NICAM Simulation Data Site

Overview of the dataset

• This dataset is a historical and future climate simulation dataset using 14 km mesh NICAM.
• The present (historical) climate simulation, which covers from June 1978 to December 2009, was performed using the boundary conditions of historical sea surface temperature (SST), greenhouse gases, and so on based on the observation.
• The future climate simulation, which covers from June 2074 to December 2105, was performed using the SST based on the future SST change of CMIP3 model ensemble mean.
• Please see the documentation and the reference papers for details of the model configuration and dataset.
• Also see this for sample data and animation of the present climate simulation.

The terms and conditions

• This dataset is published under CC BY 4.0 with the aim of making it widely available for research, education, and other activities.
• Please cite the following reference(s) if you publish a paper or report using this dataset. We would be grateful if you could provide us with publication information.
  • Reference paper (present climate simulation)
    • C. Kodama, Y. Yamada, A. T. Noda, K. Kikuchi, Y. Kajikawa, T. Nasuno, T. Tomita, T. Yamaura, H. G. Takahashi, M. Hara, Y. Kawatani, M. Satoh, and M. Sugi (2015), A 20-year climatology of a NICAM AMIP-type simulation, J. Meteor. Soc. Japan, 93, 4, 393-424, doi:10.2151/jmsj.2015-024.
  • Reference paper (future climate simulation)
    • M. Satoh, Y. Yamada, M. Sugi, C. Kodama, and A. T. Noda (2015), Constraint on future change in global frequency of tropical cyclones due to global warming, J. Meteor. Soc. Japan, 93, 4, 489-500, doi:10.2151/jmsj.2015-025.
• This dataset was created and has been maintained by the following projects. The copyright of the dataset is held by the participating institutes including JAMSTEC in the project.
  • The Strategic Programs for Innovative Research (SPIRE) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan, using the K computer at the RIKEN Advanced Institute for Computational Science (Proposal number hp120279, hp130010, and hp140219),
  • The FLAGSHIP2020 within the priority study4 (Advancement of meteorological and global environmental predictions utilizing observational “Big Data”) of MEXT,
  • Program for Promoting Researches on the Supercomputer Fugaku (Large Ensemble Atmospheric and Environmental Prediction for Disaster Prevention and Mitigation) of MEXT,
  • The Program for Risk Information on Climate Change (SOSEI) of MEXT,
  • The Integrated Research Program Advancing Climate Models (TOUGOU) of MEXT (Grant Number JPMXD0717935457),
  • The Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency of Japan (Grant Number JPMEERF20172R01), and
  • JSPS KAKENHI (Grant Number 17H04856 and 20H05728).
• JAMSTEC and other copyright holders of the dataset are not responsible to users for any direct and indirect damage that may be caused by the use of the dataset.

Publications

Publication list using the dataset.

• Peer-review papers
  • Yokoi, S., and Y. Kajikawa (2024): Precipitation diurnal cycle over tropical coastal regions represented in climate experiments with a global cloud-system resolving model. SOLA, 2024–2020, doi:10.2151/sola.2024-020.
  • D. Matsuoka, C. Kodama, Y. Yamada, M. Nakano (2023): Tropical cyclone dataset for a high-resolution global nonhydrostatic atmospheric simulation, Data in Brief, 48, doi:10.1016/j.dib.2023.109135.
  • T. Suematsu, H. Miura, C. Kodama, and D. Takasuka: Deceleration of Madden-Julian Oscillation speed in NICAM AMIP-type simulation associated with biases in the Walker circulation strength, Geophys. Res. Lett., 49, 11, e2022GL098628, doi:10.1029/2022GL098628.
  • Y. Na, Q. Fu, L. R. Leung, C. Kodama, and R. Lu: Mesoscale Convective Systems Simulated by a High-Resolution Global Nonhydrostatic Model over the United States and China, J. Geophys. Res., 127, 7, e2021JD035916, doi:10.1029/2021JD035916.
  • Y.-W. Chen, M. Satoh, C. Kodama, A. T. Noda, and Y. Yamada, Projection of high clouds and its link to ice hydrometeors: An approach by using longterm global cloud-system resolving simulations, J. Climate, accepted.
  • D. Matsuoka (2021), Classification of imbalanced cloud image data using deep neural networks: performance improvement through a data science competition. Prog. Earth Planet. Sci., 8, 68, doi:10.1186/s40645-021-00459-y.
  • Y. Na, R. Lu, Q. Fu and C. Kodama (2021), Precipitation characteristics and future changes over the southern slope of Tibetan Plateau simulated by a high-resolution global nonhydrostatic model, J. Geophys. Res., 126, 3, e2020JD033630, doi:10.1029/2020JD033630.
  • H. G. Takahashi, N. Kamizawa, T. Nasuno, Y. Yamada, C. Kodama, S. Sugimoto, M. Satoh (2020), Response of the Asian summer monsoon precipitation to global warming in a high-resolution global nonhydrostatic model, J. Climate, 33, 18, 8147-8164, doi:10.1175/JCLI-D-19-0824.1.
    • Press release: http://www.jamstec.go.jp/j/about/press_release/20200721/
  • M. Sugi, Y. Yamada, K. Yoshida, R. Mizuta, M. Nakano, C. Kodama, M. Satoh (2020), Future changes in the global frequency of tropical cyclone seeds, SOLA, 16, 70-74, doi:10.2151/sola.2020-012.
  • Y. Na, Q. Fu, and C. Kodama (2020), Precipitation probability and its future changes from a global cloud-resolving model and CMIP6 simulations, J. Geophys. Res., 125, 5, e2019JD031926, doi:10.1029/2019JD031926.
  • C. Kodama, B. Stevens, T. Mauritsen, T. Seiki, and M. Satoh (2019), A new perspective for future precipitation change from intense extratropical cyclones, Geophys. Res. Lett., 46, 21, 12435-12444, doi:10.1029/2019GL084001.
    • Press release: http://www.jamstec.go.jp/j/about/press_release/20191114/
  • C. Kodama, A. Kuwano-Yoshida, S. Watanabe, T. Doi, H. Kashimura, and T. Nasuno (2019), JAMSTEC Model Intercomparision Project (JMIP), JAMSTEC Report of Research and Development, 28, 5-34, doi:10.5918/jamstecr.28.5.
  • A. T. Noda, C. Kodama, Y. Yamada, M. Satoh, T. Ogura, and T. Ohno (2019): Responses of clouds and large-scale circulation to global warming evaluated from multi-decadal simulations using a global nonhydrostatic model, J. Adv. Model. Earth Syst., 11, 9, 2980-2995, doi:10.1029/2019MS001658. (Top 10% most downloaded paper 2018-2019)
  • Y. Yamada, C. Kodama, M. Satoh, M. Nakano, T. Nasuno, and M. Sugi (2019), High-resolution ensemble simulations of intense tropical cyclones and their internal variability during the El Ninos of 1997 and 2015, Geophys. Res. Lett., 46, 13, 7592-7601, doi:10.1029/2019GL082086.
    • Press release: http://www.jamstec.go.jp/j/about/press_release/20190703/
  • D. T. McCoy, P. R. Field, G. S. Elsaesser, A. Bodas-Salcedo, B. H. Kahn, M. D. Zelinka, C. Kodama, T. Mauritsen, B. Vanniere, M. Roberts, P. L. Vidale, D. Saint-Martin, A. Voldoire, R. Haarsma, A. Hill, B. Shipway, and J. Wilkinson (2019), Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations, Atmos. Chem. Phys., 19, 1147-1172, doi:10.5194/acp-19-1147-2019.
  • Nakano, M., Kikuchi, K., 2019: Seasonality of Intraseasonal Variability in Global Climate Models. Geophys. Res. Lett., 46, https://doi.org/10.1029/2019GL082443 .
  • M. Satoh, A. T. Noda, T. Seiki, Y.-W. Chen, C. Kodama, Y. Yamada, N. Kuba, and Y. Sato (2018), Toward reduction of the uncertainties in climate sensitivity due to cloud processes using a global non-hydrostatic atmospheric model, Prog. Earth and Planet. Sci., 5, 67, doi:10.1186/s40645-018-0226-1.
  • Matsuoka, D., Nakano, M., Sugiyama, D., Uchida, D., 2018: Deep learning approach for detecting tropical cyclones and their precursors in the simulation by a cloud-resolving global nonhydrostatic atmospheric model. Prog. Earth Planet. Sci., 5, 80.
    • Press release: http://www.jamstec.go.jp/j/about/press_release/20181219/
  • Y. Yamada, M. Satoh, M. Sugi, C. Kodama, A. T. Noda, M. Nakano and T. Nasuno (2017), Response of tropical cyclone activity and structure to global warming in a high-resolution global nonhydrostatic model, J. Climate, 30, 23, 9703-9724, doi:10.1175/JCLI-D-17-0068.1.
    • Press release: http://www.jamstec.go.jp/j/about/press_release/20170914/
  • K. Kikuchi, C. Kodama, T. Nasuno, M. Nakano, H. Miura, M. Satoh, A. T. Noda and Y. Yamada (2017), Tropical intraseasonal oscillation simulated in an AMIP-type experiment by NICAM, Climate Dyn., 48, 2507-2528, doi:10.1007/s00382-016-3219-z.
  • M. Satoh, H. Tomita, H. Yashiro, Y. Kajikawa, Y. Miyamoto, T. Yamaura, T. Miyakawa, M. Nakano, C. Kodama, A. T. Noda, T. Nasuno, Y. Yamada and Y. Fukutomi (2017), Outcomes and challenges of global high-resolution non-hydrostatic atmospheric simulations using the K computer, Prog. Earth and Planet. Sci., 4, 13, doi:10.1186/s40645-017-0127-8.
  • Y.-W. Chen, T. Seiki, C. Kodama, M. Satoh, A. T. Noda and Y. Yamada (2016), High cloud responses to global warming simulated by two different cloud microphysics schemes implemented in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), J. Climate, 29, 16, 5949-5964, doi:10.1175/JCLI-D-15-0668.1.
  • C. Kodama, Y. Yamada, A. T. Noda, K. Kikuchi, Y. Kajikawa, T. Nasuno, T. Tomita, T. Yamaura, H. G. Takahashi, M. Hara, Y. Kawatani, M. Satoh, and M. Sugi (2015), A 20-year climatology of a NICAM AMIP-type simulation, J. Meteor. Soc. Japan, 93, 4, 393-424, doi:10.2151/jmsj.2015-024.
  • M. Satoh, Y. Yamada, M. Sugi, C. Kodama, and A. T. Noda (2015), Constraint on future change in global frequency of tropical cyclones due to global warming, J. Meteor. Soc. Japan, 93, 4, 489-500, doi:10.2151/jmsj.2015-025.
  • Y. Fukutomi, C. Kodama, Y. Yamada, A. T. Noda, and M. Satoh (2015), Tropical synoptic-scale wave disturbances over the western Pacific simulated by a global cloud-system resolving model, Theor. Appl. Climatol., 124, 737-755, doi:10.1007/s00704-015-1456-4.