Project Details
Cloud Droplet Number Concentration – satellite retrievals Advanced by Atmospheric models for Assessing Aerosol-Cloud Interactions
Applicant
Professor Dr. Johannes Quaas
Subject Area
Atmospheric Science
Term
since 2020
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 446279238
Aerosol-cloud interactions imply an effective radiative forcing that is a key uncertainty when understanding and interpreting observed climate change. Global data are needed to better quantify the relevant processes, but a key quantity – the cloud droplet number concentration (CDNC, Nd) - is not available from operational products. Building on preliminary work, CDNC4aci will work towards reliable retrievals of Nd from satellites in close observations – model interaction: newly-available cloud-resolving simulations will inform the retrieval development and refinement, and the data, in turn, will be used to improve understanding and quantification of aerosol-cloud interactions in the model and from statistical analysis. Specifically, the project will include multi-angle and polarimetric observations for better Nd data, it will revise retrieval approaches using model-informed cloud vertical stratification conditioned on cloud regime and thoroughly quantify and correct retrieval errors and biases and assess aerosol-cloud interaction processes from data. The project will assess the cloud-process information in the retrieved data using model sensitivity analyses, it will make model and data comparable by forward-simulating measured polarized radiances and retrieval products, and assess aerosol-cloud interactions in a global model evaluated using the data and the process understanding in model-data assessment. The final goal is a consistent quantification of the aerosol-cloud forcing between model and data analysis.
DFG Programme
Research Grants
International Connection
France
Partner Organisation
Agence Nationale de la Recherche / The French National Research Agency
Cooperation Partner
Professor Odran Sourdeval, Ph.D.