The accurate identification of the presence of cloud in the ground scenes observed by remote sensing satellites is an end in itself. Our lack of knowledge of cloud at high latitudes increases the error and uncertainty in the evaluation and assessment of the changing impact of aerosol and cloud in a warming climate. A prerequisite for the accurate retrieval of Aerosol Optical Thickness, AOT, is the knowledge of the presence of cloud in a ground scene. In this study observations of the up welling radiance in the visible (VIS), near infrared (NIR), shortwave infrared (SWIR), and the thermal infrared (TIR) are used to determine the reflectance. We have developed a new cloud identification algorithm for application to the observations of Advanced Along-Track Scanning Radiometer (AATSR) on European Space Agency (ESA)-Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on-board the ESA Copernicus Sentinel-3A and -3B. The AATSR/SLSTR Cloud Identification Algorithm (ASCIA) developed addresses the requirements for the study AOT at high latitudes and utilizes time-series measurements. It is assumed that cloud free surfaces have unchanged or little changed patterns for a given sampling period, whereas cloudy or partly cloudy scenes show much higher variability in space and time. In this method, the Pearson Correlation Coefficient (PCC) parameter is used to measure the stability of the atmosphere-surface system observed by satellites. The cloud free surface is classified by analyzing the PCC values at the block scale 25 × 25 km 2 . Subsequently, the reflection of 3.7 μm is used for accurate cloud identification at the scene level either 1 × 1 km 2 or 0.5 × 0.5 km 2 . The ASCIA data product has been validated by comparison with independent observations e,g. Surface synoptic observations (SYNOP), AErosol RObotic NETwork (AERONET) and the following satellite-products from i) ESA standard cloud product from AATSR L2 nadir cloud flag, ii) one method based on clear-snow spectral shape developed at IUP Bremen (Istomina et al., 2010), which we call, ISTO, iii) Moderate Resolution Imaging Spectroradiometer (MODIS). In comparison to ground based SYNOP measurements, we achieved a promising agreement better than 95 % and 83 % within ±2 and ±1 okta respectively. In general, ASCIA shows an improved performance in comparison to other algorithms applied to AATSR measurements for cloud identification at high latitudes.