Add to ORKGMotivated by a real world problem, this study develops a neural network approach to identify and evaluate the relationship between atmospheric radar reflectivity and ground level rainfall intensity. Rainfall is one of the most difficult elements of hydrologic cycle to measure and forecast. This is due to the tremendous range of variability it displays over a wide range of scales both in space and time. Weather radar constitutes an attractive possibility for improving the description of rainfall fields as it can provide high resolution images in space and time of the atmospheric reflectivity over large area
Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. C...
A procedure for the estimation of rainfall rate, capitalizing on a radar-based raindrop size distrib...
Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. C...
Motivated by a real world problem, this study develops a neural network approach to identify and eva...
Motivated by a real world problem, this study develops a neural network approach to identify and eva...
Motivated by a real world problem, this study develops a neural network approach to identify and eva...
Artificial neural networks are used to identify the relationship between weather radar observations ...
Rainfall is one of the most difficult elements of hydrologic cycle tomeasure and forecast. This is d...
Abstract—Rainfall estimation based on radar measurements has been an important topic in radar meteor...
Today the weather radar is an indispensable tool in the field of meteorology and hydrology. Its gapl...
Recent research has shown that neural network techniques can be used successfully for ground rainfal...
The identification of the relationship between radar reflectivity factor Z, expressed in mm6 m-3, an...
Weather radar can offer synoptic measurement at a higher temporal and spatial resolution to extract ...
The application of ANNs (Artifi cial Neural Networks) has been studied by many researchers in model...
The reflectivity (Z)—rain rate (R) model has not been tested on single polarization radar for estima...
Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. C...
A procedure for the estimation of rainfall rate, capitalizing on a radar-based raindrop size distrib...
Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. C...
Motivated by a real world problem, this study develops a neural network approach to identify and eva...
Motivated by a real world problem, this study develops a neural network approach to identify and eva...
Motivated by a real world problem, this study develops a neural network approach to identify and eva...
Artificial neural networks are used to identify the relationship between weather radar observations ...
Rainfall is one of the most difficult elements of hydrologic cycle tomeasure and forecast. This is d...
Abstract—Rainfall estimation based on radar measurements has been an important topic in radar meteor...
Today the weather radar is an indispensable tool in the field of meteorology and hydrology. Its gapl...
Recent research has shown that neural network techniques can be used successfully for ground rainfal...
The identification of the relationship between radar reflectivity factor Z, expressed in mm6 m-3, an...
Weather radar can offer synoptic measurement at a higher temporal and spatial resolution to extract ...
The application of ANNs (Artifi cial Neural Networks) has been studied by many researchers in model...
The reflectivity (Z)—rain rate (R) model has not been tested on single polarization radar for estima...
Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. C...
A procedure for the estimation of rainfall rate, capitalizing on a radar-based raindrop size distrib...
Weather radars are used to measure the electromagnetic radiation backscattered by cloud raindrops. C...