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 con- trast with recent advances for liquid clouds, few observational constraints exist on the ice crys- tal number concentration (Nice).

DARDAR-Nice offers satellite retrievals of Nice profiles obtained from combined lidar-radar measurements. This product is based on the VarCloud algorithm (Delanoë and Hogan, 2010), which provides retrievals of ice cloud properties from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar measurements. Ice crystal number concentra- tions are provided along the CloudSat footprint (1.7 km) with a vertical resolution of 60 m. A variational method was used to associate rigorous uncertainties to the retrievals of ice cloud properties. For convenience, the ice water content (IWC) and cloud mask retrieved by VarCloud are also provided in DARDAR-Nice. This product is limited to ice clouds with an IWC larger than 10-8 kg.m-3. Retrievals obtained within mixed-phase clouds (typically ice clouds with a liq- uid top) are indicated by a flag and should be carefully considered due to larger uncertainties.

Ice crystal number estimates are obtained by using the sensitivity of lidar and radar measure- ments to constrain moments of a parameterized particle size distribution (PSD). Once con- strained, this PSD is integrated from 3 minimum size thresholds in order to provide Nice corre- sponding to particules larger than 5, 25 and 100 um. Each of these concentrations are provid- ed in DARDAR-Nice together with their respective uncertainties.

DARDAR-Nice has been thoroughly evaluated against theoretical considerations and a large amount of in situ measurements (Sourdeval et al., 2018). Known limitations concern Nice in cloud parcels warmer than about -30°C, which can be overestimated due to the assumption of a monomodal PSD shape in the current method. Retrievals associated with Tc > −30°C should therefore be used with care.

Two orbital (L2) products are available:

  • DARDAR-Nice PRO : Profiles of Nice retrievals provided along the A-Train track with a vertical resolution of 60 m.
  • DARDAR-Nice LAY : Nice retrievals provided for up to 10 ice cloud layers (layers are defined as clouds separated by 500 m). This product notably contains explicit values for Nice at cloud top and cloud base.

In order to make DARDAR-Nice convenient for climate studies, multiple gridded products (L3) are also available. Nice is provided in lat-lon grids and for multiple temperature / pressure bins or model vertical levels. Gridded DARDAR-Nice for missing grids can be processed upon re- quest.

Version History

v1.0.0 : First release of the products.


Odran Sourdeval (odran.sourdeval@univ-lille.fr)


  • Delanoë, J., and R. J. Hogan, 2010: Combined CloudSat-CALIPSO-MODIS retrievals of the properties of ice clouds. J. Geophys. Res., 115, D00H29, doi: 10.1029/2009JD012346.
  • Gryspeerdt, E., Sourdeval, O., Quaas, J., Delanoë, J., Krämer, M., and Kühne, P.: Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 2: Controls on the ice crystal number concentration, Atmos. Chem. Phys., 18, 14351–14370, https://doi.org/10.5194/acp-18-14351-2018, 2018.
  • 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., 18, 14327–14350, https://doi.org/10.5194/acp-18-14327-2018, 2018.