[E] Oral

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI34] Data-driven approaches for weather and hydrological predictions

Mon. May 25, 2026 9:00 AM - 10:30 AM 106 (International Conference Hall, Makuhari Messe)

Chairperson:Sekiyama Thomas(Meteorological Research Institute), Kotsuki Shunji(Center for Environmental Remote Sensing, Chiba University)

In the digital era, data-driven techniques are transforming our understanding and prediction capabilities of complex earth systems. This session aims to explore the cutting-edge methodological and applicational studies for weather, climate and hydrological predictions. Key themes includes: (1) methodological studies to deepen data-driven approaches for geoscience problems, (2) machine/deep learning studies applied for extreme weather-related disasters, (3) climate predictive analysis to discern climate variability, trends, and anomalies, (4) integrating remote sensing and ground data to refine prediction models. This session aims to foster a rich dialogue among experts, highlighting both the advancements and challenges in data-driven environmental modeling. Participants will gain insights into current best practices and envision the future trajectory of this rapidly evolving domain.

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9:00 AM - 9:15 AM

[MGI34-01] Spatio-Temporal Radar-Gauge Rainfall Data Assimilation for Extreme Events: A Case Study of Taipei Taiwan

*Sumriti Ranjan Patra¹, Hwa-Lung Yu¹, Shih-Yao Lee¹ (1. Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan)

9:15 AM - 9:30 AM

[MGI34-02] Precipitation “Extremeness” Assessment Relative to the Environmental Field: Analysis of Linear Rainband Events Using Diffusion Models

*Yuki H. Takano¹, Takuya Kawabata¹ (1. Meteorological Research Institute, Japan Meteorological Agency)

9:30 AM - 9:45 AM

[MGI34-03] Precipitation Downscaling via Knowledge-guided Mixture of Experts for Explicit Representation of Physical Mechanisms

*Takumi Bannai^1,2, Yuki Kita³ (1. LTS, Inc., 2. ME-Lab Japan, Inc., 3. Gaia Vision Inc.)

9:45 AM - 10:00 AM

[MGI34-04] Downscaling emulator with Classifier Free Diffusion Guidance Model

*Ryo Kaneko¹, Atsushi Okazaki¹, Shunji Kotsuki¹ (1. Chiba University)

10:00 AM - 10:15 AM

[MGI34-05] Enhancing Ensemble Temperature Forecasts with CNN: Analyzing AI-based Post-processing through Forecast Information–Noise Error Decomposition

*Takuya Inoue¹, Takuya Kawabata¹ (1. Meteorological Research Institute, Japan Meteorological Agency)

10:15 AM - 10:30 AM

[MGI34-06] Data-Driven Regional Weather Prediction for Japan: Exploring the Role of High-Resolution Reanalysis and Customized Loss Functions

*Hiroki Ikeuchi¹, Tsuyoshi Thomas Sekiyama^1,2, Takafumi Miyasaka¹, Kenichi Kuma¹, Hisashi Nakamura¹ (1. The University of Tokyo, 2. Meteorological Research Institute)

Session information