CEReS, Chiba University

Achievement

Publications

Publications submitted, in revision, or in progress

  1. Kurosawa K. and Poterjoy J.: A Local Particle Filter-Variational Data Assimilation System for a Regional Application of the Unified Forecast System
  2. Kurosawa K. and Poterjoy J.: Augmented background perturbations to mitigate sampling errors: Experiments for a regional application of the NOAA Unified Forecast System
  3. Kurosawa K., Poterjoy J., and Schwartz C.: An Adaptive Blending of Particle Filters with Ensemble Kalman Filters for Convective-Scale Data Assimilation
  4. Kotsuki S., Kurosawa K., Kanemaru K., Terasaki K., and Miyoshi T.: A New Evaluation Method for Cloud Microphysics Schemes Using GPM Dual-frequency Precipitation Radar.

Refereed journal publications

  1. Kurosawa K., Kotsuki S., and Miyoshi T. (2023): Comparative study of strongly and weakly coupled data assimilation with a global land–atmosphere coupled model, Nonlinear Processes in Geophysics, doi.org/10.5194/npg-30-457-2023 [NPG] (PDF)
  2. Kurosawa K. and Poterjoy J. (2023): A statistical hypothesis testing strategy for adaptively blending particle filters and ensemble Kalman filters for data assimilation. Monthly Weather Review, doi.org/10.1175/MWR-D-22-0108.1[MWR] (PDF)
  3. Kurosawa K. and Poterjoy J. (2021): Data assimilation challenges posed by nonlinear operators: A comparative study of ensemble and variational filters and smoothers. Monthly Weather Review, doi.org/10.1175/MWR-D-20-0368.1 [MWR] (PDF)
  4. Kurosawa K., Uchiyama Y., and Kosako, T. (2020): Development of a numerical marine weather routing system for coastal and marginal seas using regional oceanic and atmospheric simulations. Ocean Eng, 195, doi:10.1016/j.oceaneng.2019.106706 [OceanEng] (PDF)
  5. Kotsuki S., Kurosawa K., Otsuka S., Terasaki K. and Miyoshi T. (2019): Global Precipitation Forecasts by Merging Extrapolation-based Nowcast and Numerical Weather Prediction with Locally-optimized Weights. Weather and Forecasting, 34, 701-714. doi:10.1175/WAF-D-18-0164.1 [WAF]
  6. Kotsuki S., Kurosawa K., and Miyoshi T. (2019): On the Properties of Ensemble Forecast Sensitivity to Observations. Quarterly Journal of the Royal Meteorological Society, 145, 1897-1914. doi: 10.1002/qj.3534 [QJRMS]

Journal papers in Japanese

  1. 王 鴻鑫, 黒澤賢太, 内山雄介: アンサンブルカルマンフィルタ海洋データ同化システムの開発と瀬戸内海流動への応用 (2021) (Development of a Data Assimilation System Based on Ensemble Kalman Filter and its Application to the Seto Inland Sea), 土木学会論文集B2（海岸工学）, Vol. 77, No. 2.
  2. 黒澤賢太, 内山雄介, 三好建正: 3 次元変分法を用いた瀬戸内海流動再解析・予報モデルの高精度化 (2018) (On Improvement of an Estuarine Reanalysis-Forecast Model for the Seto Inland Sea Based on 3D Variational Assimilation), 土木学会論文集B2(海岸工学), Vol. 73, No. 2, pp. I_1663-1668, doi:10.2208/kaigan.73.I_1663 (pdf) (with English abstract)
  3. 内山雄介, 岡田信瑛, 黒澤賢太: 衛星海面高度データを用いた北太平洋における中規模渦の発生伝播特性の解析 (2018) (Eddy Analysis in the North Pacific Using an Eddy-Tracking Algorithm), 土木学会論文集B2(海岸工学), Vol. 73, No. 2., pp. I_1429-I_1437, doi:10.2208/kaigan.73.I_1429 (pdf) (with English abstract)
  4. 内山雄介, 千郷直斗, 黒澤賢太: HYCOM-ROMSダウンスケーリング海洋流動モデルの開発と南シナ海周辺海域への応用 (2018) (Development of a HYCOM-ROMS Downscaling Ocean Model and its Application to the South China Sea), 土木学会論文集B2(海岸工学), Vol. 74, No. 2, pp. I_625─I_630, doi:10.2208/kaigan.74.I_625 (pdf) (with English abstract)
  5. 内山雄介, 黒澤賢太, 小硲大地, 多田拓晃: グラフ理論とコンパクト海洋モデルを用いた最適航路選定法の開発 (2017) (Development of a Weather Routing System Based on Graph Theory Coupled with a Compact Ocean Model for Optimal Vessel Navigation), 土木学会論文集B2(海岸工学), Vol. 72, No. 2, pp. I_1549-I_1554. doi:10.2208/kaigan.72.I_1549 (pdf) (with English abstract)

Presentations

2023

  1. Kurosawa K. and Poterjoy J.: Convective-Scale Ensemble Prediction Using Adaptive Gaussian/Non-Gaussian Ensemble Filters, 9th NOAA Ensemble Users Workshop, 22-24 August 2023, NCWCP, College Park, MD (link)
  2. Kurosawa K. and Poterjoy J.: Augmented background perturbations to mitigate sampling errors: Experiments for a regional application of the NOAA Unified Forecast System, PSU-UMD Data Assimilation Workshop 2023, 14-15 August 2023, online (link)
  3. Kurosawa K. and Poterjoy J.: Augmented Global Background Perturbations for Mitigating Sampling Errors for Regional Applications of the UFS, Unifying Innovations in Forecasting Capabilities Workshop 2023, 24-28 July 2023, Boulder, CO (link)
  4. Kurosawa K. and Poterjoy J.: Blending Gaussian and Non-Gaussian Data Assimilation for State Estimation with High-Dimensional Geophysical Models, The 2023 CEAFM-Burgers-GWU Research Symposium on Environmental and Applied Fluid Dynamics, 30 May 2023, Johns Hopkins University, Baltimore, MD (link)
  5. Kurosawa K., Poterjoy J., and Schwartz C.: A Statistical Hypothesis Testing Strategy for Adaptively Blending Particle Filters and Ensemble Kalman Filters for Convective-Scale Data Assimilation, 103rd AMS Annual Meeting, 8–12 January 2023, Denver, CO (link)

2022

  1. Kurosawa K., Poterjoy J., and Schwartz C.: An Adaptive Mixed PF-EnKF for Convective-Scale Data Assimilation, PSU-UMD Data Assimilation Workshop 2022, Dec. 15, 2022
  2. Kurosawa K. and Poterjoy J.: An Adaptive Blending of Particle Filters with Ensemble Kalman Filters for Convective-Scale Data Assimilation, AGU Fall Meeting 2022, 12-16 December 2022, Chicago, IL & Online (link)
  3. Kurosawa K. and Poterjoy J.: Mixed PF-EnKF data assimilation for multiscale weather prediction, 8th International Symposium on Data Assimilation, Colorado State University, CO, 6-10 June 2022 (link)
  4. Kurosawa K. and Poterjoy J.: Combining particle filters with ensemble Kalman filters for multiscale weather prediction, 35th Conference on Hurricanes and Tropical Meteorology, New Orleans, LA, 9-13 May 2022 (link)
  5. Kurosawa K. and Poterjoy J.: Toward a Mixed Particle Filter Ensemble Kalman Filter Data Assimilation Methodology for Multiscale Weather Prediction, American Meteorological Society, 102nd Annual Meeting, Houston, Texas online, 23-27 Jan. 2022 (link)

2021

  1. Kurosawa K. and Poterjoy J.: Data Assimilation Challenges Posed by Nonlinear Measurement Operators: A Comparative Study Using a Simplified Model, American Meteorological Society, 101st Annual Meeting, online, 11-15 Jan. 2021 (link)

2020

  1. Kurosawa K. and Poterjoy J.: Data assimilation challenges posed by nonlinear measurement operators: A comparative study using a simplified model, PSU-UMD Data Assimilation Workshop 2020, online, Aug. 21, 2020
  2. Kurosawa K. and Poterjoy J.: A Comparison of Iterative Ensemble Kalman Smoothers to Hybrid 4DVar, The 9th EnKF Data Assimilation Workshop, Penn State University Park Campus, State College, PA, USA, June 2-3, 2020 (link) Canceled

2019

  1. 黒澤賢太, 小槻峻司, 大塚成徳, 寺崎康児, 三好建正: 数値天気予報とナウキャストを組み合わせた全球降水予測, 平成30年度GPMおよび衛星シミュレータ合同研究集会, 名古屋大学環境総合館, 名古屋市, 2019年3月18-19日 (link)
  2. Kurosawa K., Kotsuki S., and Miyoshi T.: Can hydrological observations improve global NWP in land-atmosphere-coupled data assimilation?, The 1st R-CCS International Symposium, Kobe, Japan, 18 Feb., 2019 (link)
  3. Kurosawa K., Kotsuki S., and Miyoshi T.: Can hydrological observations improve global NWP in land-atmosphere-coupled data assimilation?, The 7th International Symposium on Data Assimilation, Kobe, Japan, 21-24 Jan., 2019 (link)
  4. Kurosawa K., Kotsuki S., Otsuka S., Terasaki K., and Miyoshi T.: Locally Optimal Weighting of Global Precipitation Forecasts from Precipitation Nowcasting and Numerical Weather Prediction, The 7th International Symposium on Data Assimilation, Kobe, Japan, 21-24 Jan., 2019 (link)

2018

  1. 黒澤賢太, 小槻峻司, 大塚成徳, 寺崎康児, 三好建正: 数値天気予報とナウキャストを組み合わせた全球降水予測,気象学会2018年度秋季大会, 仙台国際センター, 仙台市, 2018年10月29日-11月01日 (link)
  2. 黒澤賢太, 小槻峻司, 寺崎康児, 三好建正: GPM/DPR の固体降水フラグの初期検証:3.5km NICAM との比較, 気象学会2018年度秋季大会, 仙台国際センター, 仙台市, 2018年10月29日-11月01日 (link)

2017

  1. 黒澤賢太, 内山雄介, 三好建正: 3 次元変分法を用いた瀬戸内海流動再解析・予報モデルの高精度化, 第64回海岸工学講演会, 札幌駅カンファレンスセンター, 札幌市, 2017年10月25-27日 (link)
  2. Kurosawa K., Uchiyama Y. and Miyoshi T.: A high-resolution coastal forecasting system with a 3DVAR assimilation optimal for a semi-enclosed estuary, 14th Annual Meeting Asia Oceania Geosciences Society, Singapore, 6-11 Aug., 2017 (link)
  3. Kurosawa K.: Development of a coastal forecasting system with a 3DVAR assimilation for the Seto Inland Sea, Japan, Complex Fluid and Thermal Engineering Research Center, Kobe, 19 Jul., 2017
  4. Kurosawa K., Uchiyama Y. and Miyoshi T.: Development of a coastal forecasting system with a 3DVAR assimilation for the Seto Inland Sea, Japan, 19th Pacific Asian Marginal Seas Meeting, Jeju, Korea, 11-13 Apr., 2017 (link)

2016

  1. Kurosawa K. and Uchiyama Y.: Development of a three-dimensional variational data assimilation system for the Seto Island Sea, Japan, AGU Fall Meeting 2016, San Francisco, USA, 12-16 Dec., 2016 (link)
  2. 黒澤賢太, 内山雄介, 小硲大地, 多田拓晃: グラフ理論とコンパクト海洋モデルを用いた最適航路選定法の開発, 第63回海岸工学講演会, 大阪大学中之島センター, 大阪市, 2016年11月16-18日 (link)
  3. 黒澤賢太, 内山雄介, 小硲大地, 多田拓晃: 船舶搭載用コンパクト海洋モデルの構築とウェザールーティングへの応用, 2016年度日本海洋学会秋季大会, 鹿児島大学郡元キャンパス, 鹿児島市, 2016年9月12-14日 (link)
  4. Kurosawa K., Uchiyama Y., Kosako T. and Tada H.: Utilizing a regional ocean model for weather routing for optimal vessel navigation, 13th Annual Meeting Asia Oceania Geosciences Society, Beijing, China, 31Jul. – 5Aug., 2016 (link)
  5. 黒澤賢太: 細密気象・海象情報とグラフ理論を統合した最適航路評価法の開発, H28年度土木学会関西支部年次学術講演会, 滋賀, 2016年5月 (link)
  6. 黒澤賢太, 内山雄介, 小硲大地, 多田拓晃: A*アルゴリズムをベースとした最適航路評価法および船舶搭載用コンパクト海洋モデルの開発, 日本航海学会 第134回春季講演会, 神戸, 2016年5月 (link)

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