Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/acp-2018-20
© 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 Chemistry and Physics (ACP).
Ice crystal number concentration estimates from lidar-radar satellite remote sensing. Part 1: Method and evaluation
Odran Sourdeval1, Edward Gryspeerdt2, Martina Krämer3, Tom Goren1, Julien Delanoë4, Armin Afchine3, Friederike Hemmer5, and Johannes Quaas1 1Institute for Meteorology, Universität Leipzig, Leipzig, Germany
2Space and Atmospheric Physics Group, Imperial College London, London, UK
3Forschungszentrum Jülich, Institut für Energie und Klimaforschung (IEK-7), Jülich, Germany
4LATMOS/UVSQ/IPSL/CNRS, Guyancourt, France
5Laboratoire d'Optique Atmosphérique, Université Lille 1, Villeneuve d'Ascq, France
Abstract. The number concentration of cloud particles is a key quantity for understanding aerosol-cloud interactions and describing clouds in climate and numerical weather prediction models. In contrast with recent advances for liquid clouds, few observational constraints exist on the ice crystal number concentration (Ni). This study investigates how combined lidar-radar measurements can be used to provide satellite estimates of Ni, using a methodology that constrains moments of a parameterized particle size distribution (PSD). The operational liDAR-raDAR (DARDAR) product serves as an existing base for this method, which focuses on ice clouds with temperatures Tc < −30 °C. Theoretical considerations demonstrate the capability for accurate retrievals of Ni, apart from a possible bias in the concentration in small crystals when Tc ≳ −50 °C, due to the assumption of a monomodal PSD shape in the current method. This is verified by comparing satellite estimates to co-incident in situ measurements, which additionally demonstrates the sufficient sensitivity of lidar-radar observations to Ni. Following these results, satellite estimates of Ni are evaluated in the context of a case study and a preliminary climatological analysis based on 10 years of global data. Despite of a lack of other large-scale references, this evaluation shows a reasonable physical consistency in Ni spatial distribution patterns. Notably, increases in Ni are found towards cold temperatures and, more significantly, in the presence of strong updraughts, such as those related to convective or orographic uplifts. Further evaluation and improvements of this method are necessary but these results already constitute a first encouraging step towards large-scale observational constraints for Ni. Part two of this series uses this new dataset to examine the controls on Ni.

Citation: Sourdeval, O., Gryspeerdt, E., Krämer, M., Goren, T., Delanoë, J., Afchine, A., Hemmer, F., and Quaas, J.: Ice crystal number concentration estimates from lidar-radar satellite remote sensing. Part 1: Method and evaluation, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-20, in review, 2018.
Odran Sourdeval et al.
Odran Sourdeval et al.
Odran Sourdeval et al.

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Short summary
The number concentration of ice crystals (Ni) is a key cloud property that remains very uncertain due to difficulties to determine it using satellites. This lack of global observational constrains 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 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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