Cargando…
Explainable deep learning for insights in El Niño and river flows
The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections. Recent research...
Autores principales: | Liu, Yumin, Duffy, Kate, Dy, Jennifer G., Ganguly, Auroop R. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9860069/ https://www.ncbi.nlm.nih.gov/pubmed/36670105 http://dx.doi.org/10.1038/s41467-023-35968-5 |
Ejemplares similares
-
DeepEmSat: Deep Emulation for Satellite Data Mining
por: Duffy, Kate, et al.
Publicado: (2019) -
Explained predictions of strong eastern Pacific El Niño events using deep learning
por: Rivera Tello, Gerardo A., et al.
Publicado: (2023) -
Prediction of Yangtze River streamflow based on deep learning neural network with El Niño–Southern Oscillation
por: Ha, Si, et al.
Publicado: (2021) -
El Niño increases the risk of lower Mississippi River flooding
por: Munoz, Samuel E., et al.
Publicado: (2017) -
Asymmetry of projected increases in extreme temperature distributions
por: Kodra, Evan, et al.
Publicado: (2014)