Outcomes of the WMO prize challenge to improve subseasonal to seasonal predictions using Artificial Intelligence
| Title: | Outcomes of the WMO prize challenge to improve subseasonal to seasonal predictions using Artificial Intelligence |
|---|---|
| Authors: | Vitart, Frederic; Robertson, Andrew W.; Spring, Aaron; Pinault, F; Roškar, Rok; Lledó, Llorenç; Palma, Luis |
| Contributors: | Barcelona Supercomputing Center |
| Publisher Information: | American Meteorological Society (AMS) |
| Publication Year: | 2022 |
| Collection: | Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
| Subject Terms: | Àrees temàtiques de la UPC::Enginyeria agroalimentària::Ciències de la terra i de la vida::Climatologia i meteorologia; Precipitation forecasting; Weather forecasting; Neural networks; Regression analysis; Statistical techniques; Forecast verification/skill; Numerical weather prediction/forecasting; Model evaluation/performance; Simulació per ordinador; Intel·ligència artificial |
| Description: | Peer Reviewed ; "Article signat per 22 autors/es: F. Vitart, A. W. Robertson, A. Spring, F. Pinault, R. Roškar, W. Cao, S. Bech, A. Bienkowski, N. Caltabiano, E. De Coning, B. Denis, A. Dirkson, J. Dramsch, P. Dueben, J. Gierschendorf, H. S. Kim, K. Nowak, D. Landry, L. Lledó, L. Palma, S. Rasp, and S. Zhou" ; Postprint (published version) |
| Document Type: | article in journal/newspaper |
| File Description: | application/pdf |
| Language: | English |
| Relation: | https://journals.ametsoc.org/view/journals/bams/103/12/BAMS-D-22-0046.1.xml; https://hdl.handle.net/2117/379222 |
| DOI: | 10.1175/BAMS-D-22-0046.1 |
| Availability: | https://hdl.handle.net/2117/379222; https://doi.org/10.1175/BAMS-D-22-0046.1 |
| Rights: | Open Access |
| Accession Number: | edsbas.C442B514 |
| Database: | BASE |