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About I3RC

The I3RC project was initiated by Robert Cahalan in the mid 1990s, with funding from the Department of Energy Atmospheric Radiation Measurement Program and the NASA Radiation Sciences Program, and with endorsements from International Radiation Commission and GEWEX Radiation Panel. Its goals include: 

  • comparing methods available for 3D atmospheric radiative transfer calculations
  • providing benchmark results for testing and debugging 3D radiative transfer codes
  • publishing an open source toolkit (community 3D Monte Carlo code)
  • helping atmospheric science education by creating an archive of illustrative images and other resources on 3D radiative transfer
  • Participation is open to anyone interested in 3D radiative transfer. (Please sign up here.) 

Latest news

  • The website of the I3RC project moved to a new server and is now at Please update your bookmarks accordingly.
  • A special issue entitled Remote Sensing of Cloud and Aerosol Properties in a Three-Dimensional Atmosphere is prepared by the journal Remote Sensing. Manuscript submissions are welcome until December 31, 2020.
  • The I3RC online simulator of 3D radiative transfer has been released.
  • Several presentations on 3D radiative transfer were given at the 15th Conference on Atmospheric Radiation of the American Meteorological Society, which took place in Vancouver, Canada, on July 9-13, 2018.
  • The 3D radiative transfer model MCBRaT3D has been released to the public in 2018. MCBRaT3D is an extended version of the I3RC Monte Carlo model that can perform 3D broadband solar radiative transfer simulations.
  • A session entitled Frontiers and Challenges in the Applications of Radiative Transfer (with interests including 3D radiative transfer) was held at the Asia Oceania Geosciences Society (AOGS) 2018 meeting that took place in Honolulu, Hawaii on June 3-8, 2018.
  • A session entitled 3D Cloud Modeling as a Tool for 3D Radiative Transfer, and Conversely was held at the 2017 AGU-JpGU Joint Assembly in Chiba, Japan. The session included 18 presentations.
  • The 3D radiative transfer model IMC-emission has been released to the public in 2017. IMC-emission is an extended version of the I3RC Monte Carlo model that can consider thermal emission in monochromatic 3D radiative transfer simulations.

Highlighted image

Assessing MODIS MBL cloud retrieval using Large-Eddy Simulation and 3D RT model

Marine Boundary Layer (MBL) clouds are thought to be at the heart of cloud feedback uncertainties in climate models. How and to what extent man-made aerosols may affect the properties of MBL clouds is poorly understood. Measures to address these issues rely heavily on satellite-based remote sensing of the microphysical and optical properties of these clouds. The image shows recent research activities by branch scientists of assessing how the 3D cloud structure (i.e., cloud top entrainment, cloud particle size vertical variation and drizzle) and 3D radiative effects influence MODIS MBL cloud retrieval. MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. The upper panel shows the cloud optical thickness simulated from a Large-Eddy Simulation (LES) model (Stevens et al. 1998 JAS). The middle panel shows the differences in the upwelling radiances at three wavelengths used for MODIS cloud retrieval at nadir between 3D (simulated using I3RC) and 1D (simulate using DISORT) radiative transfer simulations. The solar zenith and azimuth are 60° and 0° (x+ direction), respectively. In 3.7 um simulation, only the solar reflectance component is considered (i.e., assuming the thermal component is perfectly corrected by the atmospheric correction step in MODIS retrieval). MODIS cloud effective radius retrievals based on simulated radiances are shown in the lower panel. Note that in the shadowing region(for example around 4km), the cloud appears darker in the 3D simulation than the 1D simulation due to the shadowing effect As a result, the effective radius retrievals based on 3D radiance are larger in these regions. This research will help scientists to better understand how cloud structure and 3D radiative effects influence satellite retrieval data.

Zhibo Zhang and Steven Platnick

Image archive