In this thesis, the radiative effect of Arctic clouds during early summer is investigated based on observations collected aboard the research vessel Polarstern during the expedition PS106 conducted in 2017 in combination with passive satellite observations. The interactions of clouds with radiation, and the relevance of several macro- and microphysical properties of clouds and surface conditions are analyzed. An investigation of the small-scale variability of solar radiation on an ice floe based on a network of autonomous pyranometers covering an area of 0.83 km x 1.59 km, and the period from 4-16 June 2017 is given. Five distinct sky conditions are identified, and the mean and variance of atmospheric transmittance of global radiation are determined. Using a wavelet-based multi-resolution analysis, a comparison of individual station records and spatially averaged observations indicates that the absolute magnitude and scale-dependence of variability contain characteristic features for different sky conditions. For overcast conditions, distinctive patterns are identified in the diurnal variability and spatial distribution of the network observations, presumably caused by multiple reflection radiation between surface and cloud base in combination with the inhomogeneous surface conditions. A sensitivity analysis of radiative fluxes is performed for clear-sky and cloudy conditions using a 1-dimensional radiative transfer model, and is used as a basis to investigate how well state-of-the-art shipborne and passive satellite remote sensing observations can constrain the radiative effect of clouds and can serve to quantify the Arctic radiation budget. Cloud properties derived from the shipborne remote sensing observations with the Cloudnet algorithm are used as input for radiative transfer simulations. Simulated fluxes are compared to shipborne observations of the downward-terrestrial and solar fluxes as well as satellite products from CERES (Clouds and the Earth's Radiant Energy System, SYN1deg Ed. 4.1) to test closure of simulated and observed radiative fluxes, and to analyse the cloud radiative effect. Closure is achieved for clear-sky conditions. Based on selected case studies and an analysis for the entire PS106 period, the largest discrepancies are identified for low-level stratus, precipitation and ice clouds. Moreover, the cloud radiative effect inferred along the cruise track is compared to the entire Arctic to expand the regional context, making use of the wide spatial coverage of the CERES products. The results indicate a strong contribution of the solar flux to the radiation budget for the study period. Due to the reduction of solar radiation by clouds, a cooling effect of -8.8 W/m² and -9.3 W/m² is found at the surface for the PS106 cruise and the central Arctic, respectively. The similarity of local and regional CRE suggests that the PS106 cloud observations can be considered as representative of Arctic cloud conditions during the early summer of 2017.:Contents 1 Introduction 1.1 Motivation 1.2 Characteristics of Arctic Clouds 1.3 Effect of Arctic Clouds on the Radiation Budget 1.4 Link Between Arctic Clouds and Surface Conditions 1.5 Objectives of (AC)3 and this Thesis 1.6 Outline 2 Theoretical Background 2.1 Radiative Quantities 2.2 Radiative Interactions 2.2.1 Absorption 2.2.2 Scattering and Extinction 2.3 Radiative Transfer Equation 2.4 Radiative Transfer in the Arctic 2.4.1 Surface Reflection and Transmission 2.4.2 Clear-sky Conditions 2.4.3 Optical Properties of Clouds 2.5 Radiative Transfer Modelling 2.5.1 Two-stream Approximation 2.5.2 Correlated k -distribution 2.5.3 RRTMG 2.6 Energy Budget and Cloud Radiative Effect 3 PS106 Expedition, Instrumentation, Data sets, and Methods 3.1 Instrumentation 3.1.1 Pyranometer Network 3.1.2 Ship-borne Instrumentation 3.2 Data sets 3.2.1 Cloudnet 3.2.2 CERES data set 3.2.3 Ancillary data set 3.3 General Conditions During PS106 3.3.1 Synoptic and Surface Conditions 3.3.2 Atmospheric Temperature and Humidity Conditions 3.3.3 Statistical Analysis of Cloud Properties 3.4 Radiative Transfer Simulation Setup 4 Sensitivity Analysis of Arctic Fluxes 4.1 Clear-sky Perturbations 4.1.1 Atmosphere 4.1.2 Surface 4.2 Clear-sky Radiative Flux Uncertainty 4.3 Cloud Perturbations 4.3.1 Cloud Water Path 4.3.2 Cloud Particle Effective Radius 4.3.3 Liquid Fraction and Surface Albedo 4.3.4 Cloud Base Height 4.3.5 Cloud Geometrical Thickness 4.4 Synopsis 5 Cloud Induced Spatiotemporal Variability of Solar Radiation 5.1 Data Analysis 5.1.1 Data Processing 5.1.2 Sky Classification 5.2 Case Studies 5.2.1 Clear-sky Case 5.2.2 Overcast Case 5.2.3 Thin Cloud Case 5.2.4 Multilayer Case 5.2.5 Broken Cloud Case 5.3 Wavelet-based Multiresolution Analysis 5.4 Synopsis and Discussion 6 Radiation Closure 6.1 Radiative Flux Comparison Between CERES and T-CARS 6.2 Radiative Closure for Clear-sky Atmosphere 6.3 Radiative Closure for Cloudy Atmosphere 6.4 Synopsis and Discussion 7 Case Studies 7.1 Clear-sky Case 7.2 Single and Multilayer Ice Cloud Case 7.3 Mixed Phase Cloud Case 7.4 Synopsis 8 Radiation Budget and Cloud Radiative Effects 8.1 Cloud Radiative Effect (CRE) Analysis 8.2 Radiation Budget 8.3 Synopsis 9 Summary, Conclusions and Outlook 9.1 Summary and Conclusions 9.2 Outlook Appendix A Cloud Microphysical Properties During PS106 B CRE of Sensitivity Analysis C CERES Aerosol Products D Additional Observations Literature List of Abbreviations List of Symbols List of Figures List of Tables Acknowledgements