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Clouds play a vital role in Earth’s energy balance by modulating atmospheric processes, thus it is crucial to have accurate information on their spatial and temporal variability. Furthermore, clouds are relevant in those processes involved in aerosol-cloud-radiation interactions. The work conducted and presented herein concentrates on the retrievals of cloud properties, as well as their application for climate studies. While remote sensing observation systems have been used to analyze the atmosphere and observe its changes for the last decades, climate models predict how climate will change in the future. Altogether, these sources of observations are needed to better understand cloud processes and their impact on climate. In this thesis aerosol and cloud properties from the three above mentioned sources are applied to evaluate their potential in representing cloud properties and applicability in climate studies on local, regional and global scales. One aim of this thesis focuses on evaluating cloud parameters from ground-based remote-sensing sensors and from climate models using the MODerate Imaging Spectroradiometer (MODIS) data as a reference dataset. It is found that ground-based measurements of liquid clouds are in good agreement with MODIS cloud droplet size while poor correlation is found in the amount of cloud liquid water due to the management of drizzle. The comparison of the cloud diagnostic from three climate models with MODIS data, enabled through the application of a satellite simulator, helped to understand discrepancies among models, as well as discover deficiencies in their simulation processes. These findings are important to further improve the parametrization of atmospheric constituents in climate models, therefore enhancing the accuracy of climate projections. In this thesis it is also assessed the impact of aerosol particles on clouds. Satellite data can be used to derive climatically crucial quantities that are otherwise not directly retrieved (such as aerosol index and cloud droplet number concentration) which can be used to infer the sensitivity of clouds to aerosols changes. Results on the local and regional scales show that contrasting aerosol backgrounds indicate a higher sensitivity of clouds to aerosol changes in cleaner ambient air and a lower sensitivity in polluted areas, further corroborating the notion that anthropogenic emission modify clouds. On the global scale, the estimates of the aerosol-cloud interaction present, overall, a good agreement between the satelliteand model-based values which are in line with the results from other models.

Application of remotely-sensed cloud properties for climate studies