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Kotsuki-Okazaki Lab
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A lab that uses data assimilation and AI to predict weather and water-related disasters.
AboutAbout the lab
Predicting Earth's future with observations and AI.
The Kotsuki-Okazaki Lab studies technologies for predicting weather and climate by combining Earth observation data with information science.
Using numerical simulations on supercomputers and machine learning, the lab links observations and predictions through data assimilation, a statistical and mathematical technique.
The lab is developing a global weather forecasting system that combines AI and data assimilation, and a system that uses generative AI to predict real-world scenes themselves.
In weather control research under the Cabinet Office's Moonshot Goal, the lab is also working on research to reduce the damage caused by torrential rain.
Key terms
- Data assimilation
- A method that uses statistical techniques to combine observation data with computer simulation results, making the current state and forecasts more reliable
- Deep learning
- A machine learning method in which a neural network with many stacked layers learns features from large amounts of data
- Quantum annealing
- A computational method that uses quantum properties to search for the best answer among a large number of combinations
NewsLab news
A Project Assistant Professor received the Paper Encouragement Award from the Japan Society of Hydrology and Water Resources
A doctoral student received an Outstanding Presentation Award at the 30th Ocean Data Assimilation Summer School
A researcher won the top prize in the weather track of the AI competition GeoSciAI2026
A student received an Outstanding Presentation Award at the Faculty of Science undergraduate thesis presentations
A student received the Dean of the Faculty of Engineering Award at Chiba University
ResearchResearch themes
The lab integrates Earth observation data and information science to conduct research on weather prediction, global precipitation maps and the water cycle, and disaster mitigation. It also emphasizes the fundamental research in data assimilation, AI, and data science that supports this work.
*Illustrative imageData assimilation and numerical weather prediction
This research uses data assimilation to improve weather prediction. It includes data assimilation for land surface models and flood inundation models, as well as mathematical research on new data assimilation methods such as the local particle filter.
*Illustrative imageDisaster prediction with AI and data science
Using deep learning, the lab works on predicting extreme precipitation, fast computation of flood inundation, and early detection of wildfires. It also develops technologies that bring out the value of observation data, such as compression of geoscience data and interpretation of phenomena.
*Illustrative imageQuantum computing, annealing, and optimization
This is research on data assimilation using quantum annealing machines. The lab conducts mathematical research on the robustness to noise that is specific to quantum computers and on reducing the number of qubits required, aiming to realize quantum data assimilation for numerical weather prediction models.
*Illustrative imageImproving global precipitation maps
The lab integrates satellite data such as that from the Global Precipitation Measurement (GPM) mission using land surface data assimilation and machine learning, working to improve JAXA's global precipitation map GSMaP. It is also pioneering data-driven satellite global precipitation maps that do not use numerical models.
MembersFaculty
The members of the Kotsuki-Okazaki Lab include faculty, project faculty and researchers, doctoral, master's, and undergraduate students, technical assistants, and visiting faculty, visiting researchers, and collaborating researchers.As of 2026
- ProfessorShunji Kotsuki
- Associate ProfessorAtsushi Okazaki
- Project Assistant ProfessorHiroya Shiojiri
- Project Assistant ProfessorYuka Muto
- Project Assistant ProfessorKenta Kurosawa
- Project Assistant ProfessorDaiko Kishikawa
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Tracking a Superstorm ( )” NASA Goddard Space Flight Center from Greenbelt, MD, USA / CC BY 2.0 (cropped)
- Data assimilation and numerical weather prediction: “NAM 500 MB” NWS, which is a branch of NOAA, a US government agency / Public domain (cropped)
- Disaster prediction with AI and data science: “Tarao heavy rainfall disaster, Shigaraki town, Koka city, Shiga pref, Japan in August 1953 no.12” 不明 Unknown / Public domain (cropped)
- Quantum computing, annealing, and optimization: “D-Wave-Washington-1000Q” Mwjohnson0 / CC BY-SA 4.0 (cropped)
- Improving global precipitation maps: “Global Precipitation Measurement (GPM) pre-launch” Bill Ingalls / Public domain (cropped)
- Related lab (第2部門 データベース技術開発部門
（梶原 康司） ): “Nyungwe rahvuspark Landsat 19jul86” Earth Observatory / Public domain (cropped) - Related lab (第3部門 ビッグデータ解析技術開発部門
（大塚 成徳） ): “Advanced Technology Demonstrator radar antenna array 02” NOAA / Public domain (cropped) - Related lab (入江研究室
（地球大気環境研究室） ): “Air Pollution Chokes Northern India (NESDIS )” NOAA / Public domain (cropped) - Related lab (楊研究室
（Yang lab） ): “Satellite image of Madagascar in September 2003” 作者不詳 / Public domain (cropped)
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