DOI: 10.26050/wdcc/quaerere_ccncams_v1
title: Cloud condensation nuclei (CCN) numbers derived from CAMS reanalysis EAC4 (Version 1)

description: Project: Quantifying aerosol-cloud-climate effects by regime - The goal of QUAERERE (Latin for researching) is a reliable, observations-based, global quantification of aerosol indirect effects, which would also imply a constraint on climate sensitivity and thus climate predictions. This goal is now reachable combining recent advances in different disciplines: (i) a decade-long satellite dataset involving retrievals of the relevant quantities is now available, complemented by a complete aerosol dataset from a new reanalysis; (ii) on the basis of high-resolved numerical weather prediction models, which include parameterisations of aerosol cycles and cloud-precipitation microphysics, cloud-system resolving simulations at a regional scale are now possible; reliable simulations beyond idealised cases are thus possible. These tools are complemented by comprehensive global climate models and reference ob­ servations from ground-based sites. The problem in aerosol-cloud-climate effects is in its complexity: Various processes counteract each other, and large spatiotemporal variability of clouds buffers the forcing effects. QUAERERE proposes a two-fold divide-and-conquer approach to this complex problem: (i) aerosol-cloud-climate effects will be investigated by regime; this allows to circumvent the problem of aerosol-cloud-climate effects being buffered when averaging over different regimes; and (ii) by investigating individual terms contributing to the aerosol-cloud-climate effects separately; this allows to analyse individual statistical relationship in satellite observations and model results consistently, and to perform model sensitivity studies for cause-effect attribution. QUAERERE is funded by European Research Council (Call ERC-2012-StG, PE10, FP7 ideas starting grant 306284).
Summary: Determining concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, a process key for aerosol-cloud interactions (ACI). However, due to sparse coverage of in-situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source, temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN is one of the goals for quantifying ACI processes and achieving uncertainty reduced estimates of their associated radiative forcing. Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service (CAMS) reanalysis (RA: EAC4) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models.

Acknowledgement: Generated using Copernicus Atmosphere Monitoring Service information [2003-2024]. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains. The source data is downloaded from the Copernicus Atmosphere Monitoring Service (CAMS) Atmosphere Data Store (ADS)
(https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-reanalysis-eac4?tab=overview).