Quantifying retrieval uncertainties in the CM-SAF cloud physical property algorithm with simulated SEVIRI observations

Abstract

Abstract. The uncertainties in the cloud physical properties derived from satellite observations make it difficult to interpret model evaluation studies. In this paper, the uncertainties in the cloud water path (CWP) retrievals derived with the cloud physical properties retrieval algorithm (CPP) of the climate monitoring satellite application facility (CM-SAF) are investigated. To this end, a numerical simulator of MSG-SEVIRI observations was developed that calculates the reflectances at 0.64 and 1.63 μm for a wide range of cloud parameters, satellite viewing geometries and surface albedos. These reflectances are used as input to CPP, and the retrieved values of CWP are compared to the original input of the simulator. It is shown that the CWP retrievals are very sensitive to the assumptions made in the CPP code. The CWP retrieval errors are generally small for unbroken single-phase clouds with COT >10, with retrieval errors of ~3% for liquid water clouds to ~10% for ice clouds. When both liquid water and ice clouds are present in a pixel, the CWP retrieval errors increase dramatically; depending on the cloud, this can lead to uncertainties of 40–80%. CWP retrievals also become more uncertain when the cloud does not cover the entire pixel, leading to errors of ~50% for cloud fractions of 0.75 and even larger errors for smaller cloud fractions. Thus, the satellite retrieval of cloud physical properties of broken clouds and multi-phase clouds is complicated by inherent difficulties, and the proper interpretation of such retrievals requires extra care.