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Clear-sky contamination is a challenging and long-lasting problem for cloud optical thickness (tau) and effective droplet radius (r(eff)) retrievals using passive satellite sensors. This study explores the feasibility of improving both tau and r(eff) retrievals for partly cloudy (PCL) pixels by using available subpixel samples in a visible to near-infrared band, which many satellite sensors offer. Data are provided by high-resolution reflectance (R) observations and cloud property retrievals by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at horizontal resolutions between 30-960m. For partly cloudy 960-m observations, the clear-sky component of the pixels induces significant underestimations of up to 58% for tau, while overestimations in r(eff) can exceed 41%. This yields underestimations in the derived liquid water path and cloud droplet number concentration of up to 68% and 72%, respectively. By means of three different assumptions it is shown that subpixel R observations in the visible to near-infrared band can be used to estimate higher-resolution R for the second band in the retrieval scheme, as well as the subpixel cloud cover. The estimated values compare well to actually observed ASTER results and are used to retrieve cloud properties, which are unbiased by the clear-sky component of PCL pixels. While the presented retrieval approach is only evaluated for marine boundary layer clouds, it is computationally efficient and can be easily applied to observations from different imagers. As an example, the PCL retrieval scheme is applied to data by the Moderate Resolution Imaging Spectroradiometer, where similar biases for PCL pixels are observed.

Plain Language Summary Clear-sky contamination is a challenging and long-lasting problem for cloud optical thickness and effective droplet radius retrievals using passive satellite sensors. This study explores the feasibility of improving both retrievals for partly cloudy (PCL) pixels by using available subpixel samples in a visible to near-infrared band, which many satellite sensors offer. For partly cloudy 960-m observations, the clear-sky component of the pixels induces significant underestimations of up to -58% for the cloud optical thickness, while overestimations in the effective droplet radius can exceed 41%. This yields underestimations in the derived liquid water path and cloud droplet number concentration of up to 68% and 72%, respectively. It is shown that subpixel reflectance observations in the visible to near-infrared band can be used to retrieve cloud properties, which are unbiased by the clear-sky component of the PCL pixels. While the presented retrieval approach is only evaluated for marine boundary layer clouds, it is computationally efficient and can be easily applied to observations from different imagers. As an example, the PCL retrieval scheme is applied to data by the Moderate Resolution Imaging Spectroradiometer, where similar biases for PCL pixels are observed.