Montreal high-resolution climate data
<p>This proof-of-concept study couples machine learning and physical modelling paradigms to develop a computationally efficient simulator-emulator framework for generating super-resolution (< 250 m) urban climate information, that is required by many sectors. The temperature and dew point fields for 2019 and 2020 and the geophysical fields (geophys.rar) for the study domain, at 2.5 km (LR) and 250 m (HR) resolutions, which are used to train and validate the proposed super-resolution deep learning (DL) model/emulator are provided. </p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 4
- Engagement
- 4
Topics
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