Articles | Volume 11, issue 6
https://doi.org/10.5194/amt-11-3397-2018
© 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-11-3397-2018
© 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 2: The optimal estimation approach
Gregory R. McGarragh
CORRESPONDING AUTHOR
Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
Caroline A. Poulsen
RAL Space, STFC, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
NCEO, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
Gareth E. Thomas
RAL Space, STFC, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
NCEO, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
Adam C. Povey
National Centre for Earth Observation, Atmospheric, Oceanic and Planetary
Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
Oliver Sus
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
Stefan Stapelberg
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
Cornelia Schlundt
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
Simon Proud
Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
Matthew W. Christensen
Department of Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
RAL Space, STFC, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
NCEO, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK
Martin Stengel
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
Rainer Hollmann
Deutscher Wetterdienst, Frankfurter Str. 135, 63067 Offenbach, Germany
Roy G. Grainger
National Centre for Earth Observation, Atmospheric, Oceanic and Planetary
Physics, University of Oxford, Clarendon Laboratory, Parks Road, Oxford OX1 3PU, UK
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Latest update: 23 Nov 2024
Short summary
Satellites are vital for measuring cloud properties necessary for climate prediction studies. We present a method to retrieve cloud properties from satellite based radiometric measurements. The methodology employed is known as optimal estimation and belongs in the class of statistical inversion methods based on Bayes' theorem. We show, through theoretical retrieval simulations, that the solution is stable and accurate to within 10–20% depending on cloud thickness.
Satellites are vital for measuring cloud properties necessary for climate prediction studies. We...
