AI for megacities: Understanding the impact of climate extremes
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AI for megacities: Understanding the impact of climate extremes
CoPED ID
18fb4667-eb29-4bc5-888d-e2a95b70a051
Status
Closed
Value
No funds listed.
Start Date
Sept. 30, 2018
End Date
May 31, 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 |
| Alexander Archibald | SUPER_PER |
| James Hosking | SUPER_PER |
Subjects by relevance
- Climate changes
- Machine learning
- Extreme phenomena
- Climate
- Modelling (representation)
- Local climate
- Temperature
- Statistics (data)
- Forecasts
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
- Mean temperature