Cargando…
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts
Despite continuous improvements, precipitation forecasts are still not as accurate and reliable as those of other meteorological variables. A major contributing factor to this is that several key processes affecting precipitation distribution and intensity occur below the resolved scale of global we...
Autores principales: | Harris, Lucy, McRae, Andrew T. T., Chantry, Matthew, Dueben, Peter D., Palmer, Tim N. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788314/ https://www.ncbi.nlm.nih.gov/pubmed/36590321 http://dx.doi.org/10.1029/2022MS003120 |
Ejemplares similares
-
Machine Learning Emulation of Gravity Wave Drag in Numerical Weather Forecasting
por: Chantry, Matthew, et al.
Publicado: (2021) -
Deep learning for twelve hour precipitation forecasts
por: Espeholt, Lasse, et al.
Publicado: (2022) -
An improved deep learning procedure for statistical downscaling of climate data
por: Kheir, Ahmed M.S., et al.
Publicado: (2023) -
Entropy-Based Temporal Downscaling of Precipitation as Tool for Sediment Delivery Ratio Assessment
por: Alencar, Pedro Henrique Lima, et al.
Publicado: (2021) -
Ensemble downscaling in coupled solar wind-magnetosphere modeling for space weather forecasting
por: Owens, M J, et al.
Publicado: (2014)