The MERIS cloud property dataset was analyzed for anomalies and trends over the available 10 year data period. In the scope of Global Warming it can be expected that global cloud patternsmay change, yet the direction of this change is still subject of discussion. The Cloud Top Pressure (CTP), Cloud Optical Thickness (COT) and Cloud Cover (CC) data is successfully able to represent familiar cloud patterns, i.e. the ITCZ or trade wind cumulus clouds, even when monthly averaged. A zonal mean analysis was able to represent the major CTP formations visible in the global monthly averages, yet revealed very little interannual variations between the months. A grid box-based linear regression was applied over the whole data period in order to determine regional cloud variable trends. It shows distinct and reliable trend regions with positive trends as high as 150hPa/Decade in the Southern Pacific that match the known pattern of the trade wind cumulus clouds as well as negative values of 50hPa/Decade in the Pacific equator region, matching the typical pattern of an El Niño SST anomaly. However, a single grid box analysis of the anomalies revealed an unexpected and sudden change in positive as well as negative anomalies with grid boxes that showed extreme decadal trends, which appear to be raw data related. The comparison with data from the FAME-C project suggests a global trend towards higher clouds with a less optically thick cloud top region. I