JP4514632B2 - Weather prediction support system - Google Patents
Weather prediction support system Download PDFInfo
- Publication number
- JP4514632B2 JP4514632B2 JP2005093457A JP2005093457A JP4514632B2 JP 4514632 B2 JP4514632 B2 JP 4514632B2 JP 2005093457 A JP2005093457 A JP 2005093457A JP 2005093457 A JP2005093457 A JP 2005093457A JP 4514632 B2 JP4514632 B2 JP 4514632B2
- Authority
- JP
- Japan
- Prior art keywords
- prediction
- weather
- data
- prediction accuracy
- accuracy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000004364 calculation method Methods 0.000 claims description 19
- 238000011156 evaluation Methods 0.000 claims description 16
- 230000008520 organization Effects 0.000 claims description 5
- 238000012937 correction Methods 0.000 description 6
- 238000000034 method Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000001556 precipitation Methods 0.000 description 2
- 230000005855 radiation Effects 0.000 description 2
- 230000000737 periodic effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012876 topography Methods 0.000 description 1
- 230000017260 vegetative to reproductive phase transition of meristem Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Description
本発明は、気象予報士等の個人気象予測者の気象予測の予測精度の改善を支援するための気象予測支援システムに関する。 The present invention relates to a weather prediction support system for supporting improvement of the prediction accuracy of a weather forecast of a personal weather forecaster such as a weather forecaster.
小売業における売上げ予測や、電力事業における電力需要予測のために、翌日から数日間の天候や気温等の短期気象予測が利用されている。このような短期気象予測は、気象庁や民間気象会社等から提供されているが、予測誤差を含んでいる。例えば、小売業では、売上げと天候の関連性が強く、電力事業では、電力需要と気象(気温)の関連性が強いことが知られており、気象予測の予測精度が、小売業における売上げ予測精度や、電力事業における電力需要の予測精度に影響するため、気象予測の精度向上が望まれている。このため、従来は、気象予測の予測誤差には統計的に一定の傾向がみられることから、これに基づいて機械的に補正する等していた。 Short-term weather forecasts such as weather and temperature for the next several days are used for forecasting sales in the retail industry and forecasting power demand in the power business. Such short-term weather forecasts are provided by the Japan Meteorological Agency, private weather companies, etc., but include forecast errors. For example, the retail industry has a strong relationship between sales and weather, and the power business is known to have a strong relationship between power demand and weather (temperature). Since it affects the accuracy and accuracy of power demand prediction in the power business, it is desired to improve the accuracy of weather forecasts. For this reason, conventionally, since there is a statistically constant tendency in the prediction error of weather prediction, mechanical correction is performed based on this tendency.
気象予測を補正する技術には、例えば、一定時間毎に、所定の地域(予測対象場所)における気象の予測値と実績値とを比較して予測誤差を算出し、この予測誤差を初期値とし、その値が所定の誤差収束期間内で段階的に収束するように補正値を設定することで予測値の補正を行う補正方法がある(例えば、特許文献1参照)。 For example, a technique for correcting weather prediction is to calculate a prediction error by comparing the predicted value of the weather in a predetermined area (prediction target location) with the actual value at regular intervals, and use this prediction error as an initial value. There is a correction method for correcting a predicted value by setting a correction value so that the value converges stepwise within a predetermined error convergence period (see, for example, Patent Document 1).
しかし、特許文献1の補正方法は、異なる地域であっても一律に同じ機械的統計処理を施して予測値の補正を行うものであり、地形等、地域特有の気象要因に応じた処理を行えるものではない。更に、地域特有の気象要因は様々であることから、従来は、各地域における個人気象予測者や民間気象会社等が個別に、当該地域における気象予測精度の向上の研究に当たっている。このため、個人気象予測者や民間気象会社等における予測精度は、地域(予測対象場所)毎に異なり、気象予測を利用する事業者は、どの気象予測を利用することが適切であるかを判断することが困難になっている。 However, the correction method of Patent Literature 1 is to perform the same mechanical statistical processing even in different regions to correct the predicted value, and can perform processing according to regional weather factors such as topography. It is not a thing. Furthermore, since there are various regional weather factors, individual weather forecasters, private weather companies, etc. in each region have been individually engaged in research on improving the accuracy of weather prediction in that region. For this reason, the prediction accuracy of individual weather forecasters, private weather companies, etc. varies from region to region (predicted location), and operators that use weather predictions determine which weather prediction is appropriate to use. It has become difficult to do.
本発明は上記の問題点に鑑みてなされたものであり、その目的は、気象予報士等の個人気象予測者や気象予測を行う事業者、及び、気象予測を利用する事業者を支援し、予測精度の向上を図ることができる気象予測支援システムを提供する点にある。 The present invention has been made in view of the above problems, and its purpose is to support personal weather predictors such as weather forecasters and business operators who perform weather forecasts, and business operators that use weather forecasts, The object is to provide a weather prediction support system capable of improving the prediction accuracy.
上記目的を達成するための本発明に係る気象予測支援システムは、複数の投稿者からの予測対象場所と気象要素別の気象予測データと当該予測の根拠としたデータ種別の入力を各別に受け付ける予測データ入力部と、前記予測対象場所と前記気象要素別の気象実績データの入力を各別に受け付ける実績データ入力部と、前記投稿者と前記予測対象場所と前記気象要素別に、前記気象予測データと前記気象実績データに基づいて、前記気象予測データの予測精度と所定の評価期間毎の期間予測精度を算出する予測精度算出部と、前記予測対象場所と前記気象要素と前記評価期間別に、少なくとも前記期間予測精度に基づく所定順位の前記投稿者と前記期間予測精度からなる予測精度情報と、前記データ種別を所定の出力形式で外部に出力する予測精度出力部とを備えてなることを特徴とする。 In order to achieve the above object, the weather prediction support system according to the present invention is a prediction that accepts, from each of a plurality of contributors, a prediction target location, weather prediction data for each weather element, and input of a data type as a basis for the prediction. A data input unit, a result data input unit that accepts input of weather result data for each of the prediction target location and the weather element, the weather prediction data, and the weather prediction data for each of the poster, the prediction target location, and the weather element A prediction accuracy calculation unit that calculates a prediction accuracy of the weather prediction data and a period prediction accuracy for each predetermined evaluation period based on the actual weather data, and at least the period for each prediction target location, the weather element, and the evaluation period and prediction accuracy information and the author of a predetermined order based on the prediction accuracy comprising the period prediction accuracy, pre outputting the data type to the outside in a predetermined output format And characterized in that it comprises a precision output unit.
上記特徴の気象予測支援システムによれば、気象予測データを提供する複数の投稿者夫々について、気象予測データと気象実績データとに基づいて、気象予測データの予測精度と期間予測精度を算出することができる。これによって、予測対象場所別、気象要素別に予測精度の高い投稿者を容易に把握することができる。また、気象予測データと気象実績データとに基づいて気象予測データの予測精度及び期間予測精度を算出するので、全ての投稿者に対し、同じ基準で予測精度を算出することができる。更に、予測精度の高い投稿者の予測技術を共有するように構成すれば、予測精度の向上を図ることが可能になる。 According to the weather prediction support system having the above characteristics, the prediction accuracy and the period prediction accuracy of the weather prediction data are calculated based on the weather prediction data and the weather performance data for each of a plurality of contributors who provide the weather prediction data. Can do. Accordingly, it is possible to easily grasp a poster who has high prediction accuracy for each prediction target place and each weather element. In addition, since the prediction accuracy and the period prediction accuracy of the weather prediction data are calculated based on the weather prediction data and the weather result data, the prediction accuracy can be calculated on the same basis for all posters. Furthermore, if it is configured to share the poster prediction technology with high prediction accuracy, it is possible to improve the prediction accuracy.
尚、気象要素としては、気圧、気温(時刻別気温、日最高気温、日最低気温、日平均気温)、湿度、日射・日照時間、風向・風速(時刻別風速、日平均風速、最大風速、最大瞬間風速)、降水量(降雪量)等が考えられる。 The weather elements include atmospheric pressure, temperature (time-specific temperature, daily maximum temperature, daily minimum temperature, daily average temperature), humidity, solar radiation / sunshine hours, wind direction / wind speed (time-specific wind speed, daily average wind speed, maximum wind speed, Maximum instantaneous wind speed), precipitation (snowfall), etc. are considered.
上記目的を達成するための本発明に係る他の気象予測支援システムは、複数の投稿者からの予測対象場所と気象要素別の気象予測データと当該予測の根拠としたデータ種別の入力を各別に受け付ける予測データ入力部と、前記投稿者と前記予測対象場所と前記気象要素別に、前記気象予測データと気象実績データに基づく前記気象予測データの予測精度の入力を各別に受け付ける予測精度入力部と、前記投稿者と前記予測対象場所と前記気象要素別に、前記気象予測データの予測精度に基づいて所定の評価期間毎の期間予測精度を算出する予測精度算出部と、前記予測対象場所と前記気象要素と前記評価期間別に区分された、少なくとも前記期間予測精度に基づく所定順位の前記投稿者と前記期間予測精度からなる予測精度情報と、前記データ種別を所定の出力形式で外部に出力する予測精度出力部と、を備えてなることを特徴とする。
In order to achieve the above object, another weather prediction support system according to the present invention separately inputs the prediction target location, the weather prediction data for each weather element from a plurality of contributors, and the data type as the basis of the prediction. A prediction data input unit for receiving, a prediction accuracy input unit for receiving input of prediction accuracy of the weather prediction data based on the weather prediction data and the actual weather data for each of the poster, the prediction target location, and the weather element; A prediction accuracy calculation unit that calculates a period prediction accuracy for each predetermined evaluation period based on a prediction accuracy of the weather prediction data for each of the poster, the prediction target location, and the weather element, the prediction target location, and the weather element to have been classified by the evaluation period, the prediction accuracy information at least the period in which the author of a predetermined order based on the prediction accuracy comprising the period prediction accuracy, the data A prediction accuracy output unit for outputting the type externally in a predetermined output format, and characterized in that it comprises a.
上記特徴の気象予測支援システムによれば、気象予測データを提供する複数の投稿者夫々について、気象予測データとその予測精度に基づいて、気象予測データの期間予測精度を算出することができる。これによって、予測対象場所別、気象要素別に予測精度の高い投稿者を容易に把握することができる。また、気象実績データに基づく気象精度を入力するように構成したので、気象精度の算出に係る手間を省力化でき、本発明の構成を簡易にできる。更に、予測精度の高い投稿者の予測技術を共有するように構成すれば、予測精度の向上を図ることが可能になる。 According to the weather prediction support system having the above characteristics, the period prediction accuracy of the weather prediction data can be calculated based on the weather prediction data and the prediction accuracy for each of a plurality of contributors who provide the weather prediction data. Accordingly, it is possible to easily grasp a poster who has high prediction accuracy for each prediction target place and each weather element. Moreover, since it comprised so that the weather precision based on weather performance data might be input, the effort which concerns on calculation of a weather precision can be saved, and the structure of this invention can be simplified. Furthermore, if it is configured to share the poster prediction technology with high prediction accuracy, it is possible to improve the prediction accuracy.
上記何れかの特徴の本発明に係る気象予測支援システムは、前記予測精度出力部が、予め登録された閲覧会員からの閲覧要求に応答して、前記予測精度情報を前記閲覧会員に対して出力することをことを特徴とする。 In the weather prediction support system according to the present invention having any one of the above features, the prediction accuracy output unit outputs the prediction accuracy information to the browsing member in response to a browsing request from a browsing member registered in advance. It is characterized by that.
上記特徴の気象予測支援システムによれば、予め登録された閲覧会員に限定して気象予測データを提供するように構成したので、本発明に係る運用面での利便性及び安全性を確保できる。例えば、閲覧会員から利用料や会費を得ることにより、本発明の運用資金の調達を容易にすることができる。 According to the weather prediction support system having the above characteristics, it is configured to provide weather prediction data limited to browsing members registered in advance. Therefore, it is possible to ensure convenience and safety in terms of operation according to the present invention. For example, by obtaining usage fees and membership fees from browsing members, it is possible to facilitate the procurement of operational funds according to the present invention.
更に、上記何れかの特徴の本発明に係る気象予測支援システムは、予め登録された閲覧会員からの閲覧要求に応答して、前記複数の投稿者の内の前記閲覧会員が指定する投稿者の前記気象予測データを所定の出力形式で前記閲覧会員に対して出力する第1予測データ出力部を備えることを特徴とする。 Further, the weather prediction support system according to the present invention having any one of the above features is configured so that the posting member designated by the browsing member among the plurality of posters in response to a browsing request from a browsing member registered in advance. A first prediction data output unit that outputs the weather prediction data to the browsing member in a predetermined output format is provided.
上記特徴の気象予測支援システムによれば、特定の閲覧会員からの閲覧要求に応答して、複数の投稿者の内の指定する投稿者の気象予測データを出力できる。これによって、閲覧会員は、投稿者の気象予測データを容易に取得することができる。 According to the weather prediction support system having the above characteristics, it is possible to output weather prediction data of a poster designated from among a plurality of posters in response to a browsing request from a specific browsing member. Thereby, the browsing member can easily acquire the weather prediction data of the poster.
また、上記何れかの特徴の本発明に係る気象予測支援システムは、前記投稿者と前記予測対象場所と前記気象要素別に、過去の前記気象予測データを所定の出力形式で外部に出力する第2予測データ出力部を備えることを特徴とする。 In addition, the weather prediction support system according to the present invention having any one of the above features outputs the past weather prediction data to the outside in a predetermined output format for each of the poster, the prediction target location, and the weather element. A prediction data output unit is provided.
上記特徴の気象予測支援システムによれば、投稿者と予測対象場所と気象要素別に、過去の気象予測データを出力できる。これによって、閲覧会員は、過去の気象予測データから投稿者の予測傾向を把握することができ、気象予測データを購入する投稿者を適切に選択することができる。 According to the weather prediction support system having the above features, it is possible to output past weather prediction data for each contributor, prediction target location, and weather element. Thereby, the browsing member can grasp the prediction tendency of the poster from the past weather prediction data, and can appropriately select the poster who purchases the weather prediction data.
更に、また、上記何れかの特徴の本発明に係る気象予測支援システムは、前記投稿者と前記予測対象場所と前記気象要素別に、所定の気象予測機関が発表した標準気象予測データに対する前記気象予測データの予測精度の改善程度を算出する予測精度改善度算出部を備えることを特徴とすることを特徴とする。 Furthermore, the weather prediction support system according to the present invention having any one of the above characteristics is characterized in that the weather prediction with respect to standard weather prediction data published by a predetermined weather prediction organization according to the contributor, the prediction target location, and the weather element. It is characterized by comprising a prediction accuracy improvement degree calculation unit for calculating the improvement degree of the prediction accuracy of data.
上記特徴の気象予測支援システムによれば、改善程度を算出することができるので、投稿者の予測精度の改善に対する意欲を高めることができ、各投稿者の予測精度の向上を図ることができる。 According to the weather prediction support system having the above characteristics, since the degree of improvement can be calculated, it is possible to increase the willingness of the contributor to improve the prediction accuracy, and to improve the prediction accuracy of each contributor.
更に、上記特徴の本発明に係る気象予測支援システムは、前記予測精度の改善程度に基づいて前記投稿者に所定のポイントを付与する改善ポイント付与部を備えることを特徴とすることを特徴とする。 Furthermore, the weather prediction support system according to the present invention having the above-described features is characterized in that it includes an improvement point giving unit that gives a predetermined point to the poster based on the degree of improvement in the prediction accuracy. .
上記特徴の気象予測支援システムによれば、改善ポイントを付与することで、投稿者の予測精度の改善に対する意欲を高めることができ、各投稿者の予測精度の向上を図ることができる。 According to the weather prediction support system having the above characteristics, by giving improvement points, it is possible to increase the willingness of the poster to improve the prediction accuracy, and it is possible to improve the prediction accuracy of each poster.
以下、本発明に係る気象予測支援システム(以下、適宜「本発明システム」と略称する)の実施形態を図面に基づいて説明する。 Embodiments of a weather prediction support system according to the present invention (hereinafter abbreviated as “the present system” as appropriate) will be described below with reference to the drawings.
本発明システムは、コンピュータのハードウェアとそのハードウェア上で実行されるアプリケーションソフトウェアで構成されており、気象予報士等の個人気象予測者の気象予測の予測精度の改善を支援する。 The system of the present invention is composed of computer hardware and application software executed on the hardware, and supports improvement of the prediction accuracy of the weather prediction of a personal weather predictor such as a weather forecaster.
〈第1実施形態〉
本発明システムの第1実施形態について、図1及び図2に基づいて説明する。図1に示すように、本実施形態の本発明システム1は、予測データ入力部11、実績データ入力部12、予測精度算出部13、及び、予測精度出力部14を備えている。更に、本発明システム1は、気象予測データを投稿する投稿者端末2、及び、閲覧会員が使用する閲覧会員端末3から、インターネットやWAN(Wide Area Netwrok)等の通信ネットワーク4を介してアクセス可能に構成されている。
<First Embodiment>
A first embodiment of the system of the present invention will be described with reference to FIGS. As shown in FIG. 1, the system 1 of the present embodiment includes a prediction data input unit 11, a performance data input unit 12, a prediction accuracy calculation unit 13, and a prediction accuracy output unit 14. Further, the system 1 of the present invention can be accessed from a contributor terminal 2 for posting weather forecast data and a browsing member terminal 3 used by browsing members via a communication network 4 such as the Internet or WAN (Wide Area Network). It is configured.
予測データ入力部11は、複数の投稿者からの予測対象場所と気象要素別の気象予測データと当該予測の根拠としたデータ種別の入力を各別に受け付ける。ここでの予測対象場所は、都道府県、市区町村毎、アメダスポイント毎に設定されるが、閲覧会員のニーズに応じて追加可能である。また、気象要素としては、本実施形態では、気温(時刻別気温、日最高気温、日最低気温、日平均気温)、風向・風速(時刻別気温、平均風速、最大風速、最大瞬間風速)等を想定している。気象予測データは、時系列データ、日予測データ、月平均予測データ等からなる。また、データ種別は、予測精度の補正を行った元のデータの出所を示しており、気象庁の気象予報や国交省レーダ、投稿者が独自に観測したデータの場合には気象観測に用いた測定機器等である。 The prediction data input unit 11 receives input of a prediction target location, weather prediction data for each weather element, and a data type as a basis for the prediction from a plurality of contributors. The prediction target place here is set for each prefecture, each municipality, and each AMeDAS point, but can be added according to the browsing member's needs. Further, as weather elements, in this embodiment, temperature (temperature according to time, daily maximum temperature, daily minimum temperature, daily average temperature), wind direction / wind speed (temperature according to time, average wind speed, maximum wind speed, maximum instantaneous wind speed), etc. Is assumed. The weather forecast data includes time series data, daily forecast data, monthly average forecast data, and the like. The data type indicates the source of the original data that has been corrected for the prediction accuracy. In the case of weather forecasts from the Japan Meteorological Agency, the Ministry of Land, Infrastructure, Transport and Tourism, or data originally observed by the contributor, the measurement used for weather observation Equipment.
続いて、予測データ入力部11の処理手順について説明する。予測データ入力部11は、投稿者端末2からの入力要求に応じて、先ず、投稿者端末2の表示部に投稿者の認証を行うための投稿者ID及びパスワードの入力を受け付ける認証ページを表示する。投稿者が認証されると、予測データ入力部11は、気象予測データの入力ページを投稿者端末2の表示部に表示する。この入力ページは、気象予測データを直接入力可能に構成し、且つ、気象予測データを所定の形式で記録したファイルを指定可能に構成してある。投稿者は、直接入力またはファイルの指定の何れかを選択して気象予測データの入力を行う。尚、直接入力が選択され、入力された気象予測データの値に誤りや抜けがある場合、ファイル指定が選択され、指定されたファイルが読み取り可能なファイル形式ではない場合には、予測データ入力部11は、エラーメッセージを出力し、再度、気象予測データの入力を促す。予測データ入力部11は、投稿者端末2から気象予測データが正しく入力されると、当該気象予測データを投稿者と関連付けて記憶する。 Subsequently, a processing procedure of the prediction data input unit 11 will be described. In response to an input request from the poster terminal 2, the prediction data input unit 11 first displays an authentication page that accepts input of a poster ID and password for authenticating the poster on the display unit of the poster terminal 2. To do. When the poster is authenticated, the prediction data input unit 11 displays the weather forecast data input page on the display unit of the poster terminal 2. This input page is configured so that weather forecast data can be directly input, and a file in which weather forecast data is recorded in a predetermined format can be specified. The contributor inputs either weather input data by selecting either direct input or file designation. If direct input is selected and there is an error or omission in the value of the input weather forecast data, the file specification is selected, and if the specified file is not in a readable file format, the forecast data input section 11 outputs an error message and prompts the input of weather forecast data again. When the weather prediction data is correctly input from the poster terminal 2, the prediction data input unit 11 stores the weather prediction data in association with the poster.
実績データ入力部12は、予測対象場所と気象要素別の気象実績データの入力を各別に受け付ける。詳細には、実績データは、定期観測によるものを前提としている。本実施形態では、これらの気象要素の実績データは、気象庁による各地の気象台や測候所、アメダス等による気象観測、生物季節観測等によって得られる実績データだけでなく、投稿者が独自に設置した気圧計、温度計、雨量計、日射日照計、風向風速計等の気象観測装置や気象衛星からの実績データ、河川の水量等を用いても良い。尚、本実施形態では、気象観測等に用いられる気象観測装置等は、気象庁の検定を受けていることを条件としている。本実施形態の実績データ入力部12は、気象庁において観測された実績データについては、自動的に定期的に取得するように構成し、気象庁以外で観測された実績データについては、投稿者からの実績データの入力要求に応じて入力可能に構成してある。 The result data input unit 12 receives input of weather result data for each prediction target place and each weather element. In detail, the performance data is based on periodic observation. In the present embodiment, the actual data of these meteorological elements is not only the actual data obtained by meteorological observations, weather stations by the Japan Meteorological Agency, Amedas, etc. It is also possible to use a meteorological observation device such as a thermometer, a rain gauge, a solar irradiometer, an anemometer, an actual data from a meteorological satellite, a river water amount, or the like. In the present embodiment, the meteorological observation apparatus used for meteorological observation or the like is subject to the certification of the Japan Meteorological Agency. The result data input unit 12 of the present embodiment is configured to automatically and periodically acquire the result data observed at the Japan Meteorological Agency, and the result data from the contributor for the result data observed outside the Japan Meteorological Agency. It is configured to be able to input in response to a data input request.
予測精度算出部13は、投稿者と予測対象場所と気象要素別に、気象予測データと気象実績データに基づいて、気象予測データの予測精度と所定の評価期間毎の期間予測精度を算出する。本実施形態の気象予測データの予測精度は、予測値と実測値との差、予測値の実測値からのずれ(比率)、及び、標準偏差の何れかであり、気象要素毎に、各気象要素の特徴に応じて設定してある。同様に、本実施形態の期間予測精度は、評価期間内における予測値と実績値との差(絶対値)の平均値、評価期間内における予測値の実測値からのずれ(絶対値)の平均値、評価期間内における各平均値の標準偏差の何れかであり、気象要素毎に、気象予測データの予測精度と同じに設定してある。また、期間予測精度の評価期間は任意に設定可能であり、本実施形態では、期間予測精度として、年間予測精度、及び、月間予測精度を算出する。 The prediction accuracy calculation unit 13 calculates the prediction accuracy of the weather prediction data and the period prediction accuracy for each predetermined evaluation period based on the weather prediction data and the actual weather data for each poster, the target location, and the weather element. The prediction accuracy of the weather prediction data of this embodiment is any one of the difference between the predicted value and the actual measurement value, the deviation (ratio) of the predicted value from the actual measurement value, and the standard deviation. It is set according to the feature of the element. Similarly, the period prediction accuracy of the present embodiment is the average value of the difference (absolute value) between the predicted value and the actual value within the evaluation period, and the average of the deviation (absolute value) from the actual measurement value of the predicted value within the evaluation period. It is either the value or the standard deviation of each average value within the evaluation period, and is set to be the same as the prediction accuracy of the weather prediction data for each weather element. Further, the evaluation period of the period prediction accuracy can be arbitrarily set, and in the present embodiment, the annual prediction accuracy and the monthly prediction accuracy are calculated as the period prediction accuracy.
予測精度出力部14は、予測対象場所と気象要素と評価期間別に、少なくとも期間予測精度に基づく所定順位の投稿者と期間予測精度を所定の出力形式で外部に出力する。尚、本実施形態の予測精度出力部14は、予め登録された閲覧会員からの閲覧要求に応答して、予測精度情報を閲覧会員に対して出力するように構成されている。詳細には、予測精度出力部14は、閲覧会員端末3からの気象予測ランキングページの表示要求に応じて、先ず、閲覧会員端末3の表示部に閲覧会員の認証を行うための閲覧会員ID及びパスワードの入力を受け付ける認証ページを表示する。閲覧会員が認証されると、予測精度出力部14は、閲覧会員端末3の表示部に各気象予測ランキングページとリンクされたトップページを表示する。 The prediction accuracy output unit 14 outputs, to a predetermined output format, a predetermined rank of posters and period prediction accuracy based on at least the period prediction accuracy for each prediction target location, weather element, and evaluation period. The prediction accuracy output unit 14 of the present embodiment is configured to output prediction accuracy information to the browsing member in response to a browsing request from a browsing member registered in advance. Specifically, the prediction accuracy output unit 14 first responds to the display request of the weather prediction ranking page from the browsing member terminal 3, and first, the browsing member ID for authenticating the browsing member on the display unit of the browsing member terminal 3 and Display the authentication page that accepts password input. When the browsing member is authenticated, the prediction accuracy output unit 14 displays the top page linked to each weather prediction ranking page on the display unit of the browsing member terminal 3.
ここで、図2は、予測精度出力部14によって出力される気象予測ランキングページの一例を示している。ここでの気象予測ランキングページは、予測対象場所の市周辺における評価期間1ヶ月のランキングを示しており、最高気温、時刻別気温、時刻別風速等夫々について、順位、投稿者名、期間予測精度、及び、データ種別を表示するように構成されている。ここでの予測精度は、予測値と実績値との差で表されており、差の値の小さい投稿者程順位が高くなる。閲覧会員は、閲覧会員端末3から気象予測ランキングページにアクセスすることで、必要とする予測対象場所の気象要素について、予測精度の高い投稿者を容易に見つけることができる。尚、ランキング表示される人数、気象要素等は、閲覧者が任意に設定変更できるように構成しても良い。 Here, FIG. 2 shows an example of a weather prediction ranking page output by the prediction accuracy output unit 14. The weather forecast ranking page here shows the ranking for the month of the evaluation period in the vicinity of the city of the forecast target place. For each of the highest temperature, hourly temperature, hourly wind speed, etc., ranking, contributor name, period prediction accuracy , And the data type is displayed. The prediction accuracy here is represented by the difference between the predicted value and the actual value, and the rank of the contributor with the smaller difference value becomes higher. By accessing the weather prediction ranking page from the browsing member terminal 3, the browsing member can easily find a poster who has high prediction accuracy for the required weather element of the target location. In addition, you may comprise so that a viewer can arbitrarily set and change the number of persons, a weather element, etc. which are displayed by ranking.
尚、本実施形態では、気象要素として、気温及び風速を用いて説明したが、気圧、湿度、日射・日照時間、降水量(降雪量)、開花日・紅葉日等であっても良い。 In the present embodiment, air temperature and wind speed are used as weather elements. However, atmospheric pressure, humidity, solar radiation / sunshine hours, precipitation (falling snowfall), flowering date / autumn day, etc. may be used.
〈第2実施形態〉
次に、本発明システム1の第2実施形態について、図3に基づいて説明する。本実施形態の本発明システム1は、予測データ入力部11、予測精度入力部15、予測精度算出部13、及び、予測精度出力部14とを備えている。尚、予測データ入力部11及び予測精度出力部14の構成は、上記第1実施形態と同様であり、本実施形態ではその説明を割愛する。
Second Embodiment
Next, 2nd Embodiment of this invention system 1 is described based on FIG. The system 1 of the present embodiment of the present embodiment includes a prediction data input unit 11, a prediction accuracy input unit 15, a prediction accuracy calculation unit 13, and a prediction accuracy output unit 14. In addition, the structure of the prediction data input part 11 and the prediction precision output part 14 is the same as that of the said 1st Embodiment, The description is omitted in this embodiment.
予測精度入力部15は、投稿者と予測対象場所と気象要素別に、気象予測データと気象実績データに基づく気象予測データの予測精度の入力を各別に受け付ける。ここでは、気象予測データの予測精度は、投稿者端末2若しくは他の任意のシステム上で求められた予測精度を用いる。例えば、所定の一般的な表計算ソフト等や本発明システム1に適合するように作成されたアプリケーションソフトを用いて算出された気象予測データの予測精度を取得する。更に、本実施形態では、予測精度を適切に比較するために、気象要素毎に予め設定された算出方法を用いて求められた予測精度のみを取得するように構成する。より詳細には、本実施形態では、気温及び風速については、予測精度が実績値との差で表されているものを取得する。 The prediction accuracy input unit 15 receives the input of the prediction accuracy of weather prediction data based on the weather prediction data and the weather result data for each poster, the place to be predicted, and the weather element. Here, the prediction accuracy obtained on the poster terminal 2 or any other system is used as the prediction accuracy of the weather prediction data. For example, the prediction accuracy of the weather prediction data calculated using predetermined general spreadsheet software or application software created so as to be compatible with the system 1 of the present invention is acquired. Furthermore, in this embodiment, in order to appropriately compare the prediction accuracy, only the prediction accuracy obtained using a calculation method set in advance for each weather element is acquired. More specifically, in the present embodiment, for the temperature and wind speed, the prediction accuracy is obtained as a difference from the actual value.
本実施形態の予測精度算出部13は、投稿者と予測対象場所と気象要素別に、気象予測データの予測精度に基づいて所定の評価期間毎の期間予測精度を算出する。本実施形態では、気温及び風速については、予測精度(絶対値)の1年及び1ヶ月での平均値を算出する。 The prediction accuracy calculation unit 13 of the present embodiment calculates the period prediction accuracy for each predetermined evaluation period based on the prediction accuracy of weather prediction data for each poster, prediction target location, and weather element. In the present embodiment, the average value for one year and one month of the prediction accuracy (absolute value) is calculated for the temperature and the wind speed.
尚、本実施形態では、気象予測データの予測精度の算出を行わないので、本発明システム1の構成を簡略化することができる。 In addition, in this embodiment, since the calculation precision of weather prediction data is not performed, the structure of this invention system 1 can be simplified.
〈第3実施形態〉
次に、本発明システム1の第3実施形態について、図4に基づいて説明する。図3に示すように、本実施形態の本発明システム1は、上記第1実施形態の各構成に加え、第1予測データ出力部16、第2予測データ出力部17、予測精度改善度算出部18、及び、改善ポイント付与部19を備えている。尚、予測データ入力部11、実績データ入力部12、及び、予測精度算出部13の構成は上記第1実施形態と同じ構成であることから、本実施形態では説明を割愛する。
<Third Embodiment>
Next, 3rd Embodiment of this invention system 1 is described based on FIG. As shown in FIG. 3, the system 1 of the present embodiment includes a first prediction data output unit 16, a second prediction data output unit 17, a prediction accuracy improvement degree calculation unit in addition to the components of the first embodiment. 18 and an improvement point assigning unit 19. In addition, since the structure of the prediction data input part 11, the performance data input part 12, and the prediction accuracy calculation part 13 is the same structure as the said 1st Embodiment, description is omitted in this embodiment.
第1予測データ出力部16は、予め登録された閲覧会員からの閲覧要求に応答して、複数の投稿者の内の閲覧会員が指定する投稿者の気象予測データを所定の出力形式で閲覧会員に対して出力する。本実施形態の第1予測データ出力部16は、指定した投稿者が複数の気象要素に対する気象予測データを投稿している場合に、投稿者毎に気象要素を指定(一部指定、全指定等)できるように構成し、任意の投稿者の任意の気象要素についての気象予測データを取得できるように構成してある。これによって、閲覧会員は、気象予測ランキングの結果に応じて、必要とする気象予測データを指定して取得することができる。 The first prediction data output unit 16 responds to a browsing request from a browsing member registered in advance, and the weather forecast data of a poster designated by a browsing member among a plurality of posters in a predetermined output format. Output for. The first forecast data output unit 16 of the present embodiment designates a weather element for each poster when the designated poster has posted weather forecast data for a plurality of weather elements (partially designated, all designated, etc.) ) To be able to obtain weather forecast data for any weather element of any contributor. Thereby, the browsing member can designate and acquire necessary weather prediction data according to the result of the weather prediction ranking.
第2予測データ出力部17は、投稿者と予測対象場所と気象要素別に、過去の気象予測データを所定の出力形式で外部に出力する。本実施形態の第2予測データ出力部17は、指定した投稿者が複数の気象要素に対する気象予測データを投稿している場合に、投稿者毎に気象要素を指定(一部指定、全指定等)できるように構成し、任意の投稿者の任意の気象要素についての過去の気象予測データを取得できるように構成してある。より具体的には、気象予測ランキングページの名前を選択することで、表示されている月のこれまでの予測結果を見ることができるように構成してある。 The second prediction data output unit 17 outputs past weather prediction data to the outside in a predetermined output format for each poster, prediction target location, and weather element. The second forecast data output unit 17 of this embodiment designates a weather element for each poster when the designated poster has posted weather forecast data for a plurality of weather elements (partially designated, all designated, etc.) ) So that past weather forecast data for any weather element of any contributor can be obtained. More specifically, by selecting the name of the weather forecast ranking page, it is configured so that the forecast results so far for the displayed month can be viewed.
予測精度改善度算出部18は、投稿者と予測対象場所と気象要素別に、所定の気象予測機関が発表した標準気象予測データに対する気象予測データの予測精度の改善程度を算出する。本実施形態では、所定の気象予測機関は、基準データ(予測の根拠としたデータ種別)を提供した気象予測機関であり、基準データからの改善程度を算出する。 The prediction accuracy improvement degree calculation unit 18 calculates the degree of improvement in the prediction accuracy of the weather prediction data with respect to the standard weather prediction data announced by a predetermined weather prediction organization, for each poster, prediction target location, and weather element. In the present embodiment, the predetermined weather prediction organization is a weather prediction organization that provides reference data (a data type as a basis for prediction), and calculates an improvement degree from the reference data.
改善ポイント付与部19は、予測精度の改善程度に基づいて投稿者に所定のポイントを付与する。本実施形態では、改善程度が大きい程、付与するポイントの値が大きくなるように設定してある。ポイントが大きい投稿者程、標準気象予測データに対し適切な補正手法を有していると考えられ、閲覧会員は、優れた補正手法をもつ投稿者を容易に特定することができることとなる。また、本実施形態では、ポイントに応じた景品の贈呈等を行う。これによって、投稿者の予測精度向上に対する意欲向上を図ることができる。 The improvement point provision part 19 provides a predetermined | prescribed point to a contributor based on the improvement degree of prediction accuracy. In the present embodiment, the value of the point to be given is set so as to increase as the improvement degree increases. The contributor with a larger point is considered to have an appropriate correction method for the standard weather prediction data, and the browsing member can easily identify a contributor who has an excellent correction method. In the present embodiment, gifts are given according to points. As a result, it is possible to improve the willingness of the poster to improve the prediction accuracy.
次に、本発明システム1の別実施形態について説明する。 Next, another embodiment of the system 1 of the present invention will be described.
上記第3実施形態では、上記第1実施形態の本発明システム1に、更に、第1予測データ出力部16、第2予測データ出力部17、予測精度改善度算出部18、及び、改善ポイント付与部19を備える構成としたが、第2実施形態の本発明システム1に、第1予測データ出力部16、第2予測データ出力部17、予測精度改善度算出部18、及び、改善ポイント付与部19を備えるように構成するのも好ましい実施態様である。 In the third embodiment, in addition to the inventive system 1 of the first embodiment, a first prediction data output unit 16, a second prediction data output unit 17, a prediction accuracy improvement degree calculation unit 18, and improvement point assignment The present invention system 1 according to the second embodiment includes a first prediction data output unit 16, a second prediction data output unit 17, a prediction accuracy improvement degree calculation unit 18, and an improvement point giving unit. It is also a preferred embodiment to be provided with 19.
1: 気象予測支援システム
2: 投稿者端末
3: 閲覧会員端末
4: 通信ネットワーク
11: 予測データ入力部
12: 実績データ入力部
13: 予測精度算出部
14: 予測精度出力部
15: 予測精度入力部
16: 第1予測データ出力部
17: 第2予測データ出力部
18: 予測精度改善度算出部
19: 改善ポイント付与部
1: Weather prediction support system 2: Contributor terminal 3: Browsing member terminal 4: Communication network 11: Prediction data input unit 12: Result data input unit 13: Prediction accuracy calculation unit 14: Prediction accuracy output unit 15: Prediction accuracy input unit 16: 1st prediction data output part 17: 2nd prediction data output part 18: Prediction accuracy improvement degree calculation part 19: Improvement point provision part
Claims (7)
前記予測対象場所と前記気象要素別の気象実績データの入力を各別に受け付ける実績データ入力部と、
前記投稿者と前記予測対象場所と前記気象要素別に、前記気象予測データと前記気象実績データに基づいて、前記気象予測データの予測精度と所定の評価期間毎の期間予測精度を算出する予測精度算出部と、
前記予測対象場所と前記気象要素と前記評価期間別に、少なくとも前記期間予測精度に基づく所定順位の前記投稿者と前記期間予測精度からなる予測精度情報と、前記データ種別を所定の出力形式で外部に出力する予測精度出力部と、
を備えてなることを特徴とする気象予測支援システム。 A forecast data input unit that receives input of a forecast type location from a plurality of contributors, weather forecast data for each weather element, and a data type as a basis for the forecast;
A result data input unit that accepts the input of weather result data for each of the prediction target location and the weather element;
Prediction accuracy calculation for calculating a prediction accuracy of the weather prediction data and a period prediction accuracy for each predetermined evaluation period based on the weather prediction data and the weather result data for each of the poster, the prediction target location, and the weather element And
For each of the prediction target location, the meteorological element, and the evaluation period, at least a predetermined rank based on the period prediction accuracy, the prediction accuracy information including the period prediction accuracy, and the data type in a predetermined output format. A prediction accuracy output unit to output,
A weather forecasting support system characterized by comprising:
前記投稿者と前記予測対象場所と前記気象要素別に、前記気象予測データと気象実績データに基づく前記気象予測データの予測精度の入力を各別に受け付ける予測精度入力部と、
前記投稿者と前記予測対象場所と前記気象要素別に、前記気象予測データの予測精度に基づいて所定の評価期間毎の期間予測精度を算出する予測精度算出部と、
前記予測対象場所と前記気象要素と前記評価期間別に区分された、少なくとも前記期間予測精度に基づく所定順位の前記投稿者と前記期間予測精度からなる予測精度情報と、前記データ種別を所定の出力形式で外部に出力する予測精度出力部と、を備えてなることを特徴とする気象予測支援システム。 A forecast data input unit that receives input of a forecast type location from a plurality of contributors, weather forecast data for each weather element, and a data type as a basis for the forecast;
A prediction accuracy input unit that receives input of prediction accuracy of the weather prediction data based on the weather prediction data and the actual weather data for each of the poster, the prediction target location, and the weather element;
A prediction accuracy calculation unit that calculates a period prediction accuracy for each predetermined evaluation period based on the prediction accuracy of the weather prediction data for each of the poster, the prediction target location, and the weather element;
Prediction accuracy information consisting of the poster and the period prediction accuracy based on at least the period prediction accuracy, divided into the prediction target location, the weather element, and the evaluation period, and the data type as a predetermined output format A weather prediction support system comprising: a prediction accuracy output unit for outputting to outside.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2005093457A JP4514632B2 (en) | 2005-03-29 | 2005-03-29 | Weather prediction support system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP2005093457A JP4514632B2 (en) | 2005-03-29 | 2005-03-29 | Weather prediction support system |
Publications (2)
Publication Number | Publication Date |
---|---|
JP2006275674A JP2006275674A (en) | 2006-10-12 |
JP4514632B2 true JP4514632B2 (en) | 2010-07-28 |
Family
ID=37210602
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP2005093457A Expired - Fee Related JP4514632B2 (en) | 2005-03-29 | 2005-03-29 | Weather prediction support system |
Country Status (1)
Country | Link |
---|---|
JP (1) | JP4514632B2 (en) |
Families Citing this family (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2009243906A (en) * | 2008-03-28 | 2009-10-22 | Panasonic Electric Works Co Ltd | Environmental information collection system |
JP6179237B2 (en) * | 2013-07-22 | 2017-08-16 | 富士通株式会社 | Power consumption prediction system, method, and program |
JP7497482B1 (en) | 2023-01-13 | 2024-06-10 | 株式会社東芝 | Weather control device and weather control system |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH08194070A (en) * | 1995-01-17 | 1996-07-30 | Tokyo Electric Power Co Inc:The | Transmission wire damage-by-snow alarming system and damage-by-snow determining apparatus |
JPH0921884A (en) * | 1995-07-04 | 1997-01-21 | Nippon Telegr & Teleph Corp <Ntt> | Hybrid meteorological forecast device |
JPH1021312A (en) * | 1996-07-05 | 1998-01-23 | Kazuhiko Sato | System and device for operating weather forecast competition |
JPH10268065A (en) * | 1997-03-24 | 1998-10-09 | Nippon Hoso Kyokai <Nhk> | Rainfall prediction method and rainfall decrease alert device |
JP2002099701A (en) * | 2000-09-25 | 2002-04-05 | Pro House:Kk | Sample providing system |
JP2002328177A (en) * | 2001-05-02 | 2002-11-15 | Digicool:Kk | Meteorological information providing system |
JP2004053520A (en) * | 2002-07-23 | 2004-02-19 | Bellsystem 24 Inc | Cenesthetic information notification system of meteorological information |
JP2005030988A (en) * | 2003-07-09 | 2005-02-03 | East Japan Railway Co | Wind speed predicting system and wind speed prediction method |
-
2005
- 2005-03-29 JP JP2005093457A patent/JP4514632B2/en not_active Expired - Fee Related
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH08194070A (en) * | 1995-01-17 | 1996-07-30 | Tokyo Electric Power Co Inc:The | Transmission wire damage-by-snow alarming system and damage-by-snow determining apparatus |
JPH0921884A (en) * | 1995-07-04 | 1997-01-21 | Nippon Telegr & Teleph Corp <Ntt> | Hybrid meteorological forecast device |
JPH1021312A (en) * | 1996-07-05 | 1998-01-23 | Kazuhiko Sato | System and device for operating weather forecast competition |
JPH10268065A (en) * | 1997-03-24 | 1998-10-09 | Nippon Hoso Kyokai <Nhk> | Rainfall prediction method and rainfall decrease alert device |
JP2002099701A (en) * | 2000-09-25 | 2002-04-05 | Pro House:Kk | Sample providing system |
JP2002328177A (en) * | 2001-05-02 | 2002-11-15 | Digicool:Kk | Meteorological information providing system |
JP2004053520A (en) * | 2002-07-23 | 2004-02-19 | Bellsystem 24 Inc | Cenesthetic information notification system of meteorological information |
JP2005030988A (en) * | 2003-07-09 | 2005-02-03 | East Japan Railway Co | Wind speed predicting system and wind speed prediction method |
Also Published As
Publication number | Publication date |
---|---|
JP2006275674A (en) | 2006-10-12 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Berg et al. | Strong increase in convective precipitation in response to higher temperatures | |
US6535817B1 (en) | Methods, systems and computer program products for generating weather forecasts from a multi-model superensemble | |
US7792664B1 (en) | Weather model predictor | |
Ewing et al. | Twister! Employment responses to the 3 May 1999 Oklahoma city tornado | |
Spangler et al. | Wet-bulb globe temperature, universal thermal climate index, and other heat metrics for US Counties, 2000–2020 | |
KR20070038058A (en) | Weather forecasting method and system with atypical grid | |
US20210026039A1 (en) | System and method for forecasting snowfall probability distributions | |
Liu et al. | Spatial and temporal variation characteristics of heatwaves in recent decades over China | |
Wu et al. | Building asset value mapping in support of flood risk assessments: A case study of Shanghai, China | |
Contreras et al. | Seasonal climate forecast skill assessment for the management of water resources in a run of river hydropower system in the Poqueira River (Southern Spain) | |
Babu et al. | Comparison of bridge live loads in US and Europe | |
JP4514632B2 (en) | Weather prediction support system | |
Brabec et al. | Tailored vs black-box models for forecasting hourly average solar irradiance | |
Jara et al. | Snow processes and climate sensitivity in an Arid Mountain Region, Northern Chile | |
Peinó et al. | Performance assessment of GPM IMERG products at different time resolutions, climatic areas and topographic conditions in Catalonia | |
Wu et al. | Revealing microclimate around buildings with long-term monitoring through the neural network algorithms | |
Miller et al. | NOAA’s national water level observation network (NWLON) | |
Evins et al. | The impact of local variations in a temperate maritime climate on building energy use | |
Ustrnul et al. | Climatologically based warning system against meteorological hazards and weather extremes: the example for Poland | |
van Vuuren et al. | Validation of a Simulation-Based Pre-Assessment Process for Solar Photovoltaic Technology Implemented on Rooftops of South African Shopping Centres | |
Ostermöller et al. | Downscaling and evaluation of seasonal climate data for the european power sector | |
Luna Carlosama et al. | Potential of photovoltaic generation in the putumayo department of Colombia | |
Arévalo et al. | Sensitivity of Simulated Conditions to Different Parameterization Choices Over Complex Terrain in Central Chile | |
Taylor et al. | Upper-level winds over southern Ontario: O-QNet wind profiler and NARR comparisons | |
Woldegebrael et al. | Development and Evaluation of a Web-Based and Interactive Flood Management Tool for Awash and Omo-Gibe Basins, Ethiopia |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
A621 | Written request for application examination |
Free format text: JAPANESE INTERMEDIATE CODE: A621 Effective date: 20071225 |
|
A977 | Report on retrieval |
Free format text: JAPANESE INTERMEDIATE CODE: A971007 Effective date: 20091224 |
|
A131 | Notification of reasons for refusal |
Free format text: JAPANESE INTERMEDIATE CODE: A131 Effective date: 20100112 |
|
A521 | Request for written amendment filed |
Free format text: JAPANESE INTERMEDIATE CODE: A523 Effective date: 20100226 |
|
TRDD | Decision of grant or rejection written | ||
A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 Effective date: 20100511 |
|
A01 | Written decision to grant a patent or to grant a registration (utility model) |
Free format text: JAPANESE INTERMEDIATE CODE: A01 |
|
A61 | First payment of annual fees (during grant procedure) |
Free format text: JAPANESE INTERMEDIATE CODE: A61 Effective date: 20100511 |
|
R150 | Certificate of patent or registration of utility model |
Free format text: JAPANESE INTERMEDIATE CODE: R150 |
|
FPAY | Renewal fee payment (event date is renewal date of database) |
Free format text: PAYMENT UNTIL: 20130521 Year of fee payment: 3 |
|
FPAY | Renewal fee payment (event date is renewal date of database) |
Free format text: PAYMENT UNTIL: 20130521 Year of fee payment: 3 |
|
LAPS | Cancellation because of no payment of annual fees |