Machine learning applications for weather and climate need greater focus on extremes
Bibliographic Data
| ID | 15550757 |
|---|---|
| Authors | P A Watson (0000-0001-5173-9903, University of Bristol, corresponding author) |
| Year | 2022 |
| Volume | 17 |
| Issue | 11 |
| Pages | 111004-111004 |
| Publication date | 2022-10-27 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/ac9d4e |
| OpenAlex | W4307642979 |
| Language | EN |
| Citations received | 2 |
| References cited | 32 |
[No abstract]
Climate change · Climate model · Climatology · Downscaling · Extrapolation · Extreme value theory · Extreme weather · Focus (optics · Geography · Machine learning · Meteorology · Precipitation · Relevance (law · Statistics · Climate variability and models · Computer Science · Environmental Science · Hydrological Forecasting Using AI · Mathematics · Meteorological Phenomena and Simulations
| Citations per year | 1 |
|---|---|
| Citation span | 2024 - 2025 (2) |
| Highly cited | No |