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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

high-resolution rapidly-updated meteorological data analysis system for aviation applications. / 一個應用於航空的高分辨率、快速更新的氣象數據分析系統 / A high-resolution rapidly-updated meteorological data analysis system for aviation applications. / Yi ge ying yong yu hang kong de gao fen bian lu, kuai su geng xin de qi xiang shu ju fen xi xi tong

January 2008 (has links)
Lau, Chi Shing = 一個應用於航空的高分辨率、快速更新的氣象數據分析系統 / 柳巳丞. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 76-78). / Abstracts in English and Chinese. / Lau, Chi Shing = Yi ge ying yong yu hang kong de gao fen bian lu, kuai su geng xin de qi xiang shu ju fen xi xi tong / Liu Sicheng. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Review on Windshear --- p.2 / Chapter 2 --- Review of the Weather Radar System --- p.5 / Chapter 2.1 --- Introduction --- p.5 / Chapter 2.2 --- Reflectivity Measurement --- p.8 / Chapter 2.3 --- Velocity Measurement --- p.11 / Chapter 2.4 --- The Doppler Dilemma --- p.14 / Chapter 2.5 --- TDWR and LIDAR used in Hong Kong --- p.16 / Chapter 3 --- Design of the System --- p.19 / Chapter 3.1 --- The Wind Analysis --- p.19 / Chapter 3.2 --- The Cloud Analysis --- p.25 / Chapter 3.3 --- Settings of the Domain --- p.26 / Chapter 4 --- Data Preparation --- p.31 / Chapter 4.1 --- Background Field --- p.31 / Chapter 4.2 --- Non-radar Observation Data --- p.33 / Chapter 4.3 --- The Radar Data --- p.33 / Chapter 5 --- A Study on Sea Breeze --- p.37 / Chapter 5.1 --- The Physical origin of Sea Breeze --- p.37 / Chapter 5.2 --- Case Study on 10 March 2006 --- p.41 / Chapter 6 --- A Study on Tropical Cyclone --- p.46 / Chapter 6.1 --- The Physics of Tropical Cyclone --- p.46 / Chapter 6.2 --- Case Study on 3 Aug 2006 --- p.51 / Chapter 7 --- A Study on Microburst --- p.57 / Chapter 7.1 --- The Physical origin of Microburst --- p.57 / Chapter 7.2 --- Case Study on 8 June 2007 --- p.60 / Chapter 8 --- Discussions and Conclusions --- p.67 / Chapter 8.1 --- Discussions --- p.67 / Chapter 8.2 --- Conclusions --- p.69 / Chapter A --- Derivation of Radar Equation --- p.70 / Chapter A.1 --- Radar Equation for Point Target --- p.70 / Chapter A.2 --- Radar Equation for Distributed Targets --- p.71 / Chapter B --- Technical Details --- p.73 / Chapter B.1 --- Hardware and Timing --- p.73 / Chapter B.2 --- Programming issues --- p.75 / Bibliography --- p.76
2

A weather radar signal and data processing system.

Fetter, Rochard Wallace. January 1970 (has links)
No description available.
3

A weather radar signal and data processing system.

Fetter, Rochard Wallace. January 1970 (has links)
No description available.
4

Positioning patterns from multidimensional data and its applications in meteorology

Wong, Ka-yan, 王嘉欣 January 2008 (has links)
published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy
5

Short-term precipitation forecast.

Bellon, Aldo January 1973 (has links)
No description available.
6

Short-term precipitation forecast.

Bellon, Aldo January 1973 (has links)
No description available.
7

On the application of artificial neural networks and genetic algorithms in hydro-meteorological modelling

Fernando, Dweepika Achela Kumarihamy. January 1997 (has links)
published_or_final_version / Civil and Structural Engineering / Doctoral / Doctor of Philosophy
8

Modelagem computacional de dados: um sistema de tomada de decisão para gestão de recursos agrometeorológicos - SIAGRO / Computer modeling of data: a system making decision for management of agrometeorology resources - SIAGRO

Diego Roman 27 August 2007 (has links)
A maioria das aplicações envolvendo a influência do clima na agricultura requer um grande volume de dados que, geralmente, não estão disponíveis. Desta forma, há necessidade de um aplicativo computacional para facilitar a organização dos dados necessários. O sistema computacional SIAGRO foi desenvolvido para dar suporte a uma plataforma de coleta de dados termo-pluviométricos e para atender à demanda dos usuários da informação agrometeorológica para agricultura. O sistema proposto permite, a partir de dados coletados a intervalos de 15 minutos, cadastrar outras estações, importar dados, calcular a evapotranspiração por diferentes modelos (Thornthwaite; Camargo; Thornthwaite modificado por Camargo e Hagreaves e Samani), utilizar a classificação climática de Thornthwaite e determinar médias para os parâmetros coletados em períodos distintos de tempo. Os resultados são apresentados em forma de gráficos e tabelas num computador pessoal ou via Internet, que podem ser exportados para uso em outros aplicativos computacionais ou comparados com os resultados de outras estações cadastradas no sistema. Disponibilizar o SIAGRO de informação que permita gerir de forma eficiente programas de irrigação para atender as carências de água nos cultivos, permitiu que se avaliasse o desempenho de três métodos de referência para estimar a evapotranspiração com dados obtidos em lisímetros de lençol freático constante. Os dados foram coletados diariamente e processados em escala mensal. O desempenho dos métodos foi analisado a partir do coeficiente de correlação r e do índice de concordância de Willmot d. Os resultados mostraram que a melhor estimativa foi obtida com o modelo de Thornthwaite modificado por Camargo, devido ao seu melhor ajuste aos dados lisimétricos, apresentando uma concordância ótima, com índice d de 0,91. / Since most of the applications involving the influence of climate in agriculture require a great amount of data that usually are unavailable, a computational tool is needed to help to organize the necessary data. The computational system SIAGRO was developed in an attempt to support such a demand of users of climate information in agriculture. The system makes it possible to register other stations, import climatic data, to calculate evapotranspiration by means of different methods (Thornthwaite; Camargo; Thornthwaite modified by Camargo and Hagreaves e Samani), to apply a climatic classification and to determine averages for different periods of time from daily data. The system presents its results in graphics and tables, which can be copied for use in other computer applications or used to be compared with results of other weather stations registered in this system. To supply SIAGRO with profitable information for irrigation scheduling and increase the efficiency in water use by crops, allowed the evaluation of three reference methods to estimating evapotranspiration through correlation with data obtained in constant water table lisimeter. The data were collected daily and processed in a monthly basis. The performance evaluations of the methods were based on the correlation coefficient r and Willmott agreement coefficient d. The results showed that the best estimate was obtained with the Thornthwaite modified by Camargo model, which shows the best adjustment to lysimeter data, with the index d equal to 0.91.
9

Modelagem computacional de dados: um sistema de tomada de decisão para gestão de recursos agrometeorológicos - SIAGRO / Computer modeling of data: a system making decision for management of agrometeorology resources - SIAGRO

Diego Roman 27 August 2007 (has links)
A maioria das aplicações envolvendo a influência do clima na agricultura requer um grande volume de dados que, geralmente, não estão disponíveis. Desta forma, há necessidade de um aplicativo computacional para facilitar a organização dos dados necessários. O sistema computacional SIAGRO foi desenvolvido para dar suporte a uma plataforma de coleta de dados termo-pluviométricos e para atender à demanda dos usuários da informação agrometeorológica para agricultura. O sistema proposto permite, a partir de dados coletados a intervalos de 15 minutos, cadastrar outras estações, importar dados, calcular a evapotranspiração por diferentes modelos (Thornthwaite; Camargo; Thornthwaite modificado por Camargo e Hagreaves e Samani), utilizar a classificação climática de Thornthwaite e determinar médias para os parâmetros coletados em períodos distintos de tempo. Os resultados são apresentados em forma de gráficos e tabelas num computador pessoal ou via Internet, que podem ser exportados para uso em outros aplicativos computacionais ou comparados com os resultados de outras estações cadastradas no sistema. Disponibilizar o SIAGRO de informação que permita gerir de forma eficiente programas de irrigação para atender as carências de água nos cultivos, permitiu que se avaliasse o desempenho de três métodos de referência para estimar a evapotranspiração com dados obtidos em lisímetros de lençol freático constante. Os dados foram coletados diariamente e processados em escala mensal. O desempenho dos métodos foi analisado a partir do coeficiente de correlação r e do índice de concordância de Willmot d. Os resultados mostraram que a melhor estimativa foi obtida com o modelo de Thornthwaite modificado por Camargo, devido ao seu melhor ajuste aos dados lisimétricos, apresentando uma concordância ótima, com índice d de 0,91. / Since most of the applications involving the influence of climate in agriculture require a great amount of data that usually are unavailable, a computational tool is needed to help to organize the necessary data. The computational system SIAGRO was developed in an attempt to support such a demand of users of climate information in agriculture. The system makes it possible to register other stations, import climatic data, to calculate evapotranspiration by means of different methods (Thornthwaite; Camargo; Thornthwaite modified by Camargo and Hagreaves e Samani), to apply a climatic classification and to determine averages for different periods of time from daily data. The system presents its results in graphics and tables, which can be copied for use in other computer applications or used to be compared with results of other weather stations registered in this system. To supply SIAGRO with profitable information for irrigation scheduling and increase the efficiency in water use by crops, allowed the evaluation of three reference methods to estimating evapotranspiration through correlation with data obtained in constant water table lisimeter. The data were collected daily and processed in a monthly basis. The performance evaluations of the methods were based on the correlation coefficient r and Willmott agreement coefficient d. The results showed that the best estimate was obtained with the Thornthwaite modified by Camargo model, which shows the best adjustment to lysimeter data, with the index d equal to 0.91.

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