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Quantitative Precipitation Estimation Using Weather Radar Data and Machine Learning Algorithms for the Southern Region of Brazil
In addressing the challenges of quantitative precipitation estimation (QPE) using weather radar, the importance of enhancing the rainfall estimates for applications such as flash flood forecasting and hydropower generation management is recognized. This study employed dual-polarization weather radar...
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Published in: | Remote sensing (Basel, Switzerland) Switzerland), 2024-06, Vol.16 (11), p.1971 |
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container_start_page | 1971 |
container_title | Remote sensing (Basel, Switzerland) |
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creator | Verdelho, Fernanda F. Beneti, Cesar Pavam, Luis G. Calvetti, Leonardo Oliveira, Luiz E. S. Zanata Alves, Marco A. |
description | In addressing the challenges of quantitative precipitation estimation (QPE) using weather radar, the importance of enhancing the rainfall estimates for applications such as flash flood forecasting and hydropower generation management is recognized. This study employed dual-polarization weather radar data to refine the traditional Z–R relationship, which often needs higher accuracy in areas with complex meteorological phenomena. Utilizing tree-based machine learning algorithms, such as random forest and gradient boosting, this research analyzed polarimetric variables to capture the intricate patterns within the Z–R relationship. The results highlight machine learning’s potential to improve the precision of precipitation estimation, especially under challenging weather conditions. Integrating meteorological insights with advanced machine learning techniques is a remarkable achievement toward a more precise and adaptable precipitation estimation method. |
doi_str_mv | 10.3390/rs16111971 |
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Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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subjects | Algorithms Artificial intelligence Calibration Comparative analysis Data collection Datasets Environmental aspects Flash floods Flood forecasting Flood management Gauges gradient boosting Hydroelectric power Hydroelectric power generation Learning algorithms Machine learning Measurement Meteorological radar Precipitation Precipitation (Meteorology) precipitation estimation quantitative precipitation estimation Radar Radar data Radar systems Rain Rainfall random forest Research methodology Variables Weather Weather forecasting |
title | Quantitative Precipitation Estimation Using Weather Radar Data and Machine Learning Algorithms for the Southern Region of Brazil |
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