Cargando…
Short-lead seasonal precipitation forecast in northeastern Brazil using an ensemble of artificial neural networks
This study assesses the deterministic and probabilistic forecasting skill of a 1-month-lead ensemble of Artificial Neural Networks (EANN) based on low-frequency climate oscillation indices. The predictand is the February-April (FMA) rainfall in the Brazilian state of Ceará, which is a prominent subj...
Autores principales: | Pinheiro, Enzo, Ouarda, Taha B. M. J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665445/ https://www.ncbi.nlm.nih.gov/pubmed/37993488 http://dx.doi.org/10.1038/s41598-023-47841-y |
Ejemplares similares
-
Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting
por: Men, Zhongxian, et al.
Publicado: (2014) -
Dynamical–statistical seasonal forecasts of winter and summer precipitation for the Island of Ireland
por: Golian, Saeed, et al.
Publicado: (2022) -
Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.
por: Reich, Nicholas G., et al.
Publicado: (2019) -
Tropical South Atlantic influence on Northeastern Brazil precipitation and ITCZ displacement during the past 2300 years
por: Utida, Giselle, et al.
Publicado: (2019) -
An Algorithm for Precipitation Correction in Flood Season Based on Dendritic Neural Network
por: Li, Tao, et al.
Publicado: (2022)