Japanese

Atmospheric and Hydrospheric Sciences (A)
Session Sub-categoryTT
Session IDA-TT29
Title Machine Learning Techniques in Weather, Climate, Ocean, Hydrology and Disease Predictions
Short Title Machine Learning Techniques application
Date & Time
Oral
session		 PM1 Mon, 22 MAY
On-site
poster
coretime		 PM3 Mon, 22 MAY
Online
Poster
session		 AM2 Tue, 23 MAY
Main ConvenerName Venkata Ratnam Jayanthi
Affiliation Application Laboratory, JAMSTEC
Co-Convener 1Name Patrick Martineau
Affiliation Japan Agency for Marine-Earth Science and Technology
Co-Convener 2Name Takeshi Doi
Affiliation JAMSTEC
Co-Convener 3Name Swadhin Behera
Affiliation Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Yokohama 236-0001
Session Language E
Scope 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 increasingly used to predict extreme events such as malaria outbreaks, heat waves, cold spells, flooding, droughts, tropical cyclones, typhoons, El Nino/Indian Ocean Dipole events among many others. In addition, machine-learning techniques are helping researchers to improve parameterization schemes in numerical prediction models. Machine-learning is also being used to improve numerical model predictions by providing methods to reduce biases and improve the horizontal resolution of the predictions. The aim of this session is to bring together researchers working on various techniques of machine learning to enhance the understanding and skill of weather, climate, ocean, hydrology and disease predictions for the benefit of the society.
Presentation Format Oral and Poster
Collaboration Joint with -
Co-sponsoring
Society		 The Oceanographic Society of Japan