WMO Artificial Intelligence for Nowcasting Pilot Project (AINPP) Workshop
The AI for Nowcasting Pilot Project (AINPP) aims to support developing countries through international collaboration in developing and evaluating AI-based nowcasting technologies. The workshop aims to share the outcomes of regional intercomparison studies, compile user requirements from developing countries, and to discuss the operational use of AI for nowcasting.
Following the successful kickoff workshop in Guangzhou, China in November 2024, AINPP has made significant progress toward its goals. Intercomparison activities in Asia, Africa, and Latin America have been launched, and technical subgroups have been established to advance data standardization, evaluation methodology, visualization tools, and public-private engagement strategies.
The WMO AINPP workshop, hosted by the National Institute of Meteorological Sciences (NIMS) of KMA, aims to consolidate these achievements, foster knowledge exchange, and assess the mid-term strategic direction for 2025-2026, with a focus on the application of AI-based nowcasting in developing countries.
Preceding the main workshop, a two-day seminar on 22-23 September will focus on Foundation Models for Weather and Climate. This pre-workshop aims to enhance participants’ understanding of emerging foundation model techniques and explore their potential applications - from demonstrating seamless Earth system prediction from minutes to centuries to supporting early warning and consecutive actions like crisis management and risk prevention.
Presentation used during the workshop is available here: Link to the shared folder
(for those approved for sharing by the speakers)
WMO News: AI-Powered Nowcasting is a game changer for weather prediction and early warnings
Workshop Agenda
(updated on 15 September)
all times in Korea Standard Time UTC+9
Day 1, Sept 22nd, 2025 | ||
Time | Items | Chair |
10:00-10:20 | 1. Open Ceremony 1.1 Opening Remarks and Welcome Address 1.2 Logistics Information | Jeong Hoon Cho, NIMS/KMA |
10:20-10:30 | Tea Break | |
10:30-12:30 | 2. Keynote I 2.1 Strategies for Utilizing Large AI Weather Models 2.2 Foundation model for the Earth System | Hyesook Lee, NIMS/KMA |
12:30-14:00 | Lunch break | |
14:00-17:30 | 3. Meteorology-AI Hackathon Presentations and Evaluation 3.1 Hackathon Project Results Presentations (4 Teams) 3.2 Open Evaluation 3.3 Break 3.4 Results & Awards Ceremony | Jeong Hoon Cho, NIMS/KMA |
Day 2, Sept 23th, 2025 | ||
Time | Items | Chair |
10:30-12:30 | 4. Keynote II 4.1 Explainable AI for Weather and Climate 4.2 Current Status of NVIDIA’s CBottle Development | Hyesook Lee, NIMS/KMA |
12:30-14:00 | Lunch break | |
14:00-15:30 | 5. Foundation Model for Weather and Climate 5.1 Data-Driven Global Atmosphere-Land Coupled Model (Yoo Geun Ham, SNU) 5.2 Efficient Adaptation of Weather Foundation Models (Hyunwoo J. Kim, KAIST) 5.3 Uncertainty Aware Prediction in Weather Forecasting Systems (Juho Lee, KAIST) | Seyoung Yun, KAIST |
15:30-16:00 | Tea Break | |
16:00-17:30 | 6. Panel Discussion 6.1 Reference Architecture for Designing a Foundation Model for Weather and Climate 6.2 Practical Value of a Foundation Model for Weather and Climate 6.3 Challenges and Issues in Developing a Foundation Model for Weather and Climate (Haiyu Dong, Microsoft) 6.4 Foundation Model Development Trends and Direction (Jeff Adie, NVIDIA) | Seok-Woo Son, SNU |
Day 3, Sept 24th, 2025 | ||
Time | Items | Chair |
9:00-9:50 | Session 1: Open Ceremony 1.1 Welcome speeches - KMA (Seung Hee Kim) - AINPP (David John Gagne) - WMO WIPPS (Yuki Honda) 1.2 Logistics Information | Jeong Hoon Cho, |
| Group photo | ||
9:50-10:20 | Tea Break | |
10:20-12:00 | Session 2: AI for Weather Forecast 2.1 KMA's Current Status and Future Plans on AI for Weather and Climate (Hyesook Lee, KMA) 2.2 WIPPS Plan to Incorporate AI Technologies 2.3 R&D on AI for Nowcasting and Forecasting at CEMC/CMA (Yong Wang, CMA) 2.4 AI Weather Prediction across Scales at US NSF NCAR (David John Gagne, NCAR) 2.5 AI for Weather Forecasting at Google, Progress Across Nowcasting, Medium Range and More (Shreya Agrawal, Google) | David John Gagne, NCAR |
12:00-14:00 | Lunch break | |
14:00-15:40 | Session 2: AI for Weather Forecast 2.6 Data-Driven Precipitaion Forecasting, 2.7 AI Weather Operations at Microsoft 2.8 NVIDIA AI Model Developments for SR Forecasting (Jeff Adie, NVIDIA) 2.9 Global Data for Local Tornado Detection: AI-Driven Tornado Detection Using Dual-Pol Radar 2.10 The AI for Weather Forecasting in National Meteorological Center of CMA | Wang Yong, |
15:40-16:10 | Tea Break | |
16:10-17:50 | Session 2: AI for Weather Forecast 2.11 AI Developments at ECMWF: AIFS and beyond (Christian Lessig, ECMWF, Online) 2.12 AI-Based Weather Forecasting Support Technology Development (Jaesik Choi, KAIST) 2.13 MLCast - An AI nowcasting community in Europe 2.14 AI-based Nowcasting in NCM Saudi Arabia (Albaraa Khayat, NCM) 2.15 AI based Precipitation Nowcasting from Satellite (Richard Muller, DWD, Online) | Haiyu Dong, Microsoft |
Day 4, Sept 25th, 2025 | ||
Time | Items | Chair |
9:00-11:00 | Session 3: AI based nowcasting 3.1 AI-based Nowcasting in Extreme Weather Prediction (Wai Kin Wong, HKO) 3.2 Application of AI Regional Model-ZHIJI 3.3 Overview of the Thunderstorm Nowcasting Research at the German Aerospace Centre (Tobias Boelle, German Aerospace Center, Online) 3.4 NowAlpha: Nowcasting with Generative Bidirectional Transformers (Jaehoon Yoo, KAIST) 3.5 AI Model for Radar-Based Extreme Rainfall Nowcasting (Changhoon Song, SNU) 3.6 AI-Based Data-to-Data Translation for Generating Ground Radar-Like Rainfall Estimates from GK-2A Satellite Observations | Hyesook Lee, KMA |
11:00-11:30 | Tea Break | |
11:30-12:30 | Session 4: Regional Intercomparison Updates 4.1 Africa Nowcasting Testbed (Abhilash Singh, University of Leeds) 4.2 Asia Nowcasting Intercomparison (Weiwei Wang, CMA-Shenzhen) 4.3 AINPP Latin America: Nowcasting Validation and Web Platform Testbed Update (Alan James Peixoto Calherios, Instituto Nacional de Pesquisa Espaciais) | Kanghui Zhou,
|
12:30-13:30 | Lunch break | |
13:30-20:00 | Session 5: Technical Tour (For international participants and speakers only) | |
Day 5, Sept 26th, 2025 | ||
Time | Items | Chair |
9:00-10:20 | Session 6: AI nowcasting for Developing Countries. 6.1 Advancing Nowcasting with Deep Learning Techniques in West Africa 6.2 Mapping Artificial Intelligence Initiatives in Hydrometeorology and Climate 6.3 AI for Nowcasting in RA VI Europe: Opportunities, Needs and EW4ALL 6.4 From Research to Operation: Experience in Deploying AI Nowcasting Model in KMA | Yuki Honda, WMO |
10:20-10:50 | Tea Break | |
10:50-12:30 | Session 7: R2O Challenges and PPE
7.1 An overview of survey results on current status and needs for AI-based nowcasting implementation (Alan James Peixoto Calherios, INPE)
7.2 Round table discussion: Q1: How can the accessibility of AI-based nowcasting products be improved for the developing countries in support of forecasting local extreme weather?
Q2: How can AI-based nowcasting products or techniques be integrated in the forecast operational process in the developing countries?
Q3: What are the major challenges and technical difficulties, and how AINPP’s outcomes or areas of future development be leveraged to address such issues?
Q4: Which areas of support can public private engagement (PPE) in AINPP be promoted to enhance the developing countries in using AI-based nowcasting products or technical development?
| Wai Kin Wong, HKO |
12:30-14:00 | Lunch break | |
14:00-16:00 | Session 8: Steering Group Meeting 8.1 Evaluation: How to connect evaluation efforts across testbeds and unify efforts 8.2 Visualization Subgroup: What visualizations are working well and how to exchange visualization tools across testbeds 8.3 Hosting/archiving AINPP datasets and code 8.4 Academic paper and mid-term report 8.5 The implementation plan for 2026 | David John Gagne, NCAR |