Generation program for display data assisting determination of flight route of aircraft, and display system for assisting determination of flight route of aircraft

Abstract

To provide a generation program for display data assisting determination of a flight route of an aircraft that narrows intervals between lightning risks upon displaying a prediction result of the lightning risk by use of a current lightning risk and a numerical forecast model, and to provide a display system for assisting determination of the flight route of the aircraft.SOLUTION: A display data generation program is configured to execute: first lightning risk degree derivation processing of deriving a current lightning risk degree for each of a plurality of areas sectioned in a mesh shape at a longitude and latitude, using rain / cloud information acquired from a weather radar; second lightning risk degree derivation processing of deriving a lightning risk degree for each of the plurality of areas up to a first time ahead using a history of the rain / cloud information acquired from the weather radar, not using a numerical forecast model; third lightning risk degree derivation processing of deriving a lightning risk degree for each of the plurality of areas up to a second time ahead after the first time ahead, using the rain / cloud information derived by using at least the numerical forecast model; and display data generation processing of generating display data for displaying a lightning risk degree derived by the first lightning risk degree derivation processing, the second lightning risk degree derivation processing and the third lightning risk degree derivation processing in time series.

Description

[Technical field]

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

[0002] Weather has a large impact on aircraft operations in terms of safety, fuel consumption, and other costs. For example, lightning strikes occur frequently throughout the year. Although the likelihood of an aircraft being struck by lightning itself directly leading to a serious accident is extremely low, it does damage the exterior panels of the aircraft, and repairs to the damage are said to cost hundreds of millions of yen per year. In addition, inspections and emergency repairs of aircraft struck by lightning take time, affecting flight schedules regardless of the scale of the damage, resulting in increased indirect costs in addition to the costs of repairing the damage caused by lightning.

[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). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-651 Summary of the Invention [Problem to be solved by the invention]

[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 at 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 will not be able to determine routes that take the risk of lightning strikes into account.

[0006] On the other hand, when a numerical weather forecast model is used to predict the risk of lightning strike at the time of landing at the time of takeoff, the prediction accuracy is low. Therefore, when the lightning risk is displayed on a display etc. for route decision making, there is a large gap between the current lightning risk and the lightning risk predicted by the numerical weather forecast model, which hinders route decision making.

[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, which reduces the gap between the current lightning risk and the predicted results of lightning risk using a numerical forecast model when displaying these lightning risks, and a display system for supporting aircraft route determination. [Means for solving the problem]

[0008] The present invention is a display data generation program for supporting aircraft route determination, 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 regions divided into a mesh-like pattern by latitude and longitude; a second lightning risk derivation process that derives a lightning risk for each of the multiple 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 process that derives a lightning risk for each of the multiple regions up to a second hour ahead, after the first hour, 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. Effect of the Invention

[0009] According to the present invention, it is possible to provide a display data generation program for supporting aircraft route determination, which reduces the gap between the current lightning risk and the predicted lightning risk using a numerical forecast model, and a display system for supporting aircraft route determination. [Brief description of the drawings]

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

[0011] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In all the drawings, the same components are denoted by the same reference numerals, and the description thereof will be omitted as appropriate.

[0012] <Outline of the program that generates display data to assist aircraft in deciding routes> First, an overview of a display data generation program for supporting aircraft route determination according to this embodiment will be described with reference to FIG. FIG. 1 is a flow chart showing an overview of a display data generation program for supporting aircraft route determination according to this embodiment.

[0013] As shown in Figure 1, the display data generation program for supporting aircraft route determination in this embodiment derives the current lightning risk level, a forecast of the lightning risk level for the next 60 minutes, and a forecast of the 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, which is the first step of a program for generating display data for assisting aircraft route determination, meteorological observation data is acquired from a plurality of weather radars and a plurality of meteorological observation devices. Here, the multiple weather radars in this embodiment are C-band radars under the jurisdiction of the Japan Meteorological Agency that irradiate a single C-band radio wave toward the atmosphere and observe the intensity of the reflected wave (hereinafter referred to as "echo intensity"). However, as some or all of the multiple weather radars, a C-band multi-parameter radar (C-band MP radar) that irradiates two types of C-band radio waves (horizontal polarization and vertical polarization) and observes the echo intensity of these, an X-band radar that irradiates a single X-band radio wave, an X-band multi-parameter radar (X-band MP radar) that irradiates X-band horizontal and vertical polarization, or a combination of these may be used. In addition, regardless of which weather radar is used, its horizontal resolution is smaller than a unit surface described later, and its vertical resolution is smaller than a unit altitude described later. In addition, the echo intensity in this embodiment is an index for evaluating the amount of raindrops contained in the target space, and its unit is dBZ. In general, there is a positive correlation between the echo intensity and the risk of lightning strike. The echo intensity is an example of the raincloud information in the present invention. Furthermore, the multiple meteorological observation devices in this embodiment are meteorological observation devices for ground-based meteorological observation by meteorological offices, and the meteorological observation data acquired from these meteorological observation devices includes temperature and air pressure. Furthermore, to derive the current altitude distribution of temperature, the altitude at which each meteorological observation device is installed and the analysis results of the hourly atmospheric analysis are also referenced, as will be described in detail later. Note that the hourly atmospheric analysis may be replaced with another atmospheric analysis, such as a 30-minute atmospheric analysis, as long as the hourly atmospheric analysis can derive the temperature corresponding to each of the 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 a current lightning risk using meteorological observation data. In step S3, a second lightning risk derivation process (described in detail below) is executed, which uses meteorological observation data to derive a prediction of the lightning risk every 10 minutes up to 60 minutes in advance (smaller than the time interval of the third lightning risk derivation process described below).

[0016] In step S4, weather forecast data is obtained from a numerical weather forecast model. Here, the numerical forecast model in this embodiment is the numerical forecast model (MSM) of the Japan Meteorological Agency that targets the atmosphere in Japan and its nearby seas. However, other numerical forecast models such as the local numerical forecast model (LFM) under the jurisdiction of the Japan Meteorological Agency may be used as the numerical forecast model, or a combination of these numerical forecast models may be used. In addition, in this embodiment, the weather forecast data acquired from the numerical forecast model includes hourly precipitation (kg / m^2) for each unit area (area divided by 0.0625 degrees longitude and 0.05 degrees latitude), ground air pressure, temperature (K) on the ground and at each of a plurality of isobaric surfaces (1000hPa, 975hPa, 950hPa, 925hPa, 900hPa, 850hPa, 800hPa, 700hPa, 600hPa, 500hPa, 400hPa, 300hPa), and altitude at each of the plurality of 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 later. 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 to derive a prediction of lightning risk for every hour (larger than the time increment of the second lightning risk derivation process) from one hour ahead (60 minutes ahead) to six hours ahead using weather forecast data.

[0018] In step S6, display data for displaying the lightning risk derived in the processes in steps S2, S3, and S5 is generated, and then the program for generating display data for assisting in aircraft route determination is terminated. In this embodiment, the display data for displaying the lightning risk level is data in which the altitude distribution of the lightning risk level is associated with each of the unit surfaces described below for the present, every 10 minutes from the present (excluding the present) up to 60 minutes ahead (including 60 minutes from now), and every hour from 60 minutes ahead (including 60 minutes from now) up to 6 hours ahead (including 6 hours from now). However, the display data generated by the generation program for display data supporting aircraft route determination according to this embodiment can be in any format as long as it is data that can identify the altitude distribution of the lightning risk level for each of the unit surfaces.

[0019] Thus, the display data generation program for supporting 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 up to 60 minutes from now, and a third lightning risk derivation process for deriving the lightning risk from one hour to six hours from now, as well as a process for generating display data for displaying the lightning risks derived in these lightning risk derivation processes. This makes it possible to determine an aircraft route after visually recognizing the lightning risk. The lightning risk deriving process will be described in detail below.

[0020] <First lightning risk calculation process> First, the first lightning risk deriving process will be described in detail with reference to Figs. 2 to 7. The first lightning risk derivation process, which derives the altitude distribution of the current lightning risk, is composed of a process to derive the altitude distribution of echo intensity, a process to derive the altitude distribution of air temperature, a process to derive each feature (VIR and MTR described below), a process to derive a two-dimensional lightning risk, and a process to derive the altitude distribution of lightning risk, and these processes are executed in the given order. FIG. 2 is a flow diagram showing a process for deriving the altitude distribution of echo intensity. FIG. 3 is a flow diagram showing a process for deriving the altitude distribution of temperature. FIG. 4(a) is a diagram showing the altitude difference between adjacent isobaric surfaces derived by the 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 diagram showing a process for deriving each feature amount. FIG. 6 is a flow diagram showing a process for deriving a two-dimensional lightning risk. FIG. 7 is a flow diagram showing a process for deriving the altitude distribution of lightning risk.

[0021] As shown in FIG. 2, in step S210, which is the first step of the process of deriving the altitude distribution of echo intensity, for each C-band radar, the echo intensity acquired within its detection range is converted into an altitude distribution of echo intensity. Specifically, the distribution of echo intensity in a spherical coordinate system centered on the above-mentioned C-band radar is first converted into a distribution of echo intensity in a Cartesian coordinate system centered on the Earth using the latitude and longitude at which the C-band radar is installed, and the result of this conversion is then converted into an altitude distribution of echo intensity. Here, the term "unit surface" refers to each surface divided into a mesh shape by latitude and longitude (in this embodiment, both latitude and longitude are divided into 0.005 degrees). The term "altitude distribution" refers to the distribution when viewed divided into 100 m in the vertical direction, and unless otherwise specified, refers to the general term for what is derived for each unit surface. In the following description, each altitude divided into 100 m in the vertical direction is referred to as a "unit altitude", and each space divided by the unit surface and the unit altitude is referred to as a "unit space". In this 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 having a horizontal size that covers the entire territory of Japan, including the seas near Japan. Similarly, the upper limit altitude for which the unit altitude is defined is not particularly limited, but in this embodiment, the upper surface altitude is set to 15,000 m in consideration of the range detectable by weather radar. This surface altitude corresponds to the upper limit of a "predetermined altitude range" described below, and the altitude (altitude) of the ground 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 intensity for each unit space derived in step S211 is smoothed, and then the process shown in FIG. 2 ends. Specifically, the echo intensity in the target unit space is determined as the simple average of the echo intensities of 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. According to this, the horizontal and vertical changes of the echo intensity related to the unit space can be smoothed. This contributes to smoothing the horizontal and vertical changes of each feature amount described later. In order to achieve this effect, the range of the unit space used for smoothing the simple average of the echo intensity is not particularly limited, and it is sufficient that the range includes the target unit space and is composed of multiple unit spaces in each of the latitude direction, longitude direction, and altitude direction.

[0024] Next, as shown in FIG. 3, in step S220, which is the first step of the process of deriving the altitude distribution of temperature (current), a Voronoi division is performed using the installation points of a plurality of meteorological observation devices. Specifically, ignoring the elevation difference between the installation points of multiple meteorological observation devices, a perpendicular bisector is drawn on the line connecting adjacent kernel points (installation points of meteorological observation devices) to derive the nearest area (hereinafter referred to as the "divided area") to each kernel point.

[0025] In step S221, the result of the Voronoi division in step S220 is used to set ground data (altitude Z0, temperature T0, and atmospheric pressure P0) corresponding to the unit surface. 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 Z0 refers to the altitude (altitude), that is, the height based on the mean sea level of Tokyo Bay.

[0026] In step S222, the results of the hourly atmospheric analysis (air temperatures corresponding to each of a plurality of 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 height formula (see Figure 4(b)), and then the process shown in Figure 3 is terminated.

[0028] Specifically, as shown in Figure 4(a) and Figure 4(b), the height measurement formula includes the mean temperature T (K) of two adjacent isobaric surfaces and the air pressure (P m , P n (both in units of hPa) and enter the thickness of the two isobaric surfaces h m,n (m) is derived. Then, the thickness h m,n By sequentially adding these, the altitude Z of the unit surface under consideration 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 isopressure surface h 1,2 When deriving the altitude formula, the mean temperature T = (temperature T1 + temperature T2) / 2, the pressure P m = Atmospheric pressure P1 (1000hPa), Atmospheric pressure P n =Enter atmospheric pressure P2 (975hPa). In particular, the thickness h from the ground to the nearest isobaric surface 0,1When deriving the above equation, the ground data (temperature T0, pressure P0) is used, and the mean temperature T = (temperature T0 + temperature T1) / 2, pressure P m = Atmospheric pressure P0, Atmospheric pressure P n = Enter the atmospheric pressure P1 (1000 hPa). Then, enter the thickness h derived at altitude Z0. 0,1 By adding the thickness h to the height Z1, the height Z1 is derived for the unit surface under consideration. 1,2 The height Z2 is derived by adding up the thicknesses of the isobaric surfaces derived in sequence, and so on. As described above, the altitude distribution of air temperature in this embodiment is the air temperature in a unit space divided into 100 m intervals for each unit surface. Therefore, in this embodiment, the air temperature in the unit space is derived by linear interpolation using the altitude and air temperature for each isobaric surface derived using the altimetry formula.

[0029] In this manner, in this embodiment, when deriving the altitude distribution of temperature for each unit surface using the height measurement formula, ground data corresponding to each unit surface is determined by Voronoi division using the installation locations of multiple meteorological observation devices (used for surface-based meteorological observation by meteorological offices). This allows the ground data of the nearest meteorological observation device to be matched to each unit surface, improving the accuracy of the altitude distribution of the current temperature. This improvement in accuracy contributes to improving the accuracy of the altitude distribution of the 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 of the process of deriving each feature amount, an integrated value (VIR) of echo intensity in the vertical direction (over a predetermined altitude range) is derived for each unit surface. In step S231, for each unit surface, an integrated value (MTR) of echo intensity in the vertical direction for unit spaces in which the air temperature in a predetermined altitude range falls within a specific temperature range (in this embodiment, -9°C to -11°C) is derived, and then the process shown in Fig. 5 is terminated. Note that in step S231, there are cases where unit spaces in which the air temperature falls within the specific temperature range are discontinuous in the vertical direction, and in such cases, all of the echo intensities corresponding to the discontinuous unit spaces are integrated.

[0031] Next, as shown in FIG. 6, in step S240, which is the first step of the process of deriving a two-dimensional lightning risk, the next unit plane is set as the target plane. Here, the target surface refers to a unit surface that is referred to in the subsequent process of deriving a two-dimensional lightning risk. The next unit surface refers to the next unit surface in the order in which all unit surfaces constituting the region in which the above-mentioned unit surface is defined are set as target surfaces, and when step S240 is executed for the first time, the first unit surface in the order is set as the target surface. The same applies to the processes shown in Figs. 7 and 9 described later.

[0032] In step S241, it is determined whether the target surface is within 10 km from a unit surface whose MTR is 15 dBZ or more, and if the condition is met, the process proceeds to step S242, and if the condition is not met, the process proceeds to step S245. Note that being within 10 km from a unit surface whose MTR is 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 from a unit surface with a VIR of 25 dBZ or more, and if the condition is met, the process proceeds to step S243, and if the condition is not met, the process proceeds to step S244. As in step S245, being within 10 km from a unit surface with a VIR of 25 dBZ or more includes the VIR of the unit surface itself being 15 dBZ or more. In step S243, the lightning danger level (two-dimensional information) of the target surface is set to "high." Note that the above-mentioned "distance from the unit surface" is the distance from the center of the unit surface, and the distance is derived by referring to the latitude and longitude of the center of the unit surface and the latitude and longitude of the center of the corresponding target surface. This is also the case in the process shown in FIG. 9, which will be described later.

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

[0034] Next, as shown in FIG. 7, in step S250, which is the first step of the process of deriving the altitude distribution of lightning risk, the next unit plane is set as the target plane. In step S251, a mask temperature zone according to the season is set. Specifically, the mask temperature range is -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 were derived from past lightning strike cases.

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

[0036] In this embodiment, as described above, for one unit surface, the air temperature of each unit space is referred to, and the air temperature is judged to be within or outside the mask temperature zone, thereby setting the lightning danger level of the unit space, but this is not limited to this. For example, the unit space corresponding to the lower limit of the mask temperature zone (if there are multiple units, the one with the lowest altitude, hereinafter referred to as the "lower limit unit space") and the unit space corresponding to the upper limit of the mask temperature zone (if there are multiple units, the one with the highest altitude, hereinafter referred to as the "upper limit unit space") may be derived, and the lightning danger level of the target surface may be set to the lightning danger levels of these unit spaces and all unit spaces sandwiched between these unit spaces. This is because, taking into account the air temperature lapse rate, the air temperature of the unit space between the lower limit unit space and the upper limit unit space falls within the air temperature range (mask temperature zone) determined by the air temperature of the lower limit unit space and the air temperature of the upper limit unit space.

[0037] In this manner, in the first lightning risk derivation process in this embodiment, when deriving the altitude distribution of the current lightning risk, the feature quantities (VIR and MTR) which are two-dimensional information are derived using the altitude distribution of the echo intensity acquired from the weather radar and the altitude distribution of the current air temperature, and after the lightning risk which is two-dimensional information is derived once using the derived feature quantities, the altitude distribution of the current air temperature is derived. In particular, the threshold value related to the feature quantity when deriving the lightning risk which is two-dimensional information (the threshold value related to steps S241 and S242 shown in FIG. 6) is a threshold value derived using past cases of aircraft being struck by lightning (a combination of the route of an aircraft that has been struck by lightning in the past and the weather conditions at that time). This allows the number of samples of past aircraft lightning strike cases required to determine a threshold for deriving the altitude distribution of lightning strike risk, which is two-dimensional information, to be reduced, while also improving the accuracy of the threshold itself. These thresholds may be appropriately changed based on future collected cases of aircraft being struck by lightning, or may be appropriately changed taking into account meteorological parameters other than echo intensity.

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

[0039] As described above, in this embodiment, when deriving the altitude distribution of lightning risk, the mask temperature zones to be referenced are temperature zones according to the seasons. This makes it possible to improve the accuracy of the altitude distribution of lightning risk. In this embodiment, the mask temperature zone may be switched by referring to weather conditions such as air temperature, atmospheric pressure distribution, etc. Furthermore, the mask temperature zone is not limited to being switched between two seasons, winter and summer, and may be switched between four seasons. Furthermore, the mask temperature zone may be determined according to the latitude, climate, and topography of the area for which the altitude distribution of lightning risk is to be derived, and may be changed as appropriate based on future collected cases of aircraft lightning strikes.

[0040] As described above, the mask temperature zone may vary depending on the above-mentioned parameters (e.g., season), but whatever the temperature zone, it is permitted to overlap partially with the above-mentioned specific temperature zone (-9°C to -11°C). In particular, the lower limit of the mask temperature zone (constant regardless of season, -10°C) is included in the specific temperature zone. According to this, when deriving the altitude distribution of lightning risk using MTR in addition to VIR, it is possible to increase the influence of the temperature range around -10°C, where clouds are likely to become charged.

[0041] <About the second lightning risk calculation process> Next, the second lightning risk derivation process for deriving the lightning risk from the present to 60 minutes ahead will be described in detail with reference to Fig. 8 and Fig. 9. In addition to these figures, the process shown in Fig. 7 already described will be used to explain the details of the process. FIG. 8 is a flow chart showing a process for predicting a two-dimensional lightning risk for every 10 minutes up to 60 minutes ahead, and this process is executed first in the second lightning risk derivation process. FIG. 9 is a conceptual diagram illustrating a prediction method using optical flow.

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

[0043] In step S312, the optical flow (movement vector field) between time N-1 and time N is derived using a grayscale image of the two-dimensional distribution of lightning risk at time N-1 and a grayscale image of the two-dimensional distribution of lightning risk at time N, and then in step S313, a grayscale image of the two-dimensional distribution of lightning risk at time N+1 is generated using the grayscale image at time N and the derived optical flow. Specifically, as shown in FIG. 9, assuming that the shading of corresponding pixels (unit surfaces) in a grayscale image at time N-1 (top left in FIG. 9) and a grayscale image at time N (top right in FIG. 9) does not change before and after movement, the optical flow (middle left in FIG. 9) between time N-1 and time N is estimated. Then, each pixel with a dark color (gray or black) in the grayscale image at time N (middle right in FIG. 9) is moved by the movement vector corresponding to the pixel to generate a grayscale image at time N+1. This is based on the assumption that the derived optical flow continues between time N and time N+1. The method of generating a grayscale image using such an optical flow is also the same in the modified example shown in FIG. 11.

[0044] In step S314, it is determined whether or not generation of a grayscale image relating to the two-dimensional distribution of lightning risk up to 60 minutes into the future has been completed. If the condition is satisfied, the process proceeds to step S316; if the condition is not satisfied, the process returns to step S310 via step S315. In step S315, time N is set to time N+1. As a result, in the subsequent processing, a grayscale image relating to the two-dimensional distribution of lightning risk after another 10 minutes is generated.

[0045] In step S316, each of the generated grayscale images is converted into a two-dimensional distribution of lightning risk, and then the short-term lightning risk prediction process is terminated. Specifically, by using the relationship between the two-dimensional lightning risk level used in the processing of steps S310 and S311 and the shades of 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 distribution of lightning risk.

[0046] Next, in the second lightning risk derivation process, the process shown in Figure 7 is executed using the two-dimensional lightning risk distribution for every 10 minutes up to 60 minutes ahead derived in the short-term lightning risk prediction process. This allows the altitude distribution of lightning risk to be predicted every 10 minutes for the next 60 minutes. In particular, in this embodiment, in the process shown in Figure 7 executed in the second lightning risk derivation process, the altitude distribution of the current air temperature is referenced, similar to the process shown in Figure 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 the next 60 minutes using the two-dimensional lightning risk distribution 10 minutes ago and the current two-dimensional lightning risk distribution (history related to the two-dimensional lightning risk distribution), and then to derive the altitude distribution of lightning risk for every 10 minutes up to the next 60 minutes using the altitude distribution of the current air temperature. In the process of predicting a two-dimensional lightning risk for every 10 minutes up to 60 minutes ahead, which is executed in the second lightning risk derivation process, an optical flow is derived from grayscale images at two adjacent times, and a grayscale image at the time following ...

[0048] <About the third lightning risk derivation process> Next, the third lightning risk derivation process for deriving the lightning risk from one hour to six hours ahead will be described in detail with reference to Fig. 10. Note that, in order to describe the details of this process, the process shown in Fig. 7 already described will be used in addition to Fig. 10. FIG. 10 is a flow chart showing a process of 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 Figure 10, in step S510, which is the first step of the process of predicting two-dimensional lightning risk for each hour up to six hours into the future (hereinafter referred to as "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 in step S510 is executed for the first time, the target time is set to one hour ahead, and thereafter, each time the process is executed, the target time is set to one hour ahead of the immediately preceding 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 on the target surface at the target time is 5 kg / m^2 or more. If the condition is met, the process proceeds to step S513, and if the condition is not met, the process proceeds to step S514. Here, the hourly precipitation is the hourly precipitation at the target time acquired from the numerical forecast model in step S4, and this also applies to the hourly precipitation described later. This hourly precipitation is an example of rain cloud information in the present invention. In step S513, the lightning danger level (two-dimensional information) of the target surface is set to "high."

[0050] In step S514, it is determined whether the hourly precipitation 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 danger level (two-dimensional information) of the target surface is set to "medium." In step S516, the lightning risk level (two-dimensional information) of the target surface is set to "low." In step S517, it is determined whether or not the processing has been completed for all unit surfaces. If the condition is satisfied, the process proceeds to step S518, and if the condition is not satisfied, 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, in the third lightning risk derivation process, the process shown in FIG. 7 is executed using the two-dimensional lightning risk for each hour up to six hours ahead derived in the short-term lightning risk prediction process. In this embodiment, the process shown in Figure 7 executed in the third lightning risk derivation process uses an altitude distribution of temperature derived using weather forecast data obtained from a numerical forecast model, unlike the first lightning risk derivation process and the second lightning risk derivation process which use the altitude distribution of the 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 1 hour to 6 hours ahead from the hourly precipitation obtained from the numerical forecast model, and then derive an hourly height distribution of lightning risk from 1 hour to 6 hours ahead using the height distribution of air temperature derived using the numerical forecast model.

[0054] <Modification of the second lightning risk derivation process> Next, a modified example of the second lightning risk deriving process will be described with reference to Fig. 11. Note that in describing this modified example, the processes shown in Figs. 5 to 7 already described will be used in addition to Fig. 11. FIG. 11 is a flow chart showing a process for predicting echo intensity for every 10 minutes up to 60 minutes ahead, and this process is executed first in the modified example of the second lightning risk deriving process.

[0055] As shown in FIG. 11, in step S320, which is the first step of the process of predicting echo intensity every 10 minutes for the next 60 minutes (hereinafter referred to as "short-term echo intensity prediction process"), the next unit altitude is set to the target altitude. Here, the target altitude refers to the unit altitude to be referred to in the following short-time echo intensity prediction process. The next unit altitude refers to the next unit altitude in the order for making all unit altitudes in the vertical direction the target altitudes. 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 the target altitude at time N-1 is imaged in gray scale. In step S322, the echo intensity distribution at the target altitude at time N is imaged in gray scale. Here, the echo intensity distribution refers to the distribution of echo intensity in the horizontal direction determined for each target altitude. In addition, in this modified example, imaging the echo intensity distribution in grayscale means making each unit surface into an image with shades of light and dark that correspond to the echo intensity value corresponding to that unit surface (the greater the echo intensity value, the darker the image), and the imaging is performed for each target altitude. Furthermore, in steps S320 to S324, when the processes in steps S321 and S322 are executed for the second or subsequent times, images in which the echo intensity distributions are grayscaled have already been generated for both time N-1 and time N. Therefore, the processes in steps S321 and S322 for the second or subsequent times do not need to be executed.

[0057] In step S323, the grayscale image of the echo intensity distribution related to time N-1 and the grayscale image of the echo intensity distribution related to time N are used to derive the optical flow corresponding to each unit surface. 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 or not generation of grayscale images of echo intensity distribution up to 60 minutes into the future has been completed. If the condition is satisfied, the process proceeds to step S327; if the condition is not satisfied, the process returns to step S321 via step S326. In step S326, time N is set to time N+1, and a grayscale image relating to the echo intensity distribution 10 minutes later is generated by the subsequent processing.

[0058] In step S327, each of the generated grayscale images is converted into an echo intensity. Specifically, by using the relationship between the echo intensity values ​​used in the processing of steps S321 and S322 and the shading of 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 an echo intensity distribution.

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

[0060] Next, in a modified example of the second lightning risk derivation process, the process shown in Fig. 5 is executed using the altitude distribution of echo intensity for every 10 minutes up to 60 minutes ahead derived by the process shown in Fig. 11, and the VIR and MTR for every 10 minutes up to 60 minutes ahead are derived. Then, using these derived feature quantities, the process shown in Fig. 6 and the process shown in Fig. 7 are executed, whereby the altitude distribution of lightning risk for every 10 minutes up to 60 minutes ahead is predicted in the modified example of the second lightning risk derivation process as well. In the process shown in FIG. 7 executed in this modified example, the altitude distribution of the current temperature is referenced.

[0061] In the process shown in FIG. 11, since the prediction target is three-dimensional information (altitude distribution of echo intensity), the derivation of the optical flow described above and the prediction of echo intensity using the optical flow are 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 by replacing the unit altitude with the unit vertical plane in the method shown in Fig. 11. This also makes it possible to derive the altitude distribution of echo intensity every 10 minutes up to 60 minutes ahead.

[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 Fig. 11 with the vertical optical flow for each unit vertical plane, and the altitude distribution of the echo intensity on the rear side used in deriving these optical flows is moved by the amount of the generated three-dimensional motion vector field to derive the altitude distribution of the echo intensity 10 minutes later. This makes it possible to take into account three-dimensional changes in echo intensity, thereby improving the prediction accuracy of the altitude distribution of 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 supporting aircraft route determination in the present invention can be said to execute the following: a first lightning risk derivation process that uses rain cloud information (echo intensity) obtained from a weather radar to derive a current lightning risk for each of multiple areas (unit surfaces) divided into a mesh-like 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 multiple areas up to a first hour ahead (60 minutes ahead) without using a numerical forecast model; a third lightning risk derivation process that derives a lightning risk for each of multiple areas up to a second hour ahead (6 hours ahead) after the first hour ahead using rain cloud information (hourly precipitation) derived using at least a 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. According to this, by sandwiching a lightning risk predicted using the history of rain cloud information without using a numerical forecast model between the lightning risk derived from the current rain cloud information and the lightning risk predicted from the rain cloud information derived using a numerical forecast model, it is possible to smooth the transition of the lightning risk over time while ensuring the prediction accuracy of the lightning risk. 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 example, the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process all derive an altitude distribution of lightning risk, but some or all of these lightning risk derivation processes may derive a two-dimensional distribution of lightning risk. In other words, some or all of the above-described "lightning risk for each of multiple regions" may be two-dimensional lightning risk. Furthermore, with regard to the above-mentioned 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, but any information that allows the amount of raindrops to be evaluated may be used for each of the rain cloud information. In addition, the above-mentioned "deriving the risk of lightning strike for multiple regions up to the first hour ahead using the history of rain cloud information" is not limited to the method using optical flow as described above, but also includes methods using machine learning such as deep learning. Regarding the above phrase "using at least rain cloud information derived using 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 risk derivation process is obtained from a numerical forecast model, but some of the rain cloud information may be obtained from forecast information other than a numerical forecast model.

[0065] Furthermore, in this embodiment and its variants, as described above, in all 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. This makes it possible to smooth the transition of the three-dimensional lightning risk along the time series.

[0066] In particular, in this embodiment and its variants, in the second lightning risk derivation process, as in the first lightning risk derivation process, the altitude distribution of the current air temperature is used to convert the two-dimensional lightning risk into an altitude distribution of lightning risk. This makes it possible to smooth the transition of the three-dimensional lightning risk from the present to the first time ahead.

[0067] Furthermore, as described above, in a modified example of the second lightning risk derivation process, as explained using Figure 11, the history of the echo intensity altitude distribution is used to derive the echo intensity altitude distribution for every 10 minutes up to 60 minutes into the future, and the lightning risk for every 10 minutes up to 60 minutes into the future is derived using the derived echo intensity altitude distribution. This makes it possible to improve the accuracy of lightning risk prediction for every 10 minutes up to 60 minutes in advance. This is because it requires predicting upstream information for deriving lightning risk, and because the horizontal resolution of echo intensity obtained from weather radar is smaller than the unit surface.

[0068] On the other hand, in the second lightning risk derivation process in this embodiment, as explained using Figure 8, the history of the derived lightning risk is used to derive the lightning risk for every 10 minutes up to the next 60 minutes. This reduces the processing load in 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 derivation interval of the lightning risk by the second lightning risk derivation process becomes shorter.

[0069] <Indication of lightning risk> In this embodiment, a display device, which will be described later, displays the lightning risk using display data generated by the program for generating display data for assisting in determining the route of an aircraft, as described above. Hereinafter, the display of the lightning danger level according to this embodiment will be described in detail with reference to Figs. The processes shown in Fig. 12(a) and Fig. 12(b) are executed by a display device described later, Fig. 12(a) is a flow showing the lightning risk display process, and Fig. 12(b) is a flow showing the section update process. In particular, the lightning risk display process is executed when the takeoff airport and landing airport are determined, and the section update process is executed when the selected route is changed. Figures 13 to 15 are diagrams showing examples of images displayed in the display area (display) of a display device, where Figure 13 shows an example of an image when the current risk of lightning is displayed, Figure 14 shows an example of an image when a forecast of the risk of lightning for the next 60 minutes is displayed, and Figure 15 shows an example of an image when a forecast of the risk of lightning for the next 6 hours is displayed.

[0070] As shown in FIG. 12(a), in step S70, which is the first step of the lightning risk display process, candidate routes are obtained. Here, the candidate route is a route that is determined when the takeoff airport and landing airport are determined, and although it depends on the determined takeoff airport and landing airport, basically there are a plurality of candidate routes. In particular, in this embodiment, the takeoff airport and landing airport are determined by an input operation to the display device (selection of an airport on a map), but these airports may be acquired from a device other than the display device, such as a display data generating device described later. Furthermore, after the takeoff airport and landing airport are determined by these methods, the route connecting these airports may be drawn by an input operation to the display device, or the route may be acquired from a device other than the display device.

[0071] In step S71, the display data is obtained. The display data is generated by the display data generation program described above that supports aircraft route decisions, 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 from the present.

[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 candidate route with the shortest range.

[0073] In step S73, the lightning risk and the candidate routes are displayed on a 3D map. This allows the lower display area to display the lightning risk (in three dimensions) together with multiple potential routes on a 3D map. Specifically, as shown in Figs. 13 to 15, the candidate routes and the degree of risk of lightning are displayed together on a 3D map displayed in a 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 in a manner that makes the level identifiable, while unit spaces with the lowest lightning risk level of "low" are not displayed. This is also the case for the cross-sectional view described below.

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

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

[0076] Next, as shown in Fig. 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 section cut vertically along the updated selected route are displayed on the 3D map, and then the 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 manner, in this embodiment, the lightning risk is displayed in the display area (display) of the display device using display data generated by the display data generation program for supporting aircraft route determination described above. According to this, by displaying the lightning risk level with a smooth transition over time, the visibility of the lightning risk level itself can be improved, making it easier to decide on a route. In order to achieve this effect, the display object may be a two-dimensional lightning strike danger level. This also applies to the display in the lower display area 501 in the following inventions. In addition, in this embodiment, when the lightning danger level is displayed in the display area of ​​the display device, the route is also displayed, but it is not necessary to display the route.

[0078] However, smoothing the transition of the lightning risk level over time makes it difficult to recognize which lightning risk level derivation process the displayed lightning risk level was derived in. This is more noticeable between the second lightning risk derivation process and the third lightning risk derivation process, which have a large difference in prediction accuracy. The function for solving this problem will be described in detail below.

[0079] First, in this embodiment, as shown in Fig. 14, a unit space whose lightning risk 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 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 easier for the user to recognize whether the lightning risk level being displayed has been derived in the second lightning risk derivation process, or whether the lightning risk level being displayed has been 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 derived in the second lightning risk derivation process is "medium" or "high" and the display mode of a unit space whose lightning risk derived in the third lightning risk derivation process is "medium" or "high" is not limited to the 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] Also, as shown in Figure 13, in this embodiment, a unit space in which the lightning risk derived in the first lightning risk derivation process is "medium" or "high" is displayed in the same display manner as a unit space in which the lightning risk derived in the second lightning risk derivation process is "medium" or "high." 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 of the same type. Here, the lightning risk being of the same type refers to having the same information (echo intensity and current lightning risk) used to derive the lightning risk and having the same derivation logic for the lightning risk (the use of the above-mentioned feature quantity), which leads to the accuracy of both lightning risks being similar.

[0081] Also, as shown in FIG. 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 portion 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 easier to recognize whether the lightning risk being displayed has been derived in the third lightning risk derivation process. Incidentally, including the following modified examples, when the display mode of the slider sb1 is different, it means that the display mode is different in the portion excluding the characters indicating the time.

[0082] Also, although different from this 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 for the user to recognize whether the lightning risk level being displayed has been derived in the second lightning risk derivation process, or whether the lightning risk level being displayed has been derived in the third lightning risk derivation process. In order 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 in 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 the case where the display mode of the marker sb2 is changed.

[0083] Furthermore, in this modified example, 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 and the display mode of the slider sb1 when the lightning risk derived in the second lightning risk derivation process is displayed be the same as each other. This also 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 of the same type.

[0084] In addition, in this embodiment, as shown in Figures 13 to 15, in a cross section cut vertically along the selected route displayed in the upper display area 502, the lightning risk derived in the first lightning risk derivation process, the lightning risk derived in the second lightning risk derivation process, and the lightning risk derived in the third lightning risk derivation process are all displayed in the same display manner. This makes it possible to maintain ease of recognition of the level of the lightning danger ("high" or "medium") even if the display mode of the lightning danger level displayed in lower display area 501 is changed.

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

[0086] As shown in Figure 16, when displaying the lightning risk level 60 minutes after the slider sb1 is operated, the lightning risk level derived by the second lightning risk level derivation process and the lightning risk level derived by the third lightning risk level derivation process are displayed superimposed on each other. This makes it easy to intuitively recognize that the lightning risk levels have been switched to different (different) levels of risk. Here, the lightning risk levels being different means that, as opposed to the above-mentioned lightning risk levels being the same, the information used to derive the lightning risk levels is different, the derivation logic for the lightning risk levels is the same, etc., which leads to a difference in accuracy between the two lightning risk levels. In order to achieve this effect, the period during which the lightning risk derived by the second lightning risk derivation process and the lightning risk derived by the third lightning risk derivation process overlap is not important, but it is preferable that this period be the derivation interval of the lightning risk in the second lightning risk derivation process (10 minutes in this embodiment). Furthermore, as shown in Figure 16, during the period in question, it is preferable to gradually increase the transparency and fade out the lightning risk derived by the second lightning risk derivation process as the display time during the period progresses.

[0087] In addition, 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 until then is hidden, and only the lightning risk level derived by the second lightning risk level derivation process is displayed. Although not shown, the lightning danger level is also displayed in the upper display area 502 in the same manner as in the lower display area 501.

[0088] Also, although not shown in the figure, when the tap button sb3 provided on the scroll bar sb is operated, the display time progresses toward the future at a constant speed from the display time at the time of operating the tap button sb3, without operating the slider sb1, and a lightning risk simulation is executed in which the display of the lightning risk changes in accordance with the progression of the display time. This allows the user to visually grasp the moving speed of the lightning danger. It should be noted that an image resembling an aircraft may be moved along the selected route in accordance with the progress of the lightning risk simulation (progression of the display time). This allows a visual assessment of the risk of lightning strike on the selected route.

[0089] <Outline of the display system to assist aircraft in deciding routes> Next, an overview of a display system for assisting in determining an aircraft's route according to this embodiment will be described with reference to FIG. FIG. 17 is a block diagram showing an outline of a 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 composed of a generation program execution device 1 that executes a generation program for display data that assists in the above-mentioned aircraft route determination, and a display device 50 that has a display and executes processing related to displaying the lightning risk described using Figures 12 to 15. Furthermore, the generation program execution device 1 includes a first lightning risk derivation unit 10 that executes the first lightning risk derivation process described above, a second lightning risk derivation unit 20 that executes the second lightning risk derivation process, a third lightning risk derivation unit 30 that executes the third lightning risk derivation process, and a display data generation unit 40 that executes the display data generation process.

[0091] In the display system 100 in 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 system 100 may be configured as a single device by including a generation program execution unit including all of the functional units possessed by the generation program execution device 1 in the display device 50, and the number of devices that constitute the display system 100 and the allocation of the functional units possessed by the display system 100 to the devices are not important.

[0092] The above description is an example of the present invention, and various configurations other than those described above can be adopted. Furthermore, the above-mentioned configurations can be appropriately combined without departing from the spirit of the present invention.

[0093] The present embodiment encompasses the following technical ideas. (1) a first lightning risk deriving process for deriving a current lightning risk for each of a plurality of regions divided into a mesh shape by latitude and longitude using rain cloud information acquired from a weather radar; A second lightning risk derivation process for deriving a lightning risk for each of the plurality of regions up to a first hour ahead using a history of raincloud information acquired from the weather radar without using a numerical forecast model; A third lightning risk derivation process deriving a lightning risk for each of the plurality of regions from the first hour ahead to a second hour ahead using rain cloud information derived at least by using the numerical forecast model; a display data generation process for generating display data for displaying the lightning risk levels derived by the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process in a chronological order; A program for generating display data to assist in aircraft routing decisions, the program executing the program. (2) The first lightning risk derivation process 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 altitude distribution of the current temperature in addition to rain cloud information acquired from the weather radar; The second lightning risk derivation process derives an altitude distribution of a lightning risk for each of the plurality of regions up to the first hour ahead using a history of raincloud information acquired from the weather radar as well as an altitude distribution of air temperature for each of the plurality of regions; The third lightning risk derivation process derives a height distribution of a lightning risk for each of the plurality of regions up to the second time ahead using at least the rain cloud information derived using the numerical forecast model and the height distribution of air temperature for each of the plurality of regions derived using the numerical forecast model. A program for generating display data to assist in determining the route of an aircraft as described in (1) above. (3) The second lightning risk deriving process derives a height distribution of the lightning risk for each of the plurality of regions up to the first hour using the history of raincloud information acquired from the weather radar as well as the height distribution of the current temperature for each of the plurality of regions. A program for generating display data to assist in determining the route of an aircraft as described in (2) above. (4) The second lightning risk derivation process includes: Using a history of raincloud information acquired from the weather radar, derive raincloud information for each of the plurality of regions up to the first time ahead; Using the derived rain cloud information for each of the plurality of regions up to the first hour ahead, a lightning risk for each of the plurality of regions up to the first hour ahead is derived. A program for generating display data to assist in determining the route of an aircraft as described in (3) above. (5) A generation program execution unit that executes a generation program for display data for supporting aircraft route determination according to any one of (1) to (4) above; A display unit; Equipped with The generation program execution unit A first lightning risk deriving unit that executes the first lightning risk deriving process; A second lightning risk deriving unit that executes the second lightning risk deriving process; A third lightning risk derivation unit that executes the third lightning risk derivation process; A display data generating unit that executes the display data generating process; Including, The display unit displays a lightning risk using the display data generated by the display data generation unit. A display system that assists aircraft in making routing decisions. (6) The display unit displays the lightning risk for each of the plurality of regions up to the first time ahead derived by the second lightning risk derivation unit and the lightning risk for each of the plurality of regions up to the second time ahead derived by the third lightning risk derivation unit in different display modes. A display system for assisting aircraft route decisions as described in (5) above. (7) The display unit displays 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 in the same display mode. A display system for assisting aircraft route decisions as described in (6) above. (8) the display unit displays an auxiliary image including a first image corresponding to a period starting from the present and ending at the second time ahead, and a second image that enables identification of a timing within the period for which the displayed lightning risk corresponds; a display mode of a portion of the first image corresponding to a period from the present time to the first time ahead and a display mode of a portion of the first image corresponding to a period from the first time ahead to the second time ahead are different from each other; A display system for assisting aircraft route determination as described in any one of (5) to (7) above. (9) the display unit displays an auxiliary image including a first image corresponding to a period starting from the present and ending at the second time ahead, and a second image that enables identification of a timing within the period for which the displayed lightning risk corresponds; 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. A display system for assisting aircraft route decisions as described in any one of (5) to (7) above. (10) The first image and the second image have the same display mode 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. A display system for assisting aircraft route decisions as described in (9) above. (11) The display unit displays, in the first time ahead, the lightning risk for each of the plurality of regions derived by the second lightning risk derivation process and the lightning risk for each of the plurality of regions derived by the third lightning risk derivation process in a superimposed manner. A display system for assisting aircraft route determination as described in any one of (5) to (10) above. [Explanation of symbols]

[0094] 1. Generator Execution Device 10 First lightning risk derivation part 20 Second lightning risk derivation part 30 Third lightning risk derivation part 40 Display data generation unit 50 Display device 100 Display System sb Scrollbar sb1 slider sb2 marker sb3 Tap button 501 Lower display area 502 Upper display area

Claims

1. a first lightning risk deriving process for deriving a current lightning risk for each of a plurality of regions divided into a mesh shape by latitude and longitude using rain cloud information acquired from a weather radar; A second lightning risk derivation process for deriving a lightning risk for each of the plurality of regions up to a first hour ahead using a history of raincloud information acquired from the weather radar without using a numerical forecast model; A third lightning risk derivation process deriving a lightning risk for each of the plurality of regions from the first hour ahead to a second hour ahead using rain cloud information derived at least by using the numerical forecast model; a display data generation process for generating display data for displaying the lightning risk levels derived by the first lightning risk derivation process, the second lightning risk derivation process, and the third lightning risk derivation process in a chronological order; A program for generating display data to assist in aircraft routing decisions, the program executing the program.

2. The first lightning risk derivation process 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 altitude distribution of the current temperature in addition to rain cloud information acquired from the weather radar; The second lightning risk derivation process derives an altitude distribution of a lightning risk for each of the plurality of regions up to the first hour ahead using a history of raincloud information acquired from the weather radar as well as an altitude distribution of air temperature for each of the plurality of regions; The third lightning risk derivation process derives a height distribution of a lightning risk for each of the plurality of regions up to the second time ahead using at least the rain cloud information derived using the numerical forecast model and the height distribution of air temperature for each of the plurality of regions derived using the numerical forecast model.

2. A program for generating display data for assisting in route determination for an aircraft according to claim 1.

3. The second lightning risk derivation process derives a height distribution of the lightning risk for each of the multiple regions up to the first hour using the history of raincloud information acquired from the weather radar as well as the height distribution of the current temperature for each of the multiple regions.

3. A program for generating display data for assisting in route determination for an aircraft according to claim 2.

4. The second lightning risk derivation process includes: Using a history of raincloud information acquired from the weather radar, derive raincloud information for each of the plurality of regions up to the first time ahead; Using the derived rain cloud information for each of the plurality of regions up to the first hour ahead, a lightning risk for each of the plurality of regions up to the first hour ahead is derived.

4. A program for generating display data for assisting in determining an aircraft route according to claim 3.

5. a generation program execution unit that executes a generation program for generating display data for supporting flight route determination of an aircraft according to any one of claims 1 to 4; A display unit; Equipped with The generation program execution unit A first lightning risk deriving unit that executes the first lightning risk deriving process; A second lightning risk deriving unit that executes the second lightning risk deriving process; A third lightning risk derivation unit that executes the third lightning risk derivation process; A display data generating unit that executes the display data generating process; Including, The display unit displays a lightning risk using the display data generated by the display data generation unit. A display system that assists aircraft in making routing decisions.

6. The display unit displays the lightning risk for each of the plurality of regions up to the first time ahead derived by the second lightning risk derivation unit and the lightning risk for each of the plurality of regions up to the second time ahead derived by the third lightning risk derivation unit in different display modes.

6. A display system for assisting aircraft routing decisions according to claim 5.

7. The display unit displays 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 in the same display mode.

7. A display system for assisting aircraft routing decisions according to claim 6.

8. the display unit displays an auxiliary image including a first image corresponding to a period starting from the present and ending at the second time ahead, and a second image that enables identification of a timing within the period for which the displayed lightning risk corresponds; a display mode of a portion of the first image corresponding to a period from the present to the first time ahead and a display mode of a portion of the first image corresponding to a period from the first time ahead to the second time ahead are different from each other; A display system for assisting aircraft routing as claimed in any one of claims 5 to 7.

9. the display unit displays an auxiliary image including a first image corresponding to a period starting from the present and ending at the second time ahead, and a second image that enables identification of a timing within the period for which the displayed lightning risk corresponds; 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. A display system for assisting aircraft routing as claimed in any one of claims 5 to 7.

10. The first image and the second image have the same display mode 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.

10. The display system for assisting aircraft routing as claimed in claim 9.

11. The display unit displays, in the first time ahead, the lightning risk for each of the plurality of regions derived by the second lightning risk derivation process and the lightning risk for each of the plurality of regions derived by the third lightning risk derivation process in a superimposed manner. A display system for assisting aircraft routing as claimed in any one of claims 5 to 7.

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