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Tightening constraints on BVOC-aerosol-cloud feedback through process-chain evaluation of Earth System Models

Authors

Blichner,  Sara
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Yli-Juuti,  Taina
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Mielonen,  Tero
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Holopainen,  Eemeli
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Heikkinen,  Liine
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Pöhlker,  Christopher
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Artaxo,  Paulo
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Meller,  Bruno Backes
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Scott,  Cat
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Svenhag,  Moa Sporre
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Svenhag,  Carl
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Partridge,  Daniel
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Tovazzi,  Emanuele
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Kokkola,  Harri
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Virtanen,  Annele
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Riipinen,  Ilona
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Blichner, S., Yli-Juuti, T., Mielonen, T., Holopainen, E., Heikkinen, L., Pöhlker, C., Artaxo, P., Meller, B. B., Scott, C., Svenhag, M. S., Svenhag, C., Partridge, D., Tovazzi, E., Kokkola, H., Virtanen, A., Riipinen, I. (2023): Tightening constraints on BVOC-aerosol-cloud feedback through process-chain evaluation of Earth System Models, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4103


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022042
Abstract
As the climate continues to warm, a range of feedbacks are expected by the response of vegetation. One of these is the BVOC-aerosol-cloud feedback, initiated by vegetation emitting more biogenic volatile organic compounds (BVOCs) with higher temperature. Once in the atmosphere, these BVOCs are oxidised and can then produce large amounts of biogenic secondary organic aerosols (BSOA) which again cool the surface both directly and through cloud-aerosol interactions (BSOA-aerosol feedback). The strength of this feedback, however, is poorly constrained, with some models suggest it holds significant importance, whereas others suggesting it to be completely negligible. Here, we use two unique long term observational datasets representing the boreal and tropical forests respectively, together with satellite data, to evaluate the BVOC-aerosol-cloud feedback in four ESMs through its chain of processes, using natural variability as a proxy for perturbed states of the climate in both models and observations. We show that the highest modelled feedback in the boreal zone is very likely an overestimate, but also that all the models seem to underestimate the feedback in the tropics. Taking full advantage of the growing number of long-term observational datasets for process evaluation in ESMs shows great promise for pin-pointing areas for model improvement, understanding and constraining variability modelled feedbacks and forcing.