CLOUD-DOC is to establish a network of early stage researchers (ESRs, all PhD students) at 12 institutions across Europe (10 EU-funded). The role of aerosol nucleation for atmospheric aerosol, clouds and climate is investigated. The focus of investigations will be to study under well-controlled laboratory conditions the oxidation chemistry, aerosol nucleation and growth processes that are responsible for aerosol particle formation in cold regions of the atmosphere: a) Arctic environments, b) the upper troposphere above the Asian monsoon region, c) the upper troposphere above tropical rain forests, and d) the Southern Ocean. The major research activity of the network will be two sets of joint experiments carried out at the CLOUD aerosol chamber at CERN to which all ESRs contribute. At the CLOUD chamber nucleation experiments are performed at an unprecedented level of precision and completeness using highly innovative instrumentation. A well-structured research and training plan is set up for every ESR as well as a comprehensive, quality-controlled supervision. A high-quality PhD training is arranged. The ESRs are brought together for network training events such as summer schools and workshops for integral data analysis. Courses by world-leading experts are taught spanning from general atmospheric aerosol chemistry and physics to specialized sessions including the role of aerosol for clouds, climate and also health. The summer schools and workshops are specifically tailored to the needs of the trainees. Transferable skills training includes courses on scientific writing, presentation skills, interaction with media, entrepreneurship, IPR, management, gender dimension and diversity in science, and good scientific conduct. The partners from the private sector (1 beneficiary, 4 partners) are closely integrated in the action.

The motivation for this project is that aerosols have persistently been assessed by the IPCC as the largest uncertainty in the radiative forcing of climate over the industrial period. This means that our ability to understand temperature changes over the industrial period is hampered by very poorly constrained aerosol processes in models. The main uncertainty is due to the effect that aerosols have on clouds - the so-called aerosol indirect effect by which anthropogenic aerosols make clouds more reflective. In the IPCC assessment, the range of predictions of the aerosol indirect forcing lies between -0.4 to -1.8 Wm-2, a far larger range than associated with CO2 forcing (1.6-1.9 Wm-2). Thus, to improve our understanding of climate change, we need to reduce the uncertainty in the aerosol indirect effect. The controlling factor in the indirect effect is the concentration in the atmosphere of "cloud condensation nuclei" (CCN). CCN are a subset of the aerosol particles in the atmosphere, typically larger than 50 nm diameter and sufficiently water soluble to form cloud drops. Only recently, global models have been developed that are able to explicitly simulate CCN concentrations. This opens up the possibility of reducing model uncertainty by exploiting extensive measurements of CCN that have been made over many years. We propose to undertake the first ever comprehensive synthesis of global CCN and related aerosol observations within the UK aerosol-chemistry-climate model. The overall aim is to reduce uncertainty in the indirect effect by constraining modern aerosol as much as possible based on present observing systems and models. We will reduce the uncertainty by producing a global model of CCN with well defined uncertainties that are constrained by worldwide observations. We will then use the "calibrated" aerosol model to quantify the indirect radiative forcing and its uncertainty. We will also use the new and better model to understand the sources of CCN in different environments, and thereby the factors that will drive future changes in the concentration. As a spin-off of the project we will also be able to use the model and data to identify the regions or environments in which new measurements would have the greatest impact on reducing the uncertainty further. An important new aspect of the project will be the use of new uncertainty information about the global model. In most similar studies it has been possible to run the model only a few times. However, in reality the model has a wide uncertainty range due to the very large number of uncertain processes in the model. In this project we will use new information that tells us how the model behaves under all possible assumptions of uncertainty. From this collection of model runs we will be able to identify the best possible model in all parts of the world. This procedure is known as "calibration", and it has not been attempted before for a complex global model. With this approach we can be sure the model is as close to observations of CCN as can presently be achieved.

As a cloud moves through environmental air, cloudy and cloud free air mix at the cloud edges in the entrainment process. Entrainment is a key cloud process central to understanding cloud morphology and microphysical processes such as precipitation formation. After decades of research, no reliable formulation exists that allows to describe and understand entrainment in terms of cloud- and environmental physical quantities ("the entrainment puzzle"). Differences in representation of entrainment in climate models are a main cause for spread in climate sensitivity estimates. The realistic treatment of entrainment in climate models will help to reduce a large part of the uncertainty in predictions of climate sensitivity. This project aims at Solving The Entrainment Puzzle (STEP): - By identification of the main physical parameters that govern the amount of air entrained into and detrained from clouds using controlled laboratory measurements. - By translating the experimental results into a new mathematical formulation to use in Large Eddy Simulations of clouds using computational fluid dynamics modelling. In a unique approach, STEP will combine observations from a novel turbulent cloud chamber, computational fluid dynamics, and Large Eddy Simulations to develop a new reliable entrainment calculation scheme. Solving the entrainment puzzle will allow quantifying the entrainment processes reliably and thus deliver the basis for climate model improvements. The STEP project builds on my expertise in cloud microphysics and dynamics gained at various international institutes and will be accomplished at a leading international research institution. The host will provide me with excellent complementary training and career development opportunities. Through various dissemination and communication activities, STEP will contribute to the visibility and excellence of the European Science Area, addressing one of the Europe 2020 strategy main targets "Climate Change and Energy".