Maximilian Maahn

Developing and Evaluating Ice Cloud Parameterizations for Forward Modeling of Radar Moments Using in situ Aircraft Observations

AbstractObserving ice clouds using zenith pointing millimeter cloud radars is challenging because the transfer functions relating the observables to meteorological quantities are not uniquely defined. Here, the authors use a spectral radar simulator to develop a consistent dataset containing particle mass, area, and size distribution as functions of size. This is an essential prerequisite for radar sensitivity studies and retrieval development. The data are obtained from aircraft in situ and ground-based radar observations during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) campaign in Alaska. The two main results of this study are as follows: 1) An improved method to estimate the particle mass–size relation as a function of temperature is developed and successfully evaluated by combining aircraft in situ and radar observations. The method relies on a functional relation between reflectivity and Doppler velocity. 2) The impact on the Doppler spectrum by replacing measurements of particle area and...

How does the spaceborne radar blind zone affect derived surface snowfall statistics in polar regions

Global statistics of snowfall are currently only available from the CloudSat satellite. But CloudSat cannot provide observations of clouds and precipitation within the so-called blind zone, which is caused by ground-clutter contamination of the CloudSat radar and covers the last 1200 m above land/ice surface. In this study, the impact of the blind zone of CloudSat on derived snowfall statistics in polar regions is investigated by analyzing three 12 month data sets recorded by ground-based Micro Rain Radar (MRR) at the Belgian Princess Elisabeth station in East Antarctica and at Ny-Alesund and Longyearbyen in Svalbard, Norway. MRR radar reflectivity profiles are investigated in respect to vertical variability in the frequency distribution, changes in the number of observed snow events, and impacts on total precipitation. Results show that the blind zone leads to reflectivity being underestimated by up to 1 dB, the number of events being altered by ±5% and the precipitation amount being underestimated by 9 to 11 percentage points. Besides investigating a blind zone of 1200 m, the impacts of a reduced blind zone of 600 m are also analyzed. This analysis will help in assessing future missions with a smaller blind zone. The reduced blind zone leads to improved representation of mean reflectivity but does not improve the bias in event numbers and precipitation amount.

First observations of triple-frequency radar Doppler spectra in snowfall: Interpretation and applications

The potential of multifrequency Doppler spectra to constrain precipitation microphysics has so far only been exploited for dual-frequency spectra in rain. In this study, we extend the dual-frequency concept to triple-frequency Doppler radar spectra obtained during a snowfall event which included rimed and unrimed snow aggregates. A large selection of spectra obtained from low-turbulence regions within the cloud reveals distinctly different signatures of the derived dual spectral ratios. Due to the third frequency, a characteristic curve can be derived which is almost independent of the underlying particle size distribution and velocity-size relation. This approach provides new opportunities for validating existing and future snow scattering models and reveals how the information content of triple-frequency radar data sets can be further exploited for snowfall studies.

Potential of Higher-Order Moments and Slopes of the Radar Doppler Spectrum for Retrieving Microphysical and Kinematic Properties of Arctic Ice Clouds

AbstractRetrievals of ice-cloud properties from cloud-radar observations are challenging because the retrieval methods are typically underdetermined. Here, the authors investigate whether additional information can be obtained from higher-order moments and the slopes of the radar Doppler spectrum such as skewness and kurtosis as well as the slopes of the Doppler peak. To estimate quantitatively the additional information content, a generalized Bayesian retrieval framework that is based on optimal estimation is developed. Real and synthetic cloud-radar observations of the Indirect and Semi-Direct Aerosol Campaign (ISDAC) dataset obtained around Barrow, Alaska, are used in this study. The 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. It is found that, for a single radar frequency, more informatio...

Atmospheric Ice Particle Shape Estimates from Polarimetric Radar Measurements and In Situ Observations

AbstractA remote sensing approach to retrieve the degree of nonsphericity of ice hydrometeors using scanning polarimetric Ka-band radar measurements from a U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program cloud radar operated in an alternate transmission–simultaneous reception mode is introduced. Nonsphericity is characterized by aspect ratios representing the ratios of particle minor-to-major dimensions. The approach is based on the use of a circular depolarization ratio (CDR) proxy reconstructed from differential reflectivity ZDR and copolar correlation coefficient ρhυ linear polarization measurements. Essentially combining information contained in ZDR and ρhυ, CDR-based retrievals of aspect ratios are fairly insensitive to hydrometeor orientation if measurements are performed at elevation angles of around 40°–50°. The suggested approach is applied to data collected using the third ARM Mobile Facility (AMF3), deployed to Oliktok Point, Alaska. Aspect ratio retrievals were also p...

A Bird’s-Eye View: Development of an Operational ARM Unmanned Aerial Capability for Atmospheric Research in Arctic Alaska

AbstractThorough understanding of aerosols, clouds, boundary layer structure, and radiation is required to improve the representation of the Arctic atmosphere in weather forecasting and climate models. To develop such understanding, new perspectives are needed to provide details on the vertical structure and spatial variability of key atmospheric properties, along with information over difficult-to-reach surfaces such as newly forming sea ice. Over the last three years, the U.S. Department of Energy (DOE) has supported various flight campaigns using unmanned aircraft systems [UASs, also known as unmanned aerial vehicles (UAVs) and drones] and tethered balloon systems (TBSs) at Oliktok Point, Alaska. These activities have featured in situ measurements of the thermodynamic state, turbulence, radiation, aerosol properties, cloud microphysics, and turbulent fluxes to provide a detailed characterization of the lower atmosphere. Alongside a suite of active and passive ground-based sensors and radiosondes deploy...