JP4586171B2 - Temperature estimation method and temperature estimation system - Google Patents
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Description
本発明は、近隣の気象観測地点における気象観測データに基づいて気温を推定する方法及びシステムに関するものである。 The present invention relates to a method and system for estimating temperature based on meteorological observation data at nearby meteorological observation points.
気温は、農業、土木、建築、環境といった様々な産業において、非常に大きな影響力を及ぼす重要な気象要素である。特に、農業生産における気温の影響は大きく、作物の生育段階や収穫量の予測、栽培施設内の環境調節などにあたり気温は不可欠な情報である。現在、日本気象協会や民間企業、自治体などが気象情報の提供を行っている。 Air temperature is an important weather factor that has a great influence on various industries such as agriculture, civil engineering, architecture, and environment. In particular, the influence of temperature on agricultural production is large, and temperature is indispensable information for predicting the growth stage and yield of crops and adjusting the environment in cultivation facilities. Currently, the Japan Weather Association, private companies, and local governments provide weather information.
一方で、ある注目地点における気温をその近隣の気象観測地点における気象観測データから推定することが試みられている。例えば、非特許文献１には、風速を変数として気温の地点間差から注目地点における気温を推定する方法が提案されている。非特許文献２には、距離による重み付けで温位を内挿することにより山間部の気温分布を推定する方法が提案されている。非特許文献３には、簡易定点観測装置による気象観測データを目的変数とし、標高や河川からの距離を説明変数として、重回帰モデルにより年平均気温を推定する方法が提案されている。
On the other hand, it has been attempted to estimate the temperature at a certain point of interest from the meteorological observation data at a nearby weather point. For example, Non-Patent
日本においては、注目地点を含むメッシュの周辺のアメダス（Automated Meteorological Data Acquisition System）観測データと１ｋｍメッシュ平年値データとの気温差を距離による重み付けにより内挿し、アメダス観測データに対応した１ｋｍメッシュの気温を推定する方法が開発されている。また、特許文献１には、過去数日の気温データと気象予報データとから、翌日又は当日の各時刻の気温を予測する方法が記載されている。さらに、特許文献２には、現在の気象観測データに対して過去の気象情報に基づく気象変化度を加味することにより将来気象を予測する方法が記載されている。
In Japan, the temperature difference between the AMeDAS (Automated Meteorological Data Acquisition System) observation data around the mesh including the point of interest and the 1 km mesh normal value data is interpolated by weighting the distance, and the 1 km mesh temperature corresponding to the AMeDAS observation data is interpolated. A method has been developed for estimating.
上記したような気象予測に必要な気象観測データは、日本気象協会や民間企業、自治体などにより提供されており、５００ｍ〜数ｋｍメッシュ程度の解像度で気温等の観測データが利用できるようになっている。 The meteorological observation data necessary for the weather forecast as described above is provided by the Japan Meteorological Association, private companies, local governments, etc., and observation data such as temperature can be used at a resolution of about 500m to several km mesh. Yes.
しかしながら、国土の約７割を中山間地域が占める日本においては、１ｋｍメッシュ内に３００ｍ以上もの標高差を有する地域もあり、そのような地域の各地点の実際の気温を推定するのには現在提供されている気象観測データでは解像度が十分ではない。また、風速等の気象要素を実際に観測することなく現在利用可能な気象観測データのみに基づいて、数十ｍメッシュ程度の解像度で気温を推定する技術は確立されていない。 However, in Japan, where the mountainous area accounts for about 70% of the country, there are areas with an altitude difference of more than 300m within a 1km mesh, and it is currently possible to estimate the actual temperature at each point in such an area. The resolution of meteorological observation data provided is not sufficient. In addition, a technique for estimating temperature with a resolution of about several tens of meters based on only currently available weather observation data without actually observing weather factors such as wind speed has not been established.
本発明は、このような実情に鑑みてなされたものであり、現在利用可能な気象観測データに基づいて、数十ｍメッシュ程度の解像度で気温推定を行うことができる方法及びシステムを提供しようとするものである。 The present invention has been made in view of such circumstances, and intends to provide a method and system capable of estimating temperature with a resolution of about several tens of meters based on currently available weather observation data. To do.
上記解決課題に鑑みて鋭意研究の結果、本発明者は、気温の地点間差が地理的要因と気象要因とから生じることに着目し、注目地点の近隣の気象観測データに対してそれぞれの要因による影響を加味することにより、注目地点の気温を推定する方法に想到した。また、山間地域では気温分布が標高（気圧）の影響を強く受けることを考慮し、気象観測地点と注目地点との気温差そのものを推定するよりも、気温を標準気圧（1000hPa）下における温位に変換して推定を行うことにより推定精度を高めることができることを考案した。 As a result of diligent research in view of the above problems, the present inventor paid attention to the fact that the temperature difference between points is caused by geographical factors and meteorological factors. We have come up with a method for estimating the temperature at a point of interest by taking into account the effects of. Considering the fact that the temperature distribution is strongly affected by altitude (atmospheric pressure) in mountainous areas, rather than estimating the temperature difference between the meteorological observation point and the point of interest, the temperature is below the standard atmospheric pressure (1000 hPa). It was devised that the estimation accuracy can be increased by performing the estimation by converting to.
以下、本発明による気温推定について説明する。
（１）注目地点の温位Ｔｐは、気象観測地点における温位Ｔｓｐと両地点間の温位差ΔＴｐとから、次式のようにして求められる。
Ｔｐ＝Ｔｓｐ＋ΔＴｐ
Hereinafter, temperature estimation according to the present invention will be described.
(1) The temperature level Tp at the point of interest is obtained from the temperature level Tsp at the weather observation point and the temperature level difference ΔTp between the two points as follows.
Tp = Tsp + ΔTp
上記したように、温位差ΔＴｐは、気象要因による温位差ΔＴＰＷと地理的要因による温位差ΔＴＰＧとに分離できるものと考える。
ΔＴｐ＝ΔＴＰＷ＋ΔＴＰＧ
As described above, the temperature difference ΔTp can be separated into the temperature difference ΔTPW due to weather factors and the temperature difference ΔTPG due to geographical factors.
ΔTp = ΔTPW + ΔTPG
（２）ここで、気象要因による温位差ΔＴＰＷは、放射冷却の強度を用いて求めることができる。本手法で用いる”放射冷却の強度”とは、高層気象台のレーウインゾンデ観測で観測される地上面と1000hpa面との温位差（1000hpa温位−地上面温位）の値である。この値が大きいほど、逆転層が発達しており放射冷却の強度が強いと考えられる。但し、放射冷却の強度が直接得られない場合には、日照率、気温の日較差、夜間風速、降水量といった気象観測データを説明変数とする重回帰分析によりΔＴＰＷの値を求めることもできる。例えば、下記のような重回帰式を利用することができる。
ΔＴＰＷ＝α×日照率＋β×日較差＋γ×夜間風速＋δ
（α，β，γ，δは定数）
(2) Here, the temperature difference ΔTPW due to weather factors can be obtained using the intensity of radiation cooling. The “radiant cooling intensity” used in this method is the value of the temperature difference between the ground surface and the 1000 hpa surface (1000 hpa temperature-surface temperature) observed by the lay insonde observation of the high-rise meteorological observatory. It is considered that the larger this value, the stronger the inversion layer is developed and the strength of radiative cooling. However, if the intensity of radiant cooling cannot be obtained directly, the value of ΔTPW can also be obtained by multiple regression analysis using meteorological observation data such as sunshine rate, daily temperature difference, nighttime wind speed, and precipitation as explanatory variables. For example, the following multiple regression equation can be used.
ΔTPW = α × Sunlight rate + β × Day range + γ × Night wind speed + δ
(Α, β, γ, and δ are constants)
（３）一方、地理的要因による温位差ΔＴＰＧは、過去に観測された日毎の注目地点と基準地点との温位差を月平均した値として、次式から求められる。 (3) On the other hand, the temperature difference ΔTPG due to geographical factors is obtained from the following equation as a monthly average value of the temperature difference between the observed point and the reference point for each day observed in the past.
上式中、ＤＡＹは観測日の総日数、ΔＴｐｄはｄ日目における注目地点と基準地点との温位差、[Ｔｐｄ]はｄ日目における基準地点と全地点との温位差の平均値である。
尚、ΔＴＰＧは、放射冷却の強度を用いて次式から求めることも可能である。
ΔＴＰＧ＝λ×ＲＣｉｎｄｅｘ＋μ
（λ，μは定数）
In the above formula, the total number of days DAY observation date, potential temperature difference between the target point and the reference point in ΔTp d is d-th day, [Tp d] is the potential temperature difference between the reference point and the whole point of the d-th day Average value.
ΔTPG can also be obtained from the following equation using the intensity of radiation cooling.
ΔTPG = λ × RCindex + μ
(Λ and μ are constants)
但し、放射冷却の強度を示すＲＣｉｎｄｅｘは次式で与えられる。
ＲＣｉｎｄｅｘ＝α×日照率＋β×日較差＋γ×夜間風速＋δ
（α，β，γ，δは定数）
However, RCindex indicating the intensity of radiant cooling is given by the following equation.
RCindex = α × Sunlight rate + β × Day range + γ × Night wind speed + δ
(Α, β, γ, and δ are constants)
以上説明したように、本発明は、注目地点の近隣にある気象観測地点から、少なくとも気温データを含む気象観測データと、放射冷却強度データと、過去における注目地点と気象観測地点との気温差のデータとを取得し、前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による気温差を推定し、前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による気温差を推定し、前記推定された気象要因による気温差及び地理的要因による気温差とから、注目地点と気象観測地点との間の気温差を決定し、注目地点における気温を推定することを特徴とする気温推定方法を提供するものである。 As described above, according to the present invention, the weather observation data including at least the temperature data, the radiation cooling intensity data, and the temperature difference between the attention point and the weather observation point in the past from the weather observation point in the vicinity of the attention point. Data, and based on the radiation cooling intensity data, estimate a temperature difference due to a weather factor between the point of interest and the weather observation point, and in the data of the temperature difference between the point of interest and the weather observation point in the past Based on the estimated temperature difference due to geographical factors between the point of interest and the meteorological observation point, the temperature difference due to the estimated meteorological factor and the temperature difference due to the geographical factor are used to determine the difference between the point of interest and the meteorological observation point. The temperature estimation method characterized by determining the temperature difference between them and estimating the temperature at a point of interest is provided.
本発明は、また、注目地点の近隣にある気象観測地点から、少なくとも気温データを含む気象観測データと、放射冷却強度データと、過去における注目地点と気象観測地点との気温差のデータとを取得し、前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による温位差を推定し、前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による温位差を推定し、前記推定された気象要因による温位差及び地理的要因による温位差とから、注目地点と気象観測地点との間の温位差を決定し、注目地点における気温を推定することを特徴とする気温推定方法を提供するものである。 The present invention also acquires meteorological observation data including at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and the meteorological observation point in the past from a meteorological observation point in the vicinity of the attention point. Then, based on the radiation cooling intensity data, to estimate the temperature difference due to weather factors between the point of interest and the weather observation point, based on the temperature difference data between the point of interest and the weather observation point in the past, The temperature difference due to the geographical factors between the attention point and the meteorological observation point is estimated, and the difference between the attention point and the meteorological observation point is calculated based on the estimated temperature difference and the temperature difference due to the geographical factor. The temperature estimation method is characterized by determining the temperature difference between the two and estimating the temperature at the point of interest.
本発明の気温推定方法では、前記放射冷却強度データに代えて、日照率、気温の日較差、夜間風速、降水量のうち少なくとも１つを含む気象観測データを説明変数とする重回帰分析により、注目地点と気象観測地点との間の気象要因による気温差又は温位差を推定することもできる。 In the temperature estimation method of the present invention, instead of the radiation cooling intensity data, by multiple regression analysis with weather observation data including at least one of sunshine rate, daily temperature difference, nighttime wind speed, and precipitation as an explanatory variable, It is also possible to estimate a temperature difference or a temperature difference due to meteorological factors between the point of interest and the weather observation point.
本発明の気温推定方法では、前記過去における注目地点と気象観測地点との気温差のデータに代えて、前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の地理的要因による気温差又は温位差を推定することもできる。 In the temperature estimation method of the present invention, instead of data on the temperature difference between the noted point and the weather observation point in the past, based on the radiation cooling intensity data, it depends on the geographical factor between the noticed point and the weather observation point. A temperature difference or a temperature difference can also be estimated.
本発明は、また、注目地点の近隣にある気象観測地点から、少なくとも気温データを含む気象観測データと、放射冷却強度データと、過去における注目地点と気象観測地点との気温差のデータとを取得し蓄積する気象観測データ蓄積データベースと、前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による気温差を推定する第１の推定部と、前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による気温差を推定する第２の推定部と、前記推定された気象要因による気温差及び地理的要因による気温差とから、注目地点と気象観測地点との間の気温差を決定し、注目地点における気温を推定する第３の推定部と、前記推定された注目地点における気温を出力する出力部とを備えた気温推定システムを提供するものである。 The present invention also acquires meteorological observation data including at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and the meteorological observation point in the past from a meteorological observation point in the vicinity of the attention point. A first estimator for estimating a temperature difference due to a weather factor between the point of interest and the meteorological observation point based on the weather observation data accumulation database to be accumulated and the radiation cooling intensity data; and the point of interest in the past A second estimation unit for estimating a temperature difference due to a geographical factor between the point of interest and the meteorological observation point based on temperature difference data from the meteorological observation point; and a temperature difference and a geography due to the estimated meteorological factor A temperature difference between the point of interest and the meteorological observation point is determined from the temperature difference due to the environmental factor, and a third estimation unit for estimating the temperature at the point of interest and the estimated point of interest There is provided a temperature estimation system and an output unit for outputting that temperature.
本発明は、また、注目地点の近隣にある気象観測地点から、少なくとも気温データを含む気象観測データと、放射冷却強度データと、過去における注目地点と気象観測地点との気温差のデータとを取得し蓄積する気象観測データ蓄積データベースと、前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による温位差を推定する第１の推定部と、前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による温位差を推定する第２の推定部と、前記推定された気象要因による温位差及び地理的要因による温位差とから、注目地点と気象観測地点との間の温位差を決定し、注目地点における気温を推定する第３の推定部と、前記推定された注目地点における気温を出力する出力部とを備えた気温推定システムを提供するものである。 The present invention also acquires meteorological observation data including at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and the meteorological observation point in the past from a meteorological observation point in the vicinity of the attention point. A first estimator for estimating a temperature level difference due to a weather factor between the point of interest and the meteorological observation point based on the accumulated weather observation data accumulation database and the radiation cooling intensity data; and the point of interest in the past A second estimation unit for estimating a temperature difference due to a geographical factor between the point of interest and the meteorological observation point based on the temperature difference data between the observation point and the meteorological observation point; A temperature estimation difference between the point of interest and the meteorological observation point is determined from the difference in temperature and the temperature difference due to geographical factors, and a third estimator for estimating the temperature at the point of interest and the estimated point of interest Oh There is provided a temperature estimation system and an output unit for outputting that temperature.
本発明の気温推定システムにおいて、前記第１の推定部は、前記放射冷却強度データに代えて、日照率、気温の日較差、夜間風速、降水量のうち少なくとも１つを含む気象観測データを説明変数とする重回帰分析により、注目地点と気象観測地点との間の気象要因による気温差又は温位差を推定するようにしてもよい。 In the temperature estimation system of the present invention, the first estimation unit describes weather observation data including at least one of a sunshine rate, a daily temperature range difference, a nighttime wind speed, and precipitation instead of the radiation cooling intensity data. You may make it estimate the temperature difference or temperature level difference by a weather factor between an attention point and a weather observation point by the multiple regression analysis made into a variable.
本発明の気温推定システムにおいて、前記第２の推定部は、前記過去における注目地点と気象観測地点との気温差のデータに代えて、前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の地理的要因による気温差又は温位差を推定するようにしてもよい。 In the temperature estimation system of the present invention, the second estimation unit is configured to use the point of interest and the weather observation point based on the radiation cooling intensity data instead of the temperature difference data between the point of interest and the weather observation point in the past. A temperature difference or a temperature difference due to a geographical factor between the two may be estimated.
以上、説明したように、本発明の気温推定方法及び気温推定システムによれば、風速等の気象要素を実際に観測することなく現在利用可能な気象観測データのみに基づいて、数十ｍメッシュ程度の解像度で気温を推定することが可能となる。これにより、地域特有の気象資源を活用した作物立地配置や栽培計画の立案を支援するシステムなどの実用化ができることとなる。また、土木建築分野においては、様々な施設における施工前の詳細な温度環境シミュレーションを行うことが可能となる。 As described above, according to the temperature estimation method and temperature estimation system of the present invention, it is about several tens of meshes based on only weather observation data that is currently available without actually observing weather elements such as wind speed. It is possible to estimate the temperature with a resolution of. As a result, it will be possible to put into practical use a system for supporting crop location arrangement and cultivation plan making use of local weather resources. Further, in the field of civil engineering and architecture, it is possible to perform detailed temperature environment simulations before construction in various facilities.
さらに、国土の約７割を中山間地域が占め、数平方ｋｍの範囲で地点間の気温差が７℃にもなり得る日本においては、地域の多様な温度環境を高精度に把握することにより、これを有効な資源として省エネルギーなどに役立てることが可能である。具体的には、本発明の気温推定方法及び気温推定システムにより、数十ｍメッシュ程度の解像度で気温を推定することができれば、複雑な地形を有する地域においても圃場単位の気象特性を考慮した作物立地配置を行うことにより、凍結防止用や遮光用の農業資材の使用量を削減し、農業施設の環境調節費用を抑えることが可能となる。 Furthermore, in Japan, where the mountainous area occupies about 70% of the country, and the temperature difference between points can be as high as 7 ° C within a range of several square kilometers, it is possible to accurately grasp the various temperature environments in the region. This can be used as an effective resource for energy saving. Specifically, if the temperature can be estimated with a resolution of several tens of meshes by the temperature estimation method and temperature estimation system of the present invention, a crop that takes into account the weather characteristics of each field even in an area having a complicated terrain. By arranging the location, it is possible to reduce the amount of agricultural materials used for preventing freezing and shading, and to reduce environmental adjustment costs for agricultural facilities.
以下、添付図面を参照しながら、本発明の気温推定方法及び気温推定システムを実施するための最良の形態を詳細に説明する。図１〜図２は、本発明の実施の形態を例示する図であり、これらの図において、同一の符号を付した部分は同一物を表わし、基本的な構成及び動作は同様であるものとする。 Hereinafter, the best mode for carrying out the temperature estimation method and the temperature estimation system of the present invention will be described in detail with reference to the accompanying drawings. 1 to 2 are diagrams illustrating embodiments of the present invention. In these drawings, the same reference numerals denote the same components, and the basic configuration and operation are the same. To do.
図１は、本発明による気温推定システムの構成を概略的に示す図である。図１において、気温推定システムはアメダス等の気象観測データを取得し蓄積する気象観測データ蓄積ＤＢと、気象観測地点と注目地点との気象要因による温位差ΔＴＰＷを計算する処理部と、気象観測地点と注目地点との地理的要因による温位差ΔＴＰＧを計算する処理部と、前記２つの処理部による処理結果及び蓄積された気象観測データから注目地点における気温を推定する処理部とから構成されている。 FIG. 1 is a diagram schematically showing a configuration of an air temperature estimation system according to the present invention. In FIG. 1, the temperature estimation system is a meteorological observation data storage DB that acquires and accumulates meteorological observation data such as AMeDAS, a processing unit that calculates a temperature difference ΔTPW due to meteorological factors between a meteorological observation point and a point of interest, and a meteorological observation A processing unit that calculates a temperature difference ΔTPG due to a geographical factor between the point and the point of interest, and a processing unit that estimates the temperature at the point of interest from the processing results of the two processing units and accumulated weather observation data. ing.
気象観測データ蓄積ＤＢには、従来から利用可能である５００ｍ〜数ｋｍメッシュ程度の解像度の気象観測データに加えて、各観測地点における放射冷却強度や日照率、気温の日較差、夜間風速、降水量といった観測データが随時蓄積されている。 The meteorological observation data storage DB includes conventional observational weather observation data with a resolution of about 500m to several km mesh, as well as radiant cooling intensity, sunshine rate, daily temperature difference, nighttime wind speed, precipitation at each observation point. Observed data such as quantity is accumulated from time to time.
ΔＴＰＷ計算部では、気象観測データ蓄積ＤＢから得られる放射冷却強度データ、あるいは日照率、気温の日較差、夜間風速、降水量等のデータに基づいて、気象観測地点と注目地点との間の気象要因による温位差ΔＴＰＷを計算する。 In the ΔTPW calculation unit, the weather between the meteorological observation point and the point of interest is based on the radiation cooling intensity data obtained from the meteorological observation data storage DB, or data such as the sunshine rate, daily temperature difference, nighttime wind speed, and precipitation. The temperature difference ΔTPW due to the factor is calculated.
ΔＴＰＧ計算部では、気象観測データ蓄積ＤＢから得られる注目地点と基準地点との温位差を月平均値（又は旬（十日）平均値、半旬平均値、日平均値を用いてもよい）に基づいて、あるいは放射冷却強度データ等に基づいて、地理的要因による温位差ΔＴＰＧを計算する。 The ΔTPG calculation unit may use a monthly average value (or seasonal (ten-day) average value, half-season average value, and daily average value) for the temperature difference between the reference point and the reference point obtained from the weather observation data storage DB. ) Or based on radiation cooling intensity data or the like, the temperature difference ΔTPG due to geographical factors is calculated.
気温推定処理部では、気象観測データ蓄積ＤＢから得られる気象観測地点における温位Ｔｓｐに対して、ΔＴＰＷ計算部及びΔＴＰＧ計算部の出力結果を足し合わせて得られる温位差ΔＴｐを加味することにより、注目地点の温位Ｔｐを計算し、この注目地点の温位Ｔｐあるいはこれを注目地点の温度に変換した値を気温推定結果として出力する。 The temperature estimation processing unit adds the temperature level difference ΔTp obtained by adding the output results of the ΔTPW calculation unit and the ΔTPG calculation unit to the temperature level Tsp at the weather observation point obtained from the weather observation data storage DB. Then, the temperature Tp of the point of interest is calculated, and the temperature Tp of the point of interest or a value obtained by converting this to the temperature of the point of interest is output as the temperature estimation result.
本発明者らは、実際の気象観測データを用いて本発明による気温推定方法を実施した。２０００年における茨城県のアメダスポイント“つくば”の気象観測データを用いて、その周辺の各アメダスポイント（土浦、筑波山、龍ヶ崎、我孫子、下妻）における１９９１〜１９９９年の月平均温位を推定し、同期間、同アメダスポイントにおける月平均温位の実測値（気温の実測値から換算される）との比較を行った。この結果を図２に示す。 The present inventors performed the temperature estimation method according to the present invention using actual weather observation data. Using the meteorological observation data of the Amedas point “Tsukuba” in Ibaraki Prefecture in 2000, we estimated the monthly average temperature in 1999-1999 at each nearby Amedas point (Tsuchiura, Mt. Tsukuba, Ryugasaki, Abiko, Shimotsuma). During the same period, we compared the monthly average temperature at the same AMeDAS point with the actual temperature (converted from the actual temperature). The result is shown in FIG.
図２の表において、各アメダスポイントにおける月平均温位の推定値と実測値とのＲＭＳＥ（Root Mean Square Error：２乗平均平方誤差）を示している。また、括弧内には、各アメダスポイントにおける月平均温位の実測値を示している。この表から、いずれのアメダスポイントのいずれの月間においても、気温の推定値と実測値とのずれが小さいことが分かる。このように、本発明の気温推定方法では、現在利用可能な５００ｍ〜数ｋｍメッシュ程度の解像度の気象観測データを用いて、かなり高精度に気温推定を行うことが可能となっている。 In the table of FIG. 2, the RMSE (Root Mean Square Error) between the estimated value and the actual measurement value of the monthly average temperature at each AMeDAS point is shown. In parentheses, actual measurement values of monthly average temperature at each AMeDAS point are shown. From this table, it can be seen that the deviation between the estimated value of the temperature and the actually measured value is small in any month of any AMeDAS point. As described above, in the temperature estimation method of the present invention, it is possible to estimate the temperature with considerably high accuracy by using weather observation data having a resolution of about 500 m to several km mesh that is currently available.
また、広島県神石郡神石高原町のアメダスポイント（油木）とその周辺２２地点に設置した気温観測装置における２００４年６〜１２月の気象観測データに基づいて、ΔＴＰＧ及びΔＴＰＷの推定モデルを作成し、この推定モデルを用いて、２００５年１〜４月の各観測地点とアメダスポイントとの間のΔＴＰＧ及び温位差ΔＴＰの月平均値を推定した。これらの推定値と実測値との比較を行った結果を図３及び図４に示す（図中Ｒは推定値と実測値との相関係数を示す）。ΔＴＰＧ、ΔＴＰともに、推定値と実測値との間に大きなずれは生じなかった。 In addition, based on the meteorological observation data from June to December 2004 on the AMeDAS point (oil tree) in Kamiishi Kogen-cho, Kamiishi-gun, Hiroshima and the surrounding 22 points, we created an estimation model for ΔTPG and ΔTPW. Using this estimation model, the monthly average values of ΔTPG and temperature difference ΔTP between each observation point and AMeDAS point in January to April 2005 were estimated. The results of comparison between these estimated values and measured values are shown in FIG. 3 and FIG. 4 (R in the figure indicates a correlation coefficient between the estimated values and the measured values). For both ΔTPG and ΔTP, there was no significant deviation between the estimated value and the actually measured value.
以上、本発明の気温推定方法及び気温推定システムについて、具体的な実施の形態を示して説明したが、本発明はこれらに限定されるものではない。当業者であれば、本発明の要旨を逸脱しない範囲内において、上記各実施形態又は他の実施形態にかかる発明の構成及び機能に様々な変更・改良を加えることが可能である。 As mentioned above, although the specific embodiment was shown and demonstrated about the temperature estimation method and temperature estimation system of this invention, this invention is not limited to these. A person skilled in the art can make various changes and improvements to the configurations and functions of the invention according to the above-described embodiments or other embodiments without departing from the gist of the present invention.
Claims (8)
前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による気温差を推定し、
前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による気温差を推定し、
前記推定された気象要因による気温差及び地理的要因による気温差とから、注目地点と気象観測地点との間の気温差を決定し、注目地点における気温を推定することを特徴とする気温推定方法。 Acquire weather observation data including at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and the weather observation point in the past, from the weather observation point in the vicinity of the attention point,
Based on the radiation cooling intensity data, estimate the temperature difference due to weather factors between the point of interest and the weather observation point,
Based on the temperature difference data between the point of interest and the weather observation point in the past, the temperature difference due to the geographical factor between the point of interest and the weather observation point is estimated,
A temperature estimation method for determining a temperature difference between a point of interest and a meteorological observation point from a temperature difference due to the estimated meteorological factor and a temperature difference due to a geographical factor, and estimating the temperature at the point of interest .
前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による温位差を推定し、
前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による温位差を推定し、
前記推定された気象要因による温位差及び地理的要因による温位差とから、注目地点と気象観測地点との間の温位差を決定し、注目地点における気温を推定することを特徴とする気温推定方法。 Acquire weather observation data including at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and the weather observation point in the past, from the weather observation point in the vicinity of the attention point,
Based on the radiation cooling intensity data, estimate the temperature difference due to weather factors between the point of interest and the weather observation point,
Based on the temperature difference data between the point of interest and the weather observation point in the past, the temperature difference due to the geographical factor between the point of interest and the weather observation point is estimated,
Determining a temperature difference between a point of interest and a meteorological observation point from a temperature difference due to the estimated weather factor and a temperature difference due to a geographical factor, and estimating the temperature at the point of interest Temperature estimation method.
前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による気温差を推定する第１の推定部と、
前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による気温差を推定する第２の推定部と、
前記推定された気象要因による気温差及び地理的要因による気温差とから、注目地点と気象観測地点との間の気温差を決定し、注目地点における気温を推定する第３の推定部と、
前記推定された注目地点における気温を出力する出力部とを備えた気温推定システム。 Meteorological observation data that collects and accumulates weather observation data that includes at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and meteorological observation points in the past from weather observation points in the vicinity of the attention point An accumulation database;
A first estimation unit that estimates a temperature difference due to a weather factor between a point of interest and a weather observation point based on the radiation cooling intensity data;
A second estimation unit for estimating a temperature difference due to a geographical factor between the point of interest and the weather observation point based on data of a temperature difference between the point of interest and the weather observation point in the past;
A third estimation unit for determining a temperature difference between the point of interest and the weather observation point from the temperature difference due to the estimated weather factor and the temperature difference due to a geographical factor, and estimating the temperature at the point of interest;
The temperature estimation system provided with the output part which outputs the temperature in the said estimated point of interest.
前記放射冷却強度データに基づいて、注目地点と気象観測地点との間の気象要因による温位差を推定する第１の推定部と、
前記過去における注目地点と気象観測地点との気温差のデータに基づいて、注目地点と気象観測地点との間の地理的要因による温位差を推定する第２の推定部と、
前記推定された気象要因による温位差及び地理的要因による温位差とから、注目地点と気象観測地点との間の温位差を決定し、注目地点における気温を推定する第３の推定部と、
前記推定された注目地点における気温を出力する出力部とを備えた気温推定システム。 Meteorological observation data that collects and accumulates weather observation data that includes at least temperature data, radiation cooling intensity data, and temperature difference data between the attention point and meteorological observation points in the past from weather observation points in the vicinity of the attention point An accumulation database;
A first estimation unit for estimating a temperature difference due to a weather factor between a point of interest and a weather observation point based on the radiation cooling intensity data;
A second estimation unit for estimating a temperature level difference due to a geographical factor between the point of interest and the meteorological observation point based on the temperature difference data between the point of interest and the meteorological observation point in the past;
A third estimation unit that determines the temperature difference between the point of interest and the meteorological observation point from the estimated temperature difference due to the weather factor and the temperature difference due to the geographical factor, and estimates the temperature at the point of interest. When,
The temperature estimation system provided with the output part which outputs the temperature in the said estimated point of interest.
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