8 papers
Preemptive Ensemble Forecast Sensitivity to Observations
Fumitoshi Kawasaki, Shunji Kotsuki
Estimating the impact of observations newly added to an existing numerical weather prediction (NWP) system requires reintegrating the ensemble forecast from the analysis that assim…
Ensemble Forecast Updates without Model Re-integration Based on Ultra-rapid Data Assimilation: Idealized Experiments with a Heavy Rainfall Case
Fumitoshi Kawasaki, Kenta Kurosawa, Atsushi Okazaki +1
Observations at high frequency have become dramatically more abundant with recent technological advances. Ultra-rapid data assimilation (URDA) has been proposed to exploit them, fr…
An extended Perron-Frobenius operator filter for nonlinear state estimation
Yuta Miwa, Yoshihiko Susuki, Shunji Kotsuki
We propose an extended Perron--Frobenius Operator Filter (PFOF) for nonlinear state estimation. The method learns the Perron--Frobenius operator, an infinite-dimensional linear ope…
A Real-Time Remote-Sensing-Guided Decision-Support Framework for Cloud-Seeding Operations: A Field Demonstration Using Himawari-9 and C-band Phased Array Weather Radar
Shunji Kotsuki, Kazuaki Yasunaga, Atsushi Hamada +11
This study proposes a real-time remote-sensing-guided decision-support framework for cloud-seeding operations using high frequency geostationary satellite and ground weather radar…
Bridging Artificial Intelligence and Data Assimilation: The Data-driven Ensemble Forecasting System ClimaX-LETKF
Akira Takeshima, Kenta Shiraishi, Atsushi Okazaki +2
While machine learning-based weather prediction (MLWP) has achieved significant advancements, research on assimilating real observations or ensemble forecasts within MLWP models re…
Exploring Ultra Rapid Data Assimilation Based on Ensemble Transform Kalman Filter with the Lorenz 96 Model
Fumitoshi Kawasaki, Atsushi Okazaki, Kenta Kurosawa +1
Ultra-rapid data assimilation (URDA) is a method that rapidly updates preemptive forecasts derived from observations without integrating a dynamical model each time additional obse…
Conditional Diffusion Models for Global Precipitation Map Inpainting
Daiko Kishikawa, Yuka Muto, Shunji Kotsuki
Incomplete satellite-based precipitation presents a significant challenge in global monitoring. For example, the Global Satellite Mapping of Precipitation (GSMaP) from JAXA suffers…
Wasserstein GAN-Based Precipitation Downscaling with Optimal Transport for Enhancing Perceptual Realism
Kenta Shiraishi, Yuka Muto, Atsushi Okazaki +1
High-resolution (HR) precipitation prediction is essential for reducing damage from stationary and localized heavy rainfall; however, HR precipitation forecasts using process-drive…