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Climate Change Modeling and Prediction:

Welcome to the dedicated session on Education, Teaching, Learning & Assessment at the 5th International Conference on Multidisciplinary and Current Educational Research (ICMCER-2024) in Bangkok, Thailand. This session is a focal point for educators, researchers, and professionals to share insights, exchange ideas, and explore innovations that contribute to the dynamic landscape of education.

Objective:

The objective of this session is to explore the advancements in climate change modeling and prediction through the integration of AI techniques. By bringing together experts in the fields of climate science and artificial intelligence, the session aims to foster a deeper understanding of how AI can enhance the accuracy, resolution, and predictive capabilities of climate models. Participants will discuss innovative approaches to leveraging machine learning for predictive modeling and uncertainty quantification in climate projections.

Theme:

"Unveiling the Future: AI-Driven Climate Modeling for Precision Prediction and Sustainable Decision-Making."

The theme of this session revolves around harnessing the power of AI to address the complexities of climate change. It emphasizes the integration of cutting-edge technologies to improve the precision of climate models and enhance our ability to predict and understand the impacts of climate change. The session will explore how AI can contribute to more effective decision-making and policy formulation in the face of global environmental challenges.

Tracks

1 Integrating AI techniques for high-resolution climate models.

2 Predictive modeling of climate change impacts using machine learning.

3 Uncertainty quantification in climate projections with AI.

4 AI-Enhanced Climate Model Development

5 Data Fusion and Integration for Climate Modeling

6 Dynamic Ensemble Climate Modeling

7 Explainable AI in Climate Science

8 Climate Impact Assessment

9 Optimizing Climate Models for Regional Predictions

10 Carbon Sequestration Modeling

11 Climate Resilience Assessment and Planning

12 Urban Climate Modeling

13 Ethical Considerations in AI-Driven Climate Modeling

Outcomes:

    Insights into AI-Enhanced Climate Models:
  • Participants will gain insights into the current state-of-the-art AI techniques employed in high-resolution climate models, understanding how these technologies contribute to improved simulations and predictions.
    Predictive Modeling Showcase:
  • The session will feature presentations and case studies showcasing successful applications of machine learning in predictive modeling of climate change impacts. Attendees will learn about real-world implementations and their implications.
    Understanding Uncertainty in Climate Projections:
  • Through discussions and presentations, participants will delve into the challenges of uncertainty quantification in climate projections and explore how AI methodologies can provide more robust and reliable predictions.
    Collaboration Opportunities:
  • The session will provide a platform for scientists, researchers, and practitioners to explore potential collaborations between the climate science and AI communities. Networking opportunities will be facilitated to encourage future interdisciplinary projects.
    Policy Implications:
  • Discussions will touch upon the policy implications of improved climate models, addressing how AI-enhanced predictions can inform and influence climate change mitigation and adaptation strategies at local, national, and global levels.
To be a Presenter please submit your Research Abstract
To be a Listener, Please register