Articles | Volume 18, issue 19
https://doi.org/10.5194/acp-18-14327-2018
© 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/acp-18-14327-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
09 Oct 2018
Research article | Highlight paper |
| 09 Oct 2018
| 09 Oct 2018
Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation
Odran Sourdeval
CORRESPONDING AUTHOR
Leipzig Institute for Meteorology, Universität Leipzig, Leipzig, Germany
now at: Laboratoire d'Optique Atmosphérique, Université Lille1, Villeneuve d'Ascq, France
Edward Gryspeerdt
Space and Atmospheric Physics Group, Imperial College London, London, UK
Martina Krämer
Forschungszentrum Jülich, Institut für Energie und Klimaforschung (IEK-7), Jülich, Germany
Tom Goren
Leipzig Institute for Meteorology, Universität Leipzig, Leipzig, Germany
Julien Delanoë
LATMOS/UVSQ/IPSL/CNRS, Guyancourt, France
Armin Afchine
Forschungszentrum Jülich, Institut für Energie und Klimaforschung (IEK-7), Jülich, Germany
Friederike Hemmer
Laboratoire d'Optique Atmosphérique, Université Lille1, Villeneuve d'Ascq, France
Johannes Quaas
Leipzig Institute for Meteorology, Universität Leipzig, Leipzig, Germany
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Latest update: 28 Mar 2025
Short summary
The number concentration of ice crystals (Ni) is a key cloud property that remains very uncertain due to difficulties in determining it using satellites. This lack of global observational constraints limits our ability to constrain this property in models responsible for predicting future climate. This pair of papers fills this gap by showing and analyzing the first rigorously evaluated global climatology of Ni, leading to new information shedding light on the processes that control high clouds.
The number concentration of ice crystals (Ni) is a key cloud property that remains very...
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