the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Hourly-scale modeling of storm transitions in Southern Brazil with Markov Chains
Camilo Ocampo-Marulanda
Jefferson Vieira Santos
Julian David Mera-Franco
Alvaro Avila-Diaz
Tiago Alessandro Espinola Ferreira
David Henriques da Matta
Antonio Samuel Alves da Silva
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A forecasting framework was developed to river flow prediction in data-scarce tropical regions. The study extracted hidden rainfall patterns from satellite precipitation records and integrated them with large-scale ocean–atmosphere climate signals into a statistical model, resulting in improved predictive accuracy. These findings can support more effective water-resources management during dry periods and strengthen early warning systems in regions with limited hydrometeorological monitoring.
A forecasting framework was developed to river flow prediction in data-scarce tropical regions. The study extracted hidden rainfall patterns from satellite precipitation records and integrated them with large-scale ocean–atmosphere climate signals into a statistical model, resulting in improved predictive accuracy. These findings can support more effective water-resources management during dry periods and strengthen early warning systems in regions with limited hydrometeorological monitoring.