Shallow marine cumulus clouds are by far the most frequently observed cloud type over the Earth's oceans; but they are poorly understood and have not been investigated as extensively as stratocumulus clouds. This study describes and discusses the properties and variations of aerosol, cloud, and precipitation associated with shallow marine cumulus clouds observed in the North Atlantic trades during a field campaign (Barbados Aerosol Cloud Experiment- BACEX, March–April 2010), which took place off Barbados where African dust periodically affects the region. The principal observing platform was the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter (TO) research aircraft, which was equipped with standard meteorological instruments, a zenith pointing cloud radar and probes that measured aerosol, cloud, and precipitation characteristics.
The temporal variation and vertical distribution of aerosols observed from
the 15 flights, which included the most intense African dust event during
all of 2010 in Barbados, showed a wide range of aerosol conditions. During
dusty periods, aerosol concentrations increased substantially in the size
range between 0.5 and 10
The TO was able to sample many clouds at various phases of growth. Maximum
cloud depth observed was less than
Shallow marine cumulus clouds are frequently observed over the Earth's oceans and are by far the most common type of cloud in the world (Norris, 1998). The fractional cloudiness associated with these cumulus clouds is typically 15 to 25 %, but the extensive areas that the shallow cumuli cover make their radiative impact an important factor in the climate system. Further, shallow cumulus clouds are part of the feeder system for deep convection in the tropics and are critical to the energy and moisture budget of the trade-wind boundary layer. Recent studies indicate that these clouds are the cause of the largest uncertainty in tropical cloud feedbacks in the climate system (e.g., Bony and Dufresne, 2005; IPCC, 2013) and therefore the characteristics and distributions of their variability must be better defined.
The landmark studies by Riehl et al. (1951), Riehl and Malkus (1957), and Malkus (1958) inferred the importance of shallow moist convection in maintaining the boundary layer structure and associated energy and moisture budgets associated with the trade winds. Field programs that followed these studies – the 1969 Atlantic Trade-Wind Experiment (ATEX) and the 1969 Barbados Oceanographic and Meteorological Experiment (BOMEX) – provided rawindsonde data sets that were used to estimate enthalpy and moisture budgets associated with shallow, undisturbed cumulus clouds (Augstein et al., 1973; Holland and Rasmussen, 1973). Although several aircraft were associated with BOMEX (Friedman et al., 1970), the instrumentation on these aircraft was not adequate for routine measurements of cloud properties. In the 2004–2005 Rain in Cumulus over the Ocean (RICO; Rauber et al., 2007), instrumented aircrafts were used to sample clouds and precipitation and key processes operating in these clouds observed over the Eastern Caribbean (e.g., Hudson and Mishra, 2007; Colón-Robles et al., 2006; Gerber et al., 2008). Further, the Barbados Cloud Observatory (operated by the Max Planck Institute for Meteorology (MPI), Stevens et al., 2016), using ceilometer, Raman lidar, and cloud radar observations, has provided a first-of-a-kind 2-year climatology of non-precipitating and precipitating cumulus (Nuijens et al., 2014), and analyzed the relative influences of aerosols and meteorology on precipitation formation (Lonitz et al., 2015). In the same area, detailed aerosol, cloud, radiation, and turbulence observations were made from a platform suspended from a helicopter operating in an area off the coast of Barbados as part of the CARRIBA (Cloud, Aerosol, Radiation and tuRbulence in the trade-wind regime over BArbados) project (Siebert et al., 2013).
The marine environment near Barbados provides an excellent area to sample shallow marine clouds that have a strong propensity to precipitate. In addition, African dust outbreaks periodically affect the clouds over the regime, and offer an excellent opportunity to observe aerosol-cloud-precipitation interactions. Furthermore, near-surface aerosol measurements have been made on the island since the 1960s (Prospero and Lamb, 2003). To better understand aerosol–cloud–precipitation interactions in the trade cumuli regime, Barbados Aerosol Cloud Experiment (BACEX) was carried out off the Caribbean island of Barbados, within the northeast trades of the North-Atlantic from mid-March and mid-April 2010 (Jung et al., 2013).
The goal of the BACEX study is to improve our understanding of aerosol–cloud–precipitation processes in the trade-wind cumulus regime, and thus, to improve and/or provide a basis for evaluating and improving the parameterization of cloud–aerosol–precipitation interactions in numerical models. As a first step, this paper is intended to document the properties of shallow marine cumulus clouds and the vertical structure of the Saharan air layer (SAL), and provide reference data for interpreting and comparing satellite data. The findings from this study confirm some previous results and also add new insights to the distribution and variability of clouds and aerosols in the North-Atlantic trades. The interactions among aerosol, cloud and precipitation will be addressed in a separate study, and thus, cloud and precipitation responses to the aerosols, including cloud particle size distributions, are not discussed in the current paper.
Satellite-based studies have been used to examine aerosol-cloud interactions over large geographical areas for extended time periods, but are known to suffer from retrieval biases (Loeb and Schuster, 2008) and the vertical distribution – a key component of the aerosol – is usually unknown. Thus, we combine the in situ aircraft data from BACEX with soundings from the island to explore the boundary layer structure and properties of clouds and aerosols over this area of the Caribbean. Data used in this study and methods are described in Sect. 2. The overall large-scale atmospheric conditions during the experiment, aerosol source regions observed in Barbados, temporal and vertical variations of aerosols are discussed in Sect. 3, along with cloud and precipitation properties including radar reflectivity and Doppler velocity distribution of clouds, two types of precipitation (classic cloud-base precipitation versus cloud-top precipitation), non-adiabatic characteristics of shallow marine cumulus clouds, and followed by the summary and discussion in Sect. 4.
The Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS)
Twin Otter (TO) research aircraft made 15 flights from 19 March to 11 April
upstream of Ragged Point (13.2
The TO research aircraft was equipped with probes that measure aerosol,
cloud and precipitation in addition to the standard meteorological
instruments for observing the mean and turbulent thermodynamic and wind
structures as described in Zheng et al. (2011) and Jung et al. (2013). The
standard meteorological variables (e.g., temperature, water vapor mixing
ratio, winds) and liquid water content (PVM-100, Gerber et al., 1994) were
obtained at 10 Hz and then averaged to 1 Hz. Aerosol data included aerosol
number concentration (
Vertically pointing cloud radar (95 GHz, bi-static, frequency modulated
continuous wave Doppler radar) was mounted on top of the aircraft fuselage
and detected fine vertical structures of updrafts and downdrafts within the
clouds and precipitation properties. The radar data were obtained at a
sampling rate of 3 Hz with range gates of 24 m, an antenna beam width of 0.7
Characteristics of instruments used in Barbados Aerosol Cloud Experiment.
Near-surface aerosol measurements were made at Ragged Point, a site located on the edge of a 30 m high bluff on the easternmost coast of Barbados. Samples were collected from the top of a 17 m high tower using a high-volume filter sampling system. Filters were changed daily and periodically returned to Miami where the soluble components were extracted with water (Li-Jones et al., 1998). The Ragged Point aerosol site is operated by Dr. Joseph Prospero's research group from the University of Miami.
The large-scale time-height variability of temperature, moisture, and wind
structures in the study area was analyzed using observations from
rawindsondes launched at Grantley Adams airport (13.06
The origin of air masses sampled by the TO was estimated using the Hybrid
Single Particle Lagrangian Integrated Trajectory (HYSPLIT;
An effective aerosol particle size (
Rainfall rate (mm h
Time-height cross section of
General features of large-scale atmospheric conditions over the study area
are shown in Fig. 1 by time-height cross-sections of humidity, temperature,
wind speed, and wind direction from the Barbados soundings for the period of
14 March to 16 April 2010. During the experiment, the Lifting Condensation
Level (LCL; calculated from the average thermodynamic properties of the
sub-cloud layer) was lower than 1 km (
Atmospheric humidity conditions (Fig. 1a) showed significant dry air
intrusions into the layer below 2 km, prior to 22 March and from 31 March to
5 April (dusty period). On 5 April, a sharp dry-to-moist transition occurred
through the entire lower atmosphere. The sub-cloud layer (below the LCL) was
relatively well-mixed throughout the field experiment (Fig. 1b), showing a
constant
There was no precipitation recorded at the surface weather station in
Barbados during the campaign (no rain or trace recorded,
The overall atmospheric conditions and variability observed from the TO are
illustrated in Fig. 2 with the vertical profiles of potential temperature
(
To determine how the BACEX thermodynamic structures compare with those
obtained from previous field campaigns in Caribbean cumulus regimes, we
compare these structures with the vertical profiles of
Profiles of
Profiles of
In Fig. 3, BOMEX shows similar moisture conditions as BACEX below the
inversion (
The 10-day back trajectories, arriving at 500 m in the middle of the BACEX flight domain. Dates for each back trajectory are shown accordingly.
Back trajectories were calculated to give a rough indication of the air mass source regions observed in the boundary layer during BACEX. The 10-day backward trajectories were calculated by using daily 12:00 UTC air masses, observed at 500 m in the middle of the flight domain (Fig. 4). The air mass within the boundary layer over Barbados (Fig. 4) originated mainly from three regions, in agreement with the findings of Dunion (2011). The first group of similar air-mass source regions occurred on 19 March and during 30 March and 5 April. They corresponded to the periods of dry air intrusion into the lower troposphere (Fig. 1a) when the air mass originated from Africa (dust outbreak period). The second group of similar air mass source regions occurred between 23 and 26 March, and originated from mid-latitude continents (e.g., North America). The third group (e.g., 3/22, 3/29, 4/10, 4/11) originated from the North Atlantic with trajectories remaining over the ocean for at least 10 days.
African dust events across the North Atlantic, including the period of
BACEX, suggested a series of SAL outbreaks (not shown). Prior to BACEX, a
large SAL event occurred on 16 March from the African coast. Over the next
few days, dust spread over the North Atlantic. Then, another surge of dust
occurred over Africa on 22, and 25–26 March based on the satellite images
and vertical structures of
Aerosol concentrations measured at the surface and in the sub-cloud layer
are shown in Fig. 5, along with the vertical structures of aerosol
concentration in the trade-wind boundary layer. Dust surface concentration
(Fig. 5c) was obtained at the Ragged Point surface site. Sub-cloud
Temporal variations of sub-cloud aerosols are shown in Fig. 5b. The mean
values of CN (black), PCASP (blue) and CCN (activated at a super-saturation
of 0.6 %, hereafter ss
The vertical distribution of
The variety of vertical structures, evident in Fig. 5a, is of interest;
The BACEX aircraft observations provided a characterization of the
variability in the aerosol particle size distributions (PSDs) (Fig. 6). PSDs
were calculated from all available PCASP measurements made on
pseudo-soundings and level flights for a given day, when no liquid water was
detected (i.e., cloud-free air), to give daily flight-averaged PSDs (Fig. 6a). Further, PSDs were calculated from PCASP measurements made at sub-cloud
layer (Fig. 6b) to show the differences in PSD with height by comparing with
PSDs in Fig. 6a (i.e., integrated PSD in Fig. 6a versus PSDs at sub-cloud layer in
Fig. 6b). The accumulation mode aerosols, which are measured by PCASP have a
maximum concentration at about 0.15
Daily averaged aerosol particle size distributions (PSDs)
that are obtained from the PCASP for
Daily averaged aerosol particle size distributions
for the sub-cloud level flights. PSDs obtained from PCASP (0.1 to
2.5
PSDs obtained from PCASP and CAS in the sub-cloud layers are shown in Fig. 7
to show the wider ranges of PSDs. As discussed earlier, PCASP (0.1–2.5
Time-height cross section of reflectivity on
During the experiment, small cumulus clouds were observed on most days,
whereas relatively deep cloud clusters (heights to
about 2.5–3 km) were sampled on only a few days (e.g., 22, 24, and 30 March)
with different characteristics relative to the small cumulus clouds. The
cloud radar data sampled during the cloud-base level-leg flights were used
to obtain a bulk sense of shallow marine cumulus cloud characteristics, such
as distributions of cloud reflectivity, velocity, thickness, tops and bases.
The dates, time periods, and average heights of level-leg flights used for
the radar analysis are summarized in Table A4. Examples of time-height
cross-sections of radar reflectivity, for the 5 min periods, are shown in
Fig. 8. Radar reflectivity
The clouds sampled on 22 and 24 March (Fig. 8a–b) were precipitating, and
characterized by strong reflectivity (e.g.,
MODIS satellite images on
To show the organizational differences between precipitating and non-precipitating clouds, satellite imagery taken on 22, 24, 29 and 30 March is shown in Fig. 9. Clouds on 22 March comprise relatively deep convective cores surrounded by cloudiness that is formed from the outflow of the deeper convection (Fig. 9a). The clouds appear to be organized around the arc-shaped outflow boundaries from earlier convection as shown in the RICO field campaign (Zuidema et al., 2012), and this organizational characteristic is also evident on 24 and 30 March (Fig. 9b and d). Convection associated with these features often reached cloud heights of about 2–3 km. On the other hand, the aircraft sampled typical fair weather cumulus clouds on 29 March (Fig. 9c). The size of the clouds was significantly smaller than the precipitating cloud systems, and clouds did not have outflow features as seen in the precipitating clouds. This shallow convection had no measurable precipitation, and often had a cloud thickness of less than 500 m (Fig. 13 shown later).
Characteristics of cloud cores sampled during BACEX are shown in Fig. 10. A
cloud core was defined by updrafts (
Normalized velocity–reflectivity number frequency
distributions on each day during BACEX from the cloud-base level-leg
flights. Intervals of 2 dBz, and 0.1 m s
To characterize the cloud and precipitation structures observed during
BACEX, radar reflectivity
Cloud composites are shown in Fig. 12 on the
Cloud reflectivity and velocity distributions estimated
from an average of all individual days (12 cases in Fig. 11),
Frequency distribution of reflectivity and velocity with
heights, by compositing
Vertical frequency distributions of
Normalized number of samples with height for all sampled
clouds (grey) and precipitating clouds (black). Precipitating clouds are
defined as data points with
The vertical structures of the individual clouds are further examined in
Fig. 14. For a given day, the total number of data points at a given height
is counted based on data sampled along the cloud-base level leg flights by
the cloud radar. Then, the number of data points is divided by the maximum
number of each day to have the same range from 0 and 1. This approach is to
facilitate comparisons with other days, since the main purpose of this
calculation is to examine the differences in vertical sampling statistics
between individual days, in particular between precipitating and
non-precipitating clouds. Here in Fig. 14, the terminology “clouds” is
used for the area and/or data points where the cloud radar detects signals.
We assume that an individual observation represents a precipitating cloud if
Two types of precipitating clouds are shown in Fig. 14. The first cloud type
has precipitation shafts that are observed mainly close to and below the
cloud base and/or throughout most of the cloud layer (this feature is
also seen in Fig. 13b with stronger downward motions close to cloud bases),
especially when the clouds are deeper than the other lightly precipitating
clouds. For example, on 22 March, the overall occurrence of precipitating
clouds (black) exceeds the occurrence of non-precipitating clouds (grey)
close to the cloud base. In addition, the height of maximum occurrence of
the precipitating clouds is slightly lower than the height of maximum
occurrence of total clouds. The second precipitating cloud type has
precipitation shafts that emanate mainly from the upper part of the cloud
and/or near cloud top (e.g., 3/24, 4/10 in Fig. 14; hereafter cloud-top
precipitation) on the downshear side of the cloud (not shown). This type of
precipitating cloud is shallower than the first type of cloud, and can also
be accompanied by precipitation shafts emanating near cloud base. For
example, on 5 April, the maximum occurrence of total clouds is observed at
around 900–1000 m (grey), while precipitating clouds are observed most
frequently near 1200 m with secondary peaks near cloud base (black). The
same patterns are shown on 3/23 and 4/7. Figure 14 shows that the second
type of precipitation (cloud-top precipitation) is more frequently observed
during BACEX. One of the examples of this type of precipitating clouds is
shown in Fig. 15 based on photo and radar measurements. Cloud-top
precipitation shafts, accompanied by precipitation shafts emanating from the
cloud base, are evident from the photo (Fig. 15a). These precipitation
shafts are shown with strong radar reflectivity (
Cloud fields documented during CARRIBA projects and by the MPI group also showed similar structures to Fig. 14. For example, frequency distributions showed bimodal peaks in the radar returns, one near cloud base and the other near cloud top (Nuijens et al., 2014). However, the peaks observed near cloud tops in this study were attributed to cloud top precipitation and not to stratiform clouds (Nuijens et al., 2014) nor to extended cloud layers near cloud tops as a result of stronger inversion (Siebert et al., 2013). Our analysis was confined to shallow marine cumulus clouds (which eliminated the possibility of Sc) and identified precipitating and non-precipitating clouds using radar returns, which facilitated identification of the peaks near the cloud tops as the precipitation.
The aircraft in situ observations are used to determine how frequently
clouds precipitate during the BACEX flights. The daily percentage of
precipitating clouds among the total number of clouds observed is shown in
Fig. 16. The percentage of precipitating clouds for a given day is estimated
by the ratio of precipitating clouds to the total number of clouds sampled.
A cloud is counted only if the LWC is larger than 0.02 g m
The total number of cloud penetrations made on each day ranged from 50 to
200 (not shown). However, the aircraft sometimes penetrated the same cloud
more than once, and sometimes avoided clouds with strong updrafts or
downdrafts. Nevertheless, Fig. 16a shows that 56 % of the clouds, on
average, sampled during BACEX precipitate somewhere in the cloud, and thus
about 44 % of clouds are non-precipitating clouds, based on our criteria.
This finding is consistent with the percentage of non-precipitating clouds
estimated from the radar measurements shown in Fig. 14; no precipitation is
observed on 5 of the 12 flights (
In this study, we examined the variations and properties of aerosol, cloud and precipitations over the Eastern Caribbean by using data collected during the Barbados Aerosol Cloud Experiment (BACEX), which took place off the Caribbean island of Barbados from 15 March to 15 April 2010. The marine environment near Barbados provided an excellent area to sample shallow marine clouds with a strong propensity to precipitate. In addition, African dust outbreaks periodically affected the region and provided an excellent opportunity to observe aerosol–cloud–precipitation interactions. The primary observing platform for the experiment was the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter (TO) research aircraft, which was equipped with standard meteorological instruments, a zenith pointing cloud radar, and probes that measured aerosol, cloud, and precipitation characteristics.
During the 1-month experiment period, the most intense African dust event
during all of 2010 (1–2 April) was observed. Temporal variations and
vertical distributions of aerosol observed on the 15 flights made by the TO
research aircraft showed a wide range of aerosol conditions. The 10-day back
trajectories of air masses observed at Barbados showed three distinct air
masses: typical maritime, Saharan, and mid-latitude. These types match well
the results from Dunion (2011), who examined about 6000 rawindsonde
observations from the Caribbean Sea region taken from July to October,
1995–2002. A variety of aerosol vertical structures were observed and
categorized by three distinct profiles associated with aerosol source
regions. First, accumulation mode aerosol concentration (
Aerosol particle size distributions from dusty days showed a
significantly higher
Despite the large differences in the total mass loading and the origin of aerosols, the overall shapes of PSDs in the accumulation mode were consistent (except for the 2 single days of transition occurring before and after a dust event). However, it should also be noted that the slight differences between the individual PSDs during the transition periods could provide some insights into the processes that affect the aerosol concentration via cloud processes. For example, Jung et al. (2013) showed that history of cloud processes in the boundary layer caused complicated stratification in the aerosols below the Saharan air layer. The observations will be useful for testing how well GCMs can reproduce the aerosol measurements.
During the experiment, the TO research aircraft was able to sample many
clouds in various phases of growth. Vertically pointing cloud radar provided
the basis for the general characteristics of clouds. Clouds sampled during
BACEX had a maximum cloud depth of less than 3 km. However, it is shown that
more than half of the clouds precipitate somewhere in the cloud (56 % on
average), even though the precipitation amount in and near the cloud was
less than 10 mm day
Two types of precipitation features were observed during the experiment. In the first type, precipitation shafts emanated mainly from cloud base (i.e., classic cloud-base precipitation) that led to evaporation in the sub-cloud layer. In the second type, precipitation shafts emanated mainly from near cloud top (or the upper parts of the cloud) with evaporation occurring in the cloud layer. The latter type of precipitating cloud was shallower than the former type, and was also sometimes accompanied by precipitation shafts emanating near cloud base. During BACEX, the cloud-top precipitation type was more frequently observed than the classic cloud-base precipitation type. These two types of precipitation patterns may impact on the trade-wind boundary layer in different ways. For instance, precipitation shafts that emerge from cloud top and evaporate in the cloud layer (i.e., cloud-top precipitation type), destabilize the atmosphere below the precipitation and provide moisture to the local environment that may affect the moisture budget and lead to an increased cloud lifetime of subsequent clouds (e.g., Albrecht, 1981) and/or later promote deeper clouds (e.g., preconditioning; Blade and Hartmann 1993). The deeper, wetter clouds would tend to produce more rain, which would offset the tendency for aerosols to suppress rain (e.g., Stevens and Seifert, 2008; Stevens and Feingold, 2009), a topic we will address in a future study.
The observations made in this study add to our knowledge of cloud characteristics and the aerosol and thermodynamic environment in which they form for an area important to the Earth's climate system. These observations provide the basis for process studies that can lead to an improved understanding of the roles that shallow cumulus play in the relevant energy and moisture budgets of the marine boundary layer.
The sounding data (Fig. 1) is available at the University of Wyoming's
online upper-air data (
Flight list.
*Local time: UTC-5. The total number of soundings is included take-off and landing soundings.
The number of the
Table of acronyms and symbols.
The lists of various vertical structures and air masses during BACEX.
Type A: aerosol concentrations decrease with height monotonically. Type B: high aerosol concentrations confine above trade-wind inversion. Type C: high aerosol concentrations prevail throughout the boundary layer and/or complicated structure. MLDA: Mid-latitude dry air, SAL: Saharan air layer
Cloud-base level-run flights for the radar analysis.
* Local time: UTC-5
Mean number concentrations of aerosols at sub-cloud layer
and
To estimate how many aerosol particles are activated during the flights,
Aerosols (cm
Droplet number concentrations
The PCASP is pretty insensitive to refractive index (RI), but the forward
scatter probe (CAS) is very sensitive to refractive index for
Calibration plot. The horizontal lines define the channel boundaries; the individual points show the actual calibrations, and the continuous lines show response curves for various refractive indexes estimated from theory.
We thank all individuals who made the observations on the CIRPAS Twin Otter during BACEX. We thank Joseph M. Prospero (University of Miami) for providing dust surface data and he and his staff for establishing and maintaining the Ragged Point AERONET sites used in this investigation. Jung and Albrecht are funded by ONR Grant N000140810465. Feingold acknowledges support from NOAA's Climate Goal. Eunsil Jung thanks Robert Seigel (publiscize.com) for scrutinizing an early stage of the manuscript. We thank two anonymous reviewers for their constructive and comprehensive comments on the manuscript.Edited by: M. PettersReviewed by: two anonymous referees