Dissecting effects of orbital drift of polar-orbiting satellites on accuracy and trends of cloud fractional cover climate data records J˛ edrzej S. Bojanowski 1 and Jan P. Musial 1 1 Institute of Geodesy and Cartography, Remote Sensing Centre, Modzelewskiego 27, PL02-679 Warsaw, Poland Correspondence: J˛ edrzej Bojanowski (jedrzej.bojanowski@igik.edu.pl) Abstract. Radiometers such as the AVHRR mounted aboard a series of the NOAA and MetOp polar-orbiting satellites pro- vide 4-decade-long global climate data records (CDRs) of cloud fractional cover. Generation of such long datasets requires combining data from consecutive satellite platforms. A varying number of satellites operating simultaneously in the morning and afternoon orbits, together with the satellite orbital drift cause the uneven sampling of the cloudiness diurnal cycle along a course of CDR. This in turn leads to significant biases, spurious trends and inhomogeneities in the data records of climate 5 variables featuring the distinct diurnal cycle (such as clouds). To quantify the uncertainty and magnitude of spurious trends in the AVHRR-based cloudiness CDRs, we sampled the 30-minute reference CM SAF Cloud Fractional Cover dataset derived from Meteosat First and Second Generation (COMET) at times of the NOAA and MetOp satellites overpasses. The sam- pled cloud fractional cover (CFC) time series were aggregated to monthly means and compared with the reference COMET dataset covering the Meteosat disc (up to 60 degrees N/S/W/E). For individual NOAA/MetOp satellites the errors in mean 10 monthly CFC reach ±10% (bias) and ±7% per decade (spurious trends). For the combined data record consisting of several NOAA/MetOp satellites, the CFC bias is 3% and the spurious trends are 1% per decade. This study proves that before 2002 the AVHRR-derived CFC CDRs do not comply with the GCOS temporal stability requirement of 1% CFC per decade just due to the satellite orbital drift effect. After this date the requirement is fulfilled due to the numerous NOAA/MetOp satellites operating simultaneously. Yet, the time series starting in 2003 is shorter than 30 years that voids climatological analyses. We 15 expect that the error estimates provided in this study will allow for a correct interpretation of the AVHRR-based CFC CDRs and ultimately will contribute to the development of a novel satellite orbital drift correction methodology widely accepted by the AVHRR-based CDRs providers. 1 Introduction Cloud feedback to the global warming remains one of the biggest uncertainties in climate projections. To improve comprehen- 20 sion of this complex physical phenomena, a long reliable time series of cloud fraction measurements are required at a global scale. In this respect, multi-decadal ground-based visual cloud observations, that have been recently supported or replaced by the ceilometers or total sky cameras, are still widely used in climatological studies. However, they are often inhomogeneous and located in densely populated regions leaving the vast oceanic areas, polar regions, high mountains, deserts, as well as trop- ical and Taiga forests under-sampled. Despite aforementioned issues, the surface synoptic observations (SYNOP) have been 25 1 https://doi.org/10.5194/amt-2020-91 Preprint. Discussion started: 23 March 2020 c  Author(s) 2020. CC BY 4.0 License.