Making Full Use of the Doppler Spectrum Reduces Uncertainties in Ice Cloud Properties

Scientists use ARM aircraft and ground-based data, along with synthetic observations, to explore improvements obtained by using higher order moments of the radar Doppler spectrum in retrieval algorithms.

The Science

Ice clouds play an important role in the Earth’s energy balance, and how much energy they scatter are absorb depends on details of the particles that make up the ice clouds.  It is difficult and expensive to sample ice clouds directly with aircraft probes, so millimeter wavelength radars are often used to obtain information about ice cloud properties.  However, radars only observe ice clouds indirectly, through the scattering of microwave energy from cloud particles. Classic radar variables of radar reflectivity factor, mean Doppler velocity, and Doppler spectral width can be ambiguous for deriving microphysical characteristics such as water content and particle size.  In this study, scientists use aircraft data, radar observations, and synthetic observations to explore whether using additional information contained in the higher moments (such as skew and kurtosis) and slopes of the radar Doppler spectrum from modern state-of-the-art research radar can improve retrievals of ice cloud properties.

The Impact

Although higher order moments and slopes of the radar Doppler spectrum are noisier than lower order moments, they provide useful information on ice cloud microphysical and kinematic properties.  Using all of the available moments reduces the uncertainty of all retrieved quantities with respect to the prior knowledge and use of multiple radar frequencies can reduce the uncertainties even further.  Together with the methods to estimate the a priori dataset developed in a previous study by these authors, this study introduces a generalized retrieval framework that can also be applied to cloud radar observations from other time periods and locations.  Reduced uncertainties in observations of ice cloud properties will help scientists better understand the processes that control ice cloud formation and properties, and their impact on the Earth’s energy balance.


The scientists developed a Bayesian ice cloud retrieval using optimal estimation methods. In situ aircraft data obtained during the ARM Indirect and Semi-Direct Aerosol Campaign (ISDAC) obtained around Utqiagvik (formerly known as Barrow), AK was used as an a priori data set. Using mainly synthetic but also real cloud radar observations, scientists compared retrievals exploiting three different sets of observations (lower moments, higher moments [includes slopes], and all moments) using one, two, or three radar frequencies. The retrieval state vector consists of the microphysical (particle-size distribution, mass-size relation, and cross section-area relation) and kinematic (vertical wind and turbulence) quantities required to forward-model the moments and slopes of the radar Doppler spectrum. To the authors’ knowledge, this is the first study characterizing simultaneously microphysical quantities and kinematic properties of ice clouds based on radar observations. The researchers found that the uncertainty of quantities describing the mass-size and the area-size relations of ice particles as well as the turbulence was reduced by the use of higher moments and the slopes. For a single radar frequency, more information can be retrieved when including higher-order moments and slopes than when using only reflectivity and mean Doppler velocity but two radar frequencies.

Principal Investigator(s)

Maximilian Maahn
University of Colorado Boulder


This study was carried out within the project ADMIRARI II supported by the German Research Association (DFG) under research Grant LO901/ 5-1 and was also supported by Energy Transition and Climate Change (ET-CC) under DFG Grant ZUK 81. Author M. Maahn was also supported by Grant GSGS- 2015B-F03 of the Graduate School of Geosciences of the University of Cologne. Data were obtained from the Atmospheric Radiation Measurement Program sponsored by the U.S. Department of Energy Office of Science Office of Biological and Environmental Research (BER). Computing time was gratefully allocated by the Cologne High Efficiency Operating Platform for Sciences (CHEOPS) at the University of Cologne.


Maahn M and U Löhnert. 2017. “Potential of higher-order moments and slopes of the radar Doppler spectrum for retrieving microphysical and kinematic properties of Arctic ice clouds.” Journal of Applied Meteorology and Climatology, 56(2), 10.1175/jamc-d-16-0020.1.