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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 19 | Copyright
Atmos. Chem. Phys., 18, 14327-14350, 2018
https://doi.org/10.5194/acp-18-14327-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Oct 2018

Research article | 09 Oct 2018

Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation

Odran Sourdeval1,a, Edward Gryspeerdt2, Martina Krämer3, Tom Goren1, Julien Delanoë4, Armin Afchine3, Friederike Hemmer5, and Johannes Quaas1 Odran Sourdeval et al.
  • 1Leipzig Institute 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 Lille1, Villeneuve d'Ascq, France
  • anow at: Laboratoire d'Optique Atmosphérique, Université Lille1, 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 regarding 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 via a comparison of satellite estimates to coincident 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 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 updrafts, such as those related to convective or orographic uplifts. Further evaluation and improvement of this method are necessary, although these results already constitute a first encouraging step towards large-scale observational constraints for Ni. Part 2 of this series uses this new dataset to examine the controls on Ni.

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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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