Armin Mehrabian
First version of the trained classifier using v4 dataset and RoBERTa base model.
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metadata
language:
- en
widget:
- text: >-
We explores the impact of initial and boundary conditions on simulating an
extra-tropical cyclones in the North Atlantic Ocean, employing the Weather
Research and Forecasting (WRF) model. The study assesses cyclone
trajectory and synoptic patterns against real-world observations, finding
that the WRF model effectively replicates Gong's entire lifecycle,
including its intensification phase. It was observed that both the genesis
of the cyclone and its Q-Vector—a meteorological vector that indicates the
potential for cyclogenesis—are significantly influenced by the initial
conditions set in the model.
example_title: LABEL_15 (Severe Storms)
Label Mapping
The model classifies inputs into the following categories, each represented by a unique label ID:
| Category | ID |
|---|---|
| Agriculture | 0 |
| Air Quality | 1 |
| Atmospheric/Ocean Indicators | 2 |
| Cryospheric Indicators | 3 |
| Droughts | 4 |
| Earthquakes | 5 |
| Ecosystems | 6 |
| Energy Production/Use | 7 |
| Environmental Impacts | 8 |
| Floods | 9 |
| Greenhouse Gases | 10 |
| Habitat Conversion/Fragmentation | 11 |
| Heat | 12 |
| Land Surface/Agriculture Indicators | 13 |
| Public Health | 14 |
| Severe Storms | 15 |
| Sun-Earth Interactions | 16 |
| Validation | 17 |
| Volcanic Eruptions | 18 |
| Water Quality | 19 |
| Wildfires | 20 |