Multi-scale Simulations of Atmospheric Pollutants Using a Non-hydrostatic Icosahedral Atmospheric Model

  • Daisuke GotoEmail author
  • Teruyuki Nakajima
  • Dai Tie
  • Hisashi Yashiro
  • Yousuke Sato
  • Kentaroh Suzuki
  • Junya Uchida
  • Shota Misawa
  • Ryoma Yonemoto
  • Tran Thi Ngoc Trieu
  • Hirofumi Tomita
  • Masaki Satoh
Part of the Springer Remote Sensing/Photogrammetry book series (SPRINGERREMO)


We have developed a seamless global-to-regional model to calculate atmospheric aerosol chemistry by coupling existing aerosol and chemical modules to a global cloud-system-resolving model (NICAM-Chem). The model can simulate air pollutants with various grid sizes ranging from global low resolution (~200 km) on yearly scales to regional high resolution (~10 km) on monthly scales and global high resolution (<10 km) on weekly scales. To date, we have confirmed that the NICAM-Chem simulated aerosols at low-to-high resolutions, and global-to-regional scales are generally comparable to validated observations. Furthermore, the very recent availability of cutting-edge computational capabilities provided by the K computer at RIKEN in Japan enabled us to perform seasonal air pollution simulations with a high global resolution model (14 km), which generally reproduced the observed aerosol distributions. In this paper, we introduce the following application studies using the NICAM-Chem model: future scenario experiments, downscaling using results obtained by a coupled atmosphere-ocean model, estimation of human health due to PM2.5, simulations of radioactive matter using a regional model, and aerosol assimilation by a localized ensemble transform Kalman filter.


Air pollution Modeling Non-hydrostatic icosahedral atmospheric model Multi-scale 



We would like to express our gratitude to the MOEJ/S-12 members, especially Drs. T. Takemura, K. Sudo, Hanaoka, K. Ueda, and A. Takami. We also acknowledge A. Miyaji and R. Murata for their help of the simulation. We also thank the model developers: NICAM (, SPRINTARS (, and CHASER (, and the measurement: MODIS (, AERONET (, AEROS (, and NCEP ( Some of the authors were supported by MOEJ/S-12 (Grant Number 14426634), the SALSA project in RECCA/MEXT (Grant Number 10101026), a Grant-in-Aid for Young Scientists B (Grant Number 26740010), a Grant-in-Aid for Young Scientists A (Grant Number 17H04711) a Grant-in-Aid for Scientific Research on Innovative Areas (Grant Number 24110002), MOE/GOSAT, JST/CREST/EMS/TEEDDA (Grant Number 12101625), JAXA/EarthCARE, GCOM-C, and MEXT/VL for climate diagnostics. The model simulations were performed using the K computer at RIKEN in Japan (general use proposal numbers 140046, 150156, 160004, and 170017), the supercomputer HITACHI SR16000 System (yayoi) and PRIMEHPC FX10 at the Information Technology Centre, University of Tokyo, Japan, and the NEC SX-9/A(ECO) at the National Institute for Environmental Studies, Japan.


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Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  • Daisuke Goto
    • 1
    Email author
  • Teruyuki Nakajima
    • 2
  • Dai Tie
    • 3
  • Hisashi Yashiro
    • 4
  • Yousuke Sato
    • 4
    • 6
  • Kentaroh Suzuki
    • 5
  • Junya Uchida
    • 5
  • Shota Misawa
    • 5
  • Ryoma Yonemoto
    • 5
  • Tran Thi Ngoc Trieu
    • 2
  • Hirofumi Tomita
    • 4
  • Masaki Satoh
    • 5
  1. 1.National Institute for Environmental Studies, JapanTsukubaJapan
  2. 2.Earth Observation Research CenterJapan Aerospace Exploration AgencyTsukubaJapan
  3. 3.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  4. 4.RIKEN Advanced Institute for Computational ScienceKobeJapan
  5. 5.Atmosphere and Ocean Research InstituteUniversity of TokyoKashiwaJapan
  6. 6.Department of Applied Energy, Graduate School of EngineeringNagoya UniversityNagoyaJapan

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