Abstract
Abstract. Radiometers such as the AVHRR (Advanced Very High Resolution Radiometer) mounted aboard a series of NOAA and MetOp (Meteorological Operational) polar-orbiting satellites provide 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 satellite orbital drift, cause the uneven sampling of the cloudiness diurnal cycle along a course of a CDR. This in turn leads to significant biases, spurious trends, and inhomogeneities in the data records of climate 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 min reference CM SAF (European Organisation for the Exploitation of Meteorological Satellites – EUMETSAT – Satellite Application Facility on Climate Monitoring) Cloud Fractional Cover dataset derived from Meteosat First and Second Generation (COMET) at times of the NOAA and MetOp satellite overpasses. The sampled 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∘ N, S, W, and E). For individual NOAA and MetOp satellites the errors in mean monthly CFC reach ±10 % (bias) and ±7 % per decade (spurious trends). For the combined data record consisting of several NOAA and 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 (Global Climate Observing System) 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 and MetOp satellites operating simultaneously. Yet, the time series starting in 2003 is shorter than 30 years, which makes it difficult to draw reliable conclusions about long-term changes in CFC. We 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 CDR providers.
Highlights
Cloud feedback to global warming remains one of the biggest uncertainties in climate projections
To estimate errors and spurious trends in the Advanced Very High Resolution Radiometer (AVHRR)-based cloud fractional cover (CFC) climate data records (CDRs) induced by satellite orbital drift and variable number of AVHRR observations a day, the artificial time series was derived from the geostationary COMET CFC dataset sampled at the AVHRR observation times (i.e. COMET CFC “as seen” by the AVHRR sensors)
The cloud fractional cover climate data records (CFC CDRs) generated from the measurements of the AVHRR sensor mounted aboard a series of the NOAA and MetOp polarorbiting satellites are subject to errors originating from the undersampling of the cloudiness diurnal cycle as well from satellite orbital drift
Summary
Cloud feedback to global warming remains one of the biggest uncertainties in climate projections. To improve comprehension of this complex physical phenomenon, a long reliable time series of cloud fraction measurements is 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. 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 They are often inhomogeneous and located in densely populated regions leaving the vast oceanic areas, polar regions, high mountains, deserts, and tropical and Taiga forests undersampled.
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