Articles | Volume 11, issue 6
https://doi.org/10.5194/amt-11-3373-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-3373-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jun 2018
Research article |
| 13 Jun 2018
| 13 Jun 2018
The Community Cloud retrieval for CLimate (CC4CL) – Part 1: A framework applied to multiple satellite imaging sensors
Oliver Sus
DWD – Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
DWD – Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Stefan Stapelberg
DWD – Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Gregory McGarragh
Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
Caroline Poulsen
RAL Space – Rutherford Appleton Laboratory, Chilton, Didcot OX11 0QX, UK
Adam C. Povey
National Centre for Earth Observation, Atmospheric, Oceanic and Planetary Physics, University of Oxford, Parks Road, Oxford OX1 3PU, UK
Cornelia Schlundt
DWD – Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Gareth Thomas
RAL Space – Rutherford Appleton Laboratory, Chilton, Didcot OX11 0QX, UK
Matthew Christensen
Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
RAL Space – Rutherford Appleton Laboratory, Chilton, Didcot OX11 0QX, UK
Simon Proud
Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
Matthias Jerg
DWD – Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
Roy Grainger
National Centre for Earth Observation, Atmospheric, Oceanic and Planetary Physics, University of Oxford, Parks Road, Oxford OX1 3PU, UK
Rainer Hollmann
DWD – Deutscher Wetterdienst, Frankfurter Straße 135, 63067 Offenbach, Germany
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Latest update: 20 Nov 2024
Short summary
This paper presents a new cloud detection and classification framework, CC4CL. It applies a sophisticated optimal estimation method to derive cloud variables from satellite data of various polar-orbiting platforms and sensors (AVHRR, MODIS, AATSR). CC4CL provides explicit uncertainty quantification and long-term consistency for decadal timeseries at various spatial resolutions. We analysed 5 case studies to show that cloud height estimates are very realistic unless optically thin clouds overlap.
This paper presents a new cloud detection and classification framework, CC4CL. It applies a...
