Dependence of Vertical Alignment of Cloud and Precipitation Properties on Their Effective Fall Speeds. Issue 4 (18th February 2019)

• Record Type: Journal Article
• Authors: Ovchinnikov, Mikhail; Giangrande, Scott; Larson, Vincent E.; Protat, Alain; Williams, Christopher R.
• Is Part Of: Journal of geophysical research. Volume 124:Issue 4(2019)
• Page Start: 2079
• Page End: 2093
• Publication Date: 2019-02-18
• Subjects: cloud and precipitation overlap -- microphysics parameterization -- hydrometeor classification -- subcolumn generator -- fall speed -- wind shear; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2018JD029346
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: The vertical structure of clouds unresolved in large‐scale weather prediction and climate models is controlled by an overlap assumption. When a binary representation (cloud or no cloud) of subgrid horizontal variability is replaced by a probability density function (PDF) treatment of cloud‐related variables, a cloud occurrence overlap needs to be replaced by a PDF overlap. The PDF overlap can be quantified by a correlation length scale, z 0, indicating how rapidly rank correlation of distributions at two levels diminishes with increasing level separation. In this study, we show that z 0 varies widely for different properties (e.g., number and mass mixing ratios) and different hydrometeor types (cloud liquid and ice, rain, snow, and graupel) and that corresponding fall speed, V f, is the primary factor controlling the degree of their vertical alignment, with vertical shear of the horizontal wind playing a smaller role. Linear and power law parametric relationships between z 0 and V f are derived using cloud‐resolving simulations of convection under midlatitude continental and tropical oceanic conditions, as well as observations from vertically pointing dual‐frequency radar profilers near Darwin, Australia. The functional form of z 0 ‐ V f relationship is further examined using simple conceptual models that link variability in horizontal and vertical directions and provide insights into the role of V f and wind shear. Being based on a physical property (i.e., fall speed) of hydrometeors rather than artificially defined and model‐specific hydrometeor types, the proposed parameterization of vertical PDF overlap can be applied to a wide range of microphysics treatments in regional and global models. Key Points: Rank correlations of cloud and precipitation distributions at adjacent levels are computed for model‐simulated and radar‐observed fields Correlation length scale, or PDF overlap, is a function of mean fall speed of considered property Wind shear reduces alignment of slow falling species, but has limited effect on faster precipitating hydrometeor categories