Clouds play an important role in precipitation, solar radiation budget and electrification of Earth's atmosphere. The presence of small ice crystals in clouds and their morphology can complicate parametrisation and climate modelling, consequently leading to a net cooling feedback on climate. In situ airborne measurements provide single particle characterisation with high temporal and spatial resolution allowing better understanding of atmosphericprocesses of ice nucleation and growth. Simulations of the preindustrial clouds and accurate characterisation and comparison of the instruments require a well-controlled and often pristine environment. The experimental chamber setup allows simulations of these and other conditions. The microphysical features of the micrometric ice particles in clouds were examined in a laboratory setup, at numerous sub-zero temperatures [-10 to -50 ⁰C]. The following instruments were sampling the content of the CLOUD chamber air volume: Cloud and Aerosol Spectrometer with Polarisation (CASPOL), Particle Phase Discriminator mark 2 (PPD-2K, Karlsruhe edition), 3-View Cloud Particle Imager (3V-CPI), and the Scattering-Intensity-Measurements-for-the-Optical-detectioN-of-icE (SIMONE-Junior). Cluster analysis was applied to the data collected with CASPOL and compared with results from the other probes. We were able to discriminate and map the aerosol and cloud particles in the pristine chamber environment using polarisation ratios (Dpol/Backscatter and Dpol/Forwardscatter) of the scattered light. We demonstrate the sensitivity of the instruments in detecting secondary organic aerosol (SOA) phase transitions. Then, we show the ability of the viscous SOA to nucleate ice in a series of SPectrometer for Ice Nuclei (SPIN) measurements. The detected viscous SOA ice nucleation efficiency may affect global modelling and estimations of ice water content in the atmosphere. Subsequently, the analysis and discrimination technique used in the CLOUD chamber was applied to airborne measurements to test its efficiency and to retrieve the composition of clouds. Data from four flight campaigns on board of the FAAM BAe-146 were analysed: Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA), COnvective-Precipitation-Experiment (COPE) in south England, CIRrus Coupled Cloud-Radiation EXperiment (CIRCCREX), and PIKNMIX in Scotland. In these and other flights, we were able to identify unique clusters such as salts, minerals, organics, volcanic ash, water and ice, confirming some of the offline laboratory elemental analysis results, and providing complementary information. Single particle polarisation measurements were compared with bulk depolarisation, diffraction patterns, and imaging. Most of the optical instruments still suffer from ambiguity in phase derivation (i.e. water/ice) of optically spherical small shapes. We discuss some of the limitations of optical cloud particle discrimination in different ambient conditions and offer possible solutions to reduce the uncertainty, e.g., surface complexity derivation from scatteringpatterns. Our findings will help to develop better instruments and improve the models which are used for weather forecasts and climate change predictions.

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Factors governing the efficiency of convective moistening in the tropical upper troposphere between 15

A lack of quality data on high clouds has led to inadequate representations within global weather and climate models. Recent advances in spaceborne measurements of the Earth’s atmosphere have provided complementary information on the interior of these clouds. This study demonstrate how an array of space-borne measurements can be used and combined, by close co-located comparisons in space and time, to form a more complete representation of high cloud processes and properties. High clouds are found in the upper atmosphere, where sub-zero temperatures frequently result in the formation of cloud particles that are composed of ice. Weather and climate models characterise the bulk properties of these ice particles to describe the current state of the cloud-sky atmosphere. By directly comparing measurements with simulations undertaken at the same place and time, this study demonstrates how improvements can be made to the representation of cloud properties. The results from this study will assist in the design of future cloud missions to provide a better quality input. These improvements will also help improve weather predictions and lower the uncertainty in cloud feedback response to increasing atmospheric temperature. Most clouds are difficult to monitor by more than one instrument due to continuous changes in: large-scale and sub-cloud scale circulation features, microphysical properties and processes and characteristic chemical signatures. This study undertakes co-located comparisons of high cloud data with a cloud ice dataset reported from the Microwave Limb Sounder (MLS) instrument onboard the Aura satellite that forms part of the A-train constellation. Data from the MLS science team include vertical profiles of temperature, ice water content (IWC) and the mixing ratios of several trace gases. Their vertical resolutions are 3 to 6 km. Initial investigations explore the link between cloud-top properties and the longwave radiation budget, developing methods for estimating cloud top heights using; longwave radiative fluxes, and IWC profiles. Synergistic trios of direct and indirect high cloud measurements were used to validate detections from the MLS by direct comparisons with two different A-train instruments; the NASA Moderate-resolution Imaging Spectroradiometer (MODIS) and the Clouds and the Earth’s Radiant Energy System (CERES) onboard on the Aqua satellite. This finding focuses later studies on two high cloud scene types that are well detected by the MLS; deep convective plumes that form from moist ascent, and their adjacent outflows that emanate outwards several hundred kilometres. The second part of the thesis identifies and characterises two different high cloud scenes in the tropics. Direct observational data is used to refine calculations of the climate sensitivity to upper tropospheric humidity and high cloud in different conditions. The data reveals several discernible features of convective outflows are identified using a large sample of MLS data. The key finding, facilitated by the use of co-location, reveals that deep convective plumes exert a large longwave warming effect on the local climate of 52 ± 28Wm−2, with their adjacent outflows presenting a more modest warming of 33 ± 20Wm−2.