JP4266858B2 - Local heavy rain monitoring system - Google Patents

Local heavy rain monitoring system Download PDF

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JP4266858B2
JP4266858B2 JP2004073155A JP2004073155A JP4266858B2 JP 4266858 B2 JP4266858 B2 JP 4266858B2 JP 2004073155 A JP2004073155 A JP 2004073155A JP 2004073155 A JP2004073155 A JP 2004073155A JP 4266858 B2 JP4266858 B2 JP 4266858B2
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cloud discharge
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健一 星
伸一郎 長山
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    • G—PHYSICS
    • G01—MEASURING; TESTING
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
    • G01S13/951—Radar or analogous systems specially adapted for specific applications for meteorological use ground based
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Description

本発明は、雲を観測することによって降雨を予測するシステムに関し、特に雷雲の雲放電現象を観測して局地的な豪雨を予測するシステムに関する。   The present invention relates to a system for predicting rainfall by observing clouds, and more particularly to a system for predicting local heavy rain by observing a cloud discharge phenomenon of a thundercloud.

従来、雲放電を計測することによって落雷を検知又は予測する方法として、非特許文献１に示されているように、雲放電に伴って発生する電磁波を計測する方法がある。また、雷雲域を観測する方法として、特許文献１に示されているように、レーダエコーの強度を計測する方法がある。   Conventionally, as a method of detecting or predicting a lightning strike by measuring cloud discharge, there is a method of measuring electromagnetic waves generated with cloud discharge as shown in Non-Patent Document 1. Moreover, as a method of observing a thundercloud region, there is a method of measuring the intensity of a radar echo as disclosed in Patent Document 1.

渡辺永作、「新しい雷観測システム」、電気評論、１９９８年７月号、Ｐ．４５−４９Eisaku Watanabe, “New Lightning Observation System”, Electric Review, July 1998, P.I. 45-49

特開平８−１２２４３３号公報JP-A-8-122433

しかし、上述した従来の落雷検知又は予測方法や、雷雲域の観測方法では、局地的な降雨の地点や時間、さらに雨量等を予測することは不可能である。
そこで、本発明は、雷雲の雲放電量及びレーダエコーを計測することによって即時的に雷雲の成長段階を判断し、その成長段階から降雨までの時間を予測すると共に雷雲の位置，移動状況，雨量を予測することを目的とする。 However, the conventional lightning strike detection or prediction method and the thundercloud region observation method described above cannot predict a local rainfall point, time, and rainfall.
Therefore, the present invention immediately determines the thundercloud growth stage by measuring the thundercloud discharge amount and radar echo, predicts the time from the growth stage to the rain, and also determines the thundercloud position, movement status, and rainfall amount. The purpose is to predict.

雲放電によって発生する電磁波を取得することによって雲放電量を検出する雲放電検出手段と、雲の位置を検出するためのレーダエコー検出手段と、前記雲放電検出手段によって取得された雲放電量から雷雲の成長段階を解析して降雨開始までの時間を予測する降雨時間予測手段と、地上雨量計測手段と、前記地上雨量計測手段によって計測した過去の地上雨量データと前記レーダエコー検出手段によって検出したレーダエコーデータと前記雲放電量との比較データの統計に基づいて降雨量を予測する降雨量予測手段と、前記雲放電検出手段と前記レーダエコー検出手段とによって雷雲位置情報を検出する雷雲位置検出手段と、前記降雨時間予測手段による予測降雨時間と前記降雨量予測手段による予測降雨量と前記雷雲位置情報とを地図データに合成する手段と、を有することを特徴とする。 And cloud discharge detection means for detecting the cloud discharge amount by obtaining the electromagnetic waves generated by the cloud discharge, and the radar echo detecting means for detecting the position of the cloud, the cloud discharge quantity obtained by the cloud discharge detecting means Rainfall time prediction means for analyzing the thundercloud growth stage and predicting the time to start rainfall, ground rain measurement means, past ground rain data measured by the ground rain measurement means, and radar radar detection means Rainfall prediction means for predicting rainfall based on statistics of comparison data between radar echo data and cloud discharge, and thundercloud position detection for detecting thundercloud position information by the cloud discharge detection means and the radar echo detection means map means, the predicted rainfall by the prediction rainfall time and the rainfall prediction means according to the rainfall time predicting means and said thundercloud position information de And having means for combining the data, the.

統計的に得られた雷雲の成長サイクルと雲放電量又はレーダエコー強度との関係を基に、降雨開始までの時間及び降雨量を算出することによって局地的豪雨が発生する位置と時間を予測して、正確な局地的豪雨警戒情報を多くの人に通知することができる。   Predict the location and time of local heavy rain by calculating the time to rainfall and the amount of rainfall based on the relationship between the thundercloud growth cycle and cloud discharge or radar echo intensity obtained statistically Thus, accurate local heavy rain warning information can be notified to many people.

次に、本発明の実施の形態について図面を参照して詳細に説明する。
図１は、本発明の一実施の形態を示す構成図である。
図１において、局地的豪雨監視システム４は、雷放電検出部１から雲放電データを、気象レーダ部２からレーダエコーデータ、地上雨量計測部から地上雨量データを収集し、収集した３つのデータを解析して局地的豪雨発生の時間と位置と雨量を予測し、その予測結果をＷＥＢ配信する。 Next, embodiments of the present invention will be described in detail with reference to the drawings.
FIG. 1 is a block diagram showing an embodiment of the present invention.
In FIG. 1, the local heavy rain monitoring system 4 collects cloud discharge data from the lightning discharge detection unit 1, radar echo data from the weather radar unit 2, and ground rainfall data from the ground rainfall measurement unit. To predict the time, position and rainfall of local heavy rain, and distribute the prediction results to the web.

局地的豪雨監視システム４の構成は、雲放電データとレーダエコーデータと地上雨量計データの入力を解析用データとして出力するデータ入出力部５と、解析用データに基づいて局地的豪雨発生までの時間や位置を予測し、その予測値を表示用データとして出力する総合解析部６と、表示用データを編集して局地的豪雨警戒表示し、さらにＷＥＢ表示用データとして出力する局地的豪雨警戒表示部７と、ＷＥＢ表示用データをＷＥＢ配信するＷＥＢサーバ８とから成る。   The configuration of the local heavy rain monitoring system 4 consists of a data input / output unit 5 that outputs the input of cloud discharge data, radar echo data, and ground rain gauge data as analysis data, and a local heavy rain occurrence based on the analysis data. The total analysis unit 6 that predicts the time and position until output, and outputs the predicted value as display data, and the local heavy rain warning display by editing the display data and further outputting as WEB display data The torrential rain warning display unit 7 and a WEB server 8 for WEB distribution of WEB display data.

雷放電検出部１は、複数地点に配置された複数の干渉計やアンテナ等の雲放電検出装置によって計測された放電数（密度）と雲放電発生位置及びその時刻を雲放電データとしてデータ入出力部５へ送信する。ここでの放電数（密度）と放電発生位置の計測方法は、雲放電に伴って発生する電磁波を複数地点で計測し、複数地点から送信されてきた同時刻に計測された同一スペクトルの複数の電磁波データを基に、電磁波の発生地点と放電数（密度）を割り出す方法である。なお、放電数（密度）とは、一定時間内において所定の区域で雲放電に伴って発生する電磁波の計測回数である。例えば、放電数（密度）は１分間当たり１平方ｋｍ内の電磁波の計測回数とする。
気象レーダ部２は、雷雲に対してレーダを発信して戻ってきたレーダエコーデータをデータ入出力部５に送信する。地上雨量計測部３は、地上雨量計データを取得してデータ入出力部５に送信する。 The lightning discharge detector 1 inputs / outputs the number of discharges (density) measured by cloud discharge detectors such as a plurality of interferometers and antennas arranged at a plurality of points, the cloud discharge occurrence position and the time as cloud discharge data. Transmit to part 5. Here, the number of discharges (density) and the method of measuring the discharge occurrence position are measured at a plurality of points for electromagnetic waves generated in association with cloud discharge, and a plurality of the same spectrum measured at the same time transmitted from a plurality of points. In this method, the generation point of electromagnetic waves and the number of discharges (density) are determined based on electromagnetic wave data. Note that the number of discharges (density) is the number of times of electromagnetic waves generated in association with cloud discharge in a predetermined area within a fixed time. For example, the number of discharges (density) is the number of times of electromagnetic wave measurement within 1 square km per minute.
The weather radar unit 2 transmits radar echo data returned from the thundercloud to the data input / output unit 5. The ground rainfall measuring unit 3 acquires the ground rain gauge data and transmits it to the data input / output unit 5.

次に、図２，７，８を参照しながら本発明の動作について説明する。
図２は、本発明の動作を示すシーケンス図である。まず、データ入出力部５にて、雷放電検出部１，気象レーダ部２，地上雨量計測部３からそれぞれ雲放電データ，レーダエコーデータ，地上雨量計データを、計測した時点の時刻データと共に取得する（Ｓ１，Ｓ２，Ｓ３）。３つのデータは、総合解析部６に入力され、３つのデータを基に定期的に局地的豪雨発生の位置と時間の予測と、各地点の降雨量の解析が行われる（Ｓ４）。局地的豪雨警戒表示部７では、総合解析部６で解析された結果を地図上に合成することによって画像編集して図７，８のように表示する（Ｓ５）。ＷＥＢサーバ８では、局地的豪雨警戒表示部７で編集された画像データをＷＥＢデータに変換してＷＥＢ配信を行う（Ｓ６）。 Next, the operation of the present invention will be described with reference to FIGS.
FIG. 2 is a sequence diagram showing the operation of the present invention. First, in the data input / output unit 5, cloud discharge data, radar echo data, and ground rain gauge data are obtained from the lightning discharge detection unit 1, weather radar unit 2, and ground rainfall measurement unit 3, respectively, together with time data at the time of measurement. (S1, S2, S3). The three data are input to the comprehensive analysis unit 6, and the location and time of the occurrence of local heavy rain are regularly estimated based on the three data, and the rainfall amount at each point is analyzed (S4). The local heavy rain warning display unit 7 synthesizes the results analyzed by the comprehensive analysis unit 6 on a map and displays the images as shown in FIGS. 7 and 8 (S5). The WEB server 8 converts the image data edited by the local heavy rain warning display unit 7 into WEB data and performs WEB distribution (S6).

次に図２の局地的豪雨予測処理（Ｓ４）について図３〜６を参照しながら詳細に説明する。ここで、図３は雲放電データ，レーダエコーデータ，地上雨量計データ，各種予測値をプロットした座標図を示し、図４は雷雲の成長サイクルを示し、図５は雲放電の放電数（密度）の時間変化と雷雲の成長段階の関係を示し、図６はレーダエコー強度の時間変化と雷雲の成長段階の関係を示している。   Next, the local heavy rain prediction process (S4) of FIG. 2 will be described in detail with reference to FIGS. 3 shows a coordinate diagram in which cloud discharge data, radar echo data, ground rain gauge data, and various predicted values are plotted, FIG. 4 shows a thundercloud growth cycle, and FIG. 5 shows the number of discharges (density) of cloud discharge. ) And the thundercloud growth stage, and FIG. 6 shows the relation between the time change of the radar echo intensity and the thundercloud growth stage.

まず、気象レーダ部２が取得したレーダエコーデータから得られたエコー強度と雷雲位置を図３のように座標上に時系列にプロットしていく。そして、雷放電検出部１が取得した雲放電の放電数（密度）とその雲放電が発生した位置とを図３のレーダエコーデータがプロットされた座標上に時系列に重ね合わせていく。レーダエコーデータと放電数（密度）を重ね合わせた図３に示す座標上のデータを基に、現在の時刻と以前の時刻の差分から、雲放電データの移動方向と放電数(密度)の変化、レーダエコーデータの移動方向と強さの変化を予測する。   First, the echo intensity and thundercloud position obtained from radar echo data acquired by the weather radar unit 2 are plotted in time series on coordinates as shown in FIG. Then, the number of discharges (density) of the cloud discharge acquired by the lightning discharge detector 1 and the position where the cloud discharge occurred are superimposed on the coordinates on which the radar echo data of FIG. 3 is plotted in time series. Based on the data on the coordinates shown in Fig. 3 where radar echo data and the number of discharges (density) are superimposed, the movement direction of cloud discharge data and the change in the number of discharges (density) from the difference between the current time and the previous time Predict changes in the direction and intensity of radar echo data.

雲放電データは、次に雷雲の成長段階を割り出すために利用する。雷雲の成長サイクルは図４に示すように４段階に分けられる。このような雷雲の成長に応じて雲放電の放電数（密度）が図５のように増加していく。そして、図５のような統計的に得られた放電数（密度）と雷雲の成長段階の相関関係と計測した放電数（密度）を基に、成熟期に到達するまでの時間を算定して降雨開始までの時間を予測する。さらに、放電数（密度）が局地的豪雨の警戒点に達したとき、雲放電データで警戒点に達している時点のレーダエコー強度も、図６に示すレーダエコー強度の局地的豪雨警戒点以上の値であれば、図３の座標上に局地的豪雨警戒情報としてプロットする。 The cloud discharge data is then used to determine the thundercloud growth stage. The thundercloud growth cycle is divided into four stages as shown in FIG. As the thundercloud grows, the number of discharges (density) of the cloud discharge increases as shown in FIG. Then, based on the correlation between the statistically obtained number of discharges (density) as shown in FIG. 5 and the thundercloud growth stage and the measured number of discharges (density), the time to reach maturity is calculated. Predict the time until the start of rainfall. Further, when the number of discharges (density) reaches the warning point for local heavy rain, the radar echo intensity at the time when the warning point is reached in the cloud discharge data is also the local heavy rain warning of the radar echo intensity shown in FIG. If the value is greater than or equal to a point, it is plotted as local heavy rain warning information on the coordinates of FIG.

降雨量は、過去の地上雨量計データとレーダエコーデータのエコー強度及び雲放電データの放電数（密度）との比較データの統計により予測する。地上雨量計データは、レーダエコーデータ及び雲放電データと共に蓄積され、降雨量予測にフィードバックする。   The rainfall is predicted by statistics of comparison data between the past ground rain gauge data and the echo intensity of radar echo data and the number of discharges (density) of cloud discharge data. Ground rain gauge data is stored together with radar echo data and cloud discharge data, and fed back to rainfall prediction.

次に局地的豪雨警戒表示部７の動作（図２の処理Ｓ５）を図７，８を参照しながら詳細に説明する。総合解析部６から入力された座標値と組合わされたエコー強度，放電数（密度），地上雨量計データを、図７に示すように座標値を基に地図上に合成する。このとき夫々のデータはレベルに応じて色分けして表示される。
また、雲放電データとレーダエコーデータを基に予測された各地の降水開始の予測時刻と予測降雨量を図７に示す地図上に表示してもよい。
さらに、雲放電データとレーダエコーデータを基に予測された局地的豪雨警戒情報は、図８に示すよう局地的豪雨警戒区域として表示する。 Next, the operation of the local heavy rain warning display unit 7 (processing S5 in FIG. 2) will be described in detail with reference to FIGS. The echo intensity, the number of discharges (density), and the ground rain gauge data combined with the coordinate value input from the comprehensive analysis unit 6 are synthesized on the map based on the coordinate value as shown in FIG. At this time, each data is displayed in different colors according to the level.
Further, the predicted precipitation start time and predicted rainfall amount in each place predicted based on cloud discharge data and radar echo data may be displayed on the map shown in FIG.
Further, the local heavy rain warning information predicted based on the cloud discharge data and the radar echo data is displayed as a local heavy rain warning area as shown in FIG.

以上のように本発明は、統計的に得られた雷雲の成長サイクルと放電数（密度）又はエコー強度との関係を基に、降雨開始までの時間及び降水量を算出することによって、局地的豪雨が発生する位置と時間を予測して正確な局地的豪雨警戒情報を多くの人に通知することできる。   As described above, the present invention calculates the time until rainfall starts and the amount of precipitation based on the relationship between the thundercloud growth cycle and the number of discharges (density) or echo intensity obtained statistically. It is possible to predict the location and time at which a torrential rain will occur and to notify accurate local torrential rain alert information to many people.

本発明の一実施形態の全体構成図である。1 is an overall configuration diagram of an embodiment of the present invention. 本発明の一実施形態の動作を示したシーケンス図である。It is the sequence diagram which showed the operation | movement of one Embodiment of this invention. 本発明の一実施形態における雲放電データ，レーダエコーデータ，地上雨量計データ，各種予測値を時系列にプロットした座標図である。FIG. 6 is a coordinate diagram in which cloud discharge data, radar echo data, ground rain gauge data, and various predicted values are plotted in time series in an embodiment of the present invention. 雷雲の成長サイクルを示した図である。It is the figure which showed the growth cycle of the thundercloud. 雲放電の放電数（密度）の時間変化と雷雲の成長段階との関係を示した図である。It is the figure which showed the relationship between the time change of the discharge number (density) of cloud discharge, and the growth stage of a thundercloud. レーダエコー強度の時間変化と雷雲の成長段階との関係を示した図である。It is the figure which showed the relationship between the time change of a radar echo intensity | strength, and the growth stage of a thundercloud. 本発明の一実施形態における雲放電データ，レーダエコーデータ，地上雨量計データの分布を示す表示画面の一例である。It is an example of the display screen which shows distribution of the cloud discharge data in one embodiment of this invention, radar echo data, and ground rain gauge data. 本発明の一実施形態における局地的豪雨警戒表示画面の一例である。It is an example of the local heavy rain warning display screen in one Embodiment of this invention.

符号の説明Explanation of symbols

１ 雷放電検出部
２ 気象レーダ部
３ 地上雨量計測部
４ 局地的豪雨監視システム
５ データ入出力部
６ 総合解析部
７ 局地的豪雨警戒表示部
８ ＷＥＢサーバ
DESCRIPTION OF SYMBOLS 1 Lightning discharge detection part 2 Weather radar part 3 Ground rainfall measurement part 4 Local heavy rain monitoring system 5 Data input / output part 6 Comprehensive analysis part 7 Local heavy rain warning display part 8 WEB server

Claims (3)

雲放電によって発生する電磁波を取得することによって雲放電量を検出する雲放電検出手段と、
雲の位置を検出するためのレーダエコー検出手段と、
前記雲放電検出手段によって取得された雲放電量から雷雲の成長段階を解析して降雨開始までの時間を予測する降雨時間予測手段と、
地上雨量計測手段と、
前記地上雨量計測手段によって計測した過去の地上雨量データと前記レーダエコー検出手段によって検出したレーダエコーデータと前記雲放電量との比較データの統計に基づいて降雨量を予測する降雨量予測手段と、
前記雲放電検出手段と前記レーダエコー検出手段とによって雷雲位置情報を検出する雷雲位置検出手段と、
前記降雨時間予測手段による予測降雨時間と前記降雨量予測手段による予測降雨量と前記雷雲位置情報とを地図データに合成する手段と、
を有することを特徴とする局地的豪雨監視システム。 Cloud discharge detecting means for detecting the amount of cloud discharge by acquiring electromagnetic waves generated by cloud discharge;
Radar echo detection means for detecting the position of the cloud;
And rainfall time predicting means for predicting the time to rain start by analyzing the growth stage of the thundercloud from cloud discharge quantity obtained by the cloud discharge detecting means,
Ground rainfall measurement means,
Precipitation prediction means for predicting rainfall based on statistics of comparison data between past ground rainfall data measured by the ground rainfall measurement means, radar echo data detected by the radar echo detection means, and cloud discharge amount;
Thundercloud position detection means for detecting thundercloud position information by the cloud discharge detection means and the radar echo detection means;
Means for synthesizing the predicted rainfall time by the rainfall time prediction means, the predicted rainfall by the rainfall prediction means, and the thundercloud position information into map data;
A local heavy rain monitoring system characterized by comprising: 前記地上雨量計測手段によって取得した地上雨量データを前記地図データに合成する手段を有することを特徴とする請求項１記載の局地的豪雨監視システム。 2. The local heavy rain monitoring system according to claim 1, further comprising means for synthesizing the ground rainfall data acquired by the ground rainfall measuring means with the map data. 前記降雨時間予測手段は、雷雲の成長段階と雲放電量との統計上の相関関係に基づいて、計測された雲放電量から降雨時間を算定することを特徴とする請求項１乃至２何れか記載の局地的豪雨監視システム。 3. The rain time prediction means calculates a rain time from a measured cloud discharge amount based on a statistical correlation between a thundercloud growth stage and a cloud discharge amount . The local heavy rain monitoring system described.
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