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The uncertainties in the cloud physical properties derived fromsatellite observations make it difficult to interpretmodel evaluation studies. In this paper, the uncertainties in thecloud water path (CWP) retrievals derived with the cloud physical propertiesretrieval algorithm (CPP) of the climate monitoring satelliteapplication facility (CM SAF) are investigated. To this end, anumerical simulator of MSG-SEVIRI observations has been developed thatcalculates the reflectances at 0.64 and 1.63 μm for a widerange of cloud parameter values, satellite viewing geometries and surfacealbedos using a plane-parallel radiative transfer model. The  reflectances thus obtained are used as input to CPP, and the  retrieved values of CWP are compared to the original input of the  simulator. Cloud parameters considered in this paper refer to e.g.  sub-pixel broken clouds and the simultaneous occurrence of ice and  liquid water clouds within one pixel. These configurations are not  represented in the CPP algorithm and as such the associated  retrieval uncertainties are potentially substantial.  It is shown that the CWP retrievals are very sensitive to theassumptions made in the CPP code. The CWP retrieval errors aregenerally small for unbroken single-layer clouds with COT > 10, withretrieval errors of ~3% for liquid water clouds to ~10% forice clouds. In a multi-layer cloud, when both liquid water and iceclouds are present in a pixel,the CWP retrieval errors increase dramatically; depending on thecloud, this can lead to uncertainties of 40–80%. CWP retrievalsalso become more uncertain when the cloud does not cover the entirepixel, leading to errors of ~50% for cloud fractions of0.75 and even larger errors for smaller cloud fractions. Thus, thesatellite retrieval of cloud physical properties of broken clouds aswell as multi-layer clouds iscomplicated by inherent difficulties, and the proper interpretation ofsuch retrievals requires extra care

A fast SEVIRI simulator for quantifying retrieval uncertainties in the CM SAF cloud physical property algorithm