AI for megacities: Understanding the impact of climate extremes
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AI for megacities: Understanding the impact of climate extremes
CoPED ID
9a62114c-48f4-4ba2-8765-ced032bfc6af
Status
Active
Value
No funds listed.
Start Date
Sept. 30, 2018
End Date
May 30, 2023
Description
Regional and local scale extreme events (such as heat waves) will become more frequent over the next few decades, with rising mean temperature and increased climate variability. While climate models capture broad scale spatial changes in climate phenomena, they struggle to represent extreme events on local scales. Such events are crucial to providing actionable and robust climate information to forecast, among other things, energy demand. The student will apply Bayesian statistics and machine learning in new and innovative ways to help transform the field of environmental data science.
| University of Cambridge | LEAD_ORG |
| James Hosking | SUPER_PER |
| Risa Ueno | STUDENT_PER |
Subjects by relevance
- Climate changes
- Machine learning
- Extreme phenomena
- Climate
- Forecasts
- Modelling (creation related to information)
- Future
- Local climate
- Temperature
- Effects (results)
Extracted key phrases
- Local scale extreme event
- Climate extreme
- Robust climate information
- Climate variability
- Climate model
- Climate phenomenon
- Broad scale spatial change
- AI
- Impact
- Megacitie
- Heat wave
- Regional