Using an Artificial Neural Network to Assess Several Rainfall Estimation Algorithms Based on X-Band Polarimetric Variables in West Africa

Quantitative precipitation estimation using polarimetric radar in attenuation-prone frequency (X-band) in tropical regions characterized by convective rain systems with high intensities is a major challenge due to strong attenuations that can lead to total signal extinction over short distances. How...

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Vydáno v:	Atmosphere Ročník 16; číslo 4; s. 371
Hlavní autoři:	Akponi, Fulgence Payot, Moumouni, Sounmaïla, Zahiri, Eric-Pascal, Kacou, Modeste, Gosset, Marielle
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.04.2025 MDPI
Témata:	African monsoon Algorithms artificial neural network (ANN) Artificial neural networks Atmospheric precipitations Design Drop size Drop size distribution drop size distribution (DSD) Forecasts and trends Gauges Matrix codes Meteorological radar Methods Multilayer perceptrons Neural networks Nonparametric statistics Observatories Polarimetric radar Polarimetry Polariscope Precipitation Precipitation estimation quantitative precipitation estimate (QPE) Radar Radar attenuation Rain Rain and rainfall Rain gauges Raindrops Rainfall Rainfall estimation Rainfall intensity Rainfall measurement Rainfall simulators Reflectance Regression analysis Sciences of the Universe Simulation Size distribution Superhigh frequencies Training Tropical environment Tropical environments tropical regions Variables Weather forecasting Weather radar X-band polarimetric radar Africa West Africa drop size distribution (DSD) quantitative precipitation estimate (QPE) artificial neural network (ANN) tropical regions X-band polarimetric radar
ISSN:	2073-4433, 2073-4433
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