Executive Summary of the Weather & Climate Forecast Conference (WCFC) 2026 June

1. Background and Central Theme of the Conference

At the 2nd Weather & Climate Forecast Conference (WCFC) held in June 2026, the focus of discussion broadened beyond pure technology to encompass wider societal concerns. In the face of intensifying meteorological disasters driven by climate change, the central theme explored how to apply rapidly evolving AI technologies to the real world, linking them to concrete disaster risk reduction actions and effectively bridging the gap from early warning to early action.

Opening Remarks Representative Director, WNI Weather Culture Creation Center
Jiro Miyabe

Connecting Early Warning to Early Action Specially Appointed Professor / Strategic Management Advisor, Tohoku University
Former Special Representative of the UN Secretary-General for Disaster Risk Reduction / Former Head of UNDRR
Mami Mizutori

2. The Paradigm Shift Brought by AI

AI is expected to catalyze human decision-making and action, including proactive evacuation, by enabling highly accurate forecasting and seamless information sharing across language barriers. Moving beyond a simple forecasting tool, AI is beginning to act as a hub, a kind of central nervous system, that translates scientific data into concrete disaster prevention actions.

Empowering Citizens for Climate Resilience: The Emerging Role of AI in Adaptation Technical Director, Weathernews Inc.
Yuichiro Nishi

NVIDIA Earth-2 Developments and Directions Program Manager, Earth System Science Domain, NVIDIA
Stan Posey

Current Status and Future Expectations of AI Implementation in JMA Operations Senior Coordinator for AI Strategy, Japan Meteorological Agency (JMA)
Yoichi Hirahara

3. Implementation Status and Impact-Based Forecasting in Asia

National meteorological agencies in countries such as Indonesia, Nepal, the Philippines, Thailand, and Vietnam are accelerating AI implementation to address challenges posed by complex terrain and increasingly severe disasters, such as the rapid intensification of typhoons. Many of these nations are urgently shifting toward impact-based forecasting, focusing not just on what the weather will be, but on what the weather will do.

Meteorological Agencies Panel The Agency for Meteorology Climatology and Geophysics of The Republic of Indonesia (BMKG), Department of Hydrology and Meteorology, Nepal (DHM), Pakistan Meteorological Department (PMD), PAGASA (Philippines), Thai Meteorological Department (TMD), Viet Nam Meteorological and Hydrological Administration (VNMHA)

Early Warning Team Panel Discussion Department of Climate Change and Environment (DCCE), National Disaster Warning Center, Office of the National Water Resources (ONWR), Thailand, Thai Meteorological Department (TMD)

AI-Driven Disaster Risk Reduction in Viet Nam: From Early Warning to Early Action Deputy Director of Department of Database Management, Viet Nam Disaster and Dyke Management Authority (VDDMA)
Le Minh Nhat

AI-driven disaster detection through remote sensing: test cases and practical examples from Vietnam Deputy Head, Department of Science, Technology and International Cooperation, Hanoi University of Natural Resources and Environment
Pham Hong Tinh

Evaluating AI-Driven Precipitation Forecasting over Southeast Asia Assoc. Professor, University of Science and Technology of Hanoi
Thanh Ngo-Duc

4. Common Challenges and Barriers

The conference also highlighted common challenges in deploying and operating AI across the Asian region:

• Data and Infrastructure: There is an urgent need to overcome the shortage of high-quality historical data required for training AI models, as well as to expand the coverage and density of observation networks.
• Resource and Talent Shortages: Securing the computational power to run advanced AI models is essential, as is cultivating interdisciplinary professionals who bridge AI expertise and meteorological knowledge.

AI-Driven Disaster Detection through Remote Sensing: Lessons from Post-Earthquake Building Assessment at Chulalongkorn University Professor, Chulalongkorn University
Withit Pansuk

From Environmental Data to Actionable Intelligence: Student Projects in Flood, Water Quality, and Air Pollution Prediction Assistant Professor, CMKL University
Raveekiat Singhaphandu

AI for Forecasting the Climate Change & Impacts and Community Actions in Yogyakarta, Indonesia Prof. Dr. Ir., Sekolah Vokasi (School of Applied Science), Universitas Gadjah Mada (UGM)
Agus Maryono

The impact of the Senyar Cyclone on biodiversity in Northern Sumatra, Indonesia. Chairman and Professor, Research Center for Climate Change, University of Indonesia
Jatna Supriatna

From Climate Projections to Community Action: Rethinking Water Resources in Thailand Assistant Professor, Department of Civil Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang
Pinit Tanachaichoksirikun

AI-SWAMP: Artificial Intelligence-based Sustainable Water Resources Management in the Philippines Assistant Professor, Institute of Environmental Science & Meteorology, University of the Philippines Diliman
Bernard Alan B. Racoma

Deep learning for climate modeling and forecasting Associate Professor, Seoul National University
Yoo-Geun Ham

5. Conclusion: The Convergence of Technology and Community

While practical applications are progressing, such as smartphone-enabled real-time disaster detection and wildfire prediction, the overarching consensus reached at the conference was that AI is not an omnipotent solution, but merely a tool designed to support a human-centric society.

No matter how sophisticated an early warning system may be, it is ultimately the citizens, the recipients of these warnings, who must take action to protect lives. Therefore, the conference concluded that in parallel with technological advancements, it is absolutely essential to enhance civic literacy and cultivate community resilience rooted in self-help and mutual assistance.

Real-time Disaster Detection - Toward Social Implementation WNI Data Store, Weathernews Inc.
Koji Nakata

Social Implementation of a Wildfire Risk Forecast System WNI Forecast Center, Weathernews Inc.
Mayuko Yoshikawa

Closing Remarks Director, Weathernews Inc.
Daisuke Abe

• Opening Remarks
  Jiro Miyabe
  Representative Director, WNI Wx Bunka Foundation
• Empowering Citizens for Climate Resilience: The Emerging Role of AI in Adaptation
  Yuichiro Nishi
  Technical Director, Weathernews Inc.
• Connecting Early Warning to Early Action
  Mami Mizutori
  Specially Appointed Professor/ Strategic Management Advisor, Tohoku University / Former Special Representative of the UN Secretary-General for Disaster Risk Reduction / Former Head of UNDRR
• NVIDIA Earth-2 Developments and Directions
  Stan Posey
  Program Manager, Earth System Science Domain, NVIDIA
• The Agency for Meteorology Climatology and Geophysics of The Republic of Indonesia (BMKG)
  Yoshua Ade Nugroho
  Project Management Officer, The Agency for Meteorology Climatology and Geophysics of The Republic of Indonesia (BMKG)
• Flood Forecasting System in Pakistan and Case Studies of 2022 & 2025 Floods
  Muhammad Aleem ul Hassan
  Director, Flood Forecasting Division, Lahore, Pakistan Meteorological Department (PMD)
• A Comparative Analysis of Floods 2022 and 2025 in Pakistan
  Muhammad Irfan Virk
  Deputy Director, Pakistan Meteorological Department (PMD)
• AI Applications in Early Warning Systems: TMD Perspective
  Fatah Masthawee
  Acting Specialist on Meteorological Forecasting System Development, Thai Meteorological Department (TMD)
• Current Challenges in Hydro-Meteorological Agencies
  Mai Van Khiem
  Director, Vietnam National Center of Hydro-Meteorology Forecasting (NCHMF)
• Climate Change Risks and Adaptation Strategies in Thailand: The Critical Role of AI-Enhanced Early Warning Systems
  Rabiab Poopha
  Director of Climate Change Adaptation Division, Department of Climate Change and Environment (DCCE), Thailand
• Comprehensive overviews & challenges of the Thailand's hazard landscape, Overview response capabilities, and operational systems
  Seree Supratid
  Special Expert, National Disaster Warning Center, Thailand
• Adaptation Strategies in Thailand : The Critical Role of AI-Enhanced Early Warning Systems
  Kanjanawan Nilklud
  Director of Water Analysis and Monitoring Sub-Division, Office of the National Water Resources (ONWR), Thailand
• Current Status and Future Expectations of AI Implementation in JMA Operations
  Yoichi Hirahara
  Senior Coordinator for AI Strategy, Japan Meteorological Agency (JMA)
• AI-Driven Disaster Risk Reduction in Viet Nam: From Early Warning to Early Action
  Le Minh Nhat
  Deputy Director of Department of Database Management, Viet Nam Disaster and Dyke Management Authority (VDDMA)
• From Environmental Data to Actionable Intelligence: Student Projects in Flood, Water Quality, and Air Pollution Prediction
  Raveekiat Singhaphandu
  Assistant Professor, CMKL University
• AI for Forecasting the Climate Change & Impacts and Community Actions in Yogyakarta, Indonesia
  Agus Maryono
  Prof. Dr. Ir., Sekolah Vokasi (School of Applied Science), Universitas Gadjah Mada (UGM)
• AI-Driven Disaster Detection through Remote Sensing: Test Cases and Practical Examples from Vietnam
  Pham Hong Tinh
  Deputy Head, Department of Science, Technology and International Cooperation, Hanoi University of Natural Resources and Environment
• Evaluating AI-Driven Precipitation Forecasting over Southeast Asia
  Thanh Ngo-Duc
  Assoc. Professor, University of Science and Technology of Hanoi
• The Impact of the Senyar Cyclone on Biodiversity in Northern Sumatra, Indonesia
  Jatna Supriatna
  Chairman and Professor, Research Center for Climate Change, University of Indonesia
• From Climate Projections to Community Action: Rethinking Water Resources in Thailand
  Pinit Tanachaichoksirikun
  Assistant Professor, Department of Civil Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang
• AI-SWAMP: Artificial Intelligence-based Sustainable Water Resources Management in the Philippines
  Bernard Alan B. Racoma
  Assistant Professor, Institute of Environmental Science & Meteorology, University of the Philippines Diliman
• Deep Learning for Climate Modeling and Forecasting
  Yoo-Geun Ham
  Associate Professor, Seoul National University
• AI-Driven Disaster Detection through Remote Sensing: Lessons from Post-Earthquake Building Assessment at Chulalongkorn University
  Withit Pansuk
  Professor, Chulalongkorn University
• Real-time Disaster Detection - Toward Social Implementation
  Koji Nakata
  WNI Data Store, Weathernews Inc.
• Social Implementation of a Wildfire Risk Forecast System
  Mayuko Yoshikawa
  WNI Forecast Center, Weathernews Inc.
• Closing Remarks
  Daisuke Abe
  Director, Weathernews Inc.