JpGU Meeting 2022
Session outline| Atmospheric and Hydrospheric Sciences (A) | ||
|---|---|---|
| Session Sub-category | Technology &Techniques (TT) | |
| Session ID | A-TT32 | |
| Title | Machine Learning Techniques in Weather, Climate, Ocean, Hydrology and Disease Predictions | |
| Short Title | Machine learning for Earth Sciences | |
| Main Convener | Name | Venkata Ratnam Jayanthi |
| Affiliation | Application Laboratory, JAMSTEC | |
| Co-Convener 1 | Name | Daisuke Matsuoka |
| Affiliation | Japan Agency for Marine-Earth Science and Technology | |
| Co-Convener 2 | Name | Takeshi Doi |
| Affiliation | JAMSTEC | |
| Co-Convener 3 | Name | Swadhin Behera |
| Affiliation | Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Yokohama 236-0001 | |
| Session Language | E | |
| Scope | The machine learning techniques have found a wide range of applications in weather, climate, ocean, hydrology and disease predictions. In recent times, these techniques are being widely used to predict extreme events such as malaria outbreaks, heat waves, cold waves, flooding, droughts, tropical cyclones, typhoons, El Nino/Indian Ocean Dipole and many others. The techniques are helping the researchers improve the parameterization schemes in the numerical models. The techniques are also being used to improve the numerical model predications by providing methods to reduce the biases and also to improve the horizontal resolution of the forecasts. The aim of the session is to bring together the researchers working on various techniques of machine learning to enhance the understanding and predictions of weather, climate, ocean, hydrology and disease predictions for the benefit of the society. | |
| Presentation Format | Oral and Poster session | |
| Joint with | ||
| Co-sponsored | The Oceanographic Society of Japan | |