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AMERICAN METEOROLOGICAL SOCIETY Journal of Applied Meteorology and Climatology EARLY ONLINE RELEASE This is a preliminary PDF of the author-produced manuscript that has been peer-reviewed and accepted for publication. Since it is being posted so soon after acceptance, it has not yet been copyedited, formatted, or processed by AMS Publications. This preliminary version of the manuscript may be downloaded, distributed, and cited, but please be aware that there will be visual differences and possibly some content differences between this version and the final published version. The DOI for this manuscript is doi: 10.1175/JAMC-D-14-0252.1 The final published version of this manuscript will replace the preliminary version at the above DOI once it is available. If you would like to cite this EOR in a separate work, please use the following full citation: Wang, Y., and B. Geerts, 2015: Vertical-plane dual-Doppler radar observations of cumulus toroidal circulations. J. Appl. Meteor. Climatol. doi:10.1175/JAMC-D-14- 0252.1, in press. © 2015 American Meteorological Society Revised manuscript Click here to download Manuscript (non-LaTeX): JAMC-D-14-0252_revision3.docx Vertical-plane dual-Doppler radar observations of cumulus toroidal circulations Yonggang Wang1, and Bart Geerts University of Wyoming Submitted to J. Appl. Meteor. Climat. October 2014 Revised version submitted in May 2015 1 Corresponding author address: Yonggang Wang, Department of Atmospheric Science, University of Wyoming, Laramie WY 82071, USA; email: [email protected] 1 Profiling dual-Doppler radar observations of cumulus toroidal circulations 2 3 Abstract 4 5 6 High-resolution vertical-plane dual-Doppler velocity data, collected by an airborne profiling 7 cloud radar in transects across non-precipitating orographic cumulus clouds, are used to examine 8 vortical circulations near cloud top. These vortices are part of a toroidal ring centered at an 9 updraft, usually near the cloud top, and they are essential to cumulus entrainment and dynamics. 10 A large number of transects across toroidal circulations is composited, in order to reveal the 11 typical kinematic structure and associated entrainment patterns. The toroidal ring circulation is 12 ~1 km wide and about half as deep in the sampled clouds (Cu mediocris). The composite flow 13 field shows two nearly-symmetric, counter-rotating vortices, with a core updraft of ~3 m s-1, 14 consistent vortex-top divergence, two flanking downdrafts of the about same strength, and 15 horizontal (toroidal) vorticity of ~0.03 s-1. Variations with vortex size, age, and ambient shear are 16 examined, and the relative dilution of air in the vortex core is estimated by comparing the liquid 17 water content, estimated from path-integrated power attenuation, to the adiabatic value. 18 1. Introduction 19 Cumulus clouds (Cu) are important in the climate system because they affect the vertical 20 structure of radiative heat flux divergence and dynamically couple the planetary boundary layer 21 to the free troposphere through vertical transports of mass, heat, moisture, aerosol, and 22 momentum. These clouds exist over a broad range of horizontal and vertical dimensions (e.g., 23 Lopez 1977; Wielicki and Welch 1986). A significant fraction of the vertical exchanges in Cu 24 circulations occurs at scales smaller than resolvable scales in numerical weather prediction 25 (NWP) and climate models (e.g., Khairoutdinov et al. 2008), therefore Cu parameterizations 26 have been developed to represent the effect of sub-grid-scale convection on precipitation and the 27 vertical profile of resolved variables (e.g., Bretherton et al. 2004). Such parameterizations make 28 assumptions about the turbulent mixing of Cu clouds with the environment (Siebesma and 29 Cuijpers 1995). They are evaluated by means of high-resolution numerical simulations, such as 30 large-eddy simulations (LES, e.g., Zhao and Austin 2005). In turn, these high-resolution 31 convection-allowing simulations need to be validated with detailed Cu observations (e.g., 32 Grabowski and Clark 1993; Craig and Dörnbrack 2008). This paper is one such observational 33 study. 34 Specifically, this paper examines updraft-driven toroidal (vortex-ring) circulations in Cu. 35 There is much evidence for the existence of such circulations near the top of buoyant clouds, 36 from modeling simulations (Klaassen and Clark 1985; Grabowski and Clark 1993; Zhao and 37 Austin 2005), laboratory experiments (Woodward 1959; Sanchez et al. 1989; Johari 1992), and 38 observational studies. The latter have used in situ aircraft data (MacPherson and Isaac 1977; 39 Blyth et al. 1988; Jonas 1990; Blyth et al. 2005), trace gas data (Stith 1992), and airborne radar 40 data (Damiani et al. 2006; Damiani and Vali 2007; Wang and Geerts 2013). 1 41 This study uses high-resolution (~30 m) vertical plane dual-Doppler radar data collected 42 along flight tracks across or just above isolated orographic Cu clouds. While the 30 m resolution 43 is sufficient to resolve vortex ring circulations, the shortest revisit time an aircraft is capable of, 44 ~2 min, is too long to capture the evolution of these circulations and entrainment events, given 45 the highly transient nature of Cu. Thus it is meaningful to examine vortex ring circulations in a 46 systematic way by compositing numerous circulations, each treated independently. Wang and 47 Geerts (2013) used this approach to examine the characteristic vertical velocity profile in Cu 48 clouds by means of numerous profiling airborne radar transects and corresponding flight-level 49 dynamical information. That study focused on vertical velocity over the depth of the cloud. It did 50 not examine horizontal winds. This paper builds on Wang and Geerts (2013) through the use of 51 two-dimensional (2D) velocity data to identify and characterize circulation features within Cu 52 clouds. These flow-based entities then are spatially normalized and composited. Division of the 53 entire sample into subgroups allows inspection of the effect of ambient wind shear, evolutionary 54 stage, and other parameters on the vortex ring circulation. 55 Data sources and analysis method are introduced in Section 2. Section 3 describes the 56 characteristic composite structure of vortex ring circulations, and stratifies this as a function of 57 size and age of circulations and ambient wind shear. Further implications are discussed in 58 Section 4. Section 5 lists the main conclusions. 59 60 2. Data sources and analysis methods 61 a. Environment of the sampled cumulus clouds 62 A dataset of 91 vortex rings is used in this study, collected from 58 Cu clouds or Cu 63 clusters penetrated or overflown by the University of Wyoming King Air (UWKA) in two 2 64 campaigns: the High-plains Cu (HiCu) campaign sampled Cu clouds mostly over the Laramie 65 Range (mostly near Laramie Peak) in southeastern Wyoming in the summer of 2003 (Damiani et 66 al. 2006). And the Cu Photogrammetric, In-situ and Doppler Observations (CuPIDO) campaign 67 was conducted over the Santa Catalina Mountain range in southern Arizona in July and August 68 2006 (Damiani et al. 2008; Geerts et al. 2008). 69 Both campaigns targeted relatively isolated non-precipitating Cu mediocris in an 70 environment with little shear. The flight track orientation was either terrain-relative (e.g., 71 following a ridge allowing multiple penetrations in a row) or a “rosette” pattern with 120° 72 separations, to minimize the time between transects across a single Cu (Damiani et al. 2008). The 73 UWKA did not by design fly along the shear vector. Most sampled clouds in this study are 74 orographic Cu clouds whose spatial relation to other clouds is controlled by the details of the 75 terrain (Demko and Geerts 2010; Wang and Geerts 2011), rather than by shear. Most clouds 76 were observed over or near terrain ridges; one case, in HiCu, involves a rather isolated Cu cloud 77 over a broad valley, about 20 km from a terrain ridge, with deeper clouds over the adjacent 78 mountains. None of the targeted clouds were aligned in cloud streets according to GOES visible 79 satellite imagery (e.g., Fig. 2, Wang and Geerts 2011). The 13 HiCu clouds in this study tend to 80 be more ‘continental’ than the 45 more “monsoonal” CuPIDO clouds, since they generally have 81 a higher cloud droplet concentration, a higher cloud base, lower liquid water content (LWC), and 82 a smaller mean drop size compared to CuPIDO clouds (Wang and Geerts 2013). Still, the 83 sampled CuPIDO clouds occurred on days that were relatively dry in the Arizona monsoon 84 period, either without deep convection, or with deep convection erupting only later in the day. 85 Mobile GAUS (GPS Advanced Upper-air Sounding) radiosonde data are used to describe 86 the typical environment of the Cu clouds sampled during CuPIDO (Fig. 1). The cloud base, 3 87 estimated from the lifting condensation level (LCL), averages around 3.0 km MSL (Fig. 1b). By 88 contrast, the average LCL for the 13 HiCu clouds sampled on three flights is ~4.3 km MSL. This 89 is estimated from near-surface conditions upon take-off and landing in Laramie Wyoming, 90 within ~100 km of the clouds, since no proximity radiosonde data were collected in HiCu. 푑휃푒 91 Potential instability ( < 0, with e equivalent potential temperature and z height) is present 푑푧 92 from the surface to ~4.7 km MSL in the CuPIDO clouds (Fig. 1a). An air parcel rising from the 93 convective boundary layer and conserving its e, will become buoyant relative to the ambient air ∗ 94 at ~3.8 km MSL (e,surface = 휃푒 , the saturated e, since the parcel from the surface is saturated at 95 this level). This is slightly above the mean level of free convection (LFC), about 3.5 km MSL 96 (Fig.

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