loading page

Understanding top-of-atmosphere flux bias in the AeroCom Phase III models: a clear-sky perspective
  • +13
  • Wenying Su,
  • Lusheng Liang,
  • Gunnar Myhre,
  • Tyler J Thorsen,
  • Norman G. Loeb,
  • Gregory L. Schuster,
  • Paul Ginoux,
  • Fabien Paulot,
  • David Neubauer,
  • Ramiro Checa-Garcia,
  • Hitoshi Matsui,
  • Kostas Tsigaridis,
  • Ragnhild Bieltvedt Skeie,
  • Toshihiko Takemura,
  • Susanne E. Bauer,
  • Michael Schulz
Wenying Su
NASA Langley Research Center

Corresponding Author:[email protected]

Author Profile
Lusheng Liang
Science Systems & Applications Inc.
Author Profile
Gunnar Myhre
CICERO, Norway
Author Profile
Tyler J Thorsen
NASA Langley Research Center
Author Profile
Norman G. Loeb
NASA Langley Research Center
Author Profile
Gregory L. Schuster
NASA Langley Research Center
Author Profile
Paul Ginoux
Author Profile
Fabien Paulot
Author Profile
David Neubauer
ETH Zurich
Author Profile
Ramiro Checa-Garcia
Laboratoire des Sciences du Climat et de l'Environnement, IPSL
Author Profile
Hitoshi Matsui
Nagoya University
Author Profile
Kostas Tsigaridis
Center for Climate Systems Research, Columbia University, and NASA Goddard Institute for Space Studies
Author Profile
Ragnhild Bieltvedt Skeie
Center for International Climate and Environmental Research - Oslo (CICERO)
Author Profile
Toshihiko Takemura
Kyushu University
Author Profile
Susanne E. Bauer
NASA Goddard Institute for Space Studies, New York, NY, USA
Author Profile
Michael Schulz
Norwegian Meteorological Institute
Author Profile


Biases in aerosol optical depths (AOD) and land surface albedos in the AeroCom models are manifested in the top-of-atmosphere (TOA) clear-sky reflected shortwave (SW) fluxes. Biases in the SW fluxes from AeroCom models are quantitatively related to biases in AOD and land surface albedo by using their radiative kernels. Over ocean, AOD contributes about 25% to the 60°S-60°N mean SW flux bias for the multi-model mean (MMM) result. Over land, AOD and land surface albedo contribute about 40% and 30%, respectively, to the 60°S-60°N mean SW flux bias for the MMM result. Furthermore, the spatial patterns of the SW flux biases derived from the radiative kernels are very similar to those between models and CERES observation, with the correlation coefficient of 0.6 over ocean and 0.76 over land for MMM using data of 2010. Satellite data used in this evaluation are derived independently from each other, consistencies in their bias patterns when compared with model simulations suggest that these patterns are robust. This highlights the importance of evaluating related variables in a synergistic manner to provide an unambiguous assessment of the models, as results from single parameter assessments are often confounded by measurement uncertainty. We also compare the AOD trend from three models with the observation-based counterpart. These models reproduce all notable trends in AOD (i.e. decreasing trend over eastern United States and increasing trend over India) except the decreasing trend over eastern China and the adjacent oceanic regions due to limitations in the emission dataset.