The interactions between aerosols and clouds are among the least understood climatic processes and were studied over Ascension Island. A ground-based UV polarization lidar was deployed on Ascension Island, which is located in the stratocumulus-to-cumulus transition zone of the southeastern Atlantic Ocean, to infer cloud droplet sizes and droplet number density near the cloud base of marine boundary layer cumulus clouds. The aerosol–cloud interaction (ACI) due to the presence of smoke from the African continent was determined during the monsoonal dry season. In September 2016, a cloud droplet number density ACIN of 0.3 ± 0.21 and a cloud effective radius ACIr of 0.18 ± 0.06 were found, due to the presence of smoke in and under the clouds. Smaller droplets near the cloud base makes them more susceptible to evaporation, and smoke in the marine boundary layer over the southeastern Atlantic Ocean will likely accelerate the stratocumulus-to-cumulus transition. The lidar retrievals were tested against more traditional radar–radiometer measurements and shown to be robust and at least as accurate as the lidar–radiometer measurements. The lidar estimates of the cloud effective radius are consistent with previous studies of cloud base droplet sizes. The lidar has the large advantage of retrieving both cloud and aerosol properties using a single instrument.@en

Accurate lidar-based measurements of cloud optical extinction, even though perhaps limited to the cloud base region, are useful. Arguably, more advanced lidar techniques (e.g. Raman) should be applied for this purpose. However, simpler polarisation and backscatter lidars offer a number of practical advantages (e.g. better resolution and more continuous and numerous time series). In this paper, we present a backscatter lidar signal inversion method for the retrieval of the cloud optical extinction in the cloud base region. Though a numerically stable method for inverting lidar signals using a far-end boundary value solution has been demonstrated earlier and may be considered as being well established (i.e. the Klett inversion), the application to high-extinction clouds remains problematic. This is due to the inhomogeneous nature of real clouds, the finite range resolution of many practical lidar systems, and multiple scattering effects. We use an inversion scheme, where a backscatter lidar signal is inverted based on the estimated value of cloud extinction at the far end of the cloud, and apply a correction for multiple scattering within the cloud and a range resolution correction. By applying our technique to the inversion of synthetic lidar data, we show that, for a retrieval of up to 90g m from the cloud base, it is possible to obtain the cloud optical extinction within the cloud with an error better than 5g %. In relative terms, the accuracy of the method is smaller at the cloud base but improves with the range within the cloud until 45g m and deteriorates slightly until reaching 90g m from the cloud base.

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This thesis presents a new method for the continuous observation of aerosol-cloud interactions with ground-based remote sensing instruments. The described method is based on the measurements from UV lidar, radar and radiometer. All of those instruments are capable of obtaining continuous, high-resolution measurements. In order to facilitate its easy implementation to measuring sites the method is based on a standardized Cloudnet data format. The main goal is to monitor the change in the cloud droplet concentration, as obtained from the measurements by cloud radar and radiometer, to then compare it to the aerosol background below the cloud, represented by the attenuated backscatter measured by UV lidar. The response of the cloud to the aerosol background can best be measured when the amount of available water is kept constant. Hence the measurements from the radiometer, specifically the derived liquid water path (LWP), which is used to constrain the cloud response. Based on the value of the LWP, analyzed data is divided into bins and for each of these the relation between cloud droplet effective radius and integrated value of the attenuated backscatter are calculated. This metric is called ACIr and is used to describe the strength of the relation between the clouds microphysical properties and the aerosol background below the cloud. The method was first tested and applied to pristine marine clouds as measured at the Graciosa Island in the Azores. The application was then extended to the Cabauw site located in the Netherlands. On both sites a decrease in the cloud size was observed in combination with a simultaneous increase of the aerosol loading below the cloud. This relation was particularly strong for a mid range of the LWP, between 40 and 60 gm-2 LWP for the cases from Azores and between 60 and 105 gm-2 for the cases from the Netherlands. These results indicate that the process of aerosol-cloud interactions is a predominant one only under those conditions where a mid amount of water is available. When the amount of available water is less than 40 gm-2 this process is harder to observe, due to the initial stage of cloud formation. In the case of LWP above 105 gm-2 other cloud processes, such as collision and coalescence, seem to be predominant. The results from the analysis of the Cabauw dataset, which was the more extensive dataset, also made clear that updraft within the cloud plays a significant role in invigorating aerosol particles into becoming cloud droplets. A possible extension of the presented method includes obtaining optical cloud extinction from the UV lidar measurements. The presented retrieval method can obtain very reliable results when compared to the simulated results. Hence the cloud optical extinction can be used as a proxy of the cloud properties and the described method of monitoring aerosol-cloud interactions can be applied to measurement sites where only UV lidar and radiometer are present. This thesis shows that ground-based remote sensing instruments used in synergy can efficiently and continuously monitor aerosol–cloud interactions.@en

The representation of aerosol-cloud interaction (ACI) processes in climate models, although long studied, still remains the source of high uncertainty. Very often there is a mismatch between the scale of observations used for ACI quantification and the ACI process itself. This can be mitigated by using the observations from groundbased remote sensing instruments. In this paper we presented a direct application of the aerosol-cloud interaction monitoring technique (ACI monitoring). ACI monitoring is based on the standardised Cloudnet data stream, which provides measurements from ground-based remote sensing instruments working in synergy. For the data set collected at the CESAR Observatory in the Netherlands we calculate ACI metrics. We specifically use attenuated backscatter coefficient (ATB) for the characterisation of the aerosol properties and cloud droplet effective radius (r_e) and number concentration (N_d) for the characterisation of the cloud properties. We calculate two metrics: ACI_r Dln(r_e)/ln(ATB) and ACI_N Dln(N_d)/ln(ATB). The calculated values of ACIr range from 0.001 to 0.085, which correspond to the values reported in previous studies. We also evaluated the impact of the vertical Doppler velocity and liquid water path (LWP) on ACI metrics. The values of ACI_r were highest for LWP values between 60 and 105 gm^-2. For higher LWP other processes, such as collision and coalescence, seem to be dominant and obscure the ACI processes. We also saw that the values of ACI_r are higher when only data points located in the updraught regime are considered. The method presented in this study allow for monitoring ACI daily and further aggregating daily data into bigger data sets.

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