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Assessment of native radar reflectivity and radar rainfall estimates for discharge forecasting in mountain catchments with a random forest model
ArticleAbstract: Discharge forecasting is a key component for early warning systems and extremely useful for decisionPalabras claves:Andes, Discharge forecasting, Machine learning, Mountain region, Native radar data, Radar rainfall, Radar reflectivity, X-bandAutores:Bendix J., Contreras P., Johanna Orellana-Alvear, Paul Muñoz, Rolando Enrique Célleri Alvear, Rollenbeck R.Fuentes:googlescopusDetermination of climatic conditions related to precipitation anomalies in the Tropical Andes by means of the random forest algorithm and novel climate indices
ArticleAbstract: Understanding precipitation and its relation with atmospheric and oceanic conditions is vital in thePalabras claves:Andes, climate anomalies, K-Means, large-scale climate oscillations, Machine learning, rainfall, SOUTH AMERICA, tropicsAutores:Johanna Orellana-Alvear, Mario Guallpa, Rolando Enrique Célleri Alvear, Rollenbeck R.Fuentes:googlescopusCalibration of X-band radar for extreme events in a spatially complex precipitation region in north peru: Machine learning vs. empirical approach
ArticleAbstract: Cost-efficient single-polarized X-band radars are a feasible alternative due to their high sensitiviPalabras claves:extreme events, Machine learning, Quantitative precipitation estimate, random forest, Tropical desert, Tropical mountains, weather radarAutores:Johanna Orellana-Alvear, Macalupu S., Nolasco P., Rodriguez R., Rollenbeck R.Fuentes:googlescopus