On the forward modeling of radar Doppler spectrum width from LES: Implications for model evaluation

Area of Science:

• Atmospheric Science
• Cloud Physics
• Remote Sensing

Background:

• Arctic mixed-phase clouds are crucial for climate.
• Profiling millimeter-wave cloud radar provides valuable data.
• Evaluating large-eddy simulations (LES) is essential for climate modeling.

Purpose of the Study:

• Assess the utility of forward modeling Doppler spectral width for LES evaluation.
• Quantify and compare broadening terms in observed and simulated Arctic clouds.
• Improve retrieval techniques for cloud microphysical properties and turbulence.

Main Methods:

• Large-eddy simulations of an observed Arctic mixed-phase cloud.
• Forward modeling of cloud radar Doppler spectral width.
• Quantification of turbulent, microphysical, and shear broadening terms.
• Analysis of power spectra of simulated vertical air velocity.

Main Results:

• Modeled turbulent broadening underestimated observed values using standard subgrid-scale models.
• Total dissipation rates (subgrid-scale + numerical) showed better agreement with retrieved values.
• Modified retrieval techniques improved accuracy of dissipation rate and broadening term estimations.
• Filtered inertial subrange spectra and corrected Doppler velocity improved retrievals.

Conclusions:

• Forward modeling of Doppler spectral width is valuable for LES evaluation.
• Improved retrieval methods enhance the accuracy of Arctic cloud property assessments.
• Accurate estimation of dissipation rates and microphysical broadening is critical for cloud model validation.