JP2002328179A - Long-term weather forecasting apparatus and method - Google Patents

Abstract

(57) [Problem] To provide a long-term weather forecasting apparatus and method capable of obtaining a long-term and accurate weather forecast. Kind Code: A1 A vibration sensor mounted on a tree τ.
Outputs a signal voltage V corresponding to the underground sound A. The signal voltage V is continuously measured by the underground sound observation device 14 and taken into the data processing device 16. The prediction processing unit 52 of the data processing device 16 performs a long-term weather prediction process based on the value of the signal voltage V (sound pressure level corresponding to the sound pressure of the underground sound A) Vd. Specifically, the sound pressure level Vd of the measurement month
Based on the change, the processing for predicting long-term weather such as cold and warm at three months and six months after the underground sound measurement is performed.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a long-term weather forecasting apparatus and method for predicting long-term weather based on ground sound measured by a sensor.

[0002]

2. Description of the Related Art Conventionally, as a method for predicting changes in long-term weather (that is, atmospheric conditions and various atmospheric phenomena such as snow, rain, wind, and lightning) after one month or longer, a correlation method, a periodic method, and the like are known. And similar methods have been used.

[0003]

SUMMARY OF THE INVENTION These prediction methods are:
Unlike the short-term weather forecast of about one week, which is characterized by the use of sophisticated weather observation equipment and the refinement of weather observation points, statistics based on empirical rules developed from the incomplete physical laws of weather Prediction is based on a statistical method, the prediction results are average trends over the past several years, for example, decades, and rough predictions are possible, but prediction accuracy is not necessarily high It is pointed out that it is not. Further, long-term weather forecasts, for example, detailed forecasts such as how many days and what day after three months or six months later, are hardly possible.

[0004] The inventor of the present application has disclosed in Japanese Patent Application No.
333929 describes a weather forecasting apparatus and method for observing underground sounds using trees and the like and for predicting short-term weather within 48 hours or the like with high accuracy from changes in the underground sounds. Proposing new technologies.

The present invention has been made in consideration of the above-described problems and the above-described novel technology, and has as its object to provide a long-term weather forecasting apparatus and method capable of obtaining a long-term and accurate weather forecast. .

[0006]

According to the present invention, there is provided a long-term weather forecasting apparatus which measures underground sound based on a change in the underground sound measured by the underground sound measuring means. And long-term weather forecasting means for forecasting long-term weather (the invention according to claim 1).

According to the present invention, long-term weather can be predicted based on a change in the current underground sound.

In this case, the long-term forecast period of weather is a period at least three to six months after the measurement of the underground sound (the invention according to claim 2). Prediction after 9 months or 12 months, which is a multiple of 3, is also possible.

[0009] More specifically, the long-term weather forecast is a forecast of cold and warm, and corresponds to the loudness of the underground sound measured on the day, and 3 hours from the day on which the relatively large underground sound was measured. A month is predicted to be a cold day near a response day after a month, while a warm day is predicted to be around a response day three months after the day on which the relatively small underground sound was measured (Claim 3). Invention).

The long-term weather forecast is a forecast of cold and warm, and a response six months after the day on which the relatively large underground sound was measured corresponding to the loudness of the underground sound measured on the day. A day is predicted to be a warm day near the day, while a cold day is predicted to be near a response day six months after the day when the relatively small underground sound was measured (the invention according to claim 4).

In the above long-term weather forecast, the loudness of the underground sound measured on the day is the average of the loudness of the underground sound continuously measured on the day or the loudness of the underground sound for several days including the day. (Moving average value) (the invention according to claim 5).

It should be noted that the underground sound changes six hours earlier than the actual weather, and furthermore, it takes a total of twelve hours for the effect of the underground sound to actually appear, that is, a total of twelve hours (see Japanese Patent Application No. Hei 11 (1999)). For example, the vicinity of the response date after 3 months can be specified as the time when 3 hours after the response date + 12 hours has passed.

Therefore, according to the present invention, a long-term weather forecast from three months to six months later can be made, and an accurate forecast result can be obtained.

Further, the long-term weather forecasting method according to the present invention includes a step of measuring an underground sound and a step of predicting a long-term weather based on a change in the underground sound. 6)).

According to this method, accurate long-term weather can be predicted.

[0016]

An embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 shows the configuration of a long-term weather forecasting apparatus 10 according to an embodiment of the present invention.

This long-term weather forecasting device 10 is a device for predicting long-term weather, and includes a vibration sensor 12 as an underground sound measuring means, an underground sound observing device 14, and a data processing device 16. I have.

FIG. 2 is a longitudinal sectional view of the vibration sensor 12 partially omitted, and FIG. 3 is a transverse sectional view of the vibration sensor 12 taken along the line AA. The vibration sensor 12 employs a moving coil type microphone, and detects a ground sound indicating a sign of slope failure used in the slope failure prediction device (see Japanese Patent Application No. 2000-189195). ) Has basically the same structure.

As shown in FIGS. 2 and 3, the vibration sensor 12
Has a cylindrical closed housing 20. A magnetic body 22 having a substantially concave cross section is mounted inside the housing 20, and a columnar permanent magnet 23 and a magnetic body 24 are fixed in a stacked state to the concave portion of the magnetic body 22.

The upper surface of the magnetic body 24 and the upper surface of the magnetic body 22 are configured to be substantially on the same plane.

On the outer peripheral side of the upper surface of the magnetic body 22, an end is fixed to the inner side surface of the housing 20, a hole 25A is opened in the center of the upper surface, and four arc-shaped portions are formed around the hole 25A. A resin diaphragm 25 provided with a notch 25B is arranged as a damper.

A movable coil 26 is mounted around the inside of the opening of the hole 25A formed in the diaphragm 25.

The movable coil 26 can move in the cylindrical groove 27 formed by the magnetic body 22 and the magnetic body 24, in other words, the outer periphery of the magnetic body 24 in the front-back direction (vertical direction in FIG. 2). It is.

The vibration sensor 12 configured as described above
It collects solid vibration noise from the ground,
Is brought into contact with a vibrating solid, that is, the trunk of a tree τ, and the housing 20 vibrates due to the vibration from the tree τ. When the housing 20 vibrates, the permanent magnet 2
3 vibrates and the magnetic field vibrates. Since the diaphragm 25 and the movable coil 26 try to stop by inertia, the permanent magnet 23
And the movable coil 26 relatively vibrate, and the linkage flux changes. As a result, a signal voltage V is generated in the movable coil 26.

The signal voltage V generated in the movable coil 26 is
The signal is supplied to a signal amplifier 40 (see FIG. 1) in the underground sound observation device 14 via a lead wire 29 connected to the movable coil 26.

FIG. 4 shows a state where the vibration sensor 12 is attached to the trunk (or branches) of the tree τ. In this case, the vibration sensor 12 is mounted on the tree τ via the belt 30 such that the upper surface 12A (see FIG. 2) is in close contact with the surface of the tree τ. The side surface 12B (see FIG. 2) may be attached so as to be in close contact with the surface of the tree τ.

Underground sound A mainly transmitted through tree τ via roots
(See FIG. 1) is detected by the vibration sensor 12, and a signal voltage V corresponding to the underground sound A is output. And
This signal voltage V is output to the underground sound observation device 14 shown in FIG.

As shown in FIG. 1, the underground sound observation device 14
Has a signal amplifying unit 40, a noise removing unit 42, a level meter 44, and a signal output unit 46. By using a differential amplifier as the signal amplifier 40, the influence of noise can be reduced.

When the signal voltage V is supplied from the vibration sensor 12, the signal amplifying unit 40 amplifies the signal voltage V, for example, by a factor of 10 ⁴ and outputs it to the noise removing unit 42.

The signal voltage V from which noise has been removed by the noise removing unit 42 is also supplied to a level meter 44. Then, the level meter 44 displays the value of the signal voltage V. That is, the user can use the level meter 4
By the display of 4, the loudness of the underground sound can be confirmed. In this case, based on the loudness of the underground sound obtained by the level meter 44, the vibration sensor 12
The height position (the position at which the underground sound is relatively high) at which the.

The signal output section 46 outputs the signal voltage V from the noise removing section 42 to the data processing device 16.

The data processing unit 16 includes a signal input unit 50
, A data storage unit 51, a prediction processing unit 52, and a clock unit 5.
3, a display unit 54, an audio output unit 56, and a printing unit 58. The data processing device 16 is actually configured by a general-purpose computer (including a personal computer) including a keyboard, a main body, a display device, an audio output device, an external storage device such as a hard disk, and the like. The prediction processing unit 52 is substantially
It is constituted by a CPU (Central Processing Unit) (including peripheral devices) in the main body.

The data processing device 16 includes a ROM (Read Only Memory) for storing system programs and application programs, a RAM (Random Access Memory) used for work and the like, and a timer for clocking. , A timer 53 having a calendar / clock function, A
Input / output interface such as a / D converter, D / A converter, etc., and a waveform observation board as a waveform observation signal acquisition / transmission unit for displaying time on the horizontal axis and ground sound on the vertical axis on the display unit Etc. are provided.

The signal input unit 50 takes in the signal voltage V from the signal output unit 46 of the underground sound observing device 14 at predetermined time intervals (for example, continuously takes in the signal voltage V every 10 minutes for 30 seconds). Then, the signal voltage V is digitally converted (A / D converted). The sound pressure level Vd corresponding to the loudness of the A / D converted underground sound is stored in the data storage unit 51 via the prediction processing unit 52. At this time, the data of the sound pressure level Vd is stored in the data storage unit 51 in time series with the address corresponding to the date and time.

In this case, the data storage unit 51 stores the data of the sound pressure level Vd for one day, five days, or one month which is continuously taken in every 10 minutes for 30 seconds.

The prediction processing unit 52 performs a long-term weather prediction process based on the data of the sound pressure level Vd stored in the data storage unit 51. Specifically, the data of the sound pressure level Vd for one day is averaged, or the moving average of the sound pressure data for several days is averaged, and the average values for one month are arranged in chronological order. Based on the long-term weather forecast.
When one month's worth of data has not been stored in the data storage unit 51, the prediction processing unit 52 continuously sends a command to record the signal voltage V to the signal input unit 50.

The data obtained by the prediction processing section 52 and stored in the data storage section 5
1 is supplied to a display unit 54 such as a CRT or a liquid crystal display device, and a printing unit 5 such as a printer.
8 is supplied.

The data of the sound pressure level Vd is converted into a sound signal by the prediction processing unit 52 as necessary. The sound signal is output to the outside as sound (underground sound) through a sound output unit 56 such as a speaker.

Next, the processing method of weather forecast by the long-term weather forecasting apparatus 10 configured as described above will be described in more detail with reference to the flowchart shown in FIG.
Note that the main part of the signal processing in the flowchart is the prediction processing unit 52.

In this case, the vibration sensor 12
Is transmitted from the vibration sensor 12 to the signal voltage V.
It is said. This signal voltage V is transmitted to the underground sound observation device 1 including the signal amplifying unit 40, the noise removing unit 42, and the signal output unit 46.
4, the signal is continuously supplied to a signal input unit 50 constituting the data processing device 16.

The frequency of the signal voltage V continuously supplied to the signal input unit 50 ranges from 16 [Hz] to 1600.
It has a band up to [Hz]. Large amplitude signal voltage V
Is in the range of 30 [Hz] to 700 [H].
z], especially in the frequency range from 30 [Hz] to 200 [Hz].

In a state where the signal voltage V corresponding to the underground sound A is continuously supplied to the signal input unit 50, first, in step S1, the timekeeping unit 53 having a calendar / clock function is used. A trigger signal is sent to the prediction processing unit 52 every 10 minutes based on the date and time.

Next, in step S2, the prediction processing unit 52 sets the received trigger signal based on
It instructs the signal input unit 50 to take in underground sound data for only 30 seconds. According to this command, the signal input unit 50 continuously A / D converts the signal voltage V for 30 seconds,
The data is transferred to the prediction processing unit 52 as data of the sound pressure level Vd which is digital data. The sound pressure level V for 30 seconds
The data d is temporarily stored in the data storage unit 51.

Next, in step S3, the signal input section 50 performs predetermined signal processing on the data of the sound pressure level Vd for 30 seconds once recorded in the data storage section 51, and performs the representative value for 30 seconds. Is determined as the sound pressure level Vd.

The predetermined signal processing means, for example, that the data of the sound pressure level Vd for 30 seconds is subjected to a fast Fourier transform, and a value having the highest power in the obtained frequency spectrum sequence is used as a representative value for the 30 seconds. It is assumed that the sound pressure level is Vd.

Next, in step S4, the data of the sound pressure level Vd as a representative value for the above-mentioned 30 seconds determined in this way is stored in the sound at the date and time (at the time of occurrence of the trigger signal) measured in step S1. The data is determined as the data of the pressure level Vd, and the measured date and time are stored in the data storage unit 51 in association with the address.

In step S5, it is determined whether or not the data of the sound pressure level Vd stored with the measured date and time corresponding to the address is stored for one day (for the current day). If the determination in step S5 is negative and the data of the sound pressure level Vd determined every 10 minutes for one day has not yet been stored in the data storage unit 51, the prediction processing unit 52 The processes in steps S1 to S5 are continued, and the data of the sound pressure level 51 determined every 10 minutes is accumulated in the data storage unit 51.

If data of the determined sound pressure level Vd for one day has been stored in the data storage unit 51, the determination in step S5 becomes affirmative, and the process proceeds to step S6.

In step S6, the prediction processing unit 52
Averaging of data of the determined sound pressure level Vd for the day, for example, arithmetic averaging is performed.

Next, in step S7, the averaged data is stored in the data storage unit 51 as the data of the sound pressure level Vd as the representative value of the day in association with the date and time.

Further, in step S8, it is determined whether or not the data of the sound pressure level Vd as a representative value of the current day has been accumulated for one month. Until the determination in step S8 becomes affirmative, steps S1 to S8 are performed. Is repeated.

When the data of the sound pressure level Vd for one month has been stored, the determination in step S8 is established.

Thereafter, in step 9, a long-term weather forecast is made in the prediction processing section 52 based on the accumulated data of the averaged sound pressure level Vd for one month as a representative value of the day.

FIG. 6 shows a place where the long-term weather forecast was performed using the long-term weather forecasting apparatus 10 of FIG. 1 and a point of temperature observation performed for the purpose of comparing with the long-term weather forecast.

The underground sound measurement and the long-term weather forecast were performed using a tree τ at 3-3-115 Shinmachi, Nagaoka City, Niigata Prefecture. The tree τ on which the vibration sensor 12 for measuring the underground sound is attached is a “fir” tree having a height of about 2.5 m and a trunk diameter of about 5 cm. A was measured. The signal voltage V of the vibration sensor 12 corresponding to the underground sound A is taken into the underground sound observation device 14, and the data processing device 16 performs long-term weather prediction,
That is, the temperature difference was predicted.

On the other hand, the temperature was measured at the Nakanoshima Snow Removal Base of the Ministry of Land, Infrastructure, Transport and Tourism in Nakanoshima Town, Niigata Prefecture, at a distance of 5.9 km in a linear distance from the location of the underground sound.

Since the underground sound A and the temperature measurement location are both located in the plain, it is considered that the geographical factor has almost no influence on the long-term weather forecast.

FIGS. 7A to 7D show the concept of long-term weather prediction according to this embodiment.

FIG. 7A shows a time-series arrangement of one month's worth of sound pressure level Vd (this month is defined as X month) processed by the data processing device 16 (refer to a black circle in FIG. 7A). Show. Here, the sound pressure level Vd refers to the data storage unit 5.
1 is obtained by averaging the data of the sound pressure level Vd for one day stored in No. 1. In the graph of FIG. 7A showing the change in the sound pressure level Vd, the direction in which the sound pressure level Vd on the vertical axis increases, in other words, the direction in which the amplitude of the sound pressure level Vd increases, is from the upper side to the lower side. is there.

FIG. 7B shows the sound pressure level V for one day in FIG. 7A.
The moving average of d is calculated, and the change in the sound pressure level Vd is represented by an approximate curve Ca (measured curve Ca or measured waveform Ca). Hereinafter, a curve is also considered as a waveform for convenience of understanding.

Here, the moving average is an average of several days including the day of measurement. For example, if the moving average is three days, ((Vd of the day before measurement) + (Vd of the day of measurement) +
(Vd on the day after measurement)) / 3. Therefore, the graph of FIG. 7B shows a change in the sound pressure level Vd as an approximate curve as a result of applying an interpolation method based on polynomial approximation to the moving average. The reason for using the moving average is to average sudden changes in the underground sound A.
Of course, the prediction can be performed without performing the moving average. Further, the period of the moving average is not limited to three days, but may be two to several days. It goes without saying that other averaging methods can be used.

Next, FIG. 7C shows a long-term weather forecast curve Cb three months after the underground sound measurement month X ((X + 3) months). In this case, an approximate curve of the sound pressure level Vd shown in FIG. 7B is used. A certain measurement curve Ca is directly used as a weather forecast for (X + 3) months. Here, the sound pressure level V of the current month, ie, month X,
The greater the amplitude of d, the colder the climate after (X + 3) months, while the smaller the amplitude of the sound pressure level Vd, the warmer the climate. That is, the predicted curve C three months later is different from the measured curve Ca (FIG. 7B) obtained based on the sound pressure level Vd obtained by measuring the underground sound A in month X.
b (FIG. 7C) has a so-called in-phase waveform relationship in terms of electric signals.

More specifically, FIG. 7B and FIG.
In C, a relatively large underground sound was measured corresponding to the magnitude of the sound pressure level Vd of the underground sound A measured on a certain day of the month X (the current day, for example, X month 2). Three months after the day, that is, the response ((X + 3) month 2) of the day ((X + 3) month 2) is a cold day, while the day on which relatively small underground sound is measured (for example, month X 4
It can be predicted that it will be a warm day after three months from the day), that is, in the vicinity of the fourth day, which is the response day of the (X + 3) month.

Next, FIG. 7D shows a long-term weather forecast curve Cc three months after the prediction of FIG. 7C, that is, six months after the ground sound measurement month X ((X + 6) months). In this case, the average value of the measurement curve Ca for month X is defined as the reference level, and the level is inverted axially symmetrically to obtain the predicted curve Cc shown as the waveform in FIG. 7D.
Is obtained. The reference level is a value corresponding to the monthly average temperature in month X when the underground sound A was measured.

That is, in the weather forecast for the month X shown in FIG. 7B and the month (X + 6) shown in FIG. 7D, unlike the weather forecast for the month (X + 3), the sound pressure level Vd of the underground sound A in month X is different. If the amplitude is larger, it is determined that the climate is warmer, while if the amplitude of the sound pressure level Vd is smaller, it is determined that the climate is colder. In other words, with respect to the measurement curve Ca (FIG. 7B) obtained based on the sound pressure level Vd of the underground sound A measured in month X, the prediction curve Cc (FIG. 7D) after 6 months is considered as an electric signal. In this case, a so-called reversed-phase waveform relationship is obtained.

More specifically, FIG. 7B and FIG.
In D, a relatively large underground sound A is measured corresponding to the magnitude of the sound pressure level Vd of the underground sound A measured on a certain day of the month X (the current day, for example, X month 2). Six months after the day, that is, the day's response of (X + 6) month ((X + 6) month 2) is a warm day, while the relatively small ground sound A is measured on the day (for example, X
Six months after the fourth day of the month, that is, in the vicinity of the fourth day, which is the response day of the (X + 6) month, a cold day can be predicted.

If the temperature difference between the beginning of the month and the end of the month is significantly different, for example, if there is a temperature difference of about 5 ° C. or more,
As the reference level, not the average of the approximate curve (corresponding to the monthly average temperature) but the value of the approximate curve at the beginning of the month (corresponding to the temperature at the beginning of the month) and the value of the approximate curve at the end of the month (corresponding to the temperature at the end of the month). Preferably, a straight line is applied. If data has been accumulated for many years, the sound pressure level Vd of the entire month concerned may be arithmetically averaged and used as a reference level.

Next, a specific example of the long-term weather forecast described with reference to FIGS. 7A to 7D will be described.

FIG. 8A is a measurement curve 100 based on the change in the sound pressure level Vd in Nagaoka City, Niigata Prefecture (see FIG. 6) in August 2000, and FIG. 8B is a curve 2000 estimated from the result of the sound pressure level. Curve 102 of the long-term weather forecast in the vicinity of Nagaoka City in November of the year (3 months later), and FIG. 8C shows the temperature of Nakanoshima Snow Removal Base (see FIG. 6) of the Ministry of Land, Infrastructure, Transport and Tourism in the same month (November 2000). The change curve 104 is shown.

As shown in FIG. 8A, the sound pressure level V in August
As for d, the amplitude of the waveform is small at the beginning of the month on some days, but the amplitude tends to increase when viewed as a whole month. That is, from the prediction curve 102 of the long-term weather forecast for November based on the measurement month of August shown in FIG. 8B, it can be expected that the cold weather day will continue to the end of the month in November. A temperature change curve (also referred to as a temperature waveform) 10 in FIG. 8C showing an actual temperature change.
In No. 4, the temperature was close to 10 ° C. at the beginning of the month, but dropped to near 0 ° C. at the end of the month, corresponding to the change of the prediction curve 102. On November 28, the first snowfall was recorded in Niigata Prefecture. Therefore, by utilizing the present invention,
It can be seen that, besides accurate cold and warm predictions, accurate first snow prediction is also possible.

FIG. 9A is a measurement curve 106 based on the change in the sound pressure level Vd in Nagaoka City, Niigata Prefecture (see FIG. 6) in September 2000, and FIG. 9B is predicted from the result of the sound pressure level Vd. The forecast curve 108 of the long-term weather forecast near Nagaoka City in December 2000 (after three months) and FIG. 9C show the temperature of the Nakanoshima Snow Removal Base (see FIG. 6) of the Ministry of Land, Infrastructure, Transport and Tourism in the same month (December 2000). Change curve 110 of
Is shown.

As shown in FIG. 9B, in the case of December, the prediction curve 108 of the long-term weather forecast swings in the cold direction throughout the month. That is, in the climate of December based on the measurement month of September, it can be expected that a cold weather day will continue until the end of the month.
Temperature change curve 110 in FIG. 9C showing actual temperature change
Corresponding to the change in the prediction curve 108,
The temperature remained at ℃ and dropped to below freezing at the end of the month. On December 26, we recorded a deep snowfall in the plains of Niigata Prefecture. Therefore, by utilizing the present invention,
In addition to the accurate prediction of the temperature, it is also possible to accurately predict the deep snow.

FIG. 10A is a measurement curve 112 based on a change in the sound pressure level Vd in Nagaoka City, Niigata Prefecture (see FIG. 6) in October 2000, and FIG.
prediction curve 114 of the long-term weather forecast near the Nagaoka city in January 2001 (three months later) predicted from the result of d,
And FIG. 10C shows the temperature change curve 1 of Nakanoshima Snow Removal Base (see FIG. 6) of the Ministry of Land, Infrastructure, Transport and Tourism in the same month (January 2001).
16 is shown.

As shown in FIG. 10B, in the case of January, the forecast curve 114 of the long-term weather forecast swings in the cold direction throughout the month, as in the case of December. In other words, in January climate based on the October measurement month,
Cold weather days are expected to last until the end of the month. The temperature change curve 116 of FIG. 10C showing the actual temperature change is also a continuous temperature below the freezing point from the beginning of the month to the end of the month, corresponding to the change of the prediction curve 114.

FIG. 11A shows a measurement curve 118 based on a change in the sound pressure level Vd in Nagaoka City, Niigata Prefecture (see FIG. 6) in August 2000, and FIG. 11B shows the sound pressure level Vd.
FIG. 11C shows the forecast curve 120 of the long-term weather forecast in the vicinity of Nagaoka city in February 2001 (after 6 months), and FIG. 11C shows the Nakanoshima snow removal base in the same month (February 2001). Temperature change curve 12 of FIG. 6)
2 is shown.

As shown in FIG. 11B, in the case of February, the prediction curve 120 for long-term weather forecast at the beginning of the month swings in the cold direction, but as the month approaches, the prediction curve 120 changes in the warm direction. I have. In other words, in the February climate based on the August measurement month, it can be expected that the cold weather day will continue at the beginning of the month, but the cold will ease at the end of the month. The temperature change curve 122 in FIG. 11C showing the actual temperature change also corresponds to the change in the prediction curve 120, but the subzero temperature continues at the beginning of the month, but rises to around 0 ° C. at the end of the month.

FIG. 12A is a measurement curve 124 based on the change in the sound pressure level Vd in Nagaoka City, Niigata Prefecture (see FIG. 6) in September 2000, and FIG. 12B is the sound pressure level Vd.
The predicted curve 126 of the long-term weather forecast in the vicinity of Nagaoka city in March 2001 (after six months) predicted from the results of FIG. 12 and FIG. 12C show the Nakanoshima snow removal base of the Ministry of Land, Infrastructure, Transport and Tourism of the same month (March 2001) ( Temperature change curve 12 of FIG. 6)
8 is shown.

As shown in FIG. 12B, in the case of March, the prediction curve 126 of the long-term weather forecast only moves near the center of the graph throughout the month. In other words, the climate in March based on the measurement month in September is different from the prediction in January and February, and it can be expected that a warm climate day will continue throughout the month. The temperature change curve 128 in FIG. 12C showing the actual temperature change also corresponds to the change in the prediction curve 126, and the state near 0 ° C. continues from the beginning of the month to the middle of the month. Followed by

The measurement curves of the sound pressure level Vd and the long-term weather prediction curves shown in FIGS. 8A to 12C are displayed on the screen of the display unit 54 shown in FIG.
Is output as a hard copy and can be used.

As described above in detail, according to the above-described embodiment, the weather three months after the measurement month changes in phase with the change characteristic of the measurement month, and further, the measurement three months after that. Based on the knowledge obtained by the inventor of the present application that the weather six months after the month changes in the opposite phase to the characteristics of the measurement month, a long-term weather forecast is performed to measure the underground sound A of the current month. Based on the three or six months ahead weather such as cold and warm,
The effect of dramatically and accurately predicting compared to the prior art can be achieved. The weather 9 months after the measurement month
It can be predicted that the weather changes in the same phase with respect to the change characteristics of the measurement month, and that the weather 12 months after the measurement month changes in the opposite phase to the change characteristics of the measurement month.

[0082]

According to the present invention, it is possible to accurately predict long-term weather such as cold and warm from the current loudness of the underground sound.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a long-term weather prediction device according to an embodiment of the present invention.

FIG. 2 is a partially omitted vertical sectional view of a vibration sensor constituting the long-term weather forecasting apparatus of FIG. 1;

FIG. 3 is a cross-sectional view of the vibration sensor of FIG. 2 taken along line AA.

FIG. 4 is a diagram showing a state where the vibration sensor of FIGS. 2 and 3 is attached to a tree.

FIG. 5 is a flowchart showing a weather forecasting process of the long-term weather forecasting apparatus of FIG. 1;

FIG. 6 is a map showing a place where the underground sound is measured and a place where the temperature is observed.

FIG. 7 is a diagram provided for explaining a long-term weather forecast based on underground sounds, and FIG. 7A is a diagram illustrating an average measurement value of sound pressure levels obtained from underground sounds. FIG. 7B shows
FIG. 7C shows an approximate curve of the average measured value in FIG. 7A, and FIG.
FIG. 7D is a diagram showing a weather forecast curve after six months, and FIG. 7D is a diagram showing a weather forecast curve after six months.

8A is a diagram showing a measurement curve of ground sound measured in August 2000, FIG. 8B is a diagram showing a prediction curve of November 2000 three months later, and FIG. Year 11
It is a figure showing a change curve of the temperature of the moon.

9A is a diagram showing a measurement curve of the underground sound measured in September 2000, FIG. 9B is a diagram showing a prediction curve of December 2000 three months later, and FIG. Year 12
It is a figure showing a change curve of the temperature of the moon.

FIG. 10A is a diagram showing a measurement curve of an underground sound measured in October 2000, and FIG. 10B is a diagram showing two curves after three months.
FIG. 10C shows a prediction curve of January 2001, and FIG.
It is a figure which shows the change curve of the temperature of January, January.

11A is a diagram showing a measurement curve of an underground sound measured in August 2000, and FIG.
FIG. 11C shows a prediction curve of February 2001, and FIG.
It is a figure which shows the change curve of the temperature of February of the year.

FIG. 12A is a diagram showing a measurement curve of an underground sound measured in September 2000, and FIG.
FIG. 12C shows a prediction curve of March 2001, and FIG.
It is a figure which shows the change curve of the temperature of March of the year.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 10 ... Long term weather forecasting device 12 ... Vibration sensor 14 ... Underground sound observation device 16 ... Data processing device 51 ... Data storage unit 52 ... Prediction processing unit 54 ... Display unit 56 ... Sound output unit 58 ... Printing unit τ ... Tree A ... Underground sound Ca: Measurement curve of this month (measurement waveform) Cb: Prediction curve after 3 months Cc: Prediction curve after 6 months V: Signal voltage Vd: Sound pressure level

Claims (6)

[Claims] An underground sound measuring means for measuring an underground sound, and a long-term weather forecasting means for predicting a long-term weather based on a change in the underground sound measured by the underground sound measuring means. A long-term weather forecasting device characterized by having. 2. The long-term weather prediction device according to claim 1, wherein the long-term weather prediction period is a period at least three to six months after the measurement of the underground sound. Characteristic long-term weather forecasting device. 3. The long-term weather forecasting device according to claim 2, wherein said long-term weather forecast is a forecast of cold and warm, and is relatively large underground sound corresponding to the loudness of the underground sound measured on the day. It is predicted to be a cold day near the response day three months after the day on which the sound was measured, while a warm day near the response day three months after the day on which the relatively small underground sound was measured. A long-term weather forecasting device characterized by predicting that the weather will be over. 4. The long-term weather forecasting device according to claim 2, wherein the long-term weather forecast is a forecast of cold and warm, and is relatively large in accordance with the loudness of the underground ground sound measured on the day. In the vicinity of the response day six months after the day on which the underground sound was measured, a warm day is predicted, while on the other hand, near the response day six months after the day on which the relatively small underground sound was measured. A long-term weather forecasting device that predicts a cold day. 5. The long-term weather forecasting device according to claim 3, wherein the loudness of the underground sound measured on the day includes an average value of the loudness of the underground sound of the day continuously measured or the day. A long-term weather forecasting apparatus characterized by a moving average of the loudness of ground sound for several days. 6. A long-term weather forecasting method, comprising: measuring underground sounds; and predicting long-term weather based on changes in underground sounds.