The vertical velocity and air mass flux in isolated convective clouds are
statistically analyzed using aircraft in situ data collected from three
field campaigns: High-Plains Cumulus (HiCu) conducted over the midlatitude
High Plains, COnvective Precipitation Experiment (COPE) conducted in a
midlatitude coastal area, and Ice in Clouds Experiment-Tropical (ICE-T)
conducted over a tropical ocean. The results show that small-scale updrafts and
downdrafts (
Convective clouds are an important component of the global energy balance and water cycle because they dynamically couple the planetary boundary layer to the free troposphere through the vertical transport of heat, moisture, and mass (Arakawa, 2004; Heymsfield et al., 2010; Wang and Geerts, 2013). The vertical velocity determines the vertical transport of cloud condensate, the cloud top height, and the detrainment into anvils, which further influences the radiative balance (Del Genio et al., 2005). Vertical velocity also has a significant impact on aerosol activation, droplet condensation, and ice nucleation in convective clouds, which in turn impacts cloud life cycle and precipitation efficiency.
In order to reasonably simulate convective clouds, the vertical air velocity must be parameterized reliably in numerical weather prediction models (NWPMs) and global circulation models (GCMs) (Donner et al., 2001; Tonttila et al., 2011; Wang and Zhang, 2014). However, the complexity of the vertical velocity structure in convective clouds makes the parameterization non-straightforward (Wang and Zhang, 2014). Observations show that in most of convective clouds the vertical velocity is highly variable, and consequently the detailed structure of convection cannot be resolved in many models (Kollias and Albrecht, 2010; Tonttila et al., 2011). Additionally, using the same parameterization of vertical velocity for different grid resolutions may result in different cloud and precipitation properties (Khairoutdinov et al., 2009). Furthermore, poorly parameterized vertical velocity may result in large uncertainties in the microphysics; for instance, the cloud droplet concentration may be underestimated due to unresolved vertical velocity (Ivanova and Leighton, 2008). Vertical velocity simulated by models with horizontal resolutions of a few hundred meters may be more realistic (e.g., Wu et al., 2009), but more observations are needed to evaluate this suggestion.
Aircraft in situ measurement has been the most reliable tool enabling us to understand the vertical velocity in convective clouds and to develop the parameterizations for models. Early studies (e.g., Byers and Braham, 1949; Schmeter, 1969) observed strong updrafts and downdrafts in convective clouds; however, their results have large uncertainties because the aircrafts were not equipped with inertial navigation systems (LeMone and Zipser, 1980). In 1974, the Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) was conducted off the west coast of Africa, focusing on tropical maritime convections (Houze Jr. and Betts, 1981). A series of findings based on the aircraft data collected from the project were reported. For example, the accumulated probability density functions (PDFs) of vertical velocity and diameter of the convective cores are lognormally distributed. The updrafts and downdrafts in GATE (tropical maritime clouds) were only one half to one third as strong as those observed in the Thunderstorm Project (continental clouds) (LeMone and Zipser, 1980; Houze Jr. and Betts, 1981). These findings stimulated later statistical studies of the vertical velocity in convective clouds. Jorgensen et al. (1985) found that the accumulated PDFs of vertical velocity in intense hurricanes were also distributed lognormally and the strength was similar to that in GATE, but the diameter of the convective region was larger. Studies of convective clouds over Taiwan (Jorgensen and LeMone, 1989) and Australia (Lucas et al., 1994) showed a magnitude of vertical velocity similar to that in GATE. Although the results from the Thunderstorm Project are suspect, the significantly stronger drafts reveal the possible difference between continental and tropical maritime convective clouds. Lucas et al. (1994) suggested that water loading and entrainment strongly reduce the strength of updrafts in maritime convection. However, this underestimation of the updraft intensity may be also due to sampling issues; e.g., penetrations were made outside the strongest cores (Heymsfield et al., 2010).
There are a few more recent aircraft measurements (e.g., Igau et al., 1999; Anderson et al., 2005), but the data are still inadequate to fully characterize the vertical velocity in convective clouds. In most of these earlier papers, the defined draft or draft core required a diameter no smaller than 500 m; this threshold excluded many narrow drafts with strong vertical velocity and air mass flux. In addition, the earlier studies used 1 Hz resolution data, which, at typical aircraft flight speeds, can resolve only vertical velocity structures larger than a few hundred meters, but the narrow drafts may be important to the total air mass flux exchange and cloud evolution. Furthermore, previous aircraft observations for continental convective clouds were based only on the Thunderstorm Project; thus, additional data are needed to study the difference between continental and maritime convections.
Remote sensing by means of, for example, wind profiling radars is another
technique that has often been used in recent years for studying the vertical
velocity in convective clouds (e.g., Kollias and Albrecht, 2010; Hogan et al.,
2009; Giangrande et al., 2013; Schumacher et al., 2015). Using profiler
data, May and Rajopadhyaya (1999) analyzed the vertical velocity in deep
convections near Darwin, Australia. They observed that the updraft
intensified with height and that the maximum vertical velocity was greater
than 15 m s
The present study provides aircraft data analysis of updrafts and downdrafts in midlatitude continental, midlatitude coastal, and tropical maritime convective clouds using the fast-response in situ measurements collected from three field campaigns: the High-Plains Cumulus (HiCu) project, the COnvective Precipitation Experiment (COPE), and the Ice in Clouds Experiment-Tropical (ICE-T). All data used in this study were compiled for individual, isolated penetrations. Statistics of the vertical velocity and air mass flux are provided. The Wyoming Cloud Radar (WCR), onboard the aircraft, is used to identify the cloud top height, and high-frequency (25 Hz) in situ measurements of vertical velocity are used to generate the statistics. The major limitations of aircraft in situ measurements are that the aircraft may not be able to sample the strongest convective cores due to safety concern and that it only provides the information of vertical air motion at single levels. These weaknesses need to be kept in mind in the following analyses. Section 2 describes the datasets and wind measuring systems. Section 3 presents the analysis method. Section 4 shows the results. Section 5 discusses the possible factors that interact with vertical air motions, and conclusions are given in Sect. 6.
The data used in the present study were collected from three field campaigns: HiCu, COPE, and ICE-T. Vigorous convective clouds were penetrated during the three field campaigns, including midlatitude continental, midlatitude coastal, and tropical maritime convective clouds. These cloud penetrations provide good-quality measurements for studying the microphysics and dynamics in the convective clouds, as well as the interactions between the clouds and the ambient air. The locations of the three field campaigns are shown in Fig. 1. Information regarding the penetrations used in this study is summarized in Table 1.
Number of penetrations, time in clouds, and flight length in clouds sampled at 0–2, 2–4, 4–6, 6–8, and 8–10 km a.m.s.l. in HiCu, COPE, and ICE-T.
Flight tracks for the three field campaigns: HiCu, COPE, and ICE-T.
The HiCu project was conducted mainly in Arizona and Wyoming (Fig. 1) from
the 18 July to the 5 August 2002, and from the 7 July to the 31 August 2003 to investigate the microphysics and
dynamics in convective clouds over the midlatitude High Plains. The
University of Wyoming King Air (UWKA) was the aircraft platform used in this
project. In 2002 and 2003, 10 and 30 research flights were conducted,
respectively. In this study, the 2002 HiCu and 2003 HiCu are analyzed
together because they were both conducted over the High Plains and the
sample size of 2002 HiCu is relatively small. Fast-response in situ
instruments and the WCR (Wang et al., 2012) were
operated during the field campaign to measure the ambient environment, cloud
dynamics and microphysics and the two-dimensional (2-D) cloud structure. As
shown in Table 1, penetrations in HiCu occurred between 2 and
10 km above mean sea level (a.m.s.l.)
The sample size is relatively large for penetrations below 8 km and
relatively small above 8 km. Accumulated aircraft flight length in cloud was
about 2000 km. In situ measurements and WCR worked well in these flights;
however, the upward-pointing radar was operated in less than half of the
research flights, and thus only a subset of the cloud top heights can be
estimated from the observations. Figure 2a(1–3) show an example of the clouds
sampled in HiCu, including WCR reflectivity, Doppler velocity, and 25 Hz
in situ measurement of the vertical velocity. In HiCu, both developing and
mature convective clouds were penetrated; some penetrations were near cloud
top, while most were more than 1 km below cloud top. The typical WCR
reflectivity ranges from 0 to 15 dBZ in the convective cores. In these
clouds, reflectivity is strongly impacted by Mie scattering at the WCR
wavelength. From the Doppler velocity and the in situ vertical velocity, we
see that, in both the developing and mature cloud, relatively strong
updrafts and downdrafts were observed, and multiple updrafts and downdrafts
existed in the same cloud. These drafts may be strong for isolated
convection but not necessarily strong compared to the strongest updrafts in
mesoscale convective systems (MCSs). No balloon soundings are available to
measure the ambient environment in HiCu, so we use aircraft measurements to
characterize the thermodynamic environment and estimate the convective
available potential energy (CAPE). In some cases, the full CAPE cannot be
calculated since the aircraft only flew at low levels (below 10 km a.m.s.l.). The
aircraft measurements suggest that the CAPE in HiCu ranged from less than
100 J kg
Examples of radar reflectivity, Doppler velocity, and 25 Hz in situ
vertical velocity measurements for the convective clouds sampled in HiCu,
COPE, and ICE-T. The red dots in
The COPE project was conducted from the 3 July to 21 August 2013 in southwest England (Fig. 1). The UWKA was used to study the
microphysics and entrainment in midlatitude coastal convective clouds (Leon
et al., 2016). Seventeen research flights were conducted. The penetrations
focused on regions near cloud top, which is verified based on the radar
reflectivity from the onboard WCR. Since COPE was conducted in a coastal
area, the convection initiation mechanism is different from that over a
purely continental or ocean area. In addition, although the ambient air
mainly came from the ocean, continental aerosols might be brought into the
clouds since many of the convective clouds formed within the boundary layer,
further impacting the microphysics and dynamics of these clouds.
Measurements from COPE include temperature, vertical velocity, liquid water
content, and particle concentration and size distributions. The WCR provided
measurements of reflectivity and Doppler velocity. The downward Wyoming
Cloud Lidar (WCL) was operated to investigate the liquid (or ice) dominated
clouds. The typical WCR reflectivity ranged from 5 to 20 dBZ in the
convective cores. Between 0 and 6 km, there were about 800 penetrations.
Accumulated flight distance in cloud totaled about 1000 km. The sample sizes
are relatively large between 2 and 6 km but relatively small between 0 and 2 km. Examples of the penetrations are given in Fig. 2b(1–3). COPE
has fewer penetrations than HiCu, and most of the penetrations are near the
cloud top. Figure 2b(2) reveals relatively simple structures of the updrafts
and downdrafts in COPE compared to HiCu, but as shown by the 25 Hz in situ
vertical velocity measurement in Fig. 2b(3), there are still many
complicated fine structures in the vertical velocity distribution. The
typical CAPE estimated from soundings in COPE was a few hundred J kg
The ICE-T project was conducted from the 1 July to the 30 July 2011 near St. Croix, U.S. Virgin Islands (Fig. 1), with
state-of-the-art airborne in situ and remote sensing instrumentations, with
the aim of studying the role of ice generation in tropical maritime
convective clouds. The NSF/NCAR C-130 aircraft was used during ICE-T to
penetrate convective clouds over the Caribbean Sea. Thirteen C-130 research
flights were conducted during the field campaign. In situ measurements from
ICE-T include the liquid and total condensed water contents, temperatures,
vertical velocities, and cloud and precipitating particle concentrations and
size distributions. The WCR was operated on seven research flights to
measure the 2-D reflectivity and Doppler velocity fields. Typical WCR
reflectivity within convective cores ranged from 10 to 20 dBZ. Accumulated
flight distance through clouds was greater than 1500 km, throughout the more
than 650 penetrations between 0 and 8 km. The sample sizes are good
except between 2 and 4 km (Table 1). Examples of the penetrations are
shown in Fig. 2c(1-3). During ICE-T, clouds at different stages were
penetrated, including developing, mature, and dissipating clouds, some near cloud
top and some considerably below cloud top. Maximum observed updrafts were 25 m s
During the sampling of isolated convective clouds in all the three field campaigns, the aircraft was typically aligned to penetrate through the center of the convective turret; however, this does not guarantee that the aircraft always penetrated through the strongest updraft at that level. In addition, aircraft in situ measurements only provide the information of vertical air motion at single levels. Moreover, the clouds sampled are isolated convective clouds, MCSs were not sampled. These limitations need to be kept in mind in interpreting the results from the following analyses.
On both the C-130 and UWKA, a five-hole gust probe is installed for
measurements of 3-D wind. On the C-130, this probe is part of the
fuselage radome, on the UWKA the probe is mounted on the end of an extended
boom protruding from the front of the aircraft. In both cases the probe
contains five pressure ports installed in a “cross” pattern. Relative wind
components (e.g., true air speed and flow angles) are sensed by a combination
of differential pressure sensors attached to the five holes (Wendisch and
Brenguier, 2013). Detailed calculation of relative wind components is
described in Wendisch and Brenguier (2013). The time response and the
accuracy of the pressure sensors is about 25 Hz and 0.1 mb. The 3-D wind
vectors are determined by subtracting the aircraft velocity from the
relative wind measurement after rotating the vectors to a common coordinate
system. On the C-130 and UWKA, aircraft velocity is measured by a Honeywell
LASEREF SM Inertial Reference System (IRS), with an accuracy of 0.15 m s
The Particle Measuring Systems (PMS) Two-Dimensional Cloud (2D-C) Probe and the Forward Scattering Spectrometer Probe (FSSP) are often used to characterize cloud microphysics (e.g., Anderson et al., 2005), although different thresholds of 2D-C and FSSP concentrations are usually used to identify the edge of a cloud. In this paper, we also use FSSP and 2D-C probes to find the cloud edges. In order to find a reasonable threshold for identifying cloudy air, we first use the WCR reflectivity to identify the clouds and the cloud-free atmosphere; for those regions we then plot the particle concentrations measured by FSSP and 2D-C in order to determine reasonable thresholds, and we apply the thresholds of particle concentrations to all the research flights without WCR.
To identify clouds using WCR, the six effective range gates nearest to the
flight level (three above and three below) are chosen in each beam. Any beam
in which the minimum reflectivity at the six gates exceeds Based on the reflectivity measured in cloud-free air, the noise level of WCR
reflectivity is
Occurrence distributions as a function of the particle
concentrations measured by FSSP versus the concentrations of the particles
Figure 3 shows the occurrence distribution as a function of the particle
concentrations measured by FSSP versus the concentrations of the particles
PDFs of the diameters for the updrafts and downdrafts sampled at 0–2, 2–4, 4–6, and higher than 6 km. The numbers shown in each panel are the coefficients of the fitted exponential function (Eq. 1).
Once a cloud is identified, the penetration details can be calculated, including the flight length, the flight height, the cloud top height if WCR data were available, and the penetration diameter. The penetration diameter is calculated as the distance between the entrance and exit of a penetration. In order to reject penetrations with significant turns, we require that the diameter of a penetration be at least 90 % of the flight length, so the cloud scale will not be significantly overestimated. Since the aircraft might not penetrate exactly through the center of a cloud, the actual cloud diameter may be larger than the penetration diameter. Based on WCR reflectivity images, there are no isolated convective clouds sampled larger than 20 km in diameter. There are a few penetrations longer than 20 km, but these clouds are more like part of MCSs, and so they are excluded from this study.
In previous studies of the vertical velocity based on in situ measurements,
the updraft and downdraft were often defined as an ascending or subsiding
air parcel with the vertical velocity continuously
The diameter threshold (500 m) is not used in this paper because drafts
narrower than 500 m frequently occur and they may make important
contributions to the total air mass flux in the atmosphere, and therefore
they are necessary to be considered in model simulations. Figure 4 shows the
PDFs of the diameters of all the updrafts and downdrafts sampled in HiCu,
COPE, and ICE-T. In all the panels, the diameters are exponentially
distributed; the PDFs can be fitted using
Occurrence distributions as
Figure 5a shows the occurrence distributions as a function of the mean
vertical velocity versus the diameter of the drafts with the vertical
velocity continuously
In this study, we delineate three different groups of updrafts and
downdrafts using three thresholds of air mass flux: 10,
100, and 500 kg m
Number of updrafts and downdrafts sampled at 0–2, 2–4, 4–6, 6–8, and 8–10 km in HiCu, COPE, and ICE-T. Three numbers are given for the updraft and downdraft at each level, according to the three different definitions: weak, moderate, and strong.
Some researchers have defined a “draft core” by selecting the strongest
portion within a draft. For example, LeMone and Zipser (1980) define an
updraft core as an ascending air motion with vertical velocity continuously
From the analysis above, we note that relatively small and weak updrafts are frequently observed in convective clouds. In this section, we provide further evidence to show the importance of the relatively weak updrafts in terms of air mass flux.
Figure 6a shows the average number of updrafts as a function of air mass flux
observed in the three field campaigns. The solid, dashed, and dotted lines
represent the penetrations with different diameters. As shown in Fig. 6a,
weak and moderate updrafts are more often observed than strong updrafts, and
more updrafts are observed in longer penetrations. Since this is an average
result, the number of updrafts could be smaller than 1 (e.g., many short
penetrations do not have strong updrafts). Figure 6b is similar to 6a but
shows the occurrence frequency of updrafts with different air mass fluxes
(i.e., the vertical axis in Fig. 6a is normalized). For the penetrations less
than 1 km in length, many of the clouds only have weak or moderate updrafts,
and relatively strong updrafts are rarely observed. For penetrations of
1–10 km, the frequency of strong updrafts increases and the frequency of
weak and moderate updrafts decreases. For even longer penetrations
(
Figure 7 shows the average percentile contributions to the total upward air
mass flux by the three different groups of updrafts as a function of
penetration diameter. In Fig. 7a, all the penetrations are included. Since
many narrow clouds have no strong updrafts in terms of air mass flux, the
total air mass flux in these narrow clouds is mostly contributed by weak
(red bar) and moderate (green bar) drafts. These narrow clouds may have a
large vertical velocity but small air mass flux. As the diameter increases
to 4 km, the contributions to total air mass flux from relatively weak
updrafts (red bar) decrease, while those from stronger updrafts (blue bar)
increase. For a penetration of 4 km length, 80–90 % of the total
upward mass flux is contributed by the strong updrafts with air mass flux
Figure 8 shows the PDFs of the vertical velocity in the drafts sampled at 0–2, 2–4, and 4–6 km and higher than 6 km in the three field campaigns.
Columns (a), (b), and (c) represent the drafts with air mass flux
In Fig. 8, the observed updrafts are stronger in ICE-T and COPE (maritime or
coastal convective clouds) than in HiCu (pure continental convective
clouds). But the aircraft might under-sample the strongest part of the
convective cores. In addition, the PDFs are plotted as a function of
mean sea level height, the relatively narrow PDFs in HiCu compared to COPE and ICE-T at the
same height are possibly because of the higher cloud bases in HiCu. Other
than the sampling issues, the triggering mechanism for convection is also
important for the updraft strength. The clouds sampled in the three field
campaigns are all isolated convective clouds, the CAPE in HiCu was smaller
than in COPE and ICE-T. Compared to the GATE project, in which the clouds
were also sampled over a tropical ocean, the PDFs of the vertical velocity
in ICE-T have a similar vertical dependence, broadening with height. But the
PDFs are broader in ICE-T than those in GATE, and the maximum vertical
velocity (25 m s
Average percentile contribution to total upward air mass flux by the weak (red), moderate (green), and strong (blue) updrafts delineated in this study. The result is a composite of HiCu, COPE, and ICE-T.
PDFs of the 25 Hz vertical velocity for the updrafts and
downdrafts with air mass flux
PDFs of the air mass flux for the updrafts and downdrafts sampled
at 0–2, 2–4, and 4–6 km and higher than 6 km. The three thresholds of the
air mass flux (
Figure 9 shows the PDFs of the air mass flux for all the drafts sampled at 0–2, 2–4, and 4–6 km and higher than 6 km. The PDFs are exponentially distributed for the three field campaigns at different heights, which can be fitted using Eq. (1). The coefficients for the fitted function are shown in each panel. In the three field campaigns, the PDFs of air mass flux have no obvious trend with height, although the PDFs of diameter and vertical velocity broaden with height. The differences among the three field campaigns are small for weak and moderate drafts, and become slightly larger for relatively strong updrafts, which could be due to the sampling issues.
Profiles of
Figure 10 is a whisker–box plot showing the profiles of the vertical velocity (a–c) and air mass flux (d–f) in the drafts based on the three defined thresholds of air mass flux. The solid box includes all three different groups of drafts, the dashed boxes excludes the weak drafts, and the dotted boxes includes strong drafts. The minimum, 10, 50, 90 %, and maximum values are shown in each box. In each panel, the absolute values of the vertical velocities and air mass flux (except the minimum and maximum ones) are relatively small for the solid boxes.
In Fig. 10a–c, the three definitions of drafts show different intensities in
the vertical velocities. Typically, the 10, 50, and 90 % values in
the dotted boxes are 1–2 times larger in magnitude than those in the solid
boxes. However, the profiles of the three definitions of drafts vary
similarly with height for each field campaign. In the updrafts sampled
during HiCu (Fig. 10a), the maximum vertical velocity increases with height
up to 8 km, then decreases with height above that. The 90 % vertical
velocity in the solid boxes increases from 4 to 8 m s
To summarize, the observed vertical velocity in the drafts varies
differently with height in the three field campaigns. Stronger downdrafts
are often observed in HiCu and COPE compared to those in ICE-T. The weak,
moderate, and strong drafts have similar variations with height, but the
magnitudes are the smallest when including all the drafts and become larger
if the weak drafts are excluded. The 10, 50, and 90 % vertical
velocities in updrafts and downdrafts over the tropical ocean (ICE-T)
observed in this study generally have similar magnitudes to those shown in
previous studies (e.g., LeMone and Zipser, 1980; Lucus et al., 1994). But
strong updrafts (downdrafts) in excess of 20 m s
Figure 10d–f show the profiles which the air mass flux statistics for the drafts
sampled during the three field campaigns. As expected, the absolute values
of the air mass flux are relatively small if all the drafts are included
(dotted boxes) and become larger if the drafts with relatively small air
mass flux are excluded. However, the variations of the observed air mass
flux with height are similar for the three different definitions in each
panel. As determined by the three thresholds, the minimum absolute values in
the solid boxes are about 10 times smaller than those in the dashed boxes
and about 50 times smaller than those in the dotted boxed. For the 10,
50, 90 %, and the maximum absolute values, the differences among the
three types of boxes become smaller. The observed air mass flux varies with
height differently for the three field campaigns and does not have an
obvious trend with height. For updraft, the observed maximum air mass flux
is on the order of 10
Composite structure of the vertical velocity as a function of the
normalized diameter for the updrafts and downdrafts with air mass flux
Figure 11 shows the composite structure for the updrafts and downdrafts with
air mass flux
In this composite analysis based on in situ measurements, the penetration direction has no obvious impact on the vertical velocity structure, whether the aircraft penetrates along or across the horizontal wind (not shown). For convective clouds, wind shear has a large impact on the cloud evolution (Weisman and Klemp, 1982); however, the aircraft data are insufficient to reveal the wind shear impact because each penetration was made at a single level and the aircraft did not always penetrate through the center of the draft. Remote sensing data can be helpful to study the 2-D or 3-D structures of the vertical velocity in convective clouds. For example, airborne radar with slant and zenith or nadir-viewing beams can provide 2-D wind structure in convective clouds (e.g., Wang and Geerts, 2013). Volumetric radar (e.g., Collis et al., 2013; Jorgensen et al., 2000) can provide 3-D structure of air (or hydrometeor) motion. Thus, in situ measurements as well as remote sensing measurements are needed to further analyze the wind shear impact.
Profiles of
Figure 12 shows the profiles of vertical velocity (a–c) and air mass flux (d–f) for the updraft and downdraft in the convective clouds with different cloud top heights (CTHs). Here, all weak, moderate, and strong updrafts are included. Different colors represent clouds with different CTHs. These profiles generally reveal the change in vertical velocity and air mass flux as the clouds evolve. The key point presented in Fig. 12a–c is that the peak vertical velocity is observed at higher levels as the clouds evolve. For clouds with CTHs lower than 4 km (red boxes), the maximum vertical velocity is observed at 2–4 km. When the cloud becomes deeper, the observed vertical velocity and air mass flux are stronger at higher levels. The maximum vertical velocity is observed within 2 km of cloud top; consistent with Doppler velocity images measured by WCR (e.g., Fig. 2b) that show the strongest updraft is typically observed 1–1.5 km below cloud top. The strongest downdrafts are sometimes observed more than 2 km below cloud top. The 10 and 50 % values do not have obvious trends as the clouds evolve, possibly because of the increasing contribution from moderate and weak drafts as the clouds become deeper and broader (Figs. 6 and 7). The observed air mass flux (Fig. 12d–f) has no obvious trend as the clouds evolve, again suggesting multiple factors (e.g., entrainment–detrainment, microphysics) may impact the evolution of these drafts. Since the aircraft provides data from just single-line penetrations, and not 2-D vertical information, additional measurements, including remote sensing measurements, are needed to better understand the evolution of the vertical velocity in convective clouds.
In this study, we provide the statistics of vertical air motion in isolated convective clouds using in situ measurements from three field campaigns. The statistical results suggest that vertical air motions in convective clouds are very complicated and could be affected by many factors.
Microphysics strongly interacts with vertical velocity through different
processes, for example, droplet condensation–evaporation, ice
nucleation–sublimation, and water loading. Yang et al. (2016) show the
liquid water content (LWC) and ice water content (IWC) are both higher in stronger updrafts in developing convective
clouds, while the liquid fraction has no obvious correlation with vertical
velocity. In mature convective clouds the LWC is also higher in stronger
updrafts, but the IWC is similar in relatively weak and strong updrafts. The
liquid fraction is correlated to the vertical velocity between
Entrainment–detrainment also has a strong interaction with vertical velocity. In the analysis above, the downdrafts observed in HiCu and COPE are stronger than those observed in ICE-T. This may be partly because the ambient relative humidity is low in HiCu and COPE compared to ICE-T, resulting in a strong evaporation–cooling effect when the ambient air mixes with cloud parcels through lateral entrainment–detrainment (Heymsfield et al., 1978). Entrainment has impacts on updrafts as well. Recent studies using in situ measurements and model simulations suggest that stronger entrainment may result in weaker updrafts (e.g., Lu et al., 2016). In this study, we also find that weaker updrafts are associated with stronger entrainment–detrainment using in situ measurements of relative humidity, equivalent potential temperature, droplet concentration, and LWC (not shown). Previous studies (e.g., Heymsfield et al., 1978; Wang and Geerts, 2013) suggest updraft cores unaffected by entrainment may exist in some convective clouds.
Again it is important to be aware of the limitations of using aircraft in situ measurements for this kind of study. More observations (in situ and remote sensing) as well as model simulations are needed to better characterize the vertical air motion in convective clouds and its interactions with microphysics and entrainment–detrainment mixing.
The vertical velocity and air mass flux in isolated convective clouds are
statistically analyzed in this study using aircraft data collected from
three field campaigns – HiCu, COPE, and ICE-T – conducted over the midlatitude
High Plains, midlatitude coastal area, and tropical ocean. Three thresholds
of air mass flux are selected to delineate weak, moderate, and strong draft:
10, 100, and 500 kg m
Small-scale updrafts and downdrafts in convective clouds are often observed in the three field campaigns.
More than 85, 90, and 74 % of the updrafts are narrower than 500 m in HiCu, COPE, and ICE-T, respectively,
and more than 90 % of the downdrafts are narrower than 500 m in the three field campaigns combined. These small-scale drafts make significant contributions to the total air mass flux. Updrafts narrower than 500 m contribute
20–35 % of the total upward flux, and downdrafts narrower than 500 m contribute 50–65 % of the total downward air mass flux. In terms of the air mass flux, the weak and moderate drafts make an important contribution to the total air mass
flux exchange. Generally, the number of drafts increases with cloud diameter. For many narrow clouds, the weak and
moderate drafts dominate and contribute most of the total air mass flux. For broader clouds, the stronger updrafts
contribute most of the total air mass flux, but the contribution from weak and moderate drafts increases as the cloud evolves. PDFs and profiles of the vertical velocity are provided for the observed drafts. In all the height ranges, the
PDFs are roughly exponentially distributed and broaden with height. The observed downdrafts are stronger in HiCu and COPE
compared to ICE-T. Relatively strong updrafts ( PDFs and profiles of the air mass flux are provided for the observed drafts. The PDFs are similarly exponentially
distributed at different heights and have no obvious trend with height. In the updrafts, the observed maximum air mass
flux has an order of 10 The composite structures of the vertical velocity in the updrafts and downdrafts have similar normalized shapes for the
three field campaigns: the vertical velocity is the strongest near the center and weakens towards the edges. Statistically,
the vertical velocity and diameter were increasing with height, but the air mass flux does not have an obvious trend with height,
suggesting that entrainment–detrainment, water loading, and other complicated processes have impacts on the evolution of the drafts. The change in vertical air motion characteristics as the cloud evolves are briefly discussed. Generally, the strongest
portion of a draft ascends with height as the cloud evolves. The maximum vertical velocity is observed within 2 km below
cloud top; the downdrafts are sometimes stronger at levels more than 2 km below cloud top.
The vertical air motion in convective clouds is very complicated and is
affected by many factors, such as convection mechanisms,
entrainment–detrainment, and microphysics. This study only deals with
isolated convective clouds, and there are many limitations of aircraft
in situ measurements. More data, including both in situ and remote sensing
measurements, are needed to better understand the vertical air motion in
convective clouds.
Data collected during ICE-T is available at
This work is supported by National Science Foundation Award AGS-1230203 and AGS-1034858, the National Basic Research Program of China under grant no. 2013CB955802, and DOE Grant DE-SC0006974 as part of the ASR program. The authors acknowledge the crew of NCAR C-130 and University of Wyoming King Air for collecting the data and for providing high-quality products. Many thanks are also extended to Gerald Heymsfield and Scott Collis for their constructive comments.Edited by: P. Chuang Reviewed by: G. Haymsfield and S. Collis