multiple regions in addition to historical rain cloud information acquired from the weather radar; and the third lightning risk derivation process derives a altitude distribution of lightning risk for each of the multiple regions up to the second hour ahead using the altitude distribution of temperature for each of the multiple regions derived using at least the numerical forecast model in addition to rain cloud information derived using the numerical forecast model. (3) The second lightning risk derivation process derives the altitude distribution of the lightning risk for each of the multiple regions up to the first hour ahead using the altitude distribution of the current temperature for each of the multiple regions in addition to the history of rain cloud information obtained from the weather radar. This is a display data generation program for supporting aircraft route determination described in (2) above.(4) The second lightning risk derivation process uses a history of rain cloud information acquired from the weather radar to derive rain cloud information for each of the multiple regions up to the first hour ahead, and uses the derived rain cloud information for each of the multiple regions up to the first hour ahead to derive a lightning risk for each of the multiple regions up to the first hour ahead, a display data generation program for supporting aircraft route determination described in any one of (1) to (3) above. (5) A display system for supporting aircraft route determination, comprising: a generation program execution unit that executes a generation program for generating display data for supporting aircraft route determination according to any one of (1) to (4) above; and a display unit, wherein the generation program execution unit includes: a first lightning risk derivation unit that executes the first lightning risk derivation process, a second lightning risk derivation unit that executes the second lightning risk derivation process, a third lightning risk derivation unit that executes the third lightning risk derivation process, and a display data generation unit that executes the display data generation process, wherein the display unit displays the lightning risk using the display data generated by the display data generation unit. (6) A display system for supporting aircraft route determination according to (5) above, wherein the display unit displays the lightning risk for each of the multiple regions up to the first time ahead derived by the second lightning risk derivation unit and the lightning risk for each of the multiple regions up to the second time ahead derived by the third lightning risk derivation unit in different display modes. (7) A display system for assisting aircraft route determination described in (6) above, wherein the display unit displays the current lightning risk for each of the multiple areas derived by the first lightning risk derivation unit and the lightning risk for each of the multiple areas up to the first time ahead derived by the second lightning risk derivation unit in the same display format.(8) A display system for assisting aircraft route determination described in any one of (5) to (7) above, wherein the display unit displays an auxiliary image consisting of a first image corresponding to a period starting from the present and ending the second time ahead, and a second image that makes it possible to identify which timing within the period the displayed lightning risk level corresponds to, and the first image has different display forms for a portion corresponding to the period from the present to the first time ahead and a portion corresponding to the period from the first time ahead to the second time ahead. (9) The display system for supporting aircraft route determination according to any one of (5) to (7), wherein the display unit displays an auxiliary image composed of a first image corresponding to a period starting from the present and ending the second time ahead, and a second image that makes it possible to identify which timing within the period the lightning strike risk being displayed corresponds to, and wherein at least one of the first image and the second image has a different display mode when the lightning strike risk derived by the second lightning strike risk derivation unit is displayed and when the lightning strike risk derived by the third lightning strike risk derivation unit is displayed. (10) The display system for supporting aircraft route determination according to (9), wherein the display mode of the first image and the second image is the same when the lightning strike risk derived by the first lightning strike risk derivation unit is displayed and when the lightning strike risk derived by the second lightning strike risk derivation unit is displayed. (11) A display system for assisting aircraft route determination described in any one of (5) to (7) above, wherein the display unit displays, in the first time ahead, the lightning risk for each of the multiple regions derived by the second lightning risk derivation process and the lightning risk for each of the multiple regions derived by the third lightning risk derivation process in a superimposed manner.(12) A display data generation device for supporting aircraft route determination, comprising: a first lightning risk derivation processing unit that derives a current lightning risk for each of a plurality of regions separated into a mesh by latitude and longitude using rain cloud information obtained from a weather radar; a second lightning risk derivation processing unit that derives a lightning risk for each of the plurality of regions up to a first hour ahead using a history of rain cloud information obtained from the weather radar without using a numerical forecast model; a third lightning risk derivation processing unit that derives a lightning risk for each of the plurality of regions up to a second hour ahead after the first hour ahead using rain cloud information derived using at least the numerical forecast model; and a display data generation processing unit that generates display data for chronologically displaying the lightning risks derived by the first lightning risk derivation processing unit, the second lightning risk derivation processing unit, and the third lightning risk derivation processing unit. (13) The display data generation device for supporting aircraft route determination described in (12) above, wherein the first lightning risk derivation processing unit derives a current altitude distribution of temperature for each of the plurality of regions using observation data acquired from a meteorological observation device, and derives a current altitude distribution of lightning risk for each of the plurality of regions using the derived current altitude distribution of temperature in addition to rain cloud information acquired from the weather radar; the second lightning risk derivation processing unit derives a altitude distribution of lightning risk for each of the plurality of regions up to the first hour ahead using the altitude distribution of temperature for each of the plurality of regions in addition to historical rain cloud information acquired from the weather radar; and the third lightning risk derivation processing unit derives a altitude distribution of lightning risk for each of the plurality of regions up to the second hour ahead using at least the altitude distribution of temperature for each of the plurality of regions derived using the numerical forecast model in addition to rain cloud information derived using the numerical forecast model. (14) The display data generation device for supporting aircraft route determination described in (13) above, wherein the second lightning risk derivation processing unit derives the altitude distribution of lightning risk for each of the multiple regions up to the first hour ahead using the altitude distribution of the current temperature for each of the multiple regions in addition to the history of rain cloud information acquired from the weather radar.(15) The display data generation device for supporting aircraft route determination described in any one of (12) to (14) above, wherein the second lightning risk derivation processing unit derives rain cloud information for each of the multiple regions up to the first hour ahead using a history of rain cloud information acquired from the weather radar, and derives a lightning risk for each of the multiple regions up to the first hour ahead using the derived rain cloud information for each of the multiple regions up to the first hour ahead.

[0094] This application claims priority based on Japanese Patent Application No. 2023-127062, filed on August 3, 2023, the disclosure of which is incorporated herein in its entirety.

[0095] REFERENCE SIGNS LIST 1 Generation program execution device 10 First lightning risk deriving unit 20 Second lightning risk deriving unit 30 Third lightning risk deriving unit 40 Display data generating unit 50 Display device 100 Display system sb Scroll bar sb1 Slider sb2 Marker sb3 Tap button 501 Lower display area 502 Upper display area

Claims

1. A display data generation program for supporting aircraft route decisions, which executes the following: a first lightning risk derivation process that uses rain cloud information obtained from a weather radar to derive a current lightning risk for each of multiple areas separated into a mesh pattern by latitude and longitude; a second lightning risk derivation process that uses a history of rain cloud information obtained from the weather radar to derive a lightning risk for each of the multiple areas up to a first hour ahead without using a numerical forecast model; a third lightning risk derivation process that derives a lightning risk for each of the multiple areas up to a second hour ahead after the first hour ahead using rain cloud information derived using at least the numerical forecast model; and a display data generation process that generates display data for displaying the lightning risk derived by the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process in chronological order.

2. A display data generation program for supporting aircraft route decisions as described in claim 1, wherein the first lightning risk derivation process derives a current temperature altitude distribution for each of the multiple regions using observation data obtained from a meteorological observation device, and derives a current altitude distribution of lightning risk for each of the multiple regions using the derived current temperature altitude distribution in addition to rain cloud information obtained from the weather radar; the second lightning risk derivation process derives a height distribution of lightning risk for each of the multiple regions up to the first hour ahead using the height distribution of temperature for each of the multiple regions in addition to historical rain cloud information obtained from the weather radar; and the third lightning risk derivation process derives a height distribution of lightning risk for each of the multiple regions up to the second hour ahead using the height distribution of temperature for each of the multiple regions derived using the numerical forecast model in addition to rain cloud information derived using at least the numerical forecast model.

3. A display data generation program for supporting aircraft route decisions as described in claim 2, wherein the second lightning risk derivation process derives the altitude distribution of lightning risk for each of the multiple regions up to the first hour ahead using the altitude distribution of the current temperature for each of the multiple regions in addition to the history of rain cloud information obtained from the weather radar.

4. A display data generation program for supporting aircraft route decisions as described in any one of claims 1 to 3, wherein the second lightning risk derivation process derives rain cloud information for each of the multiple regions up to the first hour ahead using a history of rain cloud information obtained from the weather radar, and derives a lightning risk for each of the multiple regions up to the first hour ahead using the derived rain cloud information for each of the multiple regions up to the first hour ahead.

5. A display system for supporting aircraft route determination, comprising: a generation program execution unit that executes a generation program for generating display data to support aircraft route determination as described in any one of claims 1 to 4; and a display unit, wherein the generation program execution unit includes: a first lightning risk derivation unit that executes the first lightning risk derivation process; a second lightning risk derivation unit that executes the second lightning risk derivation process; a third lightning risk derivation unit that executes the third lightning risk derivation process; and a display data generation unit that executes the display data generation process, and the display unit displays the lightning risk using the display data generated by the display data generation unit.

6. A display system for supporting aircraft route decisions as described in claim 5, wherein the display unit displays the lightning risk for each of the multiple regions up to the first time ahead derived by the second lightning risk derivation unit and the lightning risk for each of the multiple regions up to the second time ahead derived by the third lightning risk derivation unit in different display formats.

7. A display system for supporting aircraft route decisions as described in claim 6, wherein the display unit displays, in the same display format, the current lightning risk for each of the multiple regions derived by the first lightning risk derivation unit and the lightning risk for each of the multiple regions up to the first time ahead derived by the second lightning risk derivation unit.

8. A display system for assisting in aircraft route determination as described in any one of claims 5 to 7, wherein the display unit displays an auxiliary image composed of a first image corresponding to a period starting from the present and ending at the second time ahead, and a second image making it possible to identify at which point in the period the lightning risk being displayed corresponds, and the first image has different display forms for a portion corresponding to the period from the present to the first time ahead and a portion corresponding to the period from the first time ahead to the second time ahead.

9. A display system for assisting in aircraft route determination as described in any one of claims 5 to 7, wherein the display unit displays an auxiliary image composed of a first image corresponding to a period starting from the present and ending the second time ahead, and a second image that makes it possible to identify which timing within the period the lightning risk being displayed corresponds to, and at least one of the first image and the second image has a different display mode when the lightning risk derived by the second lightning risk derivation unit is displayed and when the lightning risk derived by the third lightning risk derivation unit is displayed.

10. A display system for assisting aircraft route decisions as described in claim 9, wherein the display manner of the first image and the second image is the same when the lightning risk derived by the first lightning risk derivation unit is displayed and when the lightning risk derived by the second lightning risk derivation unit is displayed.

11. A display system for supporting aircraft route determination as described in any one of claims 5 to 7, wherein the display unit displays, in the first time ahead, a superimposed lightning risk level for each of the multiple regions derived by the second lightning risk derivation process and a lightning risk level for each of the multiple regions derived by the third lightning risk derivation process.

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