ACCurate AEROsols in Climate Simulations (ACCAERO)

Acronym

ACCAERO

Description of the granted funding

Climate change mitigation and adaptation depend on our ability to predict climate. Aerosols (small particles in the air that interact with sunlight and clouds) and clouds cause a lot of uncertainty in climate models. A large part of this uncertainty comes from unknowns in the inputs to the model that inform it about emissions, properties and processes that affect aerosol and cloud. To better understand aerosols and clouds and their effect on climate, observations have been made from instruments on the ground, on aircraft and on satellites. We will use observations from all these platforms to improve a climate model. To do this, we use a machine learning technique to examine model predictions taking into account the major unknowns in the model aerosol and cloud inputs. By comparing these predictions to the observations, we can rule out model versions that are incompatible with observational evidence. This will reduce the model uncertainty, improving our ability to predict climate.
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Starting year

2024

End year

2026

Granted funding

Risto Makkonen Orcid -palvelun logo
283 966 €


Funder

Research Council of Finland

Funding instrument

Targeted Academy projects

Other information

Funding decision number

359165

Fields of science

Geosciences

Research fields

Meteorologia ja ilmakehätieteet, ilmastotutkimus