Institute for Advanced Academic Research (IAAR),
Chiba UniversityEnvironmental Prediction Science,
Kotsuki and Okazaki Laboratory
JAPANESE
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Publications

Preprint

  • Kotsuki, S., Shiraishi, K. and Okazaki, A. (2024): Integrating Ensemble Kalman Filter with AI-based Weather Prediction Model ClimaX. arXiv.
  • Ohtsuka T., Okazaki A., Ogura M. and Kotsuki, S.(2024): Convex Optimization of Initial Perturbations toward Quantitative Weather Control. arXiv.

Peer-reviewed Articles

  • FY2024
    • Yamamoto, K., Ma, W., Matsugishi, S., Satoh, M., Kotsuki, S., Miyoshi, T., Kachi, M., Kubota, T. and Yoshimura, K. (2024): Development and validation of a global ensemble hydrological simulation system: TE-Global NEXRA. Hydrol. Res. Lett. (accepted)
    • Muto, Y. and Kotsuki, S.(2024): Estimating global precipitation fields by interpolating rain gauge observations using the local ensemble transform Kalman filter and reanalysis precipitation. Hydrol. Earth Syst. Sci., 28, 5401–5417. doi: 10.5194/hess-28-5401-2024 (Dec. 17, 2024)
    • Oettli, P. and Kotsuki, S. (2024): An Objective Detection of Separation Scenario in Tropical Cyclone Trajectories Based on Ensemble Weather Forecast Data. J. Geophys. Res., 129, e2024JD040830. doi: 10.1029/2024JD040830 (Jul. 20, 2024)
    • Kawasaki, F. and Kotsuki, S. (2024): Leading the Lorenz-63 system toward the prescribed regime by model predictive control coupled with data assimilation. Nonlin. Processes Geophys., 31, 319-333. doi: 10.5194/npg-31-319-2024 (Jul. 10, 2024) (博士1年)
    • Kotsuki, S., Kawasaki, F. and Ohashi, M. (2024): Quantum data assimilation: a new approach to solving data assimilation on quantum annealers. Nonlin. Processes Geophys. Lett., 31, 237-245. doi: 10.5194/npg-31-237-2024 (Jun. 07, 2024) [Link to Press Release in English]
  • FY2023
    • Hu, J., Kotsuki, S., Igarashi, Y., Yang, Z., Talerko, M., Tischenkof, O., Protsak, V. and Kirieiev, S. (2024): A tuning-free moderate scale burned area detection algorithm — A case study in Chornobyl contaminated region. Int. J. Remote Sens., 45, 2444-2461. doi: 10.1080/01431161.2024.2331976 (Mar. 27, 2024)
    • Kurosawa, K., Kotsuki, S., and Miyoshi, T. (2023): Comparative Study of Strongly and Weakly Coupled Data Assimilation with a Global Land-Atmosphere Coupled Model. Nonlin. Processes Geophys., 30, 457-479. doi: 10.5194/npg-30-457-2023 (Oct. 23, 2023)
    • Muto, Y., Kanemaru, K., and Kotsuki, S. (2023): Correcting GSMaP through histogram matching against satellite-borne radar-based precipitation, SOLA, 19, 217-224. doi: 10.2151/sola.2023-028 (Sep. 26, 2023)
    • Oishi, K., and Kotsuki, S. (2023): Applying the Sinkhorn Algorithm for Resamling of Local Particle Filter, SOLA, 19, 185-193. doi: 10.2151/sola.2023-024 (Aug. 30, 2023)
    • Ouyang, M., Tokuda, K., and Kotsuki, S. (2023): Reducing manipulations in a control simulation experiment based on instability vectors with the Lorenz-63 model. Nonlin. Processes Geophys., 30, 183–193. doi: 10.5194/npg-30-183-2023 (Jun. 22, 2023)
  • FY2022
    • Hu, J., Igarashi, Y., Kotsuki, S., Yang, Z., Talerko, M., Landin, V., Tischenko, O., Zheleznyak, M., Protsak, V., and Kirieiev, S. (2023): Application of a tuning-free burned area detection algorithm to the Chornobyl wildfires in 2022. Sci. Rep., 13, 5236. doi: 10.1038/s41598-023-32300-5 (Mar. 31, 2023)
    • Kotsuki, S., Terasaki, K., Satoh, M., and Miyoshi, T. (2023): Ensemble-based Data Assimilation of GPM DPR Reflectivity: Cloud Microphysics Parameter Estimation with the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), J. Geophys. Res., 128, e2022JD037447. doi: 10.1029/2022JD037447 (Feb. 17, 2023)
    • Momoi, M., Kotsuki, S., Kikuchi, R., Watanabe, S., Yamada, M., and Abe, S. (2023): Emulating rainfall-runoff-inundation model using deep neural network with dimensionality reduction. Artificial Intelligence for the Earth Systems (AIES), 2, 1-25. doi: 10.1175/AIES-D-22-0036.1 (Jan. 10,2023)
    • Ouyang, M., Kotsuki, S., Ito, Y., and Tokunaga, T. (2022): Employment of hydraulic model and social media data for flood hazard assessment in an urban city. J. Hydrol. Reg. Stud., 44, 101261. doi: 10.1016/j.ejrh.2022.101261 (Nov. 18, 2022)
    • Kotsuki, S., Miyoshi, T., Kondo K., and Potthast R. (2022): A Local Particle Filter and Its Gaussian Mixture Extension Implemented with Minor Modifications to the LETKF. Geosci. Model Dev., 15, 8325–8348. doi: 10.5194/gmd-15-8325-2022 (Nov. 18, 2022)
  • FY2021
    • Kotsuki, S., and Bishop, H. C. (2022): Implementing Hybrid Background Error Covariance into the LETKF with Attenuation-based Localization: Experiments with a Simplified AGCM. Mon. Wea. Rev., 150, 283-302. doi: 10.1175/MWR-D-21-0174.1 (Nov. 24, 2021; CR)
    • Miyoshi, T., Terasaki, K., Kotsuki, S., Otsuka, S., Chen, Y.-W., Kanemaru, K., Okamoto, K., Kondo, K., Lien, G.-Y., Yashiro, H., Tomita, H., Sato, M., and Kalnay, E. (2022): Enhancing data assimilation of GPM observations. Precipitation Science, Measurement Remote Sensing, Microphysics, and Modeling. Elsevier, 787-804. doi: 10.1016/B978-0-12-822973-6.00020-2 (Nov. 12, 2021; CR)
    • Arakida, H., Kotsuki, S., Otsuka, S., Sawada, Y., and Miyoshi, T. (2021): Regional-scale data assimilation with the Spatially Explicit Individual-based Dynamic Global Vegetation Model (SEIB-DGVM) over Siberia. Prog. Earth Planet. Sci., 8:52. doi: 10.1186/s40645-021-00443-6 (Sep. 14, 2021; CR)
    • Taler, J., Okazaki, A., Honda, T., Kotsuki, S., Yamaji, M., Kubota, T., Oki, R., Iguchi, T., and Miyoshi, T.: Oversampling Reflectivity Observations from a Geostationary Precipitation Radar Satellite: Impact on Typhoon Forecasts within a Perfect Model OSSE Framework. J. Adv. Modeling Earth Syst., 13, e2020MS002332.  doi: 10.1029/2020MS002332 (May 08, 2021; CR)
  • FY2020
    • Carrio, D. S., Bishop, C. H. and Kotsuki, S. (2021): Empirical determination of the covariance of forecast errors: an empirical justification and reformulation of Hybrid covariance models. Q. J. R. Meteorol. Soc., 147, 2033-2052. doi: 10.1002/qj.4008 (Feb. 20, 2021; CR)
    • Watanabe, S., Kotsuki, S., Kanae, S., Tanaka, K. and Higuchi, A.: Snow water scarcity induced by the record breaking warm winter in 2020 in Japan. Sci. Rep., 10, 18541.  doi: 10.1038/s41598-020-75440-8 (Oct. 29, 2020; CR)
    • Kotsuki, S., Pensoneault, A., Okazaki, A., and Miyoshi, T. (2020): Weight Structure of the Local Ensemble Transform Kalman Filter: A Case with an Intermediate AGCM. Q. J. R. Meteorol. Soc., 146, 3399-3415. doi: 10.1002/qj.3852 (Jun. 16, 2020; CR)
    • Miyoshi, T., Kotsuki, S., Terasaki, K., Otsuka, S., Lien, G.-Y., Yashiro, H., Tomita, H., Satoh, M., and Kalnay, E. (2020): Precipitation Ensemble Data Assimilation in NWP Models. Satellite Precipitation Measurement. Advances in Global Change Research, 69, Springer, 983-991. doi:10.1007/978-3-030-35798-6_25 (Apr. 15, 2020; CR)
  • FY2019
    • Kotsuki, S., Sato, Y., and Miyoshi, T. (2020): Data Assimilation for Climate Research: Model Parameter Estimation of Large Scale Condensation Scheme. J. Geophys. Res., 125, e2019JD031304. doi: 10.1029/2019JD031304 (Jan. 03, 2020; CR)
  • See further publications by Prof. S. Kotsuki before the launch of the laboratory on Nov. 2019

Peer-reviewed Conference Proceeding Papers

  • FY2023
    • Sakaino, H., Gaviphatt, N., Insisiengmay, A., Zamora, L., Ningrum, D. F., and Kotsuki, S. (2023). DeepTrCy: Life Stage Identification of Satellite Tropical Cyclone Images. IEEE International Geoscience and Remote Sensing Symposium, 5186-5189. doi: 10.1109/IGARSS52108.2023.10282363 (Jul. 16-21, 2023)

Peer-reviewed Articles in Japanese

  • FY2024
    • 井貫恵多朗, 金子凌, 岡﨑淳史, 小槻峻司(2024): 深層学習に基づく生成モデルを用いたドップラー風速データからのランキン渦再構成． 水工学論文集 (accepted; Sep. , 2024) (学部4年)
    • 毛束隆太, 武藤裕花, 岡﨑淳史, 小槻峻司(2024): 災害被害数理モデルを用いた強化学習による洪水被害削減のための投資策の最適化.　AI・データサイエンス論文集 (accepted; Sep. , 2024) (修士2年)
  • FY2023
    • 武藤裕花, 塩尻大也, 小槻峻司(2024): 局所アンサンブルデータ同化を用いた地上雨量観測からの全球降水分布の推定． 水工学論文集, Vol.80, No.16,  - . doi: 10.2208/jscejj.23-16197 (accepted; Aug. , 2023)
    • 佐々木景悟, 武藤裕花, 塩尻大也, 小槻峻司(2023): ベイズ最適化を用いた降雨流出氾濫モデルの計算効率性の高いパラメータ最適化に関する研究.　AI・データサイエンス論文集, Vol.4, No.3, 602-610. doi: 10.11532/jsceiii.4.3_602 (accepted; Aug. , 2023)
    • 関令法, 塩尻大也, 小槻峻司 (2023):日本の降水量の次元圧縮を対象とした特異値分解と非負値行列因子展開の比較．AI・データサイエンス論文集, Vol.4, No.3, 772-778. doi: 10.11532/jsceiii.4.3_772 (accepted; Aug. , 2023)
    • 島袋隆也, 塩尻大也, 小槻峻司(2023): 深層学習モデルを用いた浸水深の時空間分布予測のエミュレーティング． AI・データサイエンス論文集, Vol.4, No.3, 553-560. doi: 10.11532/jsceiii.4.3_553 (accepted; Aug. , 2023)
    • 白石健太, 武藤裕花, 小槻峻司(2023): 深層学習に基づく超解像技術を用いた降水量データの高解像度化に関する研究．AI・データサイエンス論文集, Vol.4, No.3, 515-521. doi: 10.11532/jsceiii.4.3_515 (accepted; Aug. , 2023)
  • FY2022
    • 塩尻大也, 小槻峻司, 齋藤匠, Mao OUYANG (2022): スパースセンサ位置最適化手法による効率的な雨量計配置手法の開発． 水工学論文集, Vol.78, No.2, 385-390. doi: 10.2208/jscejhe.78.2_I_385 (accepted; Aug. , 2022)
    • 藤村健介, 小槻峻司, 山田真史, 塩尻大也, 渡部哲史 (2022): 降雨流出氾濫モデルのアンサンブルデータ同化安定化に関する研究． 水工学論文集, Vol.78, No.2, 409-411. doi: 10.2208/jscejhe.78.2_I_409 (accepted; Aug. , 2022)
    • 齋藤匠,  小槻峻司, Mao OUYANG, 塩尻大也 (2022): スパースセンサ最適化を用いた大次元力学系における有効な観測位置決定手法の開発． 水工学論文集, Vol.78, No.2, 391-396. doi: 10.2208/jscejhe.78.2_I_391 (accepted; Aug. , 2022)
  • FY2021
    • 赤塚洋介, 瀬戸里枝, 鼎信次郎, 小槻峻司, 渡部哲史 (2021): 豪雪地帯に位置するダム対象とした融雪期の操作におけるAIダム操作モデルの応用可能性． 水工学論文集, Vol.77, No.2, pp.I_109-I_114. doi: 10.2208/jscejhe.77.2_I_109 (accepted; Dec. , 2021; C)
  • FY2020
    • 小槻峻司, 桃井裕広，菊地亮太, 渡部哲史, 山田真史, 阿部紫織，綿貫翔 (2020): 回帰学習器のアンサンブル学習による降雨洪水氾濫モデル・エミュレータ． 水工学論文集, Vol.76, No.2, pp.I_367-I_372. doi: 10.2208/jscejhe.76.2_I_367 (accepted; Nov. 04, 2020; C)
    • 関本大晟, 渡部哲史, 小槻峻司, 山田真史, 阿部紫織，綿貫翔 (2020): 降雨流出氾濫モデル・エミュレータによる浸水範囲予測． 水工学論文集, Vol.76, No.2, pp. I_547-I_552. doi: 10.2208/jscejhe.76.2_I_547 (accepted; Nov. 04, 2020; C)

    Non-peer-reviewed Articles

    • FY2021
      • 滝野晶平, 本田匠, 三好建正, 大東真利茂, 小槻峻司, 塚田智之, 中田安彦 (2021): 機械学習を活用した発電ダムの運用最適化システムの開発． 大ダム, No.257(2021-10), 30-36.

    Others in Japanese