Implementing microscopic charcoal particles into a global aerosol-climate model

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Gilgen, Anina, Adolf, Carole, Brügger, Sandra O., Ickes, Luisa, Schwikowski, Margit, van Leeuwen, Jacqueline F. N., Tinner, Willy, Lohmann, Ulrike
• Format: Article in Journal/Newspaper
• Language: English
• Published: European Geosciences Union 2018
• Subjects: 570 Life sciences; biology; 540 Chemistry; 580 Plants (Botany); ice core
• Online Access: https://boris.unibe.ch/119790/1/2018_AtmosChemPhys_18_11813.pdf; https://boris.unibe.ch/119790/

Microscopic charcoal particles are fire-specific tracers, which are ubiquitous in natural archives such as lake sediments or ice cores. Thus, charcoal records from lake sediments have become the primary source for reconstructing past fire activity. Microscopic charcoal particles are generated during forest and grassland fires and can be transported over large distances before being deposited into natural archives. In this paper, we implement microscopic charcoal particles into a global aerosol–climate model to better understand the transport of charcoal on a large scale. Atmospheric transport and interactions with other aerosol particles, clouds, and radiation are explicitly simulated. To estimate the emissions of the microscopic charcoal particles, we use recent European charcoal observations from lake sediments as a calibration data set. We found that scaling black carbon fire emissions from the Global Fire Assimilation System (a satellite-based emission inventory) by approximately 2 orders of magnitude matches the calibration data set best. The charcoal validation data set, for which we collected charcoal observations from all over the globe, generally supports this scaling factor. In the validation data set, we included charcoal particles from lake sediments, peats, and ice cores. While only the Spearman rank correlation coefficient is significant for the calibration data set (0.67), both the Pearson and the Spearman rank correlation coefficients are positive and significantly different from zero for the validation data set (0.59 and 0.48, respectively). Overall, the model captures a significant portion of the spatial variability, but it fails to reproduce the extreme spatial variability observed in the charcoal data. This can mainly be explained by the coarse spatial resolution of the model and uncertainties concerning fire emissions. Furthermore, charcoal fluxes derived from ice core sites are much lower than the simulated fluxes, which can be explained by the location properties (high altitude and steep ...