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公开(公告)号：KR1020090035066A
公开(公告)日：2009-04-09
申请号：KR1020070100116
申请日：2007-10-05
Applicant: 부산대학교 산학협력단
CPC classification number: G01W1/08 , G01J3/108 , G01J2003/425 , G01W1/02
Abstract: A fog forecasting system using weather satellite and a fog forecasting method thereof are provided to distinguish fog and low-level clouds by calculating Laplacian about luminance temperature distribution of the determined observation region, thereby increasing the accuracy of fog detection. A fog forecasting system using weather satellite comprises a stationary orbit meteorological satellite detecting he intensity of the near infrared ray and infrared ray radiated from the observation region, which is equipped with an observation sensor for the near infrared ray channel and an observation sensor for the infrared channel; a remote-sensing satellite detecting the sea-surface wind speed of the observation region by employing a sea-surface wind detecting sensor; a receiver of satellite signal received with the detected information from the stationary orbit meteorological satellite and remote-sensing satellite; and an analysis equipment presuming the fog generation region, which is equipped with an operator programmed with analysis algorithm and a memory stored with Laplacian boundary value/sea-surface wind speed of boundary value about luminance temperature difference boundary value/luminance temperature distribution.
Abstract translation: 提供一种使用气象卫星的雾预报系统及其雾预报方法，通过对确定的观测区域的亮度温度分布计算拉普拉斯算子来区分雾和低云，从而提高雾度检测的准确性。 使用气象卫星的雾预报系统包括一个固定轨道气象卫星，检测其近距离红外线的强度和从观察区域辐射的红外线，该卫星装备有用于近红外线通道的观测传感器和用于红外线的观测传感器 渠道; 遥感卫星通过采用海面风检测传感器检测观测区域的海面风速; 卫星信号接收机与来自固定轨道气象卫星和遥感卫星的检测信息一起接收; 以及分析设备，假设雾化区域配备有用分析算法编程的操作者和存储有拉普拉斯边界值/边界值的海面风速关于亮度温差边界值/亮度温度分布的存储器。
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公开(公告)号：KR1020120110463A
公开(公告)日：2012-10-10
申请号：KR1020110028338
申请日：2011-03-29
Applicant: 부산대학교 산학협력단
IPC: G01W1/00
Abstract: PURPOSE: A drag coefficient parameterization device and a method for the same are provided to accurately consider a frictional influence on the surface of an ocean in a weather model and a local weather model. CONSTITUTION: A drag coefficient parameterization method includes the following steps: 10 m wind speed from an observing machine to an ocean observing point, roughness length, and Monin-Obukhov length are detected in a weather information detecting part(S301); a weather verifying part verifies a season on the basis of an inputted date(S302); atmospheric stability is verified by calculating and then by inputting the roughness length and the Monin-Obukhov length in a stability verifying part(S304, S305); and a drag coefficient is calculated(S306). [Reference numerals] (AA) Start; (BB) End; (S301) Detecting 10 m wind speed, roughness length, and Monin-Obukhov length; (S302) Verifying seasons on the basis of dates; (S303) Inputting the roughness length and the Monin-Obukhov length; (S304) Calculating the ratio of the roughness length and the Monin-Obukhov length; (S305) Verifying stability on the basis of the calculated ratio; (S306) Calculating drag coefficient by respectively applying different drag coefficient calculating formulas to verified seasons/stabilities
Abstract translation: 目的：提供一种阻力系数参数化装置及其方法，以便在气象模式和当地气象模型中准确考虑对海洋表面的摩擦影响。 构成：拖曳系数参数化方法包括以下步骤：在天气信息检测部分检测从观测机到海洋观测点的10m风速，粗糙度长度和莫尼奥霍霍夫长度（S301）; 天气验证部分基于输入日期验证季节（S302）; 通过计算稳定性验证部分中的粗糙度长度和Monin-Obukhov长度来计算大气稳定性（S304，S305）; 并计算阻力系数（S306）。 （附图标记）（AA）开始; （BB）结束; （S301）检测10米风速，粗糙度长度和Monin-Obukhov长度; （S302）根据日期验证季节; （S303）输入粗糙度长度和Monin-Obukhov长度; （S304）计算粗糙度长度和Monin-Obukhov长度的比率; （S305）根据计算出的比例验证稳定性; （S306）通过分别应用不同的阻力系数计算公式来验证季节/稳定性来计算阻力系数
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Patent Agency Ranking
公开(公告)号：KR100934700B1
公开(公告)日：2009-12-31
申请号：KR1020080001115
申请日：2008-01-04
Applicant: 부산대학교 산학협력단
Abstract: A method for detecting fog by using the meteorological satellite by the standard deviation criterion, and its system are provided to allow fog to be detect precisely both in the daytime and at night. A method for detecting fog by using the meteorological satellite by the standard deviation criterion comprises the steps of detecting the intensity and distribution profile of the near infrared ray and infrared ray radiated from the whole observation region from the meteorological satellite equipped with a sensor for near infrared ray channel and a sensor for infrared ray channel; receiving the intensity and distribution profile of near infrared ray and infrared ray radiated from the whole observation region from the meteorological satellite by using the receiver of satellite signal; and calculating the standard deviation about the infrared ray brightness temperature distribution of the determined observation region from the received information, and comparing it with the standard deviation boundary value about the infrared ray brightness temperature distribution of the preset fog generation region, thereby determining the region showing the standard deviation lower than the standard deviation boundary value to be the fog generation region.
Abstract translation: 根据标准偏差标准使用气象卫星检测雾的方法及其系统，可以在白天和晚上精确检测雾。 利用标准偏差标准使用气象卫星检测雾的方法包括以下步骤：检测从配备有近红外传感器的气象卫星的整个观测区域辐射的近红外线和红外线的强度和分布轮廓 红外线通道和红外线通道传感器; 利用卫星信号接收器接收气象卫星从整个观测区域辐射的近红外线和红外线的强度和分布特征; 从接收到的信息中计算出所确定的观测区域的红外线亮度温度分布的标准偏差，并将其与预先设定的雾化区域的红外线亮度温度分布的标准偏差边界值进行比较， 标准偏差低于标准偏差边界值作为雾产生区域。
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公开(公告)号：KR1020090075301A
公开(公告)日：2009-07-08
申请号：KR1020080001115
申请日：2008-01-04
Applicant: 부산대학교 산학협력단
Abstract: A method for detecting fog by using the meteorological satellite by the standard deviation criterion, and its system are provided to allow fog to be detect precisely both in the daytime and at night. A method for detecting fog by using the meteorological satellite by the standard deviation criterion comprises the steps of detecting the intensity and distribution profile of the near infrared ray and infrared ray radiated from the whole observation region from the meteorological satellite equipped with a sensor for near infrared ray channel and a sensor for infrared ray channel; receiving the intensity and distribution profile of near infrared ray and infrared ray radiated from the whole observation region from the meteorological satellite by using the receiver of satellite signal; and calculating the standard deviation about the infrared ray brightness temperature distribution of the determined observation region from the received information, and comparing it with the standard deviation boundary value about the infrared ray brightness temperature distribution of the preset fog generation region, thereby determining the region showing the standard deviation lower than the standard deviation boundary value to be the fog generation region.
Abstract translation: 一种通过标准偏差判据使用气象卫星进行雾化的方法，提供了系统，可以在白天和晚上精确检测雾。 通过标准偏差判据利用气象卫星检测雾的方法包括：从配备有近红外传感器的气象卫星检测近红外线的强度和分布特征以及从整个观测区辐射的红外线的步骤 射线通道和红外线通道传感器; 通过卫星信号接收机接收来自气象卫星的整个观测区域辐射的近红外线和红外线的强度和分布特征; 并根据接收到的信息计算所确定的观测区域的红外线亮度温度分布的标准偏差，并将其与关于预设雾发生区域的红外线亮度温度分布的标准偏差边界值进行比较，从而确定显示 标准偏差低于标准偏差边界值为雾产生区域。
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公开(公告)号：KR1020120125048A
公开(公告)日：2012-11-14
申请号：KR1020110043093
申请日：2011-05-06
Applicant: 부산대학교 산학협력단
IPC: G01W1/00
Abstract: PURPOSE: A post-treatment system for ocean turbulent flux observation data and a method for the same are provided to improve predictability by using the data for improving the parameterization of atmosphere-ocean interaction in the boundary layer of a weather model and a climate module. CONSTITUTION: A post-treatment method for ocean turbulent flux observation data includes the following steps: the physical errors of ocean turbulent flux are verified according to the rainfall, visibility, and relative humidity of an observation point(S101); the physical errors of the ocean turbulent flux are verified according to the standard deviation of the ocean turbulent flux(S102); data without errors undergoes parallel inspections(S103); and the coordinate axis of a post-treatment system for ocean turbulent flux observation data is changed to a wind blowing direction in order to remove the physical errors from the data(S107). [Reference numerals] (AA) Turbulent flux observation data; (BB,DD,EE) Physical error; (CC) Electric error; (FF) Yes; (GG) No; (HH) Turbulence flux data after post-treatment process; (S101) 0.0 mm or more of rainfall, 2 Km or less of visibility, 85% or more of relative humidity; (S102) Within a range of ± standard deviation calculated for ± 2.5 minutes(total 5 minutes) X 3.5 times; (S103) Parallel inspection; (S104) Two or less of major errors; (S105) Calculating average wind blowing direction for ±15 minutes(total 30 minutes); (S106) Wind blowing direction is more than -135 degrees or less than +135 degrees at a machine installed direction; (S107) Coordinate axis changing process
Abstract translation: 目的：提供一种用于海洋湍流通量观测数据的后处理系统及其方法，以通过使用数据改善天气模型和气候模块边界层中大气 - 海洋相互作用参数化的数据来提高可预测性。 构成：海洋湍流通量观测数据的后处理方法包括以下步骤：根据观测点的降雨，可见度和相对湿度验证海洋湍流通量的物理误差（S101）; 根据海洋湍流通量的标准偏差验证海洋湍流通量的物理误差（S102）; 没有错误的数据进行平行检查（S103）; 并且将用于海洋湍流通量观测数据的后处理系统的坐标轴改变为吹风方向，以便从数据中去除物理误差（S107）。 （AA）湍流通量观测数据; （BB，DD，EE）物理错误; （CC）电气错误; （FF）是; （GG）否 （HH）后处理后的湍流通量数据; （S101）0.0mm以上的降雨量，2Km以下的能见度，85％以上的相对湿度; （S102）在±2.5分钟（共5分钟）×±3.5次±标准偏差范围内， （S103）平行检查; （S104）两次以下重大错误; （S105）计算平均吹风方向±15分钟（共30分钟）; （S106）机器安装方向吹风方向大于-135度或小于+135度; （S107）坐标轴变更处理
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公开(公告)号：KR101176007B1
公开(公告)日：2012-08-21
申请号：KR1020110043100
申请日：2011-05-06
Applicant: 부산대학교 산학협력단
IPC: G01W1/00
Abstract: PURPOSE: A system and a method for evaluating the simulation performance of a global climate model are provided to increase the reliability of climate prediction by reducing the climate prediction uncertainty of the East Asia. CONSTITUTION: A method for evaluating the simulation performance of a global climate model includes the following: climate data are detected from global climate simulation data and global observing data(S201); the signal-to-noise ratio, the empirical orthogonal function, the correlation coefficient, the standard deviation of the climate data are calculated(S202); the empirical orthogonal function of the global observing data is calculated(S203); the correlation coefficient of the empirical orthogonal function of the global observing data is calculated; the correlation coefficient and the standard deviation of the global climate simulation data and the global observing data are calculated to verify the climate simulation capability of a global climate model(S204); and the calculated correlation coefficient is compared with a saved boundary value to select a global climate model with superior simulation performance(S205, S206).
Abstract translation: 目的：提供一种用于评估全球气候模式的模拟性能的系统和方法，以通过降低东亚气候预测的不确定性来提高气候预测的可靠性。 构成：评估全球气候模式模拟性能的方法包括：从全球气候模拟数据和全球观测数据中检测出气候数据（S201）; 计算信噪比，经验正交函数，相关系数，气候数据的标准偏差（S202）; 计算全局观测数据的经验正交函数（S203）; 计算全局观测数据的经验正交函数的相关系数; 计算全球气候模拟数据和全球观测数据的相关系数和标准差，以验证全球气候模式的气候模拟能力（S204）; 并将计算的相关系数与保存的边界值进行比较，以选择具有卓越模拟性能的全球气候模型（S205，S206）。
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公开(公告)号：KR100894482B1
公开(公告)日：2009-04-22
申请号：KR1020070100116
申请日：2007-10-05
Applicant: 부산대학교 산학협력단
Abstract: 본 발명은 안개와 하층운의 혼합된 날씨 상태에서 안개 지역만을 구별해 내기 위한 기상위성을 이용한 안개 탐지시스템 및 그를 사용한 안개 탐지방법을 제공한다. 이와 같은 안개 탐지시스템 및 그를 사용한 안개 탐지방법은 안개의 표면이 하층운의 표면보다 균질한 분포를 가지는 특성을 이용하여 정해진 관측지역의 휘도온도 분포에 대한 라플라시안을 산출하여 안개와 하층운을 구별할 수 있도록 함으로써 안개 탐지의 정확도가 높아지게 된다.
본 발명에 따른 기상위성을 이용한 안개 탐지시스템은 근적외선 채널용 관측센서와 적외선 채널용 관측센서가 구비되어 정해진 관측지역으로부터 복사되는 근적외선과 적외선의 세기 및 분포상태를 검출하는 정지궤도기상위성과; 해상풍 탐지센서가 구비되어 관측지역의 해상풍 풍속을 검출하는 지구관측위성와; 정지궤도기상위성 및 지구관측위성로부터 검출된 정보를 수신받는 위성신호수신기 및; 안개 탐지를 위한 분석알고리즘이 프로그래밍된 연산기와 정해진 관측지역의 휘도온도차 경계값, 휘도온도 분포에 대한 라플라시안 경계값, 해상풍 풍속 경계값이 저장된 메모리가 구비되어, 위성신호수신기로부터 정해진 관측지역의 근적외선과 적외선의 세기 및 분포상태, 해상풍의 풍속을 입력받아 정해진 관측지역의 휘도온도 분포 및 휘도온도 분포에 대한 라플라시안을 계산하고, 정해진 관측지역의 근적외선과 적외선의 휘도온도차, 휘도온도 분포에 대한 라플라시안, 해상풍 풍속을 연산기에 저장된 휘도온도차 경계값, 휘도온도 분포에 대한 라플라시안 경계값, 해상풍 풍속 경계값과 비교하여 안개발생지역을 추정하는 분석장치를 포함하여 이루어진다. 그리고, 본 발명에 따른 기상위성을 이용한 안개 탐지방법은 근적외선 채널용 관측센서, 적외선 채널용 관측센서, 해상풍 탐지센서를 구비하는 하나 이상의 기상위성으로부터 정해진 관측지역으로부터 복사되는 근적외선과 적외선의 세기 및 분포상태, 정해진 관측지역의 해상풍 풍속을 검출하는 기상정보 검출단계와; 위성신호수신기를 이용하여 기상위성으로부터 정해진 관측지역으로부터 복사되는 근적외선과 적외선의 세기 및 분포상태, 정해진 관측지역의 해상풍 풍속을 수신받는 기상정보 수신단계와; 정해진 관측지역으로부터 복사되는 근적외선과 적외선의 세기 및 분포상태를 입력받아, 정해진 관측지역의 근적외선의 휘도온도와 적외선의 휘도온도를 계산하여 휘도온도차를 산출하여, 이를 정해진 관측지역의 휘도온도차 경계값과 비교하여 휘도온도차 경계값보다 낮은 휘도온도차를 보이는 지역을 안개 또는 하층운 발생지역으로 판단하는 휘도온도차 판단단계와; 정해진 관측지역의 해상풍 풍속을 입력받아, 이를 정해진 관측지역의 해상풍 풍속 경계값과 비교하여 해상풍 풍속 경계값보다 낮은 해상풍 풍속을 보이는 지역을 안개 발생 의심지역으로 판단하는 해상풍 풍속 판단단계와; 휘도온도차 판단단계에서 계산된 정해진 관측지역의 근적외선 휘도온도 분포와 적외선 휘도온도 분포로부터 각각의 휘도온도 분포에 대한 라플라시안을 산출하여, 이를 정해진 관측지역의 휘도온도 분포에 대한 라플라시안과 비교하여 휘도온도 분포에 대한 라플라시안 경계값보다 낮은 라플라시안을 보이는 지역을 최종적으로 안개 발생지역으로 판단하는 라플라시안 판단단계를 포함하여 이루어진다.
안개, 안개, 하층운, 근적외선, 적외선, 휘도온도, 해상풍, 라플라시안
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