Severe Rapid Indian Monsoon Weakening Due To Emissions From 2023 Canadian Wildfires

The current repository contains inputs, products, and codes associated with the study by Rosu et al., "Severe Rapid Indian Monsoon Weakening Due To Emissions From 2023 Canadian Wildfires". This study investigates the short-term, large-scale impacts of the 2023 Canadian wildfire emissions on the Indian monsoon using the Earth System Model EC-Earth3 (EC-Earth3-AerChem configuration - FORCes branch [1-2]. For this work, two sets of simulations were conducted, one considering 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 simulations, specifically atmospheric temperature, cloud cover, precipitation, surface atmospheric pressure, zonal wind, meridional wind, and specific humidity. Moreover, this repository also contains the Himawari 8,9 data [6] and Aerosonde data [7] employed in this study. 

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://doi.org/10.24381/a05253c7

[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] Entry Terminal JP Himawari Datasets, Data Integration and Analysis Systems (DIAS), https://search.diasjp.net/en/dataset/Himawari_8_9 , ID Himawari_8_920251020094156-DIAS20221121113753-en

[7] University of Wyoming, College of Engineering, Department of Atmospheric Science, Atmospheric Soundings Repository, https://weather.uwyo.edu/upperair/sounding.html