Aviation has a large impact on the Earth's atmosphere and climate by various
processes. Line-shaped contrails and contrail cirrus clouds lead to changes
in the natural cirrus cloud cover and have a major contribution to the
effective radiative forcing from aviation. In addition, aviation-induced
aerosols might also change the microphysical properties and optical
properties of naturally formed cirrus clouds. Latter aerosol–cloud
interactions show large differences in the resulting effective radiative
forcing, and our understanding on how aviation-induced aerosols affect cirrus
cloud properties is still poor. Up to now, observations of this aviation-induced aerosol effect have been rare. In this study, we use combined airborne
lidar and in situ ice cloud measurements to investigate differences in the
microphysical and optical properties of naturally formed cirrus clouds,
which formed in regions that are highly affected by aviation-induced aerosol
emissions and, of those, which formed in regions rather unaffected by
aviation. Urbanek et al. (2018) showed that those cirrus clouds, which are
more affected by aviation-induced soot emission, are characterized by larger
values of the particle linear depolarization ratio (PLDR). In this follow-on
study we relate collocated lidar measurements performed aboard HALO during
the ML-CIRRUS mission of the particle linear depolarization ratio with
in situ cloud probe measurements of the number concentration and effective
diameter of the ice particles. In situ measurements for both cloud types
(high-PLDR-mode – aviation-affected – and low-PLDR-mode – pristine – cirrus) can
be reliably compared in a temperature range between 210 and 215 K. Within
this temperature range we find that high-PLDR-mode cirrus clouds tend to
show larger effective ice particle diameters with a median value of 61.4
compared to 50.7 µm for low-PLDR-mode pristine cirrus
clouds. Larger effective ice particles in aviation-influenced (high-PLDR-mode) cirrus are connected to lower ice particle number concentration with a
median value of 0.05 compared to 0.11 cm-3 (low-PLDR-mode),
which evolved in more pristine regions with only little impact from
aviation. We suspect that a suppression of homogeneous ice formation by the
heterogeneously freezing soot aerosol particles included in the areas
affected by air traffic is the cause of the reduced ice crystal
concentrations.
Deutsche ForschungsgemeinschaftVO1504/7-1Introduction
Aviation has a large impact on the Earth's radiation budget and atmosphere
(Lee et al., 2021) by various interactions; e.g., aerosols and trace gases
are emitted, which directly interact with incoming and outgoing radiation
(Lund et al., 2017). Line-shaped contrails can form in the exhaust plume of
an aircraft (Voigt et al., 2010; Burkhardt et al., 2010) and might evolve
into contrail-induced cirrus clouds in the aftermath (e.g., Haywood et al.,
2009). A lot of research activities have been performed over the last few years
to measure (Heymsfield et al., 2010a; Voigt et al., 2011,
2017) and understand contrails and contrail cirrus (e.g., Kärcher et al.,
2015; Schuman et al., 2017), as well as to investigate their climate effect
(Burkhardt and Kärcher, 2011; Kärcher, 2018; Bock and Burkhardt,
2019; Quaas et al., 2021). Contrails and contrail-induced cirrus clouds are
supposed to have the largest aviation-induced impact on the Earth's
radiation budget with a clearly warming effect (Lee et al., 2021). Recent
studies show that the climate impact from contrails can be reduced by
burning sustainable aviation fuels with a low aromatic content (Moore et
al., 2017; Burkhardt et al., 2018; Voigt et al., 2021; Bräuer et
al., 2021) or by climate friendly flight routing (Grewe et al., 2017).
Contrails can further lead to an increase in the cirrus cloud optical
properties (Tesche et al., 2016) and to changes in their ice crystal
effective diameter (Haywood et al., 2009) and ice crystal number
concentration (Marjani et al., 2022).
Besides contrail formation and its effect on already existing clouds,
aviation-induced aerosols might also act as ice nuclei (ice nucleating
particles, INPs) for naturally
formed clouds. The aerosols change the microphysical properties – i.e., the number
concentration and size of ice crystals of naturally formed cirrus clouds
(Kärcher, 2017) and thus their optical and radiative effect. Model
studies investigating the impact of this aviation-induced aerosol–cloud
interaction show large differences in the resulting effective radiative
forcing. In particular, the estimates of the impact of emitted soot particles
on cirrus clouds are connected with large uncertainties. Several studies
focused on the impact of aviation soot on cirrus clouds and thus on the
resulting climate effect (e.g., Hendricks et al., 2005, 2011; Liu et al.,
2009; Gettelman and Chen, 2013). Large differences in the magnitude and even
in the sign of the effect (Penner et al., 2009, 2018; Zhou and Penner, 2014)
were reported. The uncertainties in the estimate of the climate effect of
aviation soot are mainly driven by the assumed efficiencies of soot
particles to act as INPs (Righi et al., 2021). While some laboratory studies
found soot particles to be efficient INPs (Möhler et al., 2005; Hoose and
Möhler, 2012), others indicate soot particles are not efficient INPs
(DeMott et al., 1999). In a recent laboratory study, Mahrt et al. (2020)
found that soot particles would increase their efficiency to act as INPs
after being pre-processed within contrails. This indicates an overestimation
of the soot effect in some of the model studies.
Although the understanding of aviation's impact on the climate system
has improved over the last few years, many uncertainties remain. However,
observations of an aviation-induced indirect aerosol effect on cirrus clouds
are rare. Urbanek et al. (2018) analyzed airborne lidar measurements over
Europe, performed during the ML-CIRRUS mission (Voigt et al., 2017), and
found larger median values of the particle linear depolarization ratio
(PLDR) of cirrus clouds formed in air traffic regions compared to those
evolved in regions with only little impact from aviation. Their analysis
further showed lower supersaturation for those clouds with high PLDR formed
in air traffic regions, which they interpreted as a signature of more
heterogeneous freezing. The measurement study by Urbanek et al. (2018) is
one of the first that could show traces of an indirect aerosol effect from
aviation. During the first COVID-19 curfew in spring 2020, civil aviation
over Europe was reduced by up to almost 90 % (https://www.eurocontrol.int/sites/default/files/2021-12/covid19-eurocontrol-comprehensive-air-traffic-assessment-16122021.pdf, last access: 5 July 2023).
This reduction caused a unique opportunity to study the effect of aviation
on cirrus clouds. Li and Groß (2021) used spaceborne lidar measurements
aboard the CALIPSO satellite (Winker et al., 2010) in March and April 2020
to investigate differences in cloud occurrence and optical properties
compared to previous years in the same time period. They found less cirrus
occurrence mainly for colder height levels and for thinner cirrus clouds.
Those findings were interpreted as a reduction of contrails and contrail-induced cloudiness due to reduced aviation. Schumann et al. (2021a, b)
investigated the changes in contrail occurrence and the formation of
persistent contrails by performing contrail simulations with the contrail
cirrus prediction model, CoCiP (Schumann et al., 2012). They found that
changes in the cirrus cloud occurrence from March to August 2020, compared
to the same period in 2019, were partly caused by the air traffic reduction.
Duda et al. (2023) used satellite measurements to investigate changes in
contrail cover, optical properties and radiative forcing during April and
May 2020. They could show a decrease in contrail coverage and shortwave
contrail radiative forcing over the United States due to decreased air
traffic. Teoh et al. (2022) found a significant decrease in contrail cirrus
cover and energy forcing in 2020, when comparing to modeled contrail cirrus
effects in the northern Atlantic flight corridor regions from 2016 to 2019.
Furthermore, a significant decrease in the mean PLDR of cirrus clouds was
found in spring 2020 compared to previous years (Li and Groß, 2021), which
can be interpreted as a reduced, aviation-induced and indirect effect on
naturally formed cirrus clouds. An integrated study, using aircraft,
satellite and modeling data, showed a reduction of the aerosol optical
depth (AOD) over Europe in May 2020 (Voigt et al., 2022). Although it is not
clear whether the decrease in AOD was caused mainly by anthropogenic or
meteorological influences, the authors suggest that it was partly caused by
the 80 % decline in air traffic, as the aerosol number concentration
decreased at flight altitudes compared to the reference years. In addition,
comparisons of the measured black carbon mass concentration with model
results from the ECHAM/MESSy Atmospheric Chemistry (EMAC) model indicated a 40 % reduction related to lockdown effects
(Krüger et al., 2022). The reduction in air traffic over Europe
furthermore led to a reduction in contrail cover and as a consequence in
radiative forcing from contrails. Contrail radiative forcing was calculated
with the contrail cirrus prediction model (CoCiP; Schumann, 2012) for
16 April 2020 for two scenarios: using air traffic data from 2019 and for 2020.
For the same meteorology, the simulated contrail radiative forcing decreases
by about 80 % for the reduced air traffic in 2020 compared to 2019. Voigt
et al. (2022) also showed reduced effective optical depth of the cirrus
clouds compared to previous years connected with reduced PLDR. Looking at
long-term cirrus observations using CALIPSO measurements, Li and Groß (2022) found a significant increase in the PLDR over the last few years, which
is clearly correlated with the increase in the number of flights over Europe.
However, besides these advances in observing the change in optical
properties due to the impact of aviation-induced soot, the link to the
microphysical properties of the cirrus clouds is still missing. In a recent
study, Zhu et al. (2022) examined CALIPSO satellite observations during the
COVID-19 lockdowns and found a significant increase in ice crystal number
concentration (Npart), which they linked to an increase in homogeneous
freezing due to reduced aviation.
In this study we extend the work by Urbanek et al. (2018) using combined
lidar and in situ measurements aboard HALO performed during the ML-CIRRUS
mission (Voigt et al., 2017) to determine differences in the microphysical
properties of natural cirrus clouds formed in air traffic regions and of
those formed in regions less affected by aviation, and thus we expand our
investigation on the non-CO2 effect of aviation. For this, we use the
same clouds that were investigated within our previous study (Urbanek et al.,
2018). In Sect. 2, we will present the campaign and the measurements. In
Sect. 3, we will show the results focusing first on two case studies of
different cirrus cloud types and afterwards on all the cloud measurements
with collocated lidar and in situ measurements. Section 4 will discuss the
results and conclude this study.
MethodML-CIRRUS campaign
The ML-CIRRUS campaign was conducted in March/April 2014 to study cirrus
clouds in meteorological regimes typical for mid-latitudes. ML-CIRRUS aimed
to investigate contrail cirrus, as well as to observe differences between
anthropogenic and natural cirrus clouds. To achieve this goal, measurement
flights with the German High Altitude and Long Range research aircraft
(HALO), equipped with a combined remote sensing (including airborne lidar)
and in situ (including cloud probes) payload, were performed out of
Oberpfaffenhofen. An overview of the mission, the performed research flights
and their main focus can be found in Voigt et al. (2017). Overall, 16
flights were performed covering the whole range of the mid-latitudes: from
36 to 58∘ N and from the Atlantic Ocean (∼ 15∘ W) to central Europe (∼ 15∘ E).
However, only 8 of the 16 flights were designed in such a way that they
provide coordinated lidar and in situ measurements. The sampling strategy
during these flights were as follows. First, the HALO aircraft flew at
higher altitudes above the cloud for cirrus cloud sounding with the
lidar (lidar leg). Subsequently, the same cirrus clouds were probed by
in situ measurements at several flight altitudes within the cirrus clouds
(in situ leg). Typical lidar legs took about 30 to 50 min, with a
typical aircraft speed of 200 m s-1 that results in an observed cloud dimension
of about 360 to 600 km. The in situ legs took a minimum of 10 min per
constant flight altitude. For our study only these eight flights with
coordinated lidar and in situ measurements are relevant. Urbanek et al. (2018) grouped these flights into cirrus clouds developed in
regions with enhanced background aerosols from aviation or in regions rather
unaffected by aviation. By means of 24 h backward trajectories calculated
with the trajectory module of CLaMS (McKenna et al., 2002), they
investigated the maximum cloud ice water content to determine the most
probable location of the cirrus formation and compared that to maps of
enhanced background aerosols due to aircraft emissions (Stettler et al.,
2013). Information on the flights (including their mission ID to make it
comparable to Urbanek et al., 2018) is given in Table 1.
Overview of the combined in situ and lidar research missions during
ML-CIRRUS showing the mission ID, date, measurement region and scope of the
mission, median PLDR, temperatures of in situ measurements, and altitude
range. Listed are only those missions with combined lidar and in situ
measurements. Entries marked with an asterisk (*) after the mission ID show flight
segments with cirrus clouds that were affected by aviation-induced
aerosols (according to Urbanek et al., 2018), and the others indicate flight
segments with cirrus clouds developed in regions with no or less aviation.
The flight missions indicated in bold letters are shown in detail in the
case studies.
The WALES (WAter vapour Lidar Experiment in Space; Wirth et al., 2009) lidar
is a combined high-spectral-resolution lidar (HSRL) and differential
absorption lidar (DIAL) system, which was developed and built at the
Institute of Atmospheric Physics of the German Aerospace Center. It measures
directly the extinction coefficient at 532 nm, using the HSRL technique with
a high vertical resolution of 15 m and of typically 0.2 s resolution in time
(Esselborn et al., 2008). Additionally, the system is equipped with
polarization sensitive channels at 532 and 1064 nm. For determining the
particle linear polarization ratio (PLDR), which is the ratio of the
measured perpendicular and the parallel component of polarization of the
backscattered light, we apply the ±45∘ calibration method
(Freudenthaler et al., 2009) and thus achieve an absolute accuracy of 5 % at typical cirrus PLDR values of about 0.35 to 0.55.
To assure that high-altitude aerosol residuals and liquid or mixed phase
clouds are excluded from our study, we restrict the considered data to
measurements of temperature ranges below 235 K and of a backscatter ratio
(R) above a threshold of R=3. The backscatter ratio is defined as the
ratio of the total backscatter coefficient (molecules and aerosol/cloud
particles) to the molecular backscatter coefficient. This threshold was
determined by carefully investigating all flights with lofted aerosol layers
(Urbanek et al., 2018). Sensitivity studies showed that the further
analyses only weakly depend on the chosen R value within a range from R=2
to R=25.
In situ instrumentation
Particle number concentrations (Npar) and effective diameter
(Deff) are calculated using a composite of particle size distributions
from three cloud probes, applying scattering detectors and light attenuation
on optical arrays. Small particles in the size range from 3 to 50 µm
were detected by the CAS (Voigt et al. 2017; Kleine et al., 2018). The
data were grouped into 16 size bins, assuming rotationally symmetrical
ellipsoids of random orientation with aspect ratios of 0.75, to avoid
Mie ambiguities in the scattering signals. Larger particles were detected by
a CIP (Cloud Imaging Probe; CIP) as part of the CCP (Cloud Combination
Probe) and a PIP (Precipitation Imaging Probe) instrument (Weigel et al.,
2016). Maximum dimension diameters were derived from 2-D images, and number
concentrations were corrected for compression effects according to Weigel et
al. (2016). The CIP was operated in the size range from 15 and 960 µm, and the PIP was operated in the size range from 100 to 6400 µm.
The effective diameter is calculated from the effective radius (2⋅reff)
according to Schumann et al. (2011). The data were averaged over 5 s
intervals. For the majority of flights, the combined particle size
distribution of the CAS, the CIP and the PIP was used, which is the same
data set as used in the work of Righi et al. (2020) and Wang et al. (2023).
For the flight of 7 April 2014, only data from the NIXE-CAPS (Novel Ice
Experiment–Cloud Aerosol and Precipitation Spectrometer; Krämer et al.,
2016; Costa et al., 2017) instrument are available due to a failure of the
CIP instrument. NIXE-CAPS is a combination probe that integrates two
techniques for measuring the particle size distribution (PSD): the PSD of
particles 0.6 to 50 µm in diameter is measured with NIXE's Cloud and
Aerosol Spectrometer (NIXE-CAS) using light scattered from individual
particles that pass through a focused laser beam. For measurements of
particles 15–937 µm in diameter, NIXE's Cloud Imaging Probe
(NIXE-CIP), which utilizes the optical array probe (OAP)
technique, is used. Using the data analysis routines collected in the data processing library NIXE-Lib (Luebke et al., 2016), the PSDs of both instruments are analyzed simultaneously,
whereby various error analyses and corrections are applied, including a
correction of possible shattering of large ice crystals at the inlet tips.
The data of NIXE-CAPS and the combined cloud probes are redundant, which was
helpful in the event of a failure but also to assure good quality and consistency
in the obtained data set. Comparison of the data sets for days when the two
combined PSD were available showed in general a good agreement. As we only
discuss relative changes in Npar and Deff, small differences arising by the
use of different probes should not affect the results.
Cirrus evolution classification scheme
To determine the evolution of the cirrus clouds, we use the cirrus lifetime
classification method presented by Urbanek et al. (2017). The classification
scheme is based on previous studies using differences of the RHi
distribution in clouds at different stages of evolution (Groß et al.,
2014). Based on combined temperature information and water vapor lidar
measurements, it identifies regions outside and inside the cloud of
supersaturation with respect to ice, heterogeneous and homogeneous
nucleation, depositional growth, and ice sublimation in the 2-D field along
the flight track.
In addition, measurements of the meteorological state parameters (e.g., T,
RHi) at flight altitude were performed with the Basic HALO Measurement and
Sensor System (BAHAMAS; Giez et al., 2023).
Results
In a previous study (Urbanek et al., 2018) we found that cirrus clouds
evolved in regions with enhanced air traffic show larger mean values of the
PLDR than cirrus clouds forming in regions rather unaffected by aviation.
In this study we extend the investigation of an impact of aviation on the
microphysical properties of the cirrus clouds by comparing in situ
measurements performed within these two cloud classes (of high and low
PLDR). During the ML-CIRRUS campaign, eight missions were performed which
provide coordinated lidar and in situ measurements (Table 1). The results of
those coordinated measurements will be presented in the following. Two case
studies show the differences of optical and microphysical properties of
similar cirrus cloud types; one formed in a region of enhanced background
aerosols due to aircraft emission and one evolved from aviation-unaffected air masses. One of the two case studies show measurements of
cirrus clouds strongly affected by embedded contrails and the other of a
warm conveyor belt cirrus. Those cases represent two of the main cirrus
types in the European mid-latitudes. In a next step, we investigate the
overall distribution of optical and microphysical properties of the observed
cirrus clouds. The results of a significance test of the comparisons are given in the Supplement.
Case study – contrail cirrus
The first case study we choose for the comparison is a cirrus case with
embedded fresh contrails (Wang et al., 2023). For the clouds observed on 26 March 2014 and 7 April 2014, the contrail cirrus prediction model (CoCiP;
Schumann, 2012) indicated a large amount of embedded fresh contrails within
the cirrus cloud (Urbanek, 2019). Back-trajectory analysis (Urbanek et al.,
2018) indicates the origin of the cloud on 26 March over the North Atlantic
with enhanced background aerosol due to aviation emission. The cirrus cloud
on 7 April evolved further south over the Atlantic Ocean, in an area that is
much less affected by aviation exhaust (Stettler et al., 2013).
The time–height cross sections of the PLDR of the two cirrus clouds with
embedded fresh contrails is shown in Fig. 1 (a and b) along with the
density distributions (c and d) of the particle linear depolarization
ratio (PLDR). Both cirrus clouds are in approximately the same temperature
and height range, so they are comparable. The values of the PLDR of the
two cirrus clouds is quite different. The cirrus on 26 March 2014 shows
larger values of the PLDR than the cirrus cloud on 7 April 2014. For the
first one, we find values up to 0.6, while the PLDR of the cloud on 7 April barely exceeds 0.45. The mode of the PLDR distribution within the
cirrus cloud on 26 March is 0.54, and its median is 0.52. In contrast, the mode and
median of the PLDR distribution of the cirrus cloud on 7 April 2014 is much
lower at values of 0.44 and 0.39, respectively. Both cirrus clouds show a
large number of embedded contrails and are still different with respect to
their PLDR. Thus, the freshly embedded contrails cannot be interpreted as a
cause for the significant differences in the PLDR.
Time–height cross section of the particle linear depolarization
ratio (PLDR) for the contrail-affected cirrus cloud cases on 26 March (a)
and 7 April 2014 (b), and the frequency distribution of the measured PLDR (c, d) of the cloud parts at temperature regions below 235 K. The color
coding of the PLDR distribution (c, d) marks the threshold defined by
Urbanek et al. (2018) for high (dark grey) and low (light grey) PLDR values.
In situ measurements were performed within the cirrus cloud at an altitude
of approximately 11 km and show mean relative humidity with respect to ice
(RHi) and temperature values of about 100 % and about 208 to 217 K,
respectively, for both clouds. So, any differences due to different
meteorological conditions within the cloud are not expected. The
distributions of the derived Deff are narrow for both cirrus cases,
with the main values below 100 µm (Fig. 2) potentially due to the
high number of embedded contrails. The median Deff value for the cirrus
cloud measured on 26 March of 58.5 µm is slightly larger than the
median value of 53.2 µm measured on 7 April 2014. Differences are
also found for the measured Npar for the two cloud cases. The
distribution for the cirrus cloud evolving in regions with a large amount of
aviation exhaust (26 March) shows a median value of 0.04 cm-3. In
contrast, the distribution of Npar on 7 April is broader and shows a
larger median value of 0.15 cm-3. In summary, the case study shows
a larger median effective diameter and lower number concentration for the
aviation-impacted cloud with the high particle linear depolarization ratio
mode. This result will be discussed more in the conclusion.
Relative distribution of the retrieved effective diameter
Deff(a) and ice particle number concentration
Npar(b) for the contrail-affected cirrus cloud
cases on 26 March (dark blue) and 7 April (light blue) 2014 from in situ
measurements during ML-CIRRUS.
Case study – warm conveyor belt cirrus
In a second case study, we compare the optical and microphysical properties
of warm conveyor belt (WCB) cirrus. WCBs are a typical flow structure of the
mid-latitudes leading to increased precipitation (Eckhardt et al., 2004). A
warm conveyor belt (WCB) is characterized by warm humid air that is lifted
fast (∼ 10 cm s-1; Browning, 1971) from the boundary layer to
the upper troposphere on the timescale of 2 d. During the lifting
process, liquid clouds form and freeze. This leads eventually to pure ice
clouds. During ML-CIRRUS, we were able to observe and probe four cases of
WCB cirrus (see Table 1). For this study, we choose the cloud observed on 27 March and on 11 April 2014. We determined the stage of evolution
(Urbanek et al., 2017) to the clouds to ensure that we are comparing clouds
in approximately the same stage of lifetime. Only about 0.4 %–0.5 % of the
clouds are in the nucleation mode, and about 30 % are in the deposition
mode. The majority of both clouds (∼ 70 %), however, is in
the sublimation mode. This analysis proves that both clouds are
comparable and that effects that might be caused by different evolution
stages of the cirrus clouds can be excluded. Trajectory analysis for the two
clouds shows that the first one evolved in rather clean conditions from aviation-exhaust-unaffected situations over northern Africa/the Mediterranean,
while the nucleation process for the second one took place over the north
Atlantic region, highly affected by air traffic exhaust (Urbanek et al.,
2018).
Figure 3 shows the time–height cross sections (a and b) and density
distributions (c and d) of the particle linear depolarization ratio
(PLDR). While the PLDR of the WCB cirrus on 27 March 2014 does not exceed
values of 0.55, the PLDR of the WCB cirrus on 11 April 2014 shows values as
high as 0.7 at the top and in the lower part of the cloud. Considering all
the measurement points within the observed WCB cirrus on 27 March, the
overall distribution of PLDR has its maximum at a value of 0.41; the median
of the distribution is at 0.4. In contrast, the distribution of the PLDR of
the WCB cirrus on 11 April has its maximum at 0.5 and its median at a value
of 0.48. As we find the differences in the measured PLDR for both WCB cases
and as their stage of evolution is approximately the same, we suggest that
neither the cirrus cloud type nor its lifetime has an effect on the
differences in the PLDR.
Time–height cross section of particle linear depolarization ratio
(PLDR) for the WCB cirrus observed on 27 March (a) and 11 April 2014 (b),
and the frequency distribution of the measured PLDR (c, d) of the cloud
parts at height regions below 235 K. The color coding of the PLDR
distribution marks the threshold defined by Urbanek et al. (2018) for clouds
characterized by high (dark grey) and low (light grey) PLDR values.
The in situ flight track for both clouds were performed approximately in the
middle of the clouds' vertical extension: at about 9 km altitude for the
cloud on 27 March and at about 9.5 km altitude for the cloud on 11
April. The relative humidity with respect to ice (RHi) along both flight
tracks (Kaufmann et al., 2018) agrees well for both clouds with mean values
of 105 % and 104 %. However, although the flights took place in
approximately the same height range, the temperatures are quite different,
with a mean value of 216 K for the measurements on 27 March and temperatures
of 226–227 K for the flight track of 11 April. Thus, the comparison of the
cloud microphysical properties has to be treated with care. The distribution
of Deff (Fig. 4; left) for the WCB cirrus on 27 March 2014 has a
narrow mono-modal structure with its maximum between about 80 to 110 µm. In contrast, Deff within the WCB cirrus on 11 April shows a broader
distribution with its maximum at about 200 µm and a second smaller
mode at about 100–120 µm. The overall mean (median) values of
Deff for the WCB cirrus on 27 March and 11 April are 93.25 µm
(95.12 µm) and 198.21 µm (193.78 µm), respectively. The
distributions of Npar show only small differences for the two WCB
cirrus cases. Both distributions show a skewness towards smaller values and
a median of about 0.02 cm-3 for 27 March and of 0.04 cm-3 for 11
April. However, the temperatures in which the in situ data were sampled are
quite different and thus might have a quite significant impact on the
retrieved results, which will be discussed in Sect. 3.3. Earlier in the day
on 11 April (∼ 07:50–08:25 UTC) we performed in situ
measurements within the same cloud system at a height of about 10.5 km and a
temperature range of 218–219 K. The mean (median) values of Deff and
Npar are 132.09 µm (131.87 µm) and 0.07 cm-3 (0.02 cm-3). Unfortunately, no lidar measurements are available at the same
time to make full use of this time range.
Relative frequency of the derived effective diameter
(a) and ice particle number concentration (b) for the warm conveyor
belt cases on 27 March (light blue) and 11 April (dark blue) 2014.
In situ data of all flight missions
Similar to its impact on the PLDR (Urbanek et al., 2018) the temperature is
also correlated with the mean/median Deff and Npar showing lower
values for Deff and higher values for Npar at the coldest
temperature. Looking at Table 1, one can see that coordinated in situ and
lidar measurements were mainly performed in cirrus clouds formed
from aviation-unaffected air masses and only within a temperature range of
208 and 217 K and that only in the temperature range between 210 and
215 K are a sufficient number of in situ measurements available for a
reliable comparison. Thus, we use only this temperature range for a first
comparison of Deff and Npar for the two cloud classes (Fig. 5).
For the temperature range colder than 209 K, in situ measurements of the high-depolarization-mode cirrus clouds dominate the available data. In
contrast, in the temperature range warmer than 215 K, in situ measurements in
cirrus clouds in the low depolarization mode dominate the data
availability. Furthermore, the available number of data points for
temperatures colder than 210 K and warmer than 215 K is small. This might
affect the overall results, as no significant comparison is possible due to
the small number of data points. Thus, we compare the derived Deff and
Npar in a temperature range between 210 and 215 K (Fig. 5), where
in situ measurements of both cirrus cloud types are available in about equal
amount. Looking at this temperature regime (210–215 K) one can see slight
differences between the two cirrus cloud classes. Although the main values
of Deff for both cloud types are between about 25 and
100 µm, the median value of the Deff distribution (50.7 µm) within low-PLDR-mode cirrus clouds is slightly smaller than the median
Deff value for the in situ measurements within high-PLDR-mode cirrus
clouds (61.4 µm). The corresponding distributions of Npar show
median values of about 0.05 for the high-PLDR-mode clouds and of 0.11 for
the low-PLDR-mode clouds.
Probability density function of the measured ice particle
effective diameter (a) and ice particle number concentration (b)
derived from CAS/CIP and NIXE-CAPS data (where available) for all
cirrus clouds during ML-CIRRUS, where coordinated lidar and in situ
measurements were available (Table 1) for both cirrus cloud types (high PLDR mode and low PLDR mode) with a significant amount of in situ samples. The
light blue color indicates measurements in low-PLDR-mode clouds, and the dark blue color shows measurements for high-PLDR-mode clouds.
In a next step, we analyze the temperature dependence of the measured
effective diameter and ice particle number concentration. For this
evaluation, we again use only the temperature range from 210 to 215 K, as
only in this temperature range can we perform a reliable comparison. We
derive the distributions of Deff and Npar in 1 K steps (Fig. 6).
One can see a tendency towards larger Deff with warmer temperatures,
which is already known from previous studies (e.g., Heymsfield et al., 2010b;
Bailey and Hallett, 2009). For the high-PLDR-mode clouds the median
Deff is 40.6 µm at a temperature of 210 K and of 71.2 µm
for a temperature of 215 K. The corresponding values for the low-PLDR-mode
clouds are 37.7 and 75.9 µm, respectively.
Temperature-dependent relative distribution of the
measured ice particle effective diameter (a) and ice particle number concentration (b) derived from CAS/CIP and NIXE-CAPS for all cirrus clouds
during ML-CIRRUS, where coordinated lidar and in situ measurements were
available (Table 1). The light blue color indicates measurements in low-PLDR-mode clouds, and the dark blue color shows measurements for high-PLDR-mode
clouds. The triangles indicate the median values, and n gives the number of
the available data points for each comparison.
The corresponding distributions of the ice particle number concentration
show that Npar is larger for the low-PLDR-mode cirrus clouds than for
the high-PLDR-mode cirrus clouds almost through the whole considered temperature
ranges with median values of 0.39 cm-1 for the low-PLDR-mode cloud and
0.15 cm-1 for the high-PLDR-mode cloud at a temperature of 210 K, as well as
about 0.01 cm-1 for the low-PLDR-mode cirrus and about 0.07 cm-1 for the high-PLDR-mode cirrus at a temperature of 215 K. However,
as can be seen from the number of data points for each comparison given in
Fig. 6, these last results have to be treated with care, as we tend to
have a larger number of high-PLDR-mode cirrus cloud cases in the warm
temperature range and a large spread of the results in the low-PLDR-mode
cirrus cloud cases.
Discussion and conclusion
In our study, we used the same method and measurements as Urbanek et al. (2018), who showed for the first time a difference in the optical properties
(i.e., the particle linear depolarization ratio) for cirrus clouds that
formed in regions with large aviation-induced emissions (having higher
values of the PLDR) and those that formed in less affected regions (lower
values of the PLDR). We connected the lidar measurements with collocated
in situ measurements of ice particle size and ice particle number
concentration from cloud combination probes on HALO, where available. A
reliable comparison of the in situ measurements of both types of clouds
(high-PLDR-mode – aviation-affected – and low-PLDR-mode – pristine – cirrus)
can be done in a temperature range between 210 and 215 K.
We found that for those temperature regimes, where we have a sufficient
contribution of both cloud types, high-PLDR-mode clouds tend to show lower
ice particle number concentrations with larger effective diameters compared
to low-PLDR-mode clouds. That is an indication for more heterogeneous
freezing due to aviation-induced emissions, as homogeneous nucleation is
expected to be suppressed by heterogeneous nucleation (DeMott et al., 1997;
Gierens, 2003). Homogeneous freezing might still occur sometime after the
heterogeneous process according to Spichtinger and Cziczo (2010). They
further showed that heterogeneous freezing takes place at lower RHi. In
their study, Urbanek et al. (2018) investigated the distribution of RHi
inside high-PLDR-mode clouds and low-PLDR-mode clouds and found differences
in the supersaturation with larger values for the low-PLDR-mode clouds.
These higher values can be thus interpreted such that homogeneous freezing
plays a larger role in the low-PLDR-mode clouds. Homogeneous freezing is
expected to produce high ice crystal number concentration and small crystal
sizes (Kärcher et al., 2006; Spichtinger and Cziczo, 2010; Krämer et
al., 2016). This was found during the COVID-19 curfew with strongly reduced
aviation (Zhu et al., 2022) and thus decreased number of ice nucleating
particles (INPs). In the presence of solid aerosol particles that act as INPs,
ice crystals form at lower supersaturation. The INPs are comparably less
numerous than the small aerosol solution droplets causing homogeneous
freezing. Thus, the available water vapor deposits on a smaller number of
ice crystals, but they grow to larger sizes and potentially also more complex ice
crystals (Schnaiter et al., 2016). The availability of INPs and thus
heterogeneous freezing processes lead furthermore to lower number ice
particle number concentration in a subsequent homogeneous freezing process
compared to pure homogenous freezing (Spichtinger and Cziczo, 2010;
Krämer et al., 2016). This effect is stronger the more INPs are
available.
The differences of Deff and Npar for the high-PLDR-mode and low-PLDR-mode
clouds, with larger Npar but slightly smaller Deff for the low-PLDR-mode clouds, can thus also be interpreted as traces of more frequent
heterogeneous freezing in the high-PLDR-mode clouds. Similar results were
also found in a recent study investigating the changes in ice crystal number
concentration during the COVID-19-caused air traffic closure (Zhu et al.,
2022). They found a reduction in the ice crystal number concentration during
that period and interpreted it as an increase in homogeneous freezing as
soot from aircraft emissions was reduced. Li and Groß (2021)
investigated the optical properties of cirrus clouds over the European
mid-latitudes and found a reduction in the PLDR of cirrus clouds during the
COVID-19 lockdown in spring 2020. However, number concentration and crystal
size are not expected to be the only microphysical properties to affect the
measured particle linear depolarization ratio, directly. It also depends on
the crystal habit or surface roughness and thus on the complexity of the
particles. Conditions during the nucleation process (e.g., temperature,
relative humidity) impact the ice crystal shape (Bailey and Hallett, 2009).
More heterogeneous freezing at lower supersaturation (Urbanek et al., 2018)
and warmer temperature regimes (Kanitz et al., 2011) as expected for the
high-PLDR-mode might lead to changes in the ice crystal complexity. Larger
particles with more complex structure were found, e.g., from balloon-borne
measurements of cirrus clouds (Heymsfield, 2003) under such conditions. In
this study, we also find a temperature dependence of Deff and Npar
with larger Deff and lower Npar for the warmer cloud temperature
range.
Although the ML-CIRRUS campaign was not designed to investigate an indirect
aviation effect of cirrus clouds and aerosols in the regions of cirrus cloud
formation were not explored in detail, it was possible to derive important
information of the data. Furthermore, the original focus of ML-CIRRUS was
not on a sufficient collocation of lidar and in situ measurements for both
cloud types. Therefore, additional measurements were performed during the
CIRRUS-HL mission in 2021, and the flight planning for the CIRRUS-HL campaign
learned from our experiences and the collocation of lidar and in situ
measurements was particularly improved. Also, the sampling of aerosol
properties in the region of the cloud formation and evolution was a focus of
CIRRUS-HL. In the following, we expect that data from the CIRRUS-HL mission
will address more of the open questions related to the impact of aviation on
ice cloud properties, e.g., how the PLDR and microphysical properties depend
on the aerosol concentration and size distribution in the region of cloud
evolution.
Data availability
The data used in this study are available at the HALO database (10.17616/R39Q0T, Re3data.org, 2023).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-23-8369-2023-supplement.
Author contributions
SG performed the lidar measurements. CV, TJW, MK and RW performed the in situ
measurements during ML-CIRRUS. MW provided the basic analysis of the lidar
data. MK and TJW provided the basic analysis of the in situ data. BU, QL and SG
preformed the analyses in this study. SG wrote the manuscript. All authors
discussed the data and findings.
Competing interests
At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.
Disclaimer
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
ML-CIRRUS was mainly funded by the Deutsches Zentrum für Luft- und
Raumfahrt (DLR), the Deutsche Forschungsgemeinschaft (DFG) within the
SPP1294-HALO project under contract VO1504/7-1, and the Helmholtz Association
under contract W2/W3-60. This study was funded by CRC project TRR 301 under
project ID 428312742 and DLR internal funding within the MABAK project.
Financial support
This research has been supported by the
Deutsche Forschungsgemeinschaft (grant no. VO1504/7-1), by CRC project TRR 301 under project ID 428312742 and by DLR internal funding within the MABAK project.The article processing charges for this open-access publication were covered by the German Aerospace Center (DLR).
Review statement
This paper was edited by Johannes Quaas and reviewed by two anonymous referees.
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