EGU2020-763, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-763
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluation of radiation forcing from snow pollution by black carbon emissions from forest fires using the SNICAR radiation model and data from the INMCM5 climate model

Alexey Chernenkov1, Sergey Kostrykin2, and Veronika Ginzburg3
Alexey Chernenkov et al.
  • 1Moscow Institute of Physics and Technology (National Research University), Phystech School of Applied Mathematics and Informatics, Dolgoprudny, Moscow region, Russian Federation (chernenkov.ayu@phystech.edu)
  • 2Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences, Moscow, Russia
  • 3Yu.A. Izrael Institute of Global Climate and Ecology, Moscow, Russia

In this study, we consider the effect on climate of one of the atmospheric aerosols - black carbon. Estimates are obtained for changes in the surface albedo and additional radiation forcing associated with account for BC emissions from forest fires. For this, we used the data of a historical experiment with the climate model INMCM5 [1] developed at the INM RAS, as well as the one-dimensional SNICAR (SNow-ICe-AErosole radiation model) [2] model of radiation transfer in the snow layer. In the historical experiment with the climate model INMCM, carried out as part of the CMIP6 project [3], the climate of the Earth system was simulated from 1850 to 2014. In this case, the external forcing on the Earth system was set as close as possible to the observed one.

Based on the monthly average model data on the height of the snow cover, as well as the flux of black carbon from the atmosphere, assuming uniform mixing of the precipitation of BC in the snow, the concentration of BC in each cell of the model grid was calculated. Then, using the obtained concentrations, radiation forcing caused by BC emission from forest fires was calculated using the SNICAR model.

Since anthropogenic emissions of black carbon far exceed emissions resulting from the burning of biomass, two seasons that differ in the intensity of forest fires were chosen to study the role of forest fires in the radiation balance. Based on the GFED (Global Fire Emission Database) [4], 1998 (corresponding to large emissions of black carbon at mid-latitudes into the atmosphere caused by biomass burning) and 2001 (corresponding to small emissions) were selected as such seasons. Moreover, it is known that the anthropogenic source for the specified period changed slightly. Additional forcing amounted to 2-3 W/m2  locally with a relative estimation error of the order of 10-15%. The results of calculations of the average annual radiation forcing for the mainland are in good agreement with [2], [5].

This work is supported by RFBR project No.18-05-60183.

List of references:

  1. Volodin E. M., Mortikov E. V., Kostrykin S. V., Galin V. Ya., Lykossov V. N., Gritsun A.S., Diansky N. A., Gusev A. V., Yakovlev N.G. Simulation of the present-day climate with the climate model INMCM5, Climate Dynamics, doi:10.1007/s00382-017-3539-7, 2017.
  2. Flanner M.G., Zender C.S., Randerson J.T., Rasch P.J., Present-day climate forcing and response from black carbon in snow, Journ. Geophys. Research, 112, D11202, doi:10.1029/2006JD008003, 2007.
  3. Eyring, V. [et al.].: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937-1958, doi:10.5194/gmd-9-1937-2016, 2016.
  4. Lamarque, J.-F. [et al.]: Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017–7039, doi:10.5194/acp-10-7017-2010, 2010.
  5. Mark Flanner, Charlie Zender, Phil Rasch, Improving Snow and Aerosol Physics in CLM and CCSM with SNICAR, 2005.

How to cite: Chernenkov, A., Kostrykin, S., and Ginzburg, V.: Evaluation of radiation forcing from snow pollution by black carbon emissions from forest fires using the SNICAR radiation model and data from the INMCM5 climate model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-763, https://doi.org/10.5194/egusphere-egu2020-763, 2019

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