Using ARM-SGP multi-sensor datasets to investigate precipitation characteristics and vertical variability

 
Poster PDF

Author

Christopher R Williams — University of Colorado, Boulder

Category

Microphysics (cloud, aerosol and/or precipitation)

Description

This poster will summarize key results from a four-year DOE ASR sponsored research grant titled, “Using ARM-SGP multi-sensor datasets to investigate precipitation characteristics and vertical variability” (2015-2019, DE-SC0014294). The overarching science goal was to analyze ARM observations to understand breakup, coalescence, and evaporation processes in precipitating clouds. One major contribution from this research was the development of liquid water content (LWC) vertical decomposition diagrams to diagnose the vertical evolution of raindrop size distributions (DSDs). These diagrams isolate changes in LWC from changes in DSD shape. If evaporation is negligible, then the decomposition diagram shows how raindrop mass is rearranged between total number of raindrops and the shape of the raindrop size distribution. These changes provide signatures due to breakup and coalescence processes. One benefit of the decomposition diagram is that it is impartial to whether the inputs came from observational retrievals or from model simulations. Analysis within this common domain is beneficial because model simulation outputs are not forced to mimic observations (e.g., radar reflectivity) and vis-a-versa (e.g., mimicking mixing ratio). This poster will have three sections. First, the poster will highlight how vertical air motion and DSD parameters were retrieved from simultaneous pairs of either (KAZR / RWP) or (W-band / RWP) vertically pointing radar Doppler velocity spectra. Second, the decomposition diagram will be described. Lastly, results will be presented from observations collected from SGP (2011-2016) and during the GoAmazon campaign (2014-2015).