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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
31 Jan 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements
Fanny Jeanneret1, Giovanni Martucci2, Simon Pinnock1, and Alexis Berne3 1ESA ECSAT, Harwell Campus, Didcot, Oxfordshire, OX11 0FD, United Kingdom
2Federal Office of Meteorology and Climatology MeteoSwiss, Ch. de l’Aérologie, Payerne, Switzerland
3EPFL, EPFL-ENAC-IIE-LTE, Lausanne, Switzerland
Abstract. The validation of long term cloud datasets retrieved from satellites is challenging due to their worldwide coverage going back as far as the 1980s, among others. A trustworthy reference cannot be found easily at every location and every time. Mountainous regions represent especially a problem since ground-based measurements are sparser. Moreover, as retrievals from passive satellite radiometers are difficult in winter due to the presence of snow on the ground, it is particularly important to develop new ways to evaluate and to correct satellite datasets over elevated areas.

In winter for ground levels above 1000 m (a.s.l.) in Switzerland, the cloud occurrence of the newly-released cloud property datasets of the ESA Climate Change Initiative Cloud_cci project (AVHRR-PM and MODIS-Aqua series) is 132 % to 217 % that of SYNOP observations, corresponding to between 24 % and 54 % of false cloud detections. Furthermore, the overestimations increase with the altitude of the sites and are associated with particular retrieved cloud properties.

In this study, a novel post-processing approach is proposed to reduce the amount of false cloud detections in the satellite datasets. A combination of ground-based downwelling longwave and shortwave radiation and temperature measurements is used to obtain a mask for the cloud cover above 41 locations in Switzerland. An agreement of 85 % is obtained when the cloud cover is compared to surface synoptic observations (90 % within ±1 okta difference). The obtained cloud mask has been co-located with the satellite observations and a decision tree is trained to automatically detect the overestimations in the satellite's cloud masks. Cross-validated results show that 62 ± 13 % of these overestimations can be identified by the model, reducing the systematic error in the satellite datasets to 4.3 ± 2.8 %, at the cost of an increase of 7 ± 2 % of missed clouds. Using this model, it is hence possible to significantly improve the cloud detection reliability in elevated areas in the Cloud_cci's AVHRR-PM and MODIS-Aqua products.

Citation: Jeanneret, F., Martucci, G., Pinnock, S., and Berne, A.: Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements, Atmos. Meas. Tech. Discuss.,, in review, 2018.
Fanny Jeanneret et al.
Fanny Jeanneret et al.
Fanny Jeanneret et al.


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Publications Copernicus
Short summary
Observing clouds is possible with satellite imagery since the 1980s, and is important for monitoring our climate’s evolution. Above mountainous regions, some satellite instruments have difficulties discriminating snow from clouds: this study proposes a new way of combining several measurements from the ground to know the state of the sky (cloudy or not) with a high temporal resolution, and then uses it as input for a model detecting when satellites might contain wrong observations.
Observing clouds is possible with satellite imagery since the 1980s, and is important for...