Microphysical, optical, and environmental properties of
contrail cirrus and natural cirrus were investigated by applying a new,
statistically based contrail–cirrus separation method to 14.7 h of cirrus
cloud measurements (sampling frequency 1 Hz, max. ∼ 290 m s-1,
total length of sampled in-cloud space ∼ 15 000 km) during the
airborne campaign ML-CIRRUS in central Europe and the northeast Atlantic
flight corridor in spring 2014. We find that pure contrail cirrus appears
frequently at the aircraft cruising altitude (CA) range with ambient
pressure varying from 200 to 245 hPa. It exhibits a higher median ice
particle number concentration (Nice), a smaller median mass mean radius
(Rice), and lower median ice water content (IWC) (median: Nice=0.045 cm-3, Rice=16.6µm, IWC = 3.5 ppmv), and it is optically thinner (median extinction coefficient Ext =∼ 0.056 km-1) than the cirrus mixture of contrail cirrus, natural in
situ-origin and liquid-origin cirrus found around the CA range (median:
Nice=0.038 cm-3, Rice=24.1µm, IWC = 8.3 ppmv, Ext =∼ 0.096 km-1). The lowest and thickest
cirrus, consisting of a few large ice particles, are identified as pure
natural liquid-origin cirrus (median: Nice=0.018 cm-3,
Rice=42.4µm, IWC = 21.7 ppmv, Ext =∼ 0.137 km-1). Furthermore, we observe that, in particular, contrail
cirrus occurs more often in slightly ice-subsaturated instead of merely ice-saturated to supersaturated air as often assumed, thus indicating the
possibility of enlarged contrail cirrus existence regions. The enlargement
is estimated, based on IAGOS long-term observations of relative humidity
with respect to ice (RHice) aboard passenger aircraft, to be
approximately 10 % for Europe and the North Atlantic region, with the
RHice threshold for contrail cirrus existence decreased from 100 % to
90 % RHice and a 4 h lifetime of contrail cirrus in slight
ice subsaturation assumed. This increase may not only lead to a
non-negligible change in contrail cirrus coverage and radiative forcing, but
also affect the mitigation strategies of reducing contrails by rerouting
flights.
Introduction
The global aviation sector makes up approximately 5 % of anthropogenic
global warming (Grewe et al., 2021; Klöwer et al., 2021). Contrail
cirrus is one of the largest radiative forcing components of aviation
(Lee et al., 2009; 2021) with uncertainties arising from many sources,
including limited knowledge of cirrus cloud properties, spatial coverage, and
life cycle (Schumann and Heymsfield, 2017; Kärcher, 2018; Burkhardt
et al., 2018). Contrail cirrus comprises line-shaped contrails in the wake
of high-flying aircraft and thin cirrus patches resulting from the
dispersion of long-living contrails. Only a few models account for the water
emitted from the aircraft causing contrails in slightly subsaturated air and
for the ice water content in contrails during their life cycle extending
their persistence (Schumann, 2012). Instead, models often
estimate contrail cirrus coverage based on simplified contrail ageing and
spreading mechanisms in ice-supersaturated regions (ISSRs) (Burkhardt et
al., 2010; Burkhardt and Kärcher, 2011).
Contrails form when hot and humid aircraft exhaust mixes rapidly with cold
and humid ambient air so that the humidity in the exhaust gases exceeds
liquid water saturation (Appleman, 1953; Schmidt, 1941; Schumann, 1996).
In such air supersaturated with respect to liquid water (RHw>100 %), aerosol particles emitted from the aircraft
(combustion soot and sulfuric acid–water droplets) or pre-existing in the
in-mixed ambient air become activated to form water droplets that freeze
subsequently to contrail ice particles. According to the purely
thermodynamic Schmidt–Appleman criterion (SAC), the threshold temperature
for contrail formation depends on ambient air pressure and humidity, on the
amount of water and heat emitted by the aircraft per fuel mass, and on the
aircraft engine's overall propulsion efficiency (Schumann, 1996; Jensen
et al., 1998). After reaching the ambient temperature by mixing with the
surrounding air, the contrails grow or shrink in size depending on ambient
humidity. If the ambient relative humidity remains supersaturated with
respect to ice (RHice>100 %), contrails grow in ice
water content and can persist for up to 5 h or even longer (Gierens and
Vázquez-Navarro, 2018; Schumann and Heymsfield, 2017)
and may spread and evolve into thin cirrus layers. Otherwise, contrail ice
particles sublimate and dissipate on a timescale dependent on their sizes
and the ambient air RHice (Schumann, 2012).
A robust estimation of contrail cirrus' radiative effect depends largely on
their optical properties (related to their microphysical properties and age)
and geographical appearance. Young contrails can exert an instantaneous
radiative forcing to warm and cool the atmosphere that is 3 orders of
magnitude larger than their net warming effect (Gierens et al.,
2020). The microphysical features of contrail cirrus at different plume ages
observed from various airborne campaigns were compiled and described in
Schröder et al. (2000),
Schumann et al. (2017) and
Chauvigné et al. (2018). Fresh contrails
are characterized by an ice crystal number concentration (Nice) of
thousands of ice crystals per cubic centimetre in size up to a few
micrometres in diameter, as observed in a plume approximately 2 min old
(Petzold et al., 1997). Contrails 2–5 min
old were frequently measured (e.g. Voigt et al., 2011; Gayet et
al., 2012). Here, contrail ice crystal number concentrations were diluted to
100 to 400 cm-3 and ice crystal diameters increased to 4 to
10 µm due to condensational growth (Jeßberger et al., 2013;
Bräuer et al., 2021). Slightly older contrails at a maximum plume age of
30 min are diluted further by the inmixing of ambient air down to less than
hundreds of ice crystals that have grown to tens of micrometres
(Schröder et al., 2000). The peculiar high
Nice of small ice particles makes young contrails easy to be
distinguished from natural cirrus. At an even later stage, Nice of
contrail cirrus further decreases significantly to a few ice particles per
cubic centimetre or less, with particle sizes being 2–3 orders of magnitude
larger, becoming similar to natural cirrus and making the discrimination
between contrail and natural cirrus difficult. Contrail cirrus is generally
characterized by low ice water content (IWC) ranging from 0.1 to about 10 mg m-3 (Schumann et al., 2017), like
natural cirrus of in situ-origin whose ice crystals have formed and grown in
an ice-cloud-only environment (Luebke et al., 2016; Krämer et al.,
2020). Different from contrail cirrus and in situ-origin cirrus,
liquid-origin cirrus clouds often yield higher IWC (Krämer et al.,
2016, 2020) because their ice crystals originally form as
liquid drops in a warmer atmosphere (ambient temperature Tamb>235 K), which subsequently freeze while being lifted into the
cirrus temperature region of the atmosphere.
The fact that contrails often coexist with natural cirrus and become
embedded within thin or subvisible cirrus (Kübbeler et al., 2011;
Gierens, 2012; Unterstrasser et al., 2017) makes it challenging to discriminate
between aged contrails and natural cirrus, thus impeding clarification of contrail
cirrus' contribution to the radiative balance.
Chauvigné et al. (2018) employed a
principal component analysis method to distinguish between contrail cirrus
particles at different ages and natural cirrus measured during the CONCERT
2008 campaign (Voigt et al., 2010), which was successful because contrails
sampled during the CONCERT campaign were rather young and more recognizable
compared to natural cirrus. However, not all required optical and
microphysical parameters can be obtained from single aircraft campaigns to
apply this method widely, and the CONCERT dataset is small, around 4.0 h of
contrail and natural cirrus sampling time in total
(Kübbeler et al., 2011).
A common assumption on the conditions for contrail cirrus formation and
evolution is that contrail cirrus occurs and persists merely in ISSRs
(Kärcher, 2018). In fact, contrails and contrail cirrus were
also observed in ice-subsaturated air, not only during contrail-dedicated
research flights (Kübbeler et al., 2011; Voigt et al., 2011; Gayet et
al., 2012; Schumann et al., 2017; Chauvigné et al., 2018) but also from
IAGOS commercial aircraft observations in the North Atlantic region
(Petzold et al., 2017). Apart from a high number of small
contrail ice particles, large particles (ice particle diameter Dp>100µm) were also detected but at relatively low
concentrations (Voigt et al., 2010; Kübbeler et al., 2011;
Chauvigné et al., 2018). Such large ice crystals were also observed in
contrail cirrus during the ML-CIRRUS campaign (Voigt et al., 2017).
However, attention to contrail cirrus in ice-subsaturated environments and
the role that large ice particles play in contrail cirrus was raised only by
Kübbeler et al. (2011) and
Schumann (2012). Kübbeler et
al. (2011) discussed that the subsaturation feature observed in contrail
cirrus during the CONCERT campaign is accompanied by the sublimation of
those large ice particles, which might be sedimented from higher levels
after being formed under ISSRs. As the contrail cirrus dataset is limited to
only a few segments of several flights, it could not be corroborated that
the existence of contrail cirrus in ice-subsaturated environments is a
common feature. But Schumann and Graf (2013) found it
necessary to reduce the critical humidity above which contrails form to a
value below ice saturation to model contrail occurrence and their longwave
radiative forcing in agreement with multi-year satellite observations over
the North and South Atlantic.
Currently, the prevalent strategy for contrail avoidance is to reroute the
aircraft around ice-supersaturated regions by flying at slightly higher or
lower altitudes to avoid contrail formation or minimize contrail radiative
forcing (Teoh et al., 2020a; Niklaß et al., 2021). Teoh et
al. (2020a) showed that focusing on the avoidance of strong contrails, the
so-called big hits, reduces the radiative forcing effect because only for
these cases does the “saved” radiative forcing overrule the additional
CO2 emitted during the rerouting of the aircraft. Gierens et
al. (2020) showed that the formation of contrails can be predicted with some
success, but there are problems in predicting contrail persistence due to
limited knowledge about the occurrence of air masses around ice saturation.
Particularly from this study, it becomes evident that further knowledge of
the distribution of air masses around ice saturation and the resulting
properties of aircraft-induced cirrus and natural cirrus is required
(Teoh et al., 2022).
In this study, we investigate a larger dataset of 14.7 h cirrus cloud
sampling (frequency 1 Hz, max. ∼ 290 m s-1) obtained during the
ML-CIRRUS 2014 campaign (Sect. 2.1) than the 4 h CONCERT dataset. With
commonly available parameters describing the microphysical properties of
cirrus, such as Nice, ice crystal sizes, and IWC, we adopt a simpler
statistical approach to separate aviation-induced cirrus from natural cirrus
compared with Chauvigné et al. (2018). It
consists of the SAC, the most frequent aircraft cruising altitude range and
a newly developed aircraft exhaust plume detection algorithm (Mahnke
et al., 2022) to differentiate aged contrail cirrus (>0.5 h
lifetime, Schumann et al., 2017; Voigt et al., 2017) and natural cirrus
(Sect. 2.3). Step by step, we show the sharpened differentiation of contrail
cirrus from natural cirrus and report on their microphysical properties and
occurrence conditions (Sect. 3.1–3.2). In addition, we analyse the humidity
of the environments of contrail and natural cirrus (Sect. 3.3). Based on
these observations, we simulate the lifetime of ice particles that have
similar microphysical properties to the contrail cirrus sampled during
ML-CIRRUS in slightly ice-subsaturated environments. Furthermore, we inspect
15 years of RHice measurements aboard passenger aircraft in the IAGOS
global monitoring framework to shed light on how the existence of contrail
cirrus in environments with RHice≥90 % might influence
contrail mitigation (Sect. 4).
Datasets and methodsML-CIRRUS dataset
The Mid-Latitude CIRRUS (ML-CIRRUS) campaign was conducted from
Oberpfaffenhofen, Germany, to probe cirrus clouds over central Europe and the
northeast Atlantic region in March and April 2014 (Voigt et al., 2017).
The High Altitude and Long-Range Research Aircraft (HALO;
Krautstrunk and Giez, 2012) was deployed to investigate the formation
mechanism, life cycle and climate impact of natural cirrus and
aircraft-induced cloudiness. Excluding test flights and the ones with strong
instrumental issues, 12 of 17 research flights with the focus on natural and
contrail cirrus, as listed in Table S1, are considered here for studying the
microphysical properties of contrail cirrus and mid-latitude natural cirrus,
which serve as the basis to distinguish contrail cirrus from natural cirrus.
The ML-CIRRUS dataset (Voigt et al., 2017) includes the parameters
important for cloud characterization – in situ relative humidity with
respect to ice RHice, ice water content IWC, ice particle number
concentration Nice, and mass mean radius Rice.
The in situ RHice was calculated using water vapour mixing ratios
measured by the tuneable diode laser hygrometer SHARC
(Meyer et al., 2015), ambient
temperature Tamb and pressure measurements provided by the Basis Halo
Measurement and Sensor System (BAHAMAS) (Mallaun et al., 2015; Giez et
al., 2017). The overall uncertainty of SHARC H2O measurement is 5 %
relative and ±1 ppm absolute offset uncertainty
(Kaufmann et al., 2018). The nominal accuracies of the
BAHAMAS pressure and Tamb measurement are 0.3 hPa and 0.5 K (Mallaun
et al., 2015; Giez et al., 2017; Kaufmann et al., 2018). The overall
accuracy of the in situ RHice measurements here is between 10 %–20 %, with the respective uncertainties of the temperature, pressure, and
water vapour measurements considered
(Krämer et al., 2016). The in situ
RHice, water vapour, and temperature measurements were compared with
other instruments on board and model data from the European Centre of
Medium-range Weather Forecasting (ECMWF) by Kaufmann et al. (2018). No systematic instrument bias in either water vapour or temperature
was identified in the upper troposphere. A further discussion on the
reliability of the RHice measurements can be found in the Supplement (Sect. S3).
Cloud measurements were performed using the cloud spectrometer NIXE-CAPS
(New Ice eXpEriment: Cloud and Aerosol Particle Spectrometer; later referred
to as NIXE) at a time resolution of 1 Hz (max. ∼ 290 m s-1) with
the instrument mounted under the aircraft wing (Krämer et al., 2016;
Luebke et al., 2016). As a combination of the two instruments CAS-DPOL
(Cloud and Aerosol Spectrometer with Detection of POLarization) and
CIPg (Cloud Imaging Probe grayscale), NIXE measures Nice in
the particle diameter (Dp) range of 0.61–937 µm, with Dp
meaning optical-equivalent diameter for CAS-DPOL and area-equivalent
diameter for CIPg, respectively. Only particles of Dp>3µm are considered for cloud measurements, while smaller
particles are classified as aerosols. In fresh contrails, particle sizes can
be smaller than 3 µm, but for consistency and comparability, the lower
threshold Dp=3µm is maintained in the analysis of contrails
and contrail cirrus. NIXE gives a total uncertainty of ±20 %
(Meyer, 2012) in particle number concentration measurement. IWC is
derived from the ice particle size distribution (PSDice) in the Dp
range of 3–930 µm. How the IWC is determined from a mass–dimension
relation and the robustness of the IWC have been stated in
Krämer et al. (2016),
Luebke et al. (2016), and
Afchine et al. (2018). The lower IWC
detection limit of NIXE is 0.15 ppmv (parts per million by volume). The ice
crystal mass mean radius Rice in micrometres (µm) is calculated with
Rice=104×10-6×IWCNice×34πρ1/3,
where IWC is in milligrams per cubic metre (mg m-3; converted from IWC in ppmv), ρ is 0.92 g cm-3, and Nice is the total number of ice crystals
(Dp>3µm) per cubic centimetre (cm-3).
Additional parameters for discriminating contrail and natural cirrus are
total aerosol particle number concentration, total reactive nitrogen
NOy mixing ratio, and airborne lidar RHice. Here, the measurements
are summarized below (see Voigt et al., 2017, for details).
The total aerosol particle number concentration was measured by the
instrument AMETYST (Voigt et al., 2017), which is a combination of four
condensation particle counters (CPCs) measuring total and non-volatile
aerosols in the size range of 4 nm–2 µm. The uncertainty of the CPCs
of AMETYST is in the typical CPC uncertainty range, which is estimated to be
of the order of 10 % (Petzold et al., 2011, 2013). NOy was
measured by the instrument AENEAS (Ziereis et al., 2000) by catalytically
converting NOy to nitrogen monoxide NO on a gold surface heated to 300 ∘C. The converted NO will then be directly detected with
chemiluminescence technique. AENEAS has an NOy detection range of 5 pptv (parts per trillion by volume) to 60 ppbv (parts per billion by volume)
(Voigt et al., 2017), with an overall uncertainty of 30 % or 40 pptv.
The airborne lidar RHice is derived from water vapour measurement in
the 935 nm absorption band of H2O by the lidar WALES and ambient
temperature from ECMWF (Wirth et al., 2009; Groß et al., 2014). For
retrieving cirrus clouds from the remote-sensing technique, only the
particles producing a back-scattering ratio (BSR) greater than 3 and having
a depolarization ratio greater than 20 % at Tamb<235 K are
interpreted as cirrus cloud particles (Urbanek et al.,
2018). Note that SHARC measures water vapour concentrations at aircraft
positions, while WALES obtains atmospheric cloud columns with its laser
penetrating through clouds from the cloud top or bottom. The two instruments
do not measure water vapour in parallel. Therefore, the in situ RHice and lidar RHice are not from the same clouds. However, the
intercomparison of in situ and lidar RHice measurements inside cirrus
clouds promotes the evaluation of the robustness of the in situ RHice
dataset and uncertainties related to the quality of the Tamb dataset.
RHice dataset from IAGOS passenger aircraft
The RHice dataset spanning from 1995 to 2010, based on the Measurement
of Ozone and Water Vapour on Airbus In-service Aircraft (MOZAIC) programme,
is used for the analysis of the RHice distribution in air masses in the
northern mid-latitudes. The MOZAIC programme (Marenco et
al., 1998) was initiated in August 1994 and was carried on within the new
European Research Infrastructure IAGOS (In-service Aircraft for a Global
Observing System; https://www.iagos.org/, last access: 6 December 2022) in 2011
(Petzold et al., 2015). The measurement of
atmospheric trace gases and aerosol particles is conducted by autonomous
instruments installed on commercial passenger aircraft. Up to now, over
63 000 flights have contributed to a global-scale dataset of water vapour and
RHice in the upper troposphere and lower stratosphere (Petzold et
al., 2017, 2020; Reutter et al., 2020).
The dataset used for this study has aerial boundaries of 40–60∘ N covering the North Atlantic (65–5∘ W) and Europe (5∘ W–30∘ E). It contains temperature,
pressure, and RHice measurements. RHice is directly measured by the
IAGOS Capacitive Hygrometer (ICH). The details regarding the principles of
the ICH sensor and sensor calibration as well as the procedures to determine
the ambient air temperature from the sensor temperature can be found
elsewhere (Neis et al., 2015; Smit et al., 2014). The ICH sensors are
usually calibrated before being deployed in the aeroplane and after
deployment. During the deployment period (3–6 months), the sensor output
signal in voltage may drift. Therefore, an in-flight calibration method is
applied to the reanalysis data to overcome the drifts of sensor signals and,
thus, to correct erroneous RHice values (Smit et al., 2008). The
overall uncertainty of IAGOS RHice is about 5 % (2 %–8 %) at 10–12 km
at cruising altitudes with a detection limitation of ∼ 10 %
RHice (Petzold et al., 2020; Smit et al., 2014). The MOZAIC
RHice dataset has been quality-checked, successfully validated against
RHice observations by high-precision instruments aboard research
aircraft, and also compared to ERA-Interim reanalysis data (Dee et al.,
2011) to be reliable for scientific studies (Neis et al., 2015; Petzold
et al., 2020; Reutter et al., 2020). The same dataset was described in
detail in the study of ice-supersaturated air masses in the northern
mid-latitudes (Petzold et al., 2020). Here, the
occurrence fractions of air masses at different RHice thresholds are
determined for the North Atlantic region and Europe from this dataset and
utilized for the discussion about the potential influence on contrail
avoidance (Sect. 3.5).
Contrails and contrail cirrus detection
Data suitable for statistically analysing the microphysical properties of
cirrus induced by aircraft emissions or by atmospheric dynamic systems
should meet the following criteria:
ambient pressure p<350 hPa, which constrains the pressure altitude
to be higher than ∼ 8.1 km under standard atmospheric
conditions, also the common cruising altitude of commercial
aeroplanes;
ambient temperature Tamb<235 K, which is the cirrus formation
temperature region.
The Schmidt–Appleman criterion (SAC)
To determine the potential for contrail formation in the air masses meeting
the above thresholds, air mass thermodynamic properties are analysed by
applying the Schmidt–Appleman criterion (SAC). The SAC at aircraft pressure
level p depends on the gradient G of the mixing line (see Fig. 1)
(Schumann, 1996):
G=EIH2OcppεQ1-η,
where p is the ambient air pressure, cp is the isobaric heat capacity of
air (1004 J kg-1 K-1), and ε is the ratio of molar masses
of water and dry air (0.622). For the calculation of G, the emission index of water vapour EIH2O and fuel heat capacity Q from burning conventional jet fuel (kerosene) are considered: EIH2O=1.25 kg (kg fuel)-1 and Q=43.2 MJ (kg fuel)-1, assuming an overall propulsion efficiency η=0.31. G (unit: Pa K-1) represents
the gradient of the trajectory of aircraft exhaust air isobaric mixing with
the surrounding ambient air – the blue line in Fig. 1, where the
dependence of the water vapour partial pressure on temperature in the
isobaric mixture of an aircraft
plume and ambient air is illustrated (adapted from Fig. 3 in
Schumann, 1996). The sampled air masses are assumed to be
released from aircraft engines and have undergone the isobaric mixing
process while detraining into ambient air. Tamb and RHice at an
assumed measuring position (the red dot in Fig. 1), therefore, mark the
ending point of an individual air parcel's
mixing line. If the mixing line touched or crossed the ice–liquid saturation
curve, for example, the blue, dashed black, or cyan lines in Fig. 1, the measured cloud
particle could have been very probably involved in the formation of
contrails during its evolution. Cirrus cloud particles sampled at
thermodynamic positions not fulfilling SAC are considered irrelevant to
contrail formation and are treated as natural cirrus.
Water vapour saturation partial pressure with respect to liquid
water (esat,w) and ice (esat,ice) as a function of
temperature. The blue line represents the isobaric mixing of the aircraft
exhaust plume with the surrounding ambient air at a gradient of G along the
black arrow. During the isobaric mixing, liquid drops form when surpassing
water saturation; the drops freeze subsequently at ∼ 235 K.
The red dot represents an in situ-measured cloud sample that marks the
ending point of the cloud sample's mixing. Tw is the threshold
temperature for contrails to form. This occurs when the isobaric mixing line
(the dashed line) just touches the water saturation curve. In this case,
contrails persist in ice-supersaturated environments and live only shortly
in ice subsaturation, as indicated by the dark- and light-grey areas,
respectively. The cyan line shows a situation where the aircraft exhaust air
parcel just reaches ice saturation so that contrail ice particles might form
directly from the gas phase heterogeneously or homogeneously at the
corresponding ice supersaturation. The red curve at RHice=90 %
represents the proposed lower RHice threshold of persistent contrails
in this work (Sect. 3.3).
The most frequent aircraft cruising altitude (CA) range
To better discriminate between contrail and natural cirrus, we define
another criterion by dividing the altitude range of the dataset fulfilling
SAC into the most frequent aircraft cruising altitude (CA) range and the
altitudes beyond. To determine the CA pressure range, we surveyed the 15 years of IAGOS-MOZAIC pressure measurements over the North Atlantic and
Europe regions aboard passenger aircraft. The occurrence probabilities of
flight levels per 10 hPa bin are shown in Fig. 2. The most frequently
visited atmospheric pressure levels are from 200 to 270 K. However, ice
cloud properties at lower altitudes with pressure greater than 245 hPa show
distinct behaviour from those at higher altitudes below 245 hPa and seem
closer to those observed at positions not fulfilling SAC, implying that they
could be natural cirrus or extensively aged contrail cirrus. Hence, the
pressure altitude range of 200–245 hPa is adopted as the CA range for
further analysis.
Occurrence fractions of passenger aircraft flight levels in
pressure (unit: hPa) measured during the IAGOS-MOZAIC period (1996–2010)
over the North Atlantic and Europe. The pressure range 200–245 hPa between
the dashed lines is adopted as the most frequent aircraft cruising altitude
(CA) range (see text for the determination of the boundary pressure
thresholds).
Aircraft plume detection
The principle of the aircraft exhaust plume detection assumes that a
simultaneous enhancement of multiple products emitted from aviation fuel
combustion, here total aerosol particles and reactive nitrogen NOy
measured by the instruments AMETYST and AENEAS (Sect. 2.1), serves as a
clear marker for air masses influenced by aircraft exhaust
(Schumann et al., 2002). In this work, the
total aerosol particle number concentration and the mixing ratio of
NOy, which can be considered a passive tracer in aircraft plumes up to
a plume age of 18 h, are used to detect aircraft exhaust plumes along the
flights from the concurrent increased particle number concentrations and
NOy mixing ratios in comparison to atmospheric background values
(Mahnke et al., 2022). The plume detection algorithm is restricted to
a minimum NOy excess of around 0.1 ppbv above the atmospheric
background, which corresponds to a maximum plume age of approximately 2–5 h, depending on the diffusion speed of aircraft exhaust and NOy
emission index according to aircraft type.
The plume detection algorithm is applied to 10 ML-CIRRUS flights, for which
both NOy and aerosol measurements are available. Only the air masses
containing ice particles detected at Tamb<235 K are
considered as contrail cirrus. Different from the passive tracer NOy, cirrus
particles are subjected to gravity waves and turbulence. As a result, at
some point the contrail ice particles may become spatially separated from
the plume, and/or the plume may become spatially associated with particles
formed in natural cirrus clouds. Therefore, the plume detection algorithm
may miss contrail cirrus particles. The contrails that can be found with the
help of the plume detection algorithm can be viewed as a subset of the
contrails because as long as the plume is detected and contains cirrus ice
particles, these ice crystals are highly likely to stem from contrails. The
final in-cloud sampling time with aircraft exhaust plume encounter, as identified by
the plume detection algorithm, is approximately 0.99 h, around 3200 cloud
samples (max. ∼ 1 km length of sampled in-cloud space) at 1 Hz
sampling frequency. The sizes in flight hours of each sub-datasets after
applying the SAC, CA, and plume detection criteria are listed in Table S2. We
use the plume subset to show that the microphysical properties of these
contrails are comparable to those from the larger dataset (determined with
SAC + CA) that also includes contrail ice particles spatially separated from
the plume. This comparison increases our confidence in the method to
identify contrails via the SAC and CA criteria.
Properties of contrail and natural cirrusCirrus cloud observations
The full ensemble of cirrus cloud properties (Nice and Rice)
observed during ML-CIRRUS as a function of ambient temperature is shown in
Fig. 3 together with in situ RHice. The number of flight hours spent in
cirrus clouds is 14.7 h, approximately 15 000 km of the sampled in-cloud
space in total. Figure 3a and b show the temperature dependence of Nice
(Dp>3µm) and Rice, respectively, binned in
1 K intervals and colour-coded by the occurrence frequency that is normalized
to the total counts in each temperature interval. One pronounced signature
of contrail cirrus is the high Nice>0.1 or even
>1 cm-3 between 208–220 K, which could be linked to
aviation-induced cirrus (Petzold et al., 2017; Schumann et al., 2017;
Krämer et al., 2020) as the median Nice of the large climatology of
cirrus shown by Krämer et al. (2020)
is 0.03 cm-3. In the same temperature range, Rice exhibits the
highest occurrence frequency at a small mass mean radius around 20 µm
or even lower. The occurrence frequency of Nice in relation to
Rice is displayed in Fig. 3c for the whole cirrus dataset with the
isolines representing IWC (in ppmv), which means that the same IWC could arise
from many small ice particles (the upper-left segment of the IWC isolines)
or a few large ice crystals (the lower-right segment).
Contrail cirrus often appears in the upper-left side of the banana-shaped
Nice–Rice relation (Fig. 3c), typical of high Nice, small
Rice and low IWC, while natural cirrus more typically clusters in the
middle and lower right parts, with low Nice, large Rice, and high
IWC. The 50th (grey) and 90th (black) percentile contours indicate
a pronounced occurrence of contrail cirrus, with IWC mostly below 10 ppmv.
The 10 ppmv IWC isoline also roughly sets in situ-origin cirrus apart from
liquid-origin cirrus with higher IWC. This classification of cirrus origins
was applied to the ML-CIRRUS measurements by
Luebke et al. (2016) and is replotted in Fig. S1
(see Supplement), where it can be seen that in situ-origin cirrus appears
more frequently with Rice<30µm and IWC <10 ppmv, while liquid-origin cirrus shows exactly the opposite.
The occurrence frequency of in-cloud RHice in relation to temperature,
as depicted in Fig. 3d, shows one maximum at around 90 % RHice in the
temperature range of 208–220 K, which corresponds to the temperature range
showing contrail cirrus signals in Fig. 3a and b. The observed occurrence of
contrail cirrus in slight subsaturation with respect to ice observed in
ML-CIRRUS is consistent with what was reported in
Kübbeler et al. (2011) based on the
CONCERT dataset. A similar feature is reported from the first analysis of
the IAGOS RHice and cloud dataset in the North Atlantic flight corridor
for the years 2014 and 2015 (Petzold et al., 2017).
In the following we will discriminate between contrail and natural cirrus
and obtain an understanding of the occurrence of contrail cirrus regarding
spatial occurrence probabilities, cloud properties, and their
favourable atmospheric conditions.
Cirrus classificationCirrus differentiated by the Schmidt–Appleman criterion (SAC)
Our attempt at SAC calculation divides the ML-CIRRUS cirrus dataset
discussed in the previous section into two categories: the dataset of cloud
particles sampled under conditions fulfilling SAC (SAC+,
∼ 11.2 h) and the complementary dataset not fulfilling SAC
(SAC-, ∼ 3.5 h); see Fig. 1d for details. As
discussed in Sect. 2.3.1 and shown in Fig. 1, a cloud sample fulfilling SAC
is considered very possibly involved in the formation of contrails
during its evolution, and the one measured at thermodynamic positions
failing SAC is considered irrelevant to contrail formation and is regarded
as natural cirrus.
Note, however, that natural cirrus could also be included in the SAC+
group, meaning that SAC alone is not a sufficient criterion to identify
contrail cirrus, while cirrus detected in the SAC- group can be
unambiguously attributed to natural cirrus. Despite the limited
differentiation between contrail and natural cirrus using SAC alone, we
will first discuss the differences in the
microphysical properties between the SAC+ and SAC- datasets. The
sharpening of the separation of the full ensemble into aviation-influenced
cirrus and natural cirrus by adding another criterion of the most frequent
cruising altitude range will then be discussed in Sect. 3.2.2.
Overview of the cirrus cloud properties measured in central Europe
and the northeast Atlantic flight corridor during the ML-CIRRUS research
aircraft campaign in spring 2014. (a) Occurrence frequency of ice particle
number concentrations (Nice) for all cirrus crystals larger than 3 µm in diameter (Dp), binned in 1 K intervals. The grey line
shows the median Nice in single temperature intervals. The horizontal
bar indicates the Nice median from in situ Nice global climatology
(Krämer et al., 2020). (b) The same
as (a) but for the mass mean radius Rice of cirrus particles. (c)
Normalized occurrence frequency of Nice as a function of Rice.
Coloured curves are ice water content (IWC) isolines in parts per million by
volume (ppmv). The same amount of IWC could consist of many small ice
particles pointing to the left end of the isoline or a few large ice
crystals to the right end. The grey and black contours enclose 50 % and
90 % of the most frequently occurring cloud particles. Ice crystals with
IWC <10 ppmv are mostly in situ-origin cirrus, while those with IWC >10 ppmv are mostly liquid-origin cirrus. (d) Normalized
occurrence frequency of in situ RHice in cirrus clouds. The water
saturation (Murphy and Koop, 2005) and homogeneous
freezing threshold (Koop et al., 2000) are added. The vertical red line
marks the temperature threshold for possible contrail formation, calculated
from the Schmidt–Appleman criterion (SAC). The most frequent aircraft
cruising altitude boundaries are marked by the vertical blue lines and
correspond to a pressure range of 200–245 hPa (207–218 K in temperature).
Microphysical properties in the cirrus fulfilling SAC and in
natural cirrus
Figure 4a and b display the Nice–Rice relations for the SAC+
and SAC- datasets, respectively, with the occurrence frequency
normalized to the total number of measurements in each dataset. Small ice
crystals in higher concentrations are mainly found in the SAC+ group.
In the SAC+ dataset, the median Nice=0.04 cm-3 doubles
the median value of the SAC- dataset. Conversely, the median
Rice of the SAC+ group (20.6 µm) is only half of the value
(42.4 µm) of the SAC- counterpart. Nice in the SAC+
dataset reaches values as high as 20 cm-3 for Rice smaller than 30 µm, while Nice in the SAC- dataset is mostly below 1 cm-3, with most particles larger than 30 µm. The highest
occurrence frequencies in the SAC+ and SAC- datasets (enclosed by
the 50th percentile contours) dwell on the lower and upper sides of the
10 ppmv IWC isoline, respectively.
Besides the fact that in the SAC+ dataset both natural and contrail
cirrus can be found, the SAC- group only contains natural
cirrus. The two groups largely correspond to cirrus formed from different
mechanisms, namely in situ- and liquid-origin cirrus. Most in situ-origin
(IWC <10 ppmv) and some liquid-origin cirrus (IWC >10 ppmv) are found in the SAC+ group; conversely, most of the
liquid-origin cirrus and a small part of the in situ-origin cirrus are in
the SAC- counterpart. Contrail cirrus belongs to the in situ-origin
cirrus type, since it appears in the temperature range Tamb<235 K, either without pre-existing cirrus (contrail cirrus) or superimposed
on existing cirrus (embedded contrails). As embedded contrails, they could
also appear as the liquid-origin cirrus.
The contrast between the SAC+ and SAC- groups is illustrated in
Fig. 4c, showing the differences between Fig. 4a and b. The reddish area
indicates that ice crystals measured in the environments satisfying SAC are
prone to contrail cirrus, whereas the bluish area, in contrast, shows ice
crystals that are linked to natural cirrus.
(a)–(c) Similar to Fig. 3c but for (a) the
Schmidt–Appleman criterion (SAC) fulfilled dataset of contrail and natural
cirrus (median: Nice=0.04 cm-3 and Rice=20.6µm); (b) the SAC unfulfilled dataset of natural cirrus (median: Nice=0.018 cm-3 and Rice=42.4µm); and (c) the difference
of data points between (a) and (b) in single Nice–Rice bins. (d)–(f) Similar to Fig. 3d but for (d) the dataset of contrail and natural
cirrus fulfilling SAC; (e) the natural cirrus not fulfilling the SAC; and (f)
the difference of data points between (d) and (e) in single
RHice–Tamb bins.
RHice in the cirrus fulfilling SAC
and in natural cirrus
The other pronounced differences between the SAC+ and SAC- groups
are the most frequently appearing RHice and the respective temperature
ranges, as shown in the lower panel of Fig. 4. The highest occurrence
frequencies of RHice in the SAC+ group concentrate at slight ice
subsaturation at ∼ 90 % RHice in the Tamb range of
207–218 K. The slight ice-subsaturation feature is associated with younger
contrails with high Nice and small Rice, as can been seen from
Fig. S2b (see Supplement), where the Nice–Rice relation is shown
colour-coded with RHice for the SAC+ group in the CA range (see
Sect. 2.3.2). In the SAC- dataset, the highest frequencies of
RHice cluster around 100 % at 10 K warmer temperatures and spread
over the Nice–Rice parameter space (Fig. S2c). The warm
temperature range, which is already shown in Fig. 3, reflects the fact that
colder temperatures are needed to fulfil SAC because the water saturation
pressure at warmer temperatures is almost always so high that the amount of
water in the ambient air together with the additional water from aircraft
exhaust is insufficient to reach supersaturation with respect to water to
form droplets.
In spite of the clear differences in ice particle properties and ambient
RHice conditions resulted from applying SAC (Fig. 4f), ambiguities
remain to characterize contrail cirrus and distinguish it from natural
cirrus because the natural cirrus of in situ-origin that has formed at
rather low temperatures can show the characteristics of medium
Nice (0.1 cm-3), low IWC, and small Rice as well and would thus be
misclassified as contrail cirrus. Additionally, even high Nice
accompanied by small Rice can appear in natural cirrus as a result of
in situ homogeneously freezing in high updraughts
(Krämer et al., 2016).
Cirrus fulfilling SAC inside and outside the cruising altitude (CA) range
Here, the SAC+ dataset shown in Fig. 4a and d is split into one group
inside the most frequent cruising altitude (CA) range and the other one
outside the CA range using the CA pressure boundaries defined in Sect. 2.3.2. The ice cloud properties and RHice occurrence frequencies
related to ambient temperature inside and outside the CA range are presented
and discussed below.
Microphysical properties inside and outside the cruising
altitude range
The Nice–Rice relation of the cirrus fulfilling the SAC and
detected inside the CA range is shown in Fig. 5a, while the cirrus outside the CA
range is depicted in Fig. 5c. Comparing the Nice–Rice relation
showing all SAC+ cirrus (Fig. 4a) to that inside and outside the CA
range, it becomes clear that the entire group of liquid-origin cirrus
(Rice>30µm and IWC >10 ppmv) and a
part of the in situ-origin cirrus (Rice<30µm and IWC <10 ppmv) occur outside the CA range; i.e., the cirrus outside the CA
range represents a mixture of contrail cirrus, in situ-origin cirrus, and liquid-origin cirrus, later referred to as a cirrus mixture. Inside the CA
range, almost only in situ-origin cirrus is present. The mean Rice and
Nice of cirrus particles inside the CA range (Fig. 5a) are
approximately 17 µm and 0.21 cm-3, corresponding to previous
field observations of pure contrail cirrus older than 30 min
(Schröder et al., 2000; Voigt et al., 2017; Schumann et al., 2017;
Chauvigné et al., 2018).
The classification that the cirrus fulfilling SAC and inside the CA range
is pure contrail cirrus is confirmed by the validated contrail cirrus,
which fulfils SAC and is identified by applying the aircraft plume detection
algorithm (Mahnke et al., 2022) described in Sect. 2.3.3. Since the
aerosol and NOy measurements for both flights on 22 March 2014 were
missing and
aircraft plumes detected at Tamb>235 K are screened out,
the valid sampling time encountered aircraft exhaust plumes is approximately
0.9 h, around 3200 cloud samples at 1 Hz sampling frequency, among which 1270
cloud samples are located in the CA range. As adding the CA constraint to
the SAC fulfilled plume dataset does not improve the validation
significantly (See Sect. S4 in the Supplement for detailed analysis), the
following discussion is based on the plume dataset with only the SAC
applied.
Nice–Rice(a, c, e) and RHice–Tamb(b, d, f)
relations colour-coded by normalized occurrence frequency, similar to Fig. 4a and d. (a, b) The contrail cirrus fulfilling the Schmidt–Appleman
criterion (SAC) and found inside the cruising altitude range (CA; ambient
pressure 200–245 hPa) (median: Nice=0.045 cm-3 and Rice=16.6µm). (c, d) The cirrus mixture fulfilling SAC and outside
the CA range (in situ- and liquid-origin cirrus) (median: Nice=0.038 cm-3 and Rice=24.1µm). (e, f) Contrail cirrus
with plume detection applied and fulfilling the SAC (median: Nice=0.027 cm-3 and Rice=21.7µm), but the CA range is not
considered here.
(a) Normalized occurrence frequency of ice particle
sizes in diameter (Dp, unit: µm) in the contrail cirrus (red),
cirrus mixture (contrail cirrus, in situ- and liquid-origin natural cirrus,
blue), and natural cirrus (black). The ice particle size ranges for contrail
cirrus, in situ-origin contrail or natural cirrus, and liquid-origin cirrus
are marked by the arrows. (b) Similar to (a) but for contrail cirrus (red)
and contrail cirrus satisfying the Schmidt–Appleman criterion (SAC) and
validated with the aircraft exhaust plume detection method (purple). Note
that Dp stands for optical-equivalent diameter for NIXE-CAS-DPOL in the
size range of 3–17 µm and area-equivalent diameter for NIXE-CIPg in
the sizes greater than 17 µm.
The Nice–Rice relation for the validated contrail cirrus is
displayed in Fig. 5e. The shape of the overall Nice–Rice
occurrence frequency distribution for the validated contrail cirrus shows
similarity to the pure contrail cirrus differentiated by combining SAC and
the CA range (Fig. 5a), especially when looking at the particle population
that contains 50 % of the most frequently appearing ice crystals. The
median Rice and Nice of the pure contrail cirrus are also close to
those of the validated cirrus. In conclusion, combining SAC and the CA range
has effectively exposed the differences in the microphysical properties of
pure
contrail cirrus (SAC+; inside the CA range, Fig. 5a), a cirrus mixture
(SAC+; outside the CA range, Fig. 5c), and mostly liquid-origin natural
cirrus (SAC-; outside the CA range, Fig. 4b).
In addition, we also inspected the frequency distributions of ice particle sizes
in diameter, which are not integrated like mass mean radius and will give
further insights into the differences among the cirrus categories and, in
addition, confirm the differentiation using the SAC–CA method.
Figure 6a shows the normalized occurrence frequencies of ice particle sizes
in the contrail cirrus (in situ-origin), cirrus mixture (contrail cirrus and in
situ- and liquid-origin natural cirrus), and mostly liquid-origin natural
cirrus. Three size modes of ice particle sizes can be identified from the
frequency distributions of the contrail cirrus and natural cirrus: ice
particles in the first size mode – Dp=3–17 µm (marked by
the short red arrow) – appear more frequently inside the CA range and are
attributed to pure contrail cirrus. The next size mode – Dp=3–200 µm (the long red arrow) – is present in contrail cirrus as
well as in natural cirrus and is attributed to aged contrails or in
situ-origin natural cirrus. The mode Dp=50–400 µm (the
black arrow) originates from liquid-origin cirrus. The maximum sizes
represent the largest ice particle size of the particle population including
90 % data. Large ice crystals up to about 200–300 µm do appear in
contrail cirrus but with a low frequency (see the blue curve in Fig. 6a
and also Kübbeler et al., 2011; Voigt et al., 2010). Also, note that 17 µm marks the instrument switches from NIXE-CAS-DPOL to NIXE-CIPg.
This might cause the jump of occurrence frequencies instead of a smooth
transition.
The histograms in Fig. 6a show that the contrail (red line) and
liquid-origin natural (black line) cirrus are most probably distinguishable
in the small ice particle diameter range (Dp<17µm)
and the larger size range (Dp>80µm). Ice crystals
between Dp=17–45 µm occur frequently in the contrail
cirrus but also in the natural cirrus, which makes it difficult to
discriminate between the contrail and natural cirrus in this size range. The
signature of a larger number of small ice crystals in natural cirrus occurs
in the early phase of homogeneous ice nucleation in faster updraughts.
However, such events are transient in time and space and are, therefore,
not often found in in situ measurements
(Krämer et al., 2020). The contrail
cirrus considered here does not contain such homogeneous freezing events.
Therefore, ice crystals in the diameter range Dp=3–17 µm
with relatively high occurrence frequencies and the large particles of
maximum size of about 200 µm can be attributed to contrail cirrus, as
already noted above. On the contrary, the natural cirrus has the second
highest frequency peak in the ice crystals larger than 54 µm, with the
maximum diameter being about 400 µm. This means that the observed
contrail cirrus was formed in situ with the special feature of frequently
appearing small ice crystals; the natural cirrus, however, as introduced
before, is a mixture of in situ-origin and liquid-origin cirrus. It is to
be noted here that adding an extra constraint of the CA range to the SAC+
group has greatly minimized the interference of the natural cirrus as well
as possibly undistinguishable, deeply aged contrail cirrus of much larger
sizes.
The cirrus mixture is interpreted above as a mixture of aged contrail
cirrus, mainly in situ-origin cirrus with a small portion of middle-sized
liquid-origin cirrus. This is confirmed by the frequency distribution of ice
particle sizes shown in Fig. 6a (blue line), where the majority (80 % of
the total frequencies) of particle diameters are between 17 and 66 µm,
and the maximum size is near 300 µm. From this analysis, it is
impossible to judge whether the in situ-origin cirrus is aged contrails,
which show the same properties as natural cirrus, or whether these cirrus
clouds have formed naturally.
Figure 6b shows that the occurrence frequency distribution of ice particle
sizes in the contrail cirrus identified using the SAC–CA combination is very
similar to that of the validated contrail cirrus aided by the plume
detection scheme. In the reference case of the plume-marked contrail cirrus,
there are even more smaller ice particles than in the SAC–CA-determined
contrail cirrus. Furthermore, the large ice particles occur with very low
frequencies not only in the plume-marked contrail cirrus but also in the
contrail cirrus constrained by SAC and the CA range. This adds confidence in
the discrimination between contrail cirrus and natural cirrus with the
SAC–CA combination.
RHice inside and outside the cruising
altitude range
The RHice–Tamb distribution for the contrail cirrus (SAC+,
inside the CA range) is shown in Fig. 5b, while Fig. 5d depicts that for the
cirrus mixture (SAC+, outside the CA range). In comparison to Fig. 4e,
where the frequencies of RHice in the natural cirrus (SAC-) centre
around 100 % at temperatures above 225 K (also reported in regional and
global research flight measurements by
Krämer et al. (2020), Patnaude et
al. (2021), Diao et al. (2014, 2017), and RHice observations on
board passenger aircraft by Spichtinger et al. (2004), the RHice inside the contrail cirrus (Fig. 5b) distributes most frequently around
90 % and appears almost exclusively in the temperature range Tamb=207–218 K. As mentioned in Sect. 3.2.1, this subsaturation feature is
associated with high Nice and small Rice inside the CA range (Fig. 5a), namely the contrail cirrus, as discussed in previous subsections and
shown in the Nice–Rice relations colour-coded with RHice in
Fig. S2 (see Supplement). Compared to the RHice distribution in the
contrail cirrus (Fig. 5b) and natural cirrus (Fig. 4e), the RHice
frequencies in the cirrus mixture (in Fig. 5d) are more broadly distributed
around 100 % RHice between 204 and 229 K, yet with slightly higher
frequencies between 80 and 100 % at Tamb=207–218 K, similar to
the contrail cirrus. The high RHice values up to 140 % in the cirrus
mixture are closely related to the in situ-origin cirrus (Nice<0.1 cm-3 and Rice<30µm) and
liquid-origin cirrus (IWC >10 ppmv, Rice>50µm), as seen from Fig. S2d.
Figure 5f shows that RHice in the validated contrail cirrus falls
mostly below ice saturation in the temperature range of 208–218 K,
consistent with the ice-subsaturation feature in the pure contrail cirrus
(Fig. 5b). We consider the agreement as verification of the method for
separating contrail cirrus from natural cirrus using only SAC and the CA
range.
In-cloud ice sub- and supersaturation – comparisons and causes
In Fig. 7a, we present the RHice occurrence frequencies of the
different cirrus types distinguished using the criteria of SAC, CA, and plume
detection: the contrail cirrus, validated contrail cirrus (identified using
the plume detection method), and natural cirrus. RHice in the contrail
and the validated contrail cirrus peaks at 90 % RHice, i.e., in slight
ice subsaturation, with much higher occurrence frequency than at 100 %
RHice. Furthermore, the RHice distribution in the contrail
cirrus tilts to the left – lower ice subsaturation (80 % RHice) –
while the distribution of RHice in the natural cirrus has a heavier
weight in the right part of the peak – more towards ice supersaturation
(110 %).
The slight subsaturation observed here seems to be doubtful, although
previous instrumental intercomparisons have suggested that there is no
non-negligible bias in the RHice measurements (see Sect. 2.1). However,
the possibility of a small bias in the in situ RHice dataset due to a
positive bias in the measured temperature (Tmeas) was brought up in
Schumann (2021; see p. 108), arguing that the true Tamb
might be slightly smaller than Tmeas from HALO BAHAMAS. Later in this
section, the effect of a possible positive Tmeas bias will be discussed
in relation to the observation of ice subsaturation contrail cirrus. But
first, the in-cloud RHice occurrence frequency distribution from the
WALES lidar observations (see Sect. 2.1) is plotted in Fig. 7b in comparison
to the in situ RHice of all cirrus. The RHice distribution of all
in situ-measured cirrus (the orange curve) peaks at 90 % RHice with
an occurrence frequency of ∼ 22 %, nearly overlapped with
the distribution of the lidar RHice shown in green, which is broader,
with a blunt peak around 95 % RHice (∼ 15 % of
occurrence frequency). The lidar RHice of mixed
contrail and natural cirrus spans from approximately 80 %–110 % at the full
width half maximum of the peak, the same RHice range observed in most in
situ measurements. Despite the different Tamb sources used for the in
situ RHice (from BAHAMAS)
and lidar RHice (from ECMWF) calculations, the RHice distributions
related to temperature of in situ (see Fig. 3d) and remote-sensing
measurements (see Fig. 8) in the same environment exhibit a consistent view
of RHice occurrence frequencies in the cirrus clouds in central Europe
and the northeast Atlantic flight corridor in spring 2014. The subsaturation
feature of cirrus is also evident in the temperature dependence of the lidar
RHice at cold temperatures between ∼ 215–220 K, while at
warmer temperatures above 220 K, RHice centres at around 100 %. The
good agreement between the independent in situ and lidar RHice
measurements gives confidence in the assignment of the slight
ice-subsaturation feature to contrail cirrus.
(a) Normalized RHice occurrence frequency distributions in
5 % RHice bin width for the contrail cirrus identified using the
combination of the Schmidt–Appleman criterion (SAC) and the cruising
altitude range (CA) (red), contrail cirrus validated by the plume detection
algorithm (purple), and natural cirrus not fulfilling SAC and located outside
the CA range (black). The most frequently occurring RHice in the
contrail cirrus and natural cirrus is marked by the dashed red and black
lines, respectively. (b) Normalized RHice occurrence frequency
distributions for all cirrus measured in situ (orange) and by the lidar
WALES (green).
Probability distribution of in-cloud RHice measured by the
lidar WALES below 235 K as a function of ECMWF model temperature. Only the
cloud particles producing a back-scattering ratio greater than 3 and
depolarization greater than 20 % are included in the plot. The water
saturation (Murphy and Koop, 2005), homogeneous
freezing threshold (Koop et al., 2000), and heterogeneous freezing
high (mineral dust as ice-nucleating particles) and low (coated soot)
thresholds (Krämer et al., 2016) are
added in the figure. Ice saturation is also marked by the horizontal blue
line.
However, because of the strong dependence of RHice on the temperature,
the above-mentioned effect of a positive temperature bias in Tmeas on
the RHice distribution is tested because lower temperatures enhance
RHice. The RHice frequency distribution in all cirrus clouds, at
temperatures assumed to be constantly 0.5 K colder than the current in situ
Tmeas, is shown in Fig. S3 (see Supplement). The peak of the RHice
frequency distribution shifts from 90 % to 95 % at slightly colder
temperatures, so the slight ice-subsaturation feature is still visible in
the contrail cirrus above central Europe and the northeast Atlantic region
in spring 2014.
Since finding contrail cirrus in an ice-subsaturated environment may seem
surprising, we discuss possible reasons for this in the following. During
the campaign phase in spring 2014, the background atmosphere in the
investigated region was relatively calm with slow vertical velocities mostly
below 0.2 m s-1 in frontal systems and warm conveyor belts. Why contrail
cirrus was sampled in slight ice subsaturation can be assumed from two
perspectives:
Contrails could have formed in slight ice-supersaturation in pre-existing
thin/subvisible cirrus, which have been formed heterogeneously and of which
the ice particles have grown to large sizes
(Kübbeler et al., 2011).
Marjani et al. (2022) have revealed from satellite
retrievals that the perturbation of aircraft on cirrus ice number
concentrations is located 300–540 m beneath the flight tracks, right
where the primary aircraft vortex descends after formation. The temperature
increase following this descent causes RHice to decrease to
ice subsaturation, which was observed for instance by
Gayet et al. (2012; Fig. 3h). In such cases, the
occurring cirrus would be contrail cirrus embedded in already existing,
possibly subvisible natural cirrus.
Contrails could also have formed in slightly ice-subsaturated to slightly
supersaturated environments where natural cirrus could not emerge because
the threshold humidity for heterogeneous freezing is not reached. But water
vapour in the environment together with that emitted from aircraft is
sufficient to surpass water saturation and form a contrail in the hot and
moist aircraft exhaust. Mixing of the ambient air together with the descent
to lower altitudes as described in (1) would also place the contrail cirrus
in a subsaturated environment. The question here is if the ice crystals can
grow to the observed sizes of maximum ∼ 200 µm during
their time in supersaturation. However, this would be the classic case of a
blue sky without any cirrus cloud, which turns into a grey sky covered with
contrail cirrus in the presence of air traffic.
The next obvious question regarding how long the contrail cirrus can persist
in a slightly ice-subsaturated environment will be discussed in Sect. 4.
Survey of cirrus and contrail cirrus characteristics
The 10th, 25th, 50th, 75th, and 90th percentiles of
the different characteristics of the cirrus types, detected over central Europe in spring 2014 and separated by the combined analysis of SAC, CA, and
the plume detection scheme (Sect. 2.3), are
summarized in Table 1. The median Nice, Rice, IWC, and RHice
in the contrail cirrus constrained by SAC and the CA range as well as that
contrail cirrus identified using the aircraft exhaust detection method are
correspondent, giving confidence in the new, statistically based
contrail–cirrus separation method.
The parameters determining the probable origin, optical property, and
evolution state of the clouds are the median IWC (Sect. 1), extinction
coefficient (Ext), and RHice. Ext is calculated from the empirical
formulation in Gayet et al. (2004): Deff=A×IWC/Ext, where the effective diameter Deff is in micrometres (µm), IWC is in grams per cubic metres (g m-3; calculated from IWC in ppmv using H2O molar mass,
ambient pressure, and temperature), and A=3000 mm3 g-1. The Deff is
converted from the mass mean radius Rice, assuming a ratio of 0.7 ± 0.3 between Rice and the effective radius Reff of ice
particles in contrails and contrail cirrus based on
Schumann et al. (2011). The uncertainty of the Ext is
approximately ±43 %. For contrail cirrus, found in the temperature
range 207–218 K, these are IWC = 3.5 ppmv, Ext =∼ 0.056 km-1, and RHice=88.8 %, thus classifying them as in
situ-origin, optically thin, sublimating cirrus clouds (Fig. 11a). The warm, natural cirrus (temperature range 225–235 K) is mostly
liquid-origin, thick and persisting cirrus (Fig. 11c) exhibiting
a higher median IWC = 21.7 ppmv, a larger Ext =∼ 0.137 km-1, and RHice=95.9 % close to saturation. The cirrus
mixture, with contrails embedded within in situ- and liquid-origin cirrus
(Fig. 11b), is in the intermediate temperature range of 218 to
225 K. Its median properties are IWC = 8.3 ppmv, Ext =∼ 0.096 km-1, and RHice=94.3 %; however, no clear assignment is
made here due to its mixed nature. The slightly subsaturated contrails
observed under the conditions (Rice, Nice, RHice, temperature
range shown in Table 1) would need ∼ 30 min to relax to ice
saturation after their descent is completed (assuming no vertical motion and
changes in the ice particle size negligible) (Korolev
and Mazin, 2003), while it would take slightly longer for the natural cirrus
to reach saturation.
Persistent cirrus in slight ice subsaturation – potential influence on aviation's climate impact
The slight ice-subsaturation feature of the contrail cirrus observed over
central Europe in spring 2014 agrees with the occurrence of contrails in ice
subsaturated atmosphere that was observed during the CONCERT campaign
(Kübbeler et al., 2011; Voigt et al., 2010; Gayet et al., 2012),
although contrail cirrus crystals sampled during ML-CIRRUS were much older
(Schumann et al., 2017; Voigt et al., 2017) than those young
contrails at the age of a few minutes detected during the CONCERT campaign
(Voigt et al., 2010; Chauvigné et al., 2018). A comprehensive
compilation of contrails and contrail cirrus measurements from a series of
research aircraft campaigns confirmed that the occurrence in slight
subsaturation with respect to ice is a pronounced characteristic of contrail
cirrus (Schumann et al., 2017).
Furthermore, Petzold et al. (2017) reported the observation of contrail
cirrus in slight ice subsaturation in the North Atlantic flight corridor
using RHice measurements aboard the passenger aircraft in the IAGOS
research infrastructure. In conclusion, contrail cirrus occurrence in slight
ice subsaturation is not an uncommon feature.
Percentiles of ice number concentration Nice, mass mean radius
Rice, ice water content IWC, relative humidity with respect to ice
RHice, and extinction coefficient Ext in the contrail cirrus, the
contrail cirrus validated with the aircraft plume detection algorithm, the
cirrus mixture, and the natural cirrus over central Europe and the northeast
Atlantic region in spring 2014.
1 SAC: the Schmidt–Appleman criterion, “+” fulfilling SAC, “–” not fulfilling SAC. 2 CA: the cruising altitude range, “+” inside CA, “–” outside CA. 3 Plume detection: the plume detection algorithm, “A” applied, “NA” not applied. 4 Phase relaxation time: the time for in-cloud air in ice subsaturation to reach saturation under quasi-steady conditions (Korolev and Mazin, 2003), i.e. with no vertical movement of the air parcels. 5IWC [mg m-3]: ice water content in milligrams per cubic metre (mg m-3) is converted from the IWC in parts per million per volume (ppmv) using H2O molar mass, ambient pressure, and temperature. 6 Ext: the extinction coefficient. It is calculated after the Eq. (3) in Gayet et al. (2004) with IWC in grams per cubic metre (g m-3); see the text for details. 750th perc.: the median values of the parameters (in bold), representing the average properties of different cirrus types.
Whether the contrail cirrus existing in slight ice subsaturation might
affect the radiative forcing is connected to the lifetime of ice crystals in
such environment. Therefore, we investigated the lifetime of cirrus ice
particles of the size and concentration identified for contrail cirrus in
slight ice subsaturation using the SAC–CA combination. A scenario of cirrus
cloud particles formed at Tamb<210 K was simulated using the
detailed microphysical box model MAID (Model for Aerosol and Ice Dynamics)
(Bunz et al., 2008; Rolf et al., 2012; Krämer et al., 2016). The
simulation was initialized with a water amount of 90 % RHice
(Tamb) and an ice-nucleating particle concentration of 0.1 cm-3.
The adiabatic cooling or warming rate at vertical wind speeds of 0.1 m s-1 was
added to present the constant updraughts or downdraughts in the atmosphere.
Ice crystal sublimation and sedimentation processes were not considered in
the simulation. The formation and evolution of cirrus particles in the
simulated scenario are plotted in Fig. 9. As the contrail cirrus formation
process is not implemented in the model, the cooling phase of the simulated
scenario in Fig. 9 is to produce cirrus particles that have similar
properties (Nice=0.2 cm-3 and Rice=17µm, Fig. 5a, within the 50 % contour) to the contrail cirrus separated by the
combined SAC–CA method. Driven by the
vortex dynamics, the distribution of the vertical velocity in the wake of
aircraft is distorted towards downdraughts, different from natural cirrus.
The warming phase in Fig. 9 simulates the descending of contrails to several
hundred metres below flight altitude, after their formation in primary
aircraft vortex; see Sect. 3.3. As the warming procedure reduces RHice
to below ice saturation, cirrus ice particles of similar properties to the
observed contrail cirrus gradually diminish, which takes approximately 4 h
for the ice particles to sublimate until RHice declines to below
80 %. This implies that contrail cirrus existing in a slightly
ice-subsaturated environment could survive for a long timescale, during
which it might also alter the Earth's radiation budget, similar to the
persistent contrails formed in ISSRs.
Simulated evolution of cirrus cloud particles initialized at 210 K
and 90 % RHice as a function of the simulation time in minutes. (a)
Temperature of air parcels (unit: K). (b) Ice particle number
concentration Nice (cm-3, blue) and mass radius mean Rice
(µm, black) of cirrus crystals. (c) Relative humidity with
respect to ice RHice (%).
Percentage of air masses as a function of RHice thresholds
in the upper troposphere, averaged over the North Atlantic (65–5∘ W) and Europe (5∘ W–30∘ E) regions for
the MOZAIC period from 1995 to 2010. The percentages of air masses above
90 % and 100 % RHice thresholds are labelled with the dashed red and black
lines, respectively.
Whether slightly ice-subsaturated regions are relevant for the influence of
contrail cirrus on climate depends on the frequency of the occurrence of
such regions. For this reason, we assessed the changes in air masses for a
further potential radiative impact of contrail cirrus when lowering the
threshold of contrail persistence in RHice from 100 % to 90 %.
Figure 10 summarizes the air mass percentages under different RHice
thresholds averaged over the North Atlantic and Europe for the IAGOS-MOZAIC
observational period from 1995 to 2010 (see
Petzold et al., 2020, for details). The air mass percentage of RHice≥90 % for the Europe and North Atlantic flight corridor is
approximately 43 %, increased by more than 10 % in comparison to the air
mass percentage of RHice≥100 %. Whether this finding might
lead to a larger impact of aviation on the climate is unclear, particularly
when the recent results on the relevance of strong warming contrails, the
so-called big hits (Teoh et al., 2020b; Gierens et al., 2020), are
considered.
The climate impact of aviation-induced cirrus clouds by today's knowledge is
predominantly linked to contrail cirrus in ISSRs and so is the current
recommendation for diverting the aircraft to avoid the formation of
contrails with strong radiative forcing potential (Teoh et al., 2020a,
b). It is unclear how the existence of contrail cirrus in slightly
ice-subsaturated regions could
influence the assessment of the climate impact of contrails and contrail
cirrus. However, as we have shown in our analysis,
contrail cirrus does survive several hours in such slight ice subsaturation
(90 % RHice), and there might be a non-negligible increase in
contrail cirrus coverage if considering the existence of contrail cirrus in
RHice≥90 %. Thus, we recommend considering the slightly
ice-subsaturated regions for the benefit of safe contrail avoidance during
air traffic management and a reliable estimation of the radiative forcing of
aviation-induce cloudiness.
Summary
Fresh contrails can be easily identified owing to their brightness and
linear shape. Apart from that, contrail cirrus, especially the one that has aged and turned into a thin cirrus layer, is difficult to be separated from natural cirrus to
tackle aviation-induced climate impact. In this work, a new approach to
filter out contrail cirrus from natural cirrus is developed: we combined the
Schmidt–Appleman criterion (SAC) – the fundamental thermodynamical
approach to predict contrail formation – with a new aircraft exhaust
plume detection algorithm to statistically discriminate between the contrail
and natural cirrus measured above central Europe during the ML-CIRRUS
research aircraft campaign in spring 2014.
Ice crystal number concentration Nice vs. mass mean radius
Rice colour-coded with extinction coefficient Ext (unit: km-1) of
ice particles. Ice water content (IWC) isolines in relation to Nice and
Rice are also plotted. (a) The contrail cirrus that fulfil the
Schmidt–Appleman criterion (SAC) inside the cruising altitude (CA; ambient
pressure 200–245 hPa, ambient temperature 207–218 K), also identified as
in situ-origin cirrus; median: Nice= 0.045 cm-3, Rice= 16.6 µm, IWC = 3.5 ppmv, Ext =∼ 0.056 km-1. (b) The cirrus
mixture (fulfilling SAC and outside the CA range), which is a mixture of
contrail cirrus and in situ- and liquid-origin natural cirrus; median:
Nice= 0.038 cm-3,
Rice= 24.1 µm, IWC = 8.3 ppmv, Ext =∼ 0.096 km-1. (c)
the natural cirrus of liquid-origin (not fulfilling SAC and below the CA
range); median: Nice= 0.018 cm-3, Rice= 42.4 µm, IWC = 21.7 ppmv, Ext =∼ 0.137 km-1. The 50 % (blue) contour encloses 50 % the
most frequently occurring ice crystals. The total sampling hours of each
cirrus dataset at 1 Hz sampling frequency are inserted in the lower left
corners of the figures.
Cloud particles matching SAC are presumably attributed to contrail cirrus,
while those missing SAC are treated as natural cirrus. Comparatively young
contrail cirrus was encountered most frequently in the cruising altitude
(CA) with ambient pressure ranging from 200 to 245 hPa (ambient temperature
range 207–218 K). Figure 11 summarizes the microphysical and optical
properties of the contrail and natural cirrus observed during the ML-CIRRUS.
It shows that the microphysical and optical properties of the contrail (Fig. 11a) and natural cirrus (Fig. 11c) differ markedly, with the
contrail cirrus
occurring in a much higher median number density Nice=0.045 cm-3 accompanied by a smaller mass mean radius Rice=16.6µm and mostly ice water content IWC <10 ppmv, compared to
Nice=0.018 cm-3, Rice=42.4µm, and IWC
frequently above 10 ppmv in the natural cirrus. The relatively low
extinction coefficients of the contrail cirrus (median 0.056 km-1
compared to 0.137 km-1 in the natural liquid-origin cirrus) reveal that
the observed contrail cirrus clouds were rather optically thin,
indicating aged contrail cirrus particles. Altogether, the contrail cirrus
sampled inside CA shares the characteristics of in situ-origin cirrus, in
contrast to the large and optically thicker natural cirrus of liquid origin.
Cirrus clouds outside CA (Fig. 11b) are a complex of in situ- and
liquid-origin cirrus with contrails embedded.
An important finding of this study is that the highest probability of
RHice in the contrail cirrus occurs in slight ice subsaturation,
centring at around 90 % RHice, concurring with previous studies based
on a smaller dataset of in situ measurements. The RHice distribution in
the natural cirrus agrees with the worldwide climatology compiled by
Krämer et al. (2020; Fig. 7), which
centres around ice saturation at Tamb>∼ 200 K. The existence of contrail cirrus in slightly ice subsaturated
environments seems to be surprising from the perspective of thermodynamic
equilibrium, but Krämer et al. (2020)
and Jensen et al. (2001) also reported natural cirrus under subsaturated
conditions. As predicted by a cirrus scenario simulated with the box model
MAID, contrail cirrus can persist up to over 4 h in around 90 % RHice
environment, which means that contrail cirrus likely plays a role in the
overall contrail radiative feedback provided that it appears frequently. An
estimation of the air mass percentage with RHice≥90 % in air
traffic cruise regions, based on 15 years of MOZAIC RHice measurements,
shows an increase by approximately 10 % in comparison to the air mass
percentage in the ISSRs. This suggests that we might need to lower the
RHice threshold to achieve the efficacy of contrail avoidance by
rerouting aircraft. We also call for deeper investigations into the spatial
coverage and optical depth of the contrail cirrus in slight ice-subsaturated
environments as well as the associated microphysical processes to predicate
their climate effect robustly. In turn, this will also facilitate the
mitigation of aviation's climate impact by reducing the occurrence of
contrails and contrail cirrus.
Data availability
The ML-CIRRUS dataset supporting this study is
available from the HALO database at https://halo-db.pa.op.dlr.de/mission/2
(last access: 6 December 2022) (10.17616/R39Q0T, German Aerospace Center, 2022), or
it may be provided by the authors upon request. The IAGOS data are available
through the IAGOS data portal at 10.25326/20
(Boulanger, 2021).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-23-2251-2023-supplement.
Author contributions
YL and MK designed the study. YL carried it
out and prepared the manuscript with contributions from all co-authors. CM
and UB developed and applied the plume detection algorithm to identify
cirrus particles influenced by aircraft exhaust. SR and AP analysed the
pressure levels of IAGOS-MOZAIC flights over the North Atlantic and Europe
and provided air mass fractions at different RHice thresholds in this
region observed during the IAGOS-MOZAIC period. NS prepared the particle size
distribution data for calculating the frequency of ice particle sizes. MK
performed the cirrus life cycle simulation. GD and SG provided the
RHice data from WALES. CV and US coordinated the ML-CIRRUS campaign.
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
We would like to thank Martin Zöger (DLR,
Germany) for providing BAHAMAS and SHARC data from ML-CIRRUS, Armin Afchine
(FZJ, Germany) for NIXE data, Daniel Sauer (DLR, Germany) for aerosol data,
and Helmut Ziereis (DLR, Germany) for providing NOy data. We are
grateful to Klaus Gierens (DLR, Germany) for helpful discussion.
MOZAIC/IAGOS data are created with support from the European Commission,
national agencies in Germany (BMBF), France (MESR), and the UK (NERC), and
the IAGOS member institutions (https://www.iagos.org/organisation/members/, last access: 6 December 2022).
The participating airlines (Deutsche Lufthansa, Air France, China Airlines,
Iberia, Cathay Pacific, Hawaiian Airlines, Air Namibia, Sabena, Austrian)
supported IAGOS by carrying the measurement equipment free of charge since
1994. The data are available at https://doi.org/10.25326/20 (Boulanger, 2021)
thanks to additional support from AERIS. Martina Krämer thanks JGU Mainz for support as
a GFK fellow. Christiane Voigt acknowledges the support from the Helmholtz Association and the German Research Foundation.
Financial support
This research has been supported by the Horizon 2020 (ACACIA (grant no. 875036)) and the Bundesministerium für Bildung und Forschung (grant no. 01LK1301A).The article processing charges for this open-access publication were covered by the Forschungszentrum Jülich.
Review statement
This paper was edited by Matthias Tesche and reviewed by Minghui Diao and Alexei Korolev.
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