Articles | Volume 14, issue 20
https://doi.org/10.5194/acp-14-11475-2014
https://doi.org/10.5194/acp-14-11475-2014
Research article
 | 
30 Oct 2014
Research article |  | 30 Oct 2014

Simulating black carbon and dust and their radiative forcing in seasonal snow: a case study over North China with field campaign measurements

C. Zhao, Z. Hu, Y. Qian, L. Ruby Leung, J. Huang, M. Huang, J. Jin, M. G. Flanner, R. Zhang, H. Wang, H. Yan, Z. Lu, and D. G. Streets

Abstract. A state-of-the-art regional model, the Weather Research and Forecasting (WRF) model (Skamarock et al., 2008) coupled with a chemistry component (Chem) (Grell et al., 2005), is coupled with the snow, ice, and aerosol radiative (SNICAR) model that includes the most sophisticated representation of snow metamorphism processes available for climate study. The coupled model is used to simulate black carbon (BC) and dust concentrations and their radiative forcing in seasonal snow over North China in January–February of 2010, with extensive field measurements used to evaluate the model performance. In general, the model simulated spatial variability of BC and dust mass concentrations in the top snow layer (hereafter BCS and DSTS, respectively) are consistent with observations. The model generally moderately underestimates BCS in the clean regions but significantly overestimates BCS in some polluted regions. Most model results fall within the uncertainty ranges of observations. The simulated BCS and DSTS are highest with > 5000 ng g−1 and up to 5 mg g−1, respectively, over the source regions and reduce to < 50 ng g−1 and < 1 μg g−1, respectively, in the remote regions. BCS and DSTS introduce a similar magnitude of radiative warming (~ 10 W m−2) in the snowpack, which is comparable to the magnitude of surface radiative cooling due to BC and dust in the atmosphere. This study represents an effort in using a regional modeling framework to simulate BC and dust and their direct radiative forcing in snowpack. Although a variety of observational data sets have been used to attribute model biases, some uncertainties in the results remain, which highlights the need for more observations, particularly concurrent measurements of atmospheric and snow aerosols and the deposition fluxes of aerosols, in future campaigns.

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