Development of a neural network for precipitable water vapor retrieval over ocean and land

In this work a method based on neural networks is proposed to retrieve precipitable water vapour over land and over ocean from brightness temperatures measured by the Advanced Microwave Scanning Radiometer - Earth Observing System. In order to train the neural network, water vapour values provided b...

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Bibliographic Details
Main Authors: Basili, P., Bonafoni, S., Mattioli, V., Pelliccia, F., Serpolla, A., Bocci, E., Ciotti, P.
Format: Conference Proceeding
Language:English
Subjects:
Brightness temperature
brightness temperatures
Earth Observing System
emissivity
Microwave measurements
Microwave radiometry
Microwave theory and techniques
neural network
Neural networks
Oceans
Precipitable water vapour
Sea measurements
Temperature measurement
Weather forecasting
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Summary:In this work a method based on neural networks is proposed to retrieve precipitable water vapour over land and over ocean from brightness temperatures measured by the Advanced Microwave Scanning Radiometer - Earth Observing System. In order to train the neural network, water vapour values provided by European Centre for Medium-Range Weather Forecasts, sampled on a regular grid with a spacing of 0.25deg in latitude and longitude, were exploited. The analysis was performed over Italy and the Mediterranean area and, as expected, the water vapour retrieval over a sea background exhibits good accuracy. Over a land background the proposed approach seems to be promising, where a RMS error of about 0.3 cm was achieved.
DOI:10.1109/MICRAD.2008.4579503