Large-scale impacts of the 2023 Canadian wildfires on the Northern Hemisphere atmosphere

The current repository contains inputs, products and codes associated with the study by Rosu et al., "Large-scale impacts of the 2023 Canadian wildfires on the Northern Hemisphere atmosphere". This study investigates the short-term large-scale weather impacts of the 2023 Canadian wildfire emissions through the use the Earth System Model (ESM) EC-Earth3 [1]. It is noted that for this work, the EC-Earth3-AerChem configuration [2] (FORCes branch) was used. For the needs of this work, two sets of simulations took place, one while considering the fire emissions (NX) and one without (NC). Regarding the emissions used, the GFAS wildfire emission dataset was applied (refer to Kaiser et al. [3] and to [4]), while for the rest of the emissions, i.e. natural and anthropogenic, refer to van Noije et al. [2] and to [5]. The current repository contains the output derived from the aforementioned simulations, specifically black carbon AOD, cloud cover, organic AOD, total AOD, net downward radiation flux, secondary organic AOD, surface atmospheric pressure, atmospheric temperature, zonal wind, and meridional wind. Moreover, this repository also contains the MODIS AOD data [6] used in the study and the Python code used for post-processing the EC-Earth3 output. Finally, the AERONET V3 [7] and the MERRA-2 dataset [8] were also used in this work. 

References

[1] Döscher et al. (2022) The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6. Geosci Model Dev 15:2973–3020. https://doi.org/10.5194/gmd-15-2973-2022

[2] van Noije et al. (2021) EC-Earth3-AerChem: a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6. Geosci Model Dev 14:5637–5668. https://doi.org/10.5194/gmd-14-5637-2021

[3] Kaiser et al. (2012) Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power. Biogeosciences 9:527–554. https://doi.org/10.5194/bg-9-527-2012

[4] Copernicus Atmosphere Monitoring Service. CAMS Global Fire Assimilation System (GFAS) [Dataset]. ECMWF. https://ads.atmosphere.copernicus.eu/datasets/cams-global-fire-emissions-gfas

[5] EC-Earth Consortium (EC-Earth) (2020). EC-Earth-Consortium EC-Earth3-AerChem model output prepared for CMIP6 ScenarioMIP ssp370. Earth System Grid Federation. https://doi.org/10.22033/ESGF/CMIP6.4885  

[6] NASA Earth Observations, MODIS Aerosol Optical Depth (MODAL2_M_AER_OD) [Dataset]. NASA GSFC. https://neo.gsfc.nasa.gov/view.php?datasetId=MODAL2_M_AER_OD   

[7] NASA Goddard Space Flight Center, Aerosol Robotic Network (AERONET) Version 3 [Dataset]. NASA.  https://aeronet.gsfc.nasa.gov/new_web/draw_map_display_inv_v3.html  

[8] Global Modeling and Assimilation Office (GMAO) (2015), MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC). https://doi.org/10.5067/VJAFPLI1CSIV