Clouds and aerosols are inseparably coupled, linked via complex pathways of interaction whose outcome manifests in the macroscopic properties of precipitation and radiation fields. On the one hand, aerosol particles are required as cloud condensation nuclei from which cloud droplets do form. On the other hand, primary ice formation in the heterogeneous freezing range from 0 to approximately -40°C requires ice nucleating particles (INP) to be present in the aerosol reservoir. The ways in which aerosols and cloud particles interact are however controlled by the dynamics and thermodynamics of the atmospheric environment. Thermodynamics are considered to dominate the cloud microphysical properties because they control the amount of water vapour that is available for being transferred to either the liquid or the ice phase. This dominance makes it difficult to isolate aerosol-related effects in observations of cloud properties. As a consequence, virtually all currently available numerical weather prediction models do not take any interaction between aerosol and cloud properties into account. Nevertheless, it is well known that aerosol properties are subject to strong spatio-temporal variability which implies that under certain situations aerosols are likely to have considerable effects on the microphysical properties of clouds. Another consequence is that the lack of aerosol-cloud interaction or the assumption of constant aerosol conditions will introduce uncertainties to numerical simulations.

The direct numerical simulation of aerosol-cloud interaction processes is challenging because the spatiotemporal scales that are needed to be covered reach from the turbulent microscale up to the scale of precipitation processes. It is thus subject to observations to disentangle the signal of aerosol-cloud interaction processes from the dynamical and thermodynamically dominated observable meteorological features. Nonetheless, also the observation of aerosol-effects on cloud properties is difficult to achieve, considering that atmospheric conditions and aerosol load are frequently correlated, as it is for instance the case for southwesterly large-scale flows over central Europe which are usually accompanied by Saharan dust outbreaks. In addition, the northern hemisphere, for which currently most cloud and aerosol datasets exist, is expected to be permanently affected by considerable aerosol loads, be it from natural sources such as deserts and forests, or from anthropogenic sources such as industry or traffic. Actual contrasting of aerosol-free to aerosol-burden cloud environments under otherwise constant meteorological conditions may thus be hardly achievable at a single site or perhaps overall in the northern hemisphere.

 

1) Aerosol Conditions

A detailed analysis of aerosol properties from space or with passive sensors is hardly achievable. Using lidar techniques as the central component for our aerosol studies will provide insights into macrophysical and microphysical aerosol properties, ranging from the vertical layering of aerosols up to retrievals of profiles of aerosol particle number size distributions.

2) Mixed-phase clouds and precipitation

What is the phase portioning in mixed-phase cloud layers? How are the properties of mixed-phase clouds and precipitation related to variations in aerosol conditions and atmospheric dynamics? Will it be possible to distinguish primary ice formation processes from secondary ice formation? Can we clearly identify regionally varying cloud and precipitation properties that can be attributed to aerosol variability? Which measurement accuracy is required to disentangle thermodynamic from aerosol-related effects on clouds and precipitation?

3) Certain aerosol types as reservoir for cloud condensation nuclei and ice-nucleating particles

Laboratory studies show that the ability to form ice heterogeneously at temperatures between 0 and -40°C depends strongly on the type of aerosol particles involved in the cloud process. By conducting campaigns in the frame of DACAPO in regions of strongly varying aerosol conditions we will obtain observational datasets that can be used to evaluate the laboratory studies. In addition, the observations will allow to develop novel parameterizations for relating lidar-observed aerosol optical properties to the availability of nuclei for cloud condensation and ice crystals.

4) Radiative Closure

Radiative properties of clouds vary strongly with their microphysical and macrophysical structure. Is a radiation closure possible using the measured cloud and aerosol properties together with their radiative properties? Are there any biases left, which are not covered by our measurements? If yes, how can these differences be explained?

5) Modeling

Numerical weather prediction models currently assume constant aerosol conditions or even the absence of any aerosol effects on modeled cloud and precipitation properties. Do these assumptions, i.e., parameterizations, hold for all regions around the globe? Or can we identify the need for considering aerosol properties in parameterizations of cloud and precipitation processes?

Also, linking highly resolved measurements of cloud and aerosol properties, precipitation and dynamics requires novel modeling approaches that also take the size and number of involved particles into account. Forward operators are needed to translate modeled microphysical parameters to measurements. The current number and capabilities of such forward operators are limited and motivates additional development efforts.

6) Overarching objectives

Observations at key places of aerosol conditions around the globe as done in the frame of DACAPO are valuable not only for the scientific goals listed above. The datasets will also be used for the evaluation of satellite retrievals and to support new satellite missions in their starting phase. Such actions are already scheduled for the upcoming ESA missions ADM Aeolus and EarthCARE.

The availability of the long-term observations at remote station will also be used to identify and characterize the individual meteorological complexity of the different sites. Such information will be helpful for both, planning of future measurement missions, and for local authorities.