| Autor: |
Anne Jones, Julian Kuehnert, Paolo Fraccaro, Ophélie Meuriot, Tatsuya Ishikawa, Blair Edwards, Nikola Stoyanov, Sekou L. Remy, Kommy Weldemariam, Solomon Assefa |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
npj Climate and Atmospheric Science, Vol 6, Iss 1, Pp 1-8 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2397-3722 |
| DOI: |
10.1038/s41612-023-00388-1 |
| Popis: |
Abstract In recent years there has been a surge of interest in the potential of Artificial Intelligence (AI) to address the global threat of climate change. Here, we consider climate change applications, and review the ability of AI technologies to better quantify climate change-induced hazards, impacts and risks, and address key challenges in this domain. We focus on three application areas: data-driven modeling, enabling uncertainty quantification, and leveraging geospatial big data. For these, we provide examples from flood-related applications to illustrate the advantages of AI, in comparison to alternative methods, whilst also considering its limitations. We conclude that by streamlining the process of translating weather and climate data into actionable information, facilitated by a suitable technology framework, AI can play a key role in building climate change resilience. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
Full text from SpringerLink