4A.6 A method for extraction of cloud microphysical properties using a continuous wavelet transform of cloud radar spectra: Preliminary results

Monday, 26 September 2011: 11:45 AM
Monongahela Room (William Penn Hotel)
Guo Yu, Pennsylvania State University, University Park, PA; and J. Verlinde, E. E. Clothiaux, G. Botta, K. Aydin, A. Avramov, A. S. Ackerman, and A. M. Fridlind
Manuscript (438.4 kB)

Stratiform clouds across the globe frequently contain both liquid- and ice-water particles in the same volume; that is, they are often mixed-phase clouds. Millimeter-wavelength cloud radar (MMCR) data are an important source of information on the microphysical properties and dynamical processes within these clouds. However, retrieving and quantifying the climatological radiatively important liquid-phase particles within these clouds remains a challenge because the radar signal is frequently dominated by the returns from the ice particles within these volumes. The ice masks the small reflectivity contribution from the liquid phase.

Here, we present a technique that extracts weak cloud-liquid drop contributions to MMCR Doppler-velocity spectra in which drizzle-particle returns dominate. In this approach spectra are first decomposed using a continuous wavelet transform. The resulting coefficients are then used to identify regions in the spectra where cloud-liquid drops contribute; Gaussian distributions are subsequently fit to these regions. Our preliminary results indicate this approach is capable of separating the cloud- and drizzle-particle contributions to the Doppler-velocity spectra. In the process the volume air motion and its turbulent broadening are also extracted.

We will extend the analysis to mixed-phase clouds for which the volume contains both liquid- and ice-hydrometeor populations. We will present results derived from synthetic spectra based on hydrometeor size distributions produced by state-of-the-art cloud resolving model (CRM) simulations of Arctic mixed-phase clouds. The retrieval of the liquid- and ice-water contributions will be evaluated against the microphysical parameters extracted from the CRM and used to generate the synthetic spectra. We will explore the sensitivity of the technique to overlapping contributions in the synthetic spectra from liquid-water drops and slowly falling ice crystals.

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