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

2nd Weather & Climate Forecast Conference 2026

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.

Jiro Miyabe

Opening RemarksJiro MiyabeRepresentative Director, WNI Weather Culture Creation Center
Mami Mizutori

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

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.

Yuichiro Nishi

Empowering Citizens for Climate Resilience: The Emerging Role of AI in AdaptationYuichiro NishiTechnical Director, Weathernews Inc.
Stan Posey

NVIDIA Earth-2 Developments and DirectionsStan PoseyProgram Manager, Earth System Science Domain, NVIDIA
Yoichi Hirahara

Current Status and Future Expectations of AI Implementation in JMA OperationsYoichi HiraharaSenior Coordinator for AI Strategy, Japan Meteorological Agency (JMA)

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

Meteorological Agencies PanelBMKG (Indonesia), DHM (Nepal), PMD (Pakistan), PAGASA (Philippines), TMD (Thailand), VNMHA (Viet Nam)
Early Warning Team Panel

Early Warning Team Panel DiscussionDCCE, National Disaster Warning Center, ONWR, TMD (Thailand)
Le Minh Nhat

AI-Driven Disaster Risk Reduction in Viet Nam: From Early Warning to Early ActionLe Minh NhatDeputy Director, Department of Database Management, Viet Nam Disaster and Dyke Management Authority (VDDMA)
Pham Hong Tinh

AI-Driven Disaster Detection through Remote Sensing: Test Cases and Practical Examples from VietnamPham Hong TinhDeputy Head, Department of Science, Technology and International Cooperation, Hanoi University of Natural Resources and Environment
Thanh Ngo-Duc

Evaluating AI-Driven Precipitation Forecasting over Southeast AsiaThanh Ngo-DucAssociate Professor, University of Science and Technology of Hanoi

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.
Withit Pansuk

AI-Driven Disaster Detection through Remote Sensing: Lessons from Post-Earthquake Building Assessment at Chulalongkorn UniversityWithit PansukProfessor, Chulalongkorn University
Raveekiat Singhaphandu

From Environmental Data to Actionable Intelligence: Student Projects in Flood, Water Quality, and Air Pollution PredictionRaveekiat SinghaphanduAssistant Professor, CMKL University
Agus Maryono

AI for Forecasting the Climate Change & Impacts and Community Actions in Yogyakarta, IndonesiaAgus MaryonoProf. Dr. Ir., Sekolah Vokasi (School of Applied Science), Universitas Gadjah Mada (UGM)
Jatna Supriatna

The Impact of the Senyar Cyclone on Biodiversity in Northern Sumatra, IndonesiaJatna SupriatnaChairman and Professor, Research Center for Climate Change, University of Indonesia
Pinit Tanachaichoksirikun

From Climate Projections to Community Action: Rethinking Water Resources in ThailandPinit TanachaichoksirikunAssistant Professor, Department of Civil Engineering, King Mongkut's Institute of Technology Ladkrabang
Bernard Alan B. Racoma

AI-SWAMP: Artificial Intelligence-based Sustainable Water Resources Management in the PhilippinesBernard Alan B. RacomaAssistant Professor, Institute of Environmental Science & Meteorology, University of the Philippines Diliman
Yoo-Geun Ham

Deep Learning for Climate Modeling and ForecastingYoo-Geun HamAssociate Professor, Seoul National University

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.

Koji Nakata

Real-time Disaster Detection - Toward Social ImplementationKoji NakataWNI Data Store, Weathernews Inc.
Mayuko Yoshikawa

Social Implementation of a Wildfire Risk Forecast SystemMayuko YoshikawaWNI Forecast Center, Weathernews Inc.
Daisuke Abe

Closing RemarksDaisuke AbeDirector, Weathernews Inc.

Presentation Video

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Presentation Materials

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