The Asian monsoon anticyclone (AMA) represents one of the
wettest regions in the lower stratosphere (LS) and is a key contributor to
the global annual maximum in LS water vapour. While the AMA wet pool is
linked with persistent convection in the region and horizontal confinement
of the anticyclone, there remain ambiguities regarding the role of
tropopause-overshooting convection in maintaining the regional LS water
vapour maximum. This study tackles this issue using a unique set of
observations from aboard the high-altitude M55-Geophysica aircraft deployed
in Nepal in summer 2017 within the EU StratoClim project. We use a
combination of airborne measurements (water vapour, ice water, water
isotopes, cloud backscatter) together with ensemble trajectory modelling
coupled with satellite observations to characterize the processes
controlling water vapour and clouds in the confined lower stratosphere (CLS)
of the AMA. Our analysis puts in evidence the dual role of overshooting
convection, which may lead to hydration or dehydration depending on the
synoptic-scale tropopause temperatures in the AMA. We show that all of the
observed CLS water vapour enhancements are traceable to convective events
within the AMA and furthermore bear an isotopic signature of the overshooting
process. A surprising result is that the plumes of moist air with mixing
ratios nearly twice the background level can persist for weeks whilst
recirculating within the anticyclone, without being subject to irreversible
dehydration through ice settling. Our findings highlight the importance of
convection and recirculation within the AMA for the transport of water into the
stratosphere.
Introduction
Water vapour in the lower stratosphere has a direct impact on surface
climate and stratospheric ozone chemistry (e.g. Dessler et al., 2013;
Dvortsov and Solomon, 2001; Anderson et al., 2017). The variability of
global lower stratospheric water vapour is, to first order, regulated by the
minimum temperature in the tropical tropopause layer (TTL) – the main
gateway for stratospheric entry of tropospheric moisture (e.g. Fueglistaler
et al., 2009, and references therein). This way, the variation of
stratospheric water vapour follows the annual cycle of TTL temperatures
experiencing the minimum during Austral summer, when the TTL is coldest and
driest above the western Pacific region (e.g. Randel and Jensen, 2013).
During boreal summer, one of the primary contributors to the annual maximum
of lower stratospheric water vapour is the Asian monsoon (e.g. Bannister et
al., 2004; Fueglistaler and Haynes, 2005; Ueyama et al., 2018) and the
associated Asian summer monsoon anticyclone (AMA).
The AMA is one of the largest atmospheric circulation features on Earth,
owing its existence to frequent deep convection above southern Asia and the
Bay of Bengal, strong surface heating over the Tibetan Plateau, and
orographic updraughts at the southern slopes of the Himalayas (e.g. Hoskins
and Rodwell, 1995). The AMA is characterized by a persistent maximum of
water vapour extending up to 68 hPa (Park et al., 2007; Santee et al.,
2017), which makes it the wettest region in the boreal summer lower
stratosphere. Generally, this large-scale maximum is conditioned by
convective uplift of moist air in the Asian monsoon region and its
horizontal confinement within the anticyclone (Dethof et al., 1999; Ploeger
et al., 2015).
The transport of moist air into the stratosphere occurs via different
pathways: slow radiatively driven ascent (e.g. Garny and Randel, 2013), fast
convective overshooting (e.g. Fu et al., 2006), and adiabatic transport
across the horizontal boundaries of the AMA (e.g. Pan et al., 2016) into the
tropical and midlatitude stratosphere (Randel et al., 2010; Wright et al.,
2011; Dethof et al., 1999; Vogel et al., 2016; Rolf et al., 2018; Nützel et
al., 2019). The role of different transport pathways, particularly of the
convective overshooting and its predominant source regions, is subject of
ongoing debate.
A relatively small impact of overshooting convection on AMA humidity is
found by James et al. (2008), Wright et al. (2011), Randel et al. (2015) and
Zhang et al. (2016), whereas Fu et al. (2006), Ueyama et al. (2018) and
Brunamonti et al. (2018) suggest that this process can be an important
contributor to the total water in the Asian TTL. The convective impact of
different source regions (e.g. Bay of Bengal, Tibetan Plateau, southern
slopes of the Himalayas or Sichuan Basin) is also under debate (Bannister et
al., 2004; Bergman et al., 2012; Fu et al., 2006; Lelieveld et al., 2007;
Wright et al., 2011; Devasthale and Fueglistaler, 2010; James et al., 2008;
Park et al., 2007; Tissier and Legras, 2016; Legras and Bucci, 2020). In
general, there is no consensus regarding the primary convective source
regions, nor regarding the net convective effect of deep convection on the
CLS water vapour, which points out the complexity of physical processes in
the AMA system.
Notably, most of the observational evidence regarding the mechanisms
controlling AMA water is derived from passive satellite measurements, which
due to their coarse vertical resolution cannot resolve the small-scale
processes such as moistening produced by localized injections of ice. The
high-resolution measurements of water vapour within the AMA using small balloons
and research aircraft have only recently become available (Bian et al.,
2012; Gottschaldt et al., 2018; Vernier et al., 2018; Brunamonti et al.,
2018). The most extensive set of high-resolution measurements including
water vapour, ice water, water isotopic ratio, aerosols and various tracers
is provided by the StratoClim aircraft campaign, which was held in
July–August 2017 and involved the high-altitude M55-Geophysica aircraft
deployed in Kathmandu, Nepal (Stroh et al., 2022;
Krämer et al., 2020).
In this study, we combine local airborne measurements with global satellite
observations to characterize the mechanisms of convective impact on water
vapour and clouds through both mass and energy transport above the cold
point tropopause. We provide observational evidence of convectively induced
lower stratosphere hydration and dehydration of both irreversible and
reversible types. The link between the local variations and phase
transitions of water with deep convection across the Asian anticyclone is
investigated using ensemble trajectory modelling constrained by satellite
detections of convective cloud tops. Section 2 of this article describes the
experimental and modelling setup, and Sect. 3 provides the satellite view of
synoptic-scale development in the TTL during the campaign period and
presents the ensemble of airborne measurements. The convective source
regions and their AMA-wide effects on water vapour are analysed in Sect. 4.
Section 5 documents and analyses the observed processes controlling water
vapour above the tropopause and is followed by the discussion and summary
in Sect. 6.
Data and methodsStratoClim campaign and airborne instruments
The main experiment of the EU Framework Programme 7 (FP7) StratoClim project
was the deployment of the Russian high-altitude M55-Geophysica aircraft in
Kathmandu, Nepal, during July–August 2017. The campaign included eight
flights (hereinafter referred to as Fx, where x is the flight number)
performed every second day during the period 27 July–10 August in both
the morning and afternoon hours. Three of the flights were performed within
the Nepali borders, whereas in the rest of the flights the aeroplane flew out
to the southwest, south and southeast from Nepal, reaching the Bay of Bengal (see
Fig. S1 of the Supplement). The Geophysica aircraft hosted a large number of
in situ and remote sensors for measuring gaseous and particulate upper-troposphere–lower-stratosphere (UTLS)
composition. A full description of the campaign is provided by Stroh et al. (2022, same issue). In this study, we use in situ measurements of
water vapour, total water, and water isotopologues respectively by the Fluorescent Lyman-Alpha Stratospheric Hygrometer (FLASH),
Fast In situ Stratospheric Hygrometer (FISH), and Chicago Water Isotope Spectrometer (ChiWIS) instruments as well as particle backscatter measurements by
the onboard multiwavelength aerosol scattersonde (MAS) and miniature aerosol lidar (MAL).
In situ water measurements
FLASH-A (Fluorescent Lyman-Alpha Stratospheric Hygrometer for Aircraft) is
an airborne instrument of the FLASH hygrometer family designed specifically
for the M55-Geophysica aircraft (Sitnikov et al., 2007). The instrument was
redesigned in 2009 (Khaykin et al., 2013) for the RECONCILE campaign (von
Hobe et al., 2013) and substantially improved for the StratoClim experiment.
FLASH-A is mounted inside a gondola under the right wing of Geophysica and
has a rear-facing inlet, enabling water vapour measurements. With the
aspiration rate of 470 cm3 s-1, the air samples in a 90 cm3
measurement chamber are fully exchanged every 0.19 s. The chamber is
maintained at constant temperature (24 ∘C) and pressure (36 hPa).
Before a flight, the instrument is ventilated for several hours using dry
air (<1 ppmv), whereas the inlet tube, heated to 30 ∘C,
is kept sealed before the aircraft climbs to a 250 hPa level to avoid chamber
contamination by moist tropospheric air.
Unlike the previous airborne versions of FLASH-A with transverse optical
setup, the StratoClim FLASH-A rendition has a coaxial optics similar to that
of the FLASH-B balloon-borne instrument (Yushkov et al., 1998). The water
vapour mixing ratio is detected by sensing the fluorescence light yielded by
photodissociation of water molecules after their exposure to Lyman-α
radiation. A near Lyman-α line (123.6 nm) is produced by a krypton
lamp, whereas the hydroxyl fluorescence at the 300–325 nm wavelength range is
detected by a photomultiplier operating in photon-counting mode. The
accuracy of water vapour measurements in the 1–100 ppmv range is estimated at
8 %, whereas the precision of 1 Hz data in the stratosphere is 0.2 ppmv
with a detection limit of 0.1 ppmv for 5 s integration time. FLASH-A was
calibrated against a reference MBW-373L frost-point hygrometer before and
after the aircraft deployment as well as during the campaign using FISH
calibration facility. During the StratoClim campaign, FLASH-A operated in all
the eight scientific flights as well as during the transfer flight to
Kathmandu.
ChiWIS (Chicago Water Isotope Spectrometer) is an airborne implementation of
the ChiWIS-lab instrument (Sarkozy et al., 2020) designed for atmospheric
chamber measurements of water vapour and water isotopologues under UTLS
conditions, i.e. low temperature and humidity environment. The new version
of the instrument is a tunable diode laser (TDL), off-axis integrated cavity
output spectrometer (Singer et al., 2022, same issue). The
spectrometer scans absorption lines of both H2O and HDO near 2.647 µm wavelength in a single current sweep. With a 90 cm long multi-pass
cell, the effective path length amounts to more than 7 km. During the
airborne campaign, the instrument has demonstrated measurement precision for
10 s integration times of 18 ppbv and 80 pptv in H2O and HDO,
respectively. The measurements were reported at 0.2–0.5 Hz frequency
depending on the ambient mixing ratio and the desired signal-to-noise ratio.
Periods of the flights where the internal cell pressure of ChiWIS was below
30 hPa are not reported because of the large influence of vapour desorption
from the cavity walls. ChiWIS reported measurements for all the StratoClim
flights except F1 and F5.
FISH (Fast In situ Stratospheric Hygrometer) is a closed-path Lyman-α fluorescence hygrometer with a forward-facing inlet, which enables
measurement of total water (sum of gas-phase water and sublimated ice
crystals). The measurement accuracy is 6 %–8 %, whereas the
precision of 1 Hz data is estimated at 0.3 ppmv (Zöger et al., 1999;
Meyer et al., 2015). Inside the cirrus clouds, the ice water content (IWC)
is calculated by subtracting the FLASH-A gas-phase water from the total
water measured by FISH, as described by Afchine et al. (2018). The minimum
detectable IWC is 3×10-2 ppmv (∼3×10-3 mg m-3). The FISH instrument has provided measurements for flights F2,
F4, F6, F7 and F8.
The point-by-point intercomparison between FLASH-A, ChiWIS and FISH
clear-air measurements reported by Singer et al. (2022) revealed a
remarkable degree of agreement and an equally high capacity of all
hygrometers to resolve fine-scale spatial structures in UTLS water vapour.
In clear-sky periods at mixing ratios below 10 ppmv, the mean bias between
FISH and FLASH-A was -1.47 % with an r2 value of 0.930. For ChiWIS
and FLASH-A, the mean bias was -1.42 % and +0.74 % with r2 values
of 0.928 and 0.930 for clear-sky and in-cloud periods at mixing ratios below
10 ppmv, respectively. Singer et al. (2022) also found good agreement of the
airborne measurements with the collocated Microwave Limb Sounder (MLS) water vapour profiles as well
as with concomitant balloon soundings in Dhulikhel, Nepal (Brunamonti et
al., 2018), using a cryogenic frost point hygrometer (CFH) instrument.
Altogether, this provides a high degree of confidence in the StratoClim
water vapour measurement.
In situ temperature and cloud measurements
The temperature was measured by TDC (thermodynamic complex), a modified
Rosemount five-hole probe that provides an accuracy of 0.5 K and precision of
0.1 K for temperature measurements at 1 Hz frequency (Shur et al., 2007). We
used TDC measurements of temperature and pressure to convert the FLASH-A water
vapour mixing ratio into relative humidity over ice (RHi) as well as to
compute the saturation mixing ratio using the saturation vapour pressure
equation by Murphy and Koop (2005). The accuracy of TDC measurements is
discussed by Singer et al. (2022) and Stroh et al. (2022).
NIXE-CAPS (New Ice eXpEriment: Cloud and Aerosol Particle Spectrometer) is
mounted under the right wing of a Geophysica aircraft and measures the cloud particle
number size distributions in the size range of 3–930 µm diameter at
a time resolution of 1 Hz (Meyer, 2012). The IWC values derived from particle size
distributions are found to be in good agreement with those derived from FISH
total water measurements (Afchine et al., 2018). The lower detection limit
of the instrument is 0.05 ppmv (≈0.005 mg m-3). NIXE-CAPS
provided measurements in all the flights.
In situ measurements of cloud/aerosol backscatter and with a time constant
of 10 s were provided by the forward-looking backscatter probe MAS
(multiwavelength aerosol scattersonde) described by Buontempo et al. (2006).
To distinguish between clear-sky and in-cloud measurements, here we use a
threshold of 1.2 units of backscatter ratio at 532 nm together with a
2.5 % threshold in the volume depolarization (corresponding to particle
depolarization of 8 %–10 %). MAS instruments operated in all the flights
except F1, for which we used NIXE-CAPS data (Afchine et al., 2018) to detect
the clouds. Singer et al. (2022) showed good agreement between the cloud
detections by both of these instruments.
Remote measurements of cloud backscatter below and above the aircraft were
conducted by miniature aerosol lidar (MAL) (Mitev et al., 2002). Backscatter
ratios at 532 nm are derived after applying a noise filter, range correction
and correction for incomplete overlap in the near range, allowing
observations as close as 40 m from the aircraft.
Satellite observations
The Microwave Limb Sounder (MLS) instrument, operating aboard the NASA Aura
satellite, measures various chemical species and temperature and provides
over 3500 vertical profiles per day between 82∘ S and 82∘ N. Here we use the version 4.2 water vapour profiles described by Livesey et al. (2017), who report for the lower to middle stratosphere a vertical
resolution of 3.0–3.1 km, horizontal resolution of 190–198 km and an
accuracy of 8 %–9 %. The data screening criteria specified by Livesey et al. (2017) have been applied to the data. To interpolate the water vapour
profiles onto a common potential temperature grid, we use the MLS
temperature product provided at the same pressure levels.
Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is a primary
instrument aboard the CALIPSO satellite, operational since 2006 (Winker et
al., 2009) and providing backscatter coefficients at 532 and 1064 nm with a
vertical resolution of 60 m and horizontal resolution of 1000 m in the UTLS.
Here we use the CALIOP 532 nm level 1B version 4.0 product for diagnosing the
cloud vertical cross sections and for quantifying the cloud top altitude. To
enhance the sampling of clouds, we also use level 1 backscatter product at
1064 nm provided by NASA's Cloud-Aerosol Transport System (CATS) lidar
operating aboard the International Space Station (Yorks et al., 2016). The CATS
1064 nm backscatter is converted to 532 nm using the CALIOP colour ratio.
The GPS radio occultation (RO) technique provides vertical profiles of
atmospheric variables with high vertical resolution (∼0.5 km
around the tropopause), global geographical and full diurnal coverage, and
high accuracy (<1 K) (Steiner et al., 1999). We use RO dry
temperature profiles from COSMIC (Anthes et al., 2008), GRACE (Beyerle et
al., 2005), and Metop A/B missions (Luntama et al., 2008) for analysing the
temperature and minimum saturation mixing ratio within the AMA during July and
August 2017.
Definitions
In this section, we define the key terms regarding the vertical structure of
AMA and physical processes therein.
The vertical boundaries of the tropical tropopause transition layer (TTL) can be defined using two different
approaches reviewed by Pan et al. (2014). The mass-flux approach
(Fueglistaler et al., 2009) defines the lower boundary as the
tropically averaged level of all-sky zero net radiative heating (14 km, 355 K) and the upper boundary as 18.5 km (425 K), where the local mass flux
becomes comparable to that of the Brewer–Dobson circulation (Fu et al.,
2006). Another approach is based on the TTL thermal structure, where the lower and upper boundaries are defined respectively as the level of minimum stability and the cold point tropopause (CPT) (Gettelman and de F. Forster, 2002). Pan et al. (2014) found that the thermally defined TTL boundaries are
consistent with those derived from the ozone–water-vapour relationship. In
this study, we adopt the thermal definition of the TTL as in this case the
boundaries can be derived from the local instantaneous measurements provided
by the Geophysica aircraft.
Since the location of the Geophysica deployment is not tropical in the
geographical sense, we refer to the TTL in this region as the Asian tropopause transition layer (ATTL) with an upper
boundary at the CPT derived from ERA5 temperature profiles collocated with
the flight tracks and using airborne temperature profiles. Following
Brunamonti et al. (2018), we refer to the upper layer of the Asian
anticyclone as the confined lower stratosphere (CLS) with a lower boundary at
the CPT level and an upper boundary corresponding to the top level of
confinement, which they estimate as 63.5 hPa (∼440 K) for the
2017 AMA season.
A convective overshoot (also termed “ice geyser” by Khaykin et al., 2009) is defined as
detrainment of ice crystals above the local CPT (Danielsen, 1993). Depending
on the relative humidity at the level of detrainment, this process can lead
either to CLS moistening by rapid ice sublimation or to irreversible
dehydration via uptake of vapour by the injected ice crystals, their growth
and sedimentation (e.g. Jensen et al., 2007; Schoeberl et al., 2018). The
clouds that have formed in the CLS as a result of local cooling are termed
in situ cirrus. An in situ cirrus cloud is not to be confused with the above anvil cirrus plume (AACP), which is a plume of ice and water vapour in the LS that occurs
in the lee of overshooting convection (Homeyer et al., 2017; O'Neill et al.,
2021). A secondary cloud refers to an in situ cirrus that has nucleated from an air mass enhanced
in water vapour as a result of convective overshoot.
Ensemble trajectory modelling and convective cloud top data
For investigating the link between the variations in water vapour observed
locally by the Geophysica aircraft and the deep convection upwind detected using
satellite IR imagery, we use the TRACZILLA Lagrangian model (Pisso and
Legras, 2008), a modified version of FLEXPART (Stohl et al., 2005). The
simulation was designed to release an ensemble of 1000 back trajectories
every second along the aircraft flight path, travelling back in time for 30 d. The calculation of back trajectories was performed using the European
Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis horizontal
winds and diabatic heating rates provided at hourly frequency and 31 km
horizontal resolution.
For detection of convective cloud encounters (convective hits) along the
diffusive back trajectories, we use cloud top information from geostationary
satellites (MSG1 and Himawari-8). To cover the entire AMA region, we make
use of the cloud top product from both the MSG1 images for longitudes west
of 90∘ E and the Himawari-8 images for longitudes east of
90∘ E. The MSG1 satellite operated by EUMETSAT carries the
Spinning Enhanced Visible and Infrared Imager (SEVIRI), providing
multi-wavelength image collection with spatial resolution of 1–3 km and
temporal resolution of 15 min (Schmetz et al., 2002). The Himawari-8
geostationary satellite, launched by the Japan Meteorological Agency (JMA),
carries the Advanced Himawari Imager (AHI), providing the images at 0.5–2 km spatial resolution with 10 min intervals (Bessho et al., 2016). For
computational reasons, we use one image every 20 min.
The cloud top height data were taken from the European Organisation for the
Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application
Facility (SAF) on Support to Nowcasting and Very Short Range Forecasting
(NWC) products (Schulz et al., 2009; Derrien et al., 2010; Sèze et al.,
2015). The analysis was restricted to the highest and opaque cloud classes
that are representative of deep convection. In this study, we consider the
convective hits above 100 hPa only, corresponding to the cloud tops
potentially overshooting the tropopause. They constitute 24.3 % of the
total number of convective hits identified by this analysis. The convective
origin of the sampled parcels is statistically diagnosed in terms of the
fraction of convective hits per 1 s sample as well as the convective age of
parcel, i.e. the time since convective hit.
It should be noted that the trajectory model integrates 1000 backward trajectories per data point along the flight track, whereas the parcels' vertical diffusion is represented by a random noise equivalent to a diffusion D=0.1 m2 s-1 as
in Bucci et al. (2020). As such, the integration is a discretization of the
adjoint equation of the advective diffusive equation, which is well posed
for backward integration (Legras et al., 2005). Unlike single-trajectory
Lagrangian calculations, this method does not generate spurious small-scale
features as backward time increases and can be shown to converge with time
for a pure passive scalar. With that, the trajectories from each data point
come from several, possibly many, sources, and the results presented are a
statistics over these 1000 trajectories.
Obviously, the results can be affected by biases in the wind field, heating
rates and the cloud height product used in this study. The ERA5 is presently
considered as the most advanced reanalysis, and it was shown to display very
consistent transport properties of diabatic versus kinematic trajectories
(Legras and Bucci, 2020), which are in excellent agreement with
observations (Brunamonti et al., 2018; von Hobe et al., 2021). The main
concern in the Asian monsoon region is that ERA5 displays high penetrative
convection over the Tibetan Plateau, which might bias the heating rates in
the upper TTL over this region (SPARC, 2022). As the
trajectories involved in this studied are mostly outside the plateau, we do
not expect any significant impact.
Evolution of AMA conditions: two modesSatellite perspective
The 2017 Asian monsoon season was not marked by an anomalous dynamical
behaviour (Manney et al., 2021); however, the campaign occurred during a break-to-active transition. The strongest convective activity took place in late July and early August above the southern slopes of the Himalayas and the Tibetan Plateau, as can be inferred from the low outgoing longwave radiation (OLR)
displayed as dashed contours in Fig. 1a. The OLR distribution in July–August 2017 is very similar to its climatological pattern reported by Randel et al. (2015) (see their Fig. 5). The thermal conditions across the Asian TTL
(ATTL) exhibit a remarkable variability with minimum saturation mixing
ratios between 14–18 ppmv in the warmer northern part of the AMA and 2 ppmv
above the colder southern slopes where the Geophysica flights took place.
The horizontal distribution of CLS water vapour (390–420 K layer) averaged
over 3 weeks before and during the Geophysica flights (Fig. 1b) reveals a
pool of moist air with two maxima near the centre of the anticyclone.
Overview and evolution of AMA UTLS conditions during July–August 2017 from satellite observations. (a) Colour map shows the GPS-RO minimum
saturation mixing ratio (ppmv) encountered within the 360–420 K layer during the
20 July–10 August period. Dashed contours indicate National Centers for Environmental Prediction (NCEP) OLR (W m-2) in the
range 190–210 W m-2 (contour interval 10 W m-2). Green arrows are wind
velocity vectors (ERA5, 70–100 hPa average for the campaign period). Pink
pixels mark the most probable sources of the hydrated features (see Sect. 4.2). White rectangle indicates the flight domain. (b) Horizontal
distribution of MLS water vapour in the confined LS (390–420 K layer)
averaged over the 20 July–10 August period with the date-coloured flight
tracks superimposed (see Fig. 2 for colour definition). Dashed contours
depict the Montgomery stream function (m-2 s-2), which is used to
define the horizontal boundaries of the AMA at 390–410 K levels (Santee et
al., 2016). (c) Evolution of the GPS-RO minimum saturation mixing ratio profile
within the flight domain (20–30∘ N, 78–92∘ E). Green curve plotted versus right-hand axis depicts the domain-mean OLR. (d) Evolution of the MLS water vapour profile within the flight domain. The solid black curve depicts the maximum level of cloud tops detected using CALIOP and CATS satellite lidars. The red curve
indicates MLS carbon monoxide (68–100 hPa mean). The vertical dashed
lines indicate the flight dates (flight number is given as Fx) and their
vertical extent, and the dashed curve marks the average CPT potential
temperature level (GPS-RO) in both panels (c) and (d).
The time evolution of temperature in terms of the H2O saturation mixing
ratio (Fig. 1c) and water vapour (Fig. 1d) within the flight domain shows an
interesting development of the UTLS conditions before and during the
campaign period. In mid-July, a humid layer in the ATTL starts to build up
and propagates above CPT up to about 410 K by early August. The first four
Geophysica flights were conducted during this moisture build-up period,
characterized by relatively warm CPT temperatures (Fig. 1c), which we term the
“warm/wet” mode. It should be noted that the 2017 AMA season was marked by
a strong positive anomaly in water vapour ranging from 1 to 2 ppmv but
without a significant tropopause temperature anomaly (Fig. S2 in the Supplement). The positive water vapour anomaly is not specific to the AMA region and
reflects the global wet anomaly in the tropics and subtropics, as revealed
by MLS observations (not shown).
(a) Water vapour mixing ratio profiles taken by FLASH hygrometer.
The flight dates are shown in the legend. The dashed rectangle marks the CPT
vertical range. The white solid and dashed lines depict the mean water
vapour profile for the warm/wet and cold/dry modes respectively (see Fig. 1c, d). (b) Saturation mixing ratio profiles computed from TDC measurements
of temperature and pressure. The horizontal dashed lines in both panels mark
the vertical range of CPT level encountered during the campaign. Note the
strong variability of water vapour at the CPT level and accumulation of
sharp enhancements in the lower stratosphere.
In early August, after the warm/wet mode period, the ATTL experienced a
rapid cooling, and the last four flights sampled a colder and drier ATTL.
This “cold/dry” mode is marked by stronger convective activity in the
region reflected by low OLR (Fig. 1c), i.e. colder and higher cloud tops,
and a higher carbon monoxide mixing ratio (Fig. 1d). Since the carbon monoxide
is a tracer for troposphere-to-stratosphere transport, the elevated CO
concentration in the LS is indicative of the enhanced upward flux across the
tropopause (e.g. Randel et al., 2010). The cold/dry mode period is also
marked by a widespread occurrence of ice clouds above the CPT (377–390 K)
and as high as the 415 K level according to high-resolution cloud profiling by
CALIOP and CATS satellite lidars (Fig. 1d). We note that the cold convective
period had a transient effect on the CLS water vapour, which mostly recovers
the late July values, after the cessation of convective activity and tropopause
warming in the flight domain by mid-August. A similar inference was reported
by Brunamonti et al. (2018) on the basis of balloon soundings in Nepal
during the airborne campaign in July–August 2017.
Airborne perspective
The airborne measurements of water vapour and temperature shown in Fig. 2
reflect the satellite-derived development of the UTLS conditions. The
ensemble of water vapour profiles obtained using the FLASH hygrometer during
the eight StratoClim flights is shown in Fig. 2a. The H2O vertical
profiles at and above the CPT level show a remarkable variability over the
2-week campaign period with mixing ratios ranging from 2.8 to 10.2 ppmv.
On average, the warm/wet mode yielded an L-shaped mean H2O profile
(solid curve), which is characteristic of the boreal subtropical conditions,
although with notable enhancements at and above the CPT. In contrast, the
cold convective period revealed the vertical distribution more typical for
the tropical tropopause conditions, with the hygropause at the CPT level.
The airborne measurements during both synoptic periods show an accumulation
of sharp moist layers above the CPT and up to the 410 K level which are
diagnosed in the following section. These layers constitute the CLS wet pool
seen by MLS, although their sharp vertical structures of sub-kilometre scale
cannot be resolved by the satellite.
The large variability of water vapour is consistent with the tropopause
temperature variability, showing a minimum saturation mixing ratio between 2.5
and 6.5 ppm and highly variable CPT vertical structure (Fig. 2b), presumably
modulated by gravity waves. The CPT potential temperature varied between 370–391 K, which is fully consistent with the GPS-RO data.
The highly variable thermal conditions led to a remarkable dispersion of RHi
around the CPT. The clear-sky measurements reveal both a subsaturated and
strongly supersaturated environment with RHi spanning 40 %–175 % (Fig. 3a). The credibility of RHi data is ensured by an excellent agreement across
the three airborne hygrometers and temperature sensors
(Singer et al., 2022). In the presence of ice crystals (Fig. 3b), the RHi is
generally well above 100 % although the subsaturated cloud occurrences
were also observed in both dry and wet parts of the water vapour spectrum.
Such occurrences are mainly caused by short excursions of temperature above
the frost point, which does not necessarily lead to permanent evaporation
and depends on the air parcel's (Lagrangian) temperature history. The
occurrence of ice crystals was recorded at levels 15 K (∼1 km) above the local CPT. The highest-level clouds were detected by the
upward-looking MAL at 412 K (18.5 km), which is consistent with
NIXE-CAPS detection of cloud particles up to 415 K (Krämer et al., 2020,
their Fig. 11) as well as with the maximum cloud altitudes inferred from
satellite lidars (415 K). The presence of ice in supersaturated air is more
specific to the cold dry parcels (see also Krämer et al., 2020, their
Fig. 10d), which suggests a local dehydration during the cold/dry period.
(a, b) Binned distribution of maximum RHi (computed from
FLASH and TDC measurements) as a function of FLASH water vapour and
potential temperature relative to the local CPT level (bin size 0.1 ppmv by
1 K) for (a) clear-sky conditions and (b) cloud occurrence detected by MAS
(see Sect. 2.1.2). (c) Binned distribution of ice water content (IWC)
exceeding 0.1 ppmv from NIXE-CAPS instrument inside clouds detected by MAS
as a function of relative humidity over ice (RHi) and potential temperature
relative to the local CPT level. The presence of ice crystals in
subsaturated air (RHi < 100 %) above the cold point tropopause
potentially leads to permanent hydration of the CLS, whereas in
supersaturated air the ice crystals are expected to sediment out of the CLS,
thereby leading to its dehydration.
A different perspective on the environmental conditions of cloud occurrence
around the CPT is provided in Fig. 3c, showing the distribution of IWC as a
function of RHi. The binned ensemble is restricted to the samples, for which
both MAS and NIXE-CAPS data indicate the presence of ice particles. The ice
crystals found in the subsaturated air above the local CPT are likely to be
in the process of sublimation and therefore have a potential for a permanent
CLS hydration. Conversely, the crystals in the supersaturated environment
will retain their aggregate state and the largest ones (characterized by
higher IWC) will sediment down below the tropopause, thereby causing
permanent dehydration of the CLS. We note that the ice particles in the
subsaturated environment account for 14 % of the particles detected above
the local CPT. This is consistent with a comprehensive analysis of airborne
data from various campaigns by Krämer et al. (2020), who pointed out
significantly larger amounts of IWC in subsaturated ice crystals above the
CPT in the AMA compared to that in the surrounding tropical regions, which
underlines the importance of the AMA as the source of LS water.
Convective influence on CLS water vapour
The influence of overshooting convection on the observed water vapour
variability was investigated using TRACZILLA ensemble trajectory modelling
constrained by satellite cloud imaging and ERA5 reanalysis (see Sect. 2.4).
Figure 4a displays a binned ensemble of the measured water vapour mixing
ratios colour-coded by the convective hits fraction. The trajectory analysis
suggests that the convective origin is characteristic to anomalously wet and
anomalously dry parcels, which points out the dual role of overshooting
convection on the AMA water vapour, i.e. hydration/dehydration. The link to
overshooting convection is particularly obvious for a strong water vapour
enhancement peaking at the 399 K level, which corresponds to F2 of the warm/wet
mode (see Sect. 5.1 for detailed analysis of this flight), and for a smaller
enhancement at 403 K, corresponding to F7 (see Sect. 5.2). The results for
the individual flights are provided in Fig. S3. The
hydrated features (layers of enhanced water vapour, exceeding 1-σ of
the campaign ensemble) are denoted throughout the article as Ax or Bx, where x is
the flight number.
The elevated convective hits fraction is also characteristic to the driest
bins between 370–400 K, corresponding to F8 of the cold/dry mode with
large-scale convection in the flight domain. While the driest parcels are
linked with the local or nearby convective events, the wettest ones are
traced back to distant convective events all along the circulation pattern
of the anticyclone, which occurred several days before their outflows were sampled by the Geophysica aircraft. The only exception is F6, which was influenced
by a young outflow of a large convective system in the vicinity of the
flight (see Sect. 4.2 and Fig. S4).
Binned ensemble (bin size 0.1 ppmv by 1 K) of FLASH H2O
measurements from all flights except F1 and F5 for which no isotopic data
are available. The pixels are colour-coded by (a) convective hits fraction
(see text for details) and (b) the ChiWIS HDO/H2O isotopic ratio. The black solid and dashed curves depict campaign-median H2O profile and 1 standard deviation respectively (all flights). The horizontal dashed lines mark the
vertical range of the CPT level encountered during the campaign. Note that the
convective origin is specific to both anomalously wet and anomalously dry
parcels (a), whereas the wettest parcels in the lower stratosphere are
isotopically enhanced (b).
Isotopic composition of convective plumes
The relation of moist layers with overshooting convection can be reliably
diagnosed using the isotopic ratio of water (HDO/H2O), which is
enhanced for water vapour molecules sublimated from ice (Moyer et al., 1996;
Hanisco et al., 2007). Figure 4b clearly shows that the wetter parcels in
the lower stratosphere are isotopically enhanced, and the wettest of them
bear the strongest isotopic signature. This unambiguously points out that
the hydrated layers have been produced by overshooting ice geysers.
Remarkably, the wet and isotopically enhanced pixels in Fig. 4b are found as
high as the 420 K level, which is 30–50 K above the cold point. Given the
diabatic heating rate of 1.1 K d-1 in the AMA and the average recirculation time
of 16 d within the anticyclone (Legras and Bucci, 2020), these hydrated
parcels could, in principle, have recirculated twice before being sampled by
the aircraft.
Geographical distribution of convective sources
Figure 5 shows the composite map of convective clouds (highest cloud
classes), which are linked by trajectories with the observed hydrated and
isotopically enhanced wet-and-heavy parcels and thereby represent the
most probable sources of the convectively processed CLS air sampled by the
aircraft. The wet-and-heavy parcels are defined as those located above the
local CPT with water mixing ratios exceeding 1 standard deviation from the
median (dashed curve in Fig. 4b) at a given potential temperature level and
with isotopic ratios above -400 ‰ (except for F1 and F5 where the HDO
measurements are not available and the selection is done based on H2O
only). The fraction of wet-and-heavy parcels to all parcels sampled above
the local CPT varies from 0.5 % (F6) to 11 % (F2) between the different
flights. No wet-and-heavy parcels have been detected in F8, which is why it
is not displayed in Fig. 5.
Composite map of convective clouds (highest cloud class) linked
by back trajectories with the observed hydrated (wet-and-heavy) parcels. The
colour of convective systems indicates the flight number (Fx; see legend) in
which the respective parcels were sampled. The same colour code is used to
mark the flight segments where these parcels were probed. The convective age
(days) is indicated for each convective system. The convective sources for
the features of interest in flight F2 (A2, B2, C2*) and F7 (A7, B7) are
annotated (see Sect. 5). The arrows are wind velocity vectors (ERA5, 70–100 hPa average).
The composite map suggests a broad geographical scatter of the convective
clouds across the Asian anticyclone. The lifetime of hydrated parcels, as
inferred from the back trajectories, ranges from ∼12 h
(F6) to about 12.7 d (F7) (see Fig. S4 for convective age
in individual flights). The wet-and-heavy parcels sampled during the
warm/wet mode (F1 through F4) originate from various convective systems in
northeastern China and the Korean Peninsula, all of them occurring north of
35∘ N. The convective age for these parcels varies between 2.6 and 9.9 d.
Sensibly, the shortest age corresponds to the lower-height moist layer at
the 390 K level (F2), whereas the longest age is found for the wet-and-heavy
parcels detected as high as at 410 K in F4. The moist features in the flight
F2 (A2 and B2; see Sect. 5), found at 390 and 399 K levels, are sourced to
different convective events that occurred 2.6 and 4.7 d before being
sampled by the Geophysica aircraft. We note that while the 1σ error of the age
estimates is generally less than an hour, the attribution of convective
sources largely depends on the cloud top data. In particular, the improved
v2018.1 trajectory product coupled with NWC SAF geostationary data analysis provided a qualitatively better correlation between the distribution of
convective hits and wet-and-heavy parcels as compared with the product used
by Bucci et al. (2020).
While the warm/wet mode flights were largely influenced by convection in the
northeastern part of the AMA, the wet-and-heavy parcels sampled during flights
F5–F7 are sourced to various different locations. A large convective
system over northeastern India in the vicinity of the flight on the same
day is responsible for the hydration feature in F6 at the 380 K level. The
convective source of the wet air sampled by F5 is found above western India,
although we note that no isotopic data are available for this flight,
whereas the number of parcels with a mixing ratio exceeding 1 standard
deviation is small for this flight. In flight F7, the enhanced water vapour
features above 400 K (A7 and B7; see Sect. 5) originate from two different
sources: the lower-level feature (A7) is traced back to a group of
relatively small systems along the eastern Chinese coast that occurred 3.9 d before the measurement, whereas the upper one (B7) originates from a
large cluster of small-scale convective systems in the centre of the Asian
anticyclone above the northern foothills of the Himalayas. We note that this
particular region is marked by enhanced water vapour amount according to MLS
averages over the campaign period (cf. Fig. 1b). The B7 parcels have thus
followed the anticyclonic circulation path for nearly a full loop before
arriving to the flight domain, which took 12.7 d.
Results of F2 measurements (29 July) with the features of interest
marked A2, B2 and C2. (a) Water vapour profile (FLASH) colour-coded by
convective hits density (see text for details). (b) Same as panel (a) but colour-coded by the ChiWIS HDO/H2O isotopic ratio. The black solid and
dashed curves depict the campaign-median H2O profile and 2 standard
deviations respectively. (c) Time series of flight altitude (black curve),
water vapour (colour-coded by convective hits density) and RHi (right-hand
axis) computed from FLASH and TDC measurements. The colour map shows
the scattering ratio measured by MAL (upward-looking).
The potential for a vapour-rich parcel travelling within the AMA CLS to
permanently hydrate the stratosphere is determined by the Lagrangian
temperature history. We did not analyse the RHi variation along the
trajectories; however, we quantified the minimum temperatures encountered
across AMA using high-resolution GPS-RO profiling. As follows from Fig. 1a,
the subtropical part of the AMA has never cooled below the H2O saturation
mixing ratios of around 8 ppmv in July–August 2017, enabling the vapour-rich
patches to travel along the northern flank of the anticyclone without
freezing. Remarkably, the majority of convective systems identified as the
most probable sources of wet-and-heavy parcels (shown in Fig. 5 and marked
by black pixels in Fig. 1a) have occurred within the warm tropopause
environment in the northern subtropical part of AMA.
It is noteworthy that the probed wet-and-heavy parcels (shown along the
flight tracks in Fig. 5) are all located in the northernmost part of the
flight domain, i.e. nearer the centre of the AMA. This is consistent with the
spatial distribution of AMA CLS water vapour inferred from MLS (Fig. 1b),
showing the maxima above the Tibetan Plateau and Sichuan region, which is
around the centre of the anticyclone. With that, the air circulating near
the outer edge of the anticyclone is bound to pass the colder TTL above
central India and the southern slopes, where the organized large-scale
convection occurring during the second part of the campaign (cf. Fig. 1) has
led to cooling and dehydration around the CPT level. The efficiency of the
convectively induced dehydration, counteracting with the convective
moistening in the warmer TTL regions of the AMA, is considered on a case-by-case
basis in the next section.
Long-range transport and evolution of moist convective plumes
The hydrated layers in the CLS characteristic of elevated convective hits
fraction and/or isotopic enhancement (wet-and-heavy) were detected at
altitudes between 16.9–19.0 km (380–415 K) in all the flights except
F8, with the magnitude of water vapour mixing ratio enhancement between 0.9–5 ppmv (see Fig. S3). The largest enhancement (5 ppmv) was
observed in F2 at 399 K (B2 feature), whereas the highest altitude of
hydrated layer centred at 18.9 km (411 K) was sampled in F7 (B7 feature).
The flights F2 and F7 represent respectively warm/wet and cold/dry modes
(see Sect. 3); however, in both of these flights the observed moist layers
originated from distant convective events. In this section, we provide
further insight into the results of F2 and F7 and describe the evolution of
the respective moist convective plumes using airborne and satellite
measurements.
Warm and wet mode: flight F2
During the warm/wet mode period, the mean CPT-level water vapour mixing
ratio was 7.2 ppmv, whereas the minimum saturation mixing ratio ranged from
5.5 to 6.9 ppmv, according to the airborne data (Fig. 2). During F2, the
aircraft was cruising side to side along the Himalayan foothills within
Nepali borders, gaining altitude in 500 m steps before climbing to 21 km
(Fig. 6c). The water vapour vertical profile in Fig. 6a and b reveals two
layers above the CPT (marked A2 and B2) with the water mixing ratio peaking at
10.2 ppmv, twice the campaign-median value at the CPT level. It should be
noted that all the three airborne hygrometers report identical spatial
structures and absolute values of humidity for these layers, providing full
confidence in this observation (see Fig. 3 in Singer et al., 2022).
The upper layer (B2) topping at 399 K (∼18 km) is
characterized by a very large fraction of convective hits reaching 0.9 (Fig. 6a) with an average age of 4.7 d (cf. Fig. 5). The convective origin of
B2 is unambiguously confirmed by a strong enhancement in the HDO/H2O
ratio of -340 ‰. This is substantially higher than the isotopic ratio
found for the equivalent-humidity air below the CPT (about -480 ‰ at
the 373 K level). The enhanced isotopic ratio in this layer clearly indicates
that the water vapour enhancement was produced by sublimation of ice. It is
remarkable that after nearly 5 d, the convective plume responsible for B2
feature has retained such an amount of moisture.
The underlying wet layer (A2) at ∼390 K (∼17.5 km) is traced back to a different convective event ageing 2.4 d (cf. Fig. 5). However, given that the magnitude of enhancement is nearly the same as
that of its upper-level twin, it is conceivable that both A2 and B2
represent the outflow of the same convective event in northeastern China,
and the lower-level A2 feature is a result of gravitational settling of ice
crystals shortly after injection.
Secondary cloud formation
For an air parcel at 82 hPa bearing 10 ppmv of water vapour (as reported for
B2), the saturation is achieved at -78.5∘C. The B2 feature was
characterized by the maximum RHi of 116 % (Fig. 6c) at -79∘C.
At these conditions, a local cooling of 2 ∘C, which can be
produced by a gravity wave (e.g. Kim and Alexander, 2015), would boost the
RHi to 165 %. This corresponds to the homogeneous freezing threshold at
this temperature; hence, such a cooling would almost certainly lead to
formation of a secondary cloud. Such a cloud was detected by the upward-looking MAL at 18–18.5 km (398–412 K) in F2 with the maximum
scattering ratio of 8.1 (marked C2 in Fig. 6c).
Interestingly, the bottom of this cloud is found at the same potential
temperature level as the hydrated layer B2 and only about 350 km away from
it. Nevertheless, these features appear to have different convective
sources. Figure 7a shows the back trajectories released from this cloud
intersecting a large convective system above northeast China (as indicated
by red circles with black filling) on 21 July, which is 8 d before F2. The
fraction of trajectories intersecting this convective system amounts to
47 %. In an attempt to investigate the evolution of humidity of this air
mass, we searched for the MLS swaths collocated in space and time (within
500 km and 1 h) with the tracked parcels. A perfect match was found on 24 July: the MLS swath lies precisely across the cluster of the tracked parcels
as shown in Fig. 7b. The nearest MLS profile reports 8 ppmv at the parcel
level, which is 2–3 ppmv wetter than the neighbouring measurements along
the same orbit. This suggests that the moist plume remained compact (at
least in the meridional plane) up to 3 d after the convective event.
Trajectory analysis of the secondary cloud (C2) detected in F2 (29 July). (a) Back trajectories (green curves) and convective hits locations
(black-filled red circles) superimposed onto the infrared brightness temperature (IR BT) at the time of
convective hits (cf. time stamp in the panel). (b) Same as panel (a) but for the time of the MLS sampling of the moist plume. The spatiotemporally collocated
MLS swath is displayed as markers colour-coded by the H2O mixing ratio at the 393 K level. The wettest MLS measurement coincides with the location of hydrated
parcels. (c) Relative humidity over ice evolution along the back
trajectories with colour coding by potential temperature computed from ERA5
temperature and assumed H2O mixing ratio of 12 ppmv (see text for
details). The black markers show the locations of convective hits, and the
vertical dashed line indicates the time of MLS sampling of the moist plume on
24 July.
The Lagrangian temperature history of this air mass (Fig. 7c) suggests that
since the convective encounter, the parcels remained subsaturated most of
the time and, in particular, during the collocated measurement by MLS. The
RHi was estimated from the ERA5 temperature and pressure along the back
trajectories, whereas the mixing ratio was assumed to be constant at 12 ppmv.
The episodes of moderate supersaturation with RHi reaching 140 % were
encountered between about 144 and 170 h before the sampling, and it is
conceivable that cirrus could have formed around that time, with some water
lost to sedimentation. However, the episodes of strong supersaturation
with RHi reaching the homogeneous freezing threshold were encountered only
during the last day before the measurement, when the parcels were entering
the colder CLS above the southern slopes. The RHi along the back
trajectories during the last day reached 160 %, which would enable
ice nucleation and repartitioning of the excessive vapour into a secondary
cloud.
Cold and dry mode: flight F7
The cold/dry mode was marked by a synoptic-scale cooling throughout the 370–400 K layer extending across the CPT. The largest vertical extent of the
cold layer was observed in F7, where the saturation mixing ratio dropped
below 4 ppmv throughout the 370–397 K layer (cf. Fig. 2b). The northbound
flight leg of F7 (see flight track in Fig. S1) included
several porpoises across the CPT level (varying between 375–383 K) as
shown in Fig. 8a. The time series of potential temperature is marked with
ice particle occurrence detected by MAS, which shows the presence of
subvisible cirrus clouds (colour tagging) with a scattering ratio below 6
extending up to the 400 K level.
Results of F7 measurements (8 August) with the features of
interest marked A7 and B7. (a) Time series of potential temperature
θ (left-hand axis) and water vapour/total water (right-hand axis).
The θ time series is tagged by cloud occurrence and colour-coded by
the scattering ratio. The IWC is shown as cyan shading stacked on the water
vapour curve, and the darker cyan curve depicts the total water (right-hand
axis). The dashed magenta line depicts the saturation mixing ratio
(right-hand axis). The CPT level displayed as the black dashed line is inferred
from airborne measurements. (b) Vertical profiles of water vapour (black
circles), total water (cyan) and IWC (cyan shading). The red dashed curve
indicates the mean water vapour profile from the previous flights (F1–F6).
(c) Binned water vapour profile with pixels colour-coded by the HDO/H2O isotopic ratio. The black solid curve depicts the campaign-median H2O profile, and the dotted curves represent 2 standard deviations respectively.
The water vapour time series in Fig. 8a reveals a remarkably large
horizontal variation of mixing ratio in this layer, spanning 3.0 to 6.2 ppmv
on a horizontal scale of 100 km. Almost the entire
CPT-porpoising segment of F7 shown in Fig. 8a (20 000–22 200 s) is
supersaturated with RHi reaching 155 %, whereas the water vapour variation
follows the saturation mixing ratio with a high degree of correlation (r=0.97). The occurrence of ice particles detected by MAS is reflected by
enhancements in IWC shown as blue shading in Fig. 8a and b. The magnitude of IWC
enhancements (up to 3.3 ppmv) is comparable to the magnitude of water vapour
reduction, which suggests that these ice crystals have formed in situ as a
result of synoptic-scale CPT cooling. Indeed, as shown in Fig. 8b, the total
water does not exceed the background level represented by the mean water
vapour from the previous flights. It is however still possible that some of
these crystals were produced by overshooting as suggested by Lee et al. (2019) for this particular flight.
Evolution of cloud occurrence and RHi along the back trajectories
released from B7 (H2O enhancement at 410 K in F7). (a) Back trajectories
(black curves) and ground tracks of CALIPSO and CATS satellite lidars colour
coded by the cloud top altitude. The magenta circles mark the locations of
the tracked parcels at the time of the nearest satellite transacts. The red
labels indicate the transacts number (T1–T6) and its UTC. The arrows are
wind vectors (ERA5) interpolated at the 410 K level. The track of the F7 flight is
shown as solid curve with altitude colour coding. (b) Attenuated scattering
ratio (SR) for T3 (contours, 3 and 6 SR units) and T4 (colour map). The white
oval shows the latitude–altitude location of the B7 parcels at the time of
T4 transect. The grey dashed curve is the projection of the F7 flight track onto
the lidar section. Note that the location of B7 parcels matches the
evaporating part of the cloud. (c) Evolution of RHi along the
back trajectories computed using ERA5 temperatures and measured H2O
mixing ratio in B7 (7.3 ppmv). The shading indicates 2 standard
deviations, the vertical lines with red labels mark the timing of satellite
transacts, and the red dashed line shows the homogeneous freezing threshold for the
given temperature and humidity.
Above the layer of thin cirrus reaching the 400 K level, the water vapour
profiles in F7 reveal two enhancements, marked in Fig. 8 as A7 and B7. The
B7 feature is characterized by a maximum enhancement of 1.9 ppmv at 410 K in
a layer extending between 405–415 K (18.5–19 km). Both A7 and B7 moist
features are characteristic of significant isotopic enhancement (Fig. 8c),
whereas the B7 is also marked by an enhanced fraction of convective hits
(cf. Figs. 4a and S3). From the convective sources'
analysis in Sect. 4.2, we know that the hydrated feature B7 has a convective
age of 12.7 d, during which the moist convective plume has made a nearly
complete circle within the AMA. During this time, the mixing within the moist
layer is expected to smoothen its vertical structure; however, the B7
enhancement reveals a rather sharp vertical structure. Such a sharp
structure is normally associated with recently sublimated ice crystals from
a nearby overshoot (e.g. Khaykin et al., 2009, 2016). The absence of recent
(<5 d) convective events (see animation in the Video supplement) upwind of
B7 has led us to investigate the satellite cloud measurements and
temperature history along the corresponding backward trajectories.
Secondary cloud sublimation
Figure 9a shows an ensemble of back trajectories released from B7 together
with the ground tracks of CALIPSO and CATS nighttime orbits nearest in time
and space with the location of the sampled air parcels along their
trajectories. The locations and timing of satellite lidar transects were
favourably close to the locations of the tracked parcels at each given time:
the largest temporal offset between the trajectory time and a lidar transect
is only about 3 h. This warrants investigation of the Lagrangian
evolution of cloud occurrence in the B7 parcel.
On 6 August, neither CATS nor CALIOP transects (marked as T1 and T2 in Fig. 9a) show the presence of clouds above 18 km, which is consistent with the
parcel's temperature history in Fig. 9c showing sub-saturated conditions
before T1. After passing the T2 point, the parcel has experienced a strong
cooling episode, boosting the maximum RHi above the homogeneous freezing
threshold. The next collocated lidar overpass (T3) took place on 7 August
when the parcel's temperatures have just relaxed down to saturation levels.
The lidar curtains labelled T3 and T4 (Fig. 9b) show evidence of partial
evaporation of the cirrus cloud cross-sampled by CATS at 17:00 UT (T3) and by
CALIOP 3 h later (T4). The location of the tracked parcels (marked
by a white rectangle in Figs. 9b and S5b) matches
precisely the evaporating fraction of the cloud. Thus, the final sublimation
of this secondary cloud has occurred about 13 h before B7 sampling,
which can explain its sharp vertical structure.
At the time of B7 sampling, the parcel's RHi – computed from ERA5
temperatures and FLASH peak value of 7.3 ppmv in the hydrated layer –
amounts to nearly 100 %, which is consistent with the airborne temperature
measurement. Downwind of the flight track there are two transects (T5 and
T6), not necessarily collocated in time with the westward progression of B7
parcel but showing an absence of ice particles at the respective level
(Figs. 9 and S5).
The above led us to conclude that while the B7 water vapour enhancement was
produced by a 12.7 d old convective plume that circumnavigated AMA, its
vertical structure was modified by strong yet transient cooling episodes
that acted to temporally repartition the vapour into ice on a scale of
several hours. As inferred from NIXE-CAPS particle size distribution
measurements in F8, a freshly nucleated in situ cirrus near the CPT level is
dominated by very small ice crystals with an effective diameter of 4–10 µm (Fig. S6). According to Müller and Peter (1992) such
crystals would sediment at a rate of 0.6–2 cm s-1. Assuming the onset of ice
crystal nucleation at B7 – 20 h (corresponding to the onset of the strong
cooling episode) – and their evaporation at T4 point, the cloud particles
should have sedimented by less than 200–700 m during their lifetime.
With this case we point out that the homogeneously nucleated crystals
smaller than 10 µm occurring in the CLS as a result of
convectively induced radiative cooling and/or gravity-wave-induced
temperature perturbations do not last long enough to sediment out from the
stratosphere and therefore have limited potential to dehydrate the CLS.
Discussion and summary
The occurrence of water vapour enhancements in the lower stratosphere
associated with overshooting convection has been reported in several studies
based on in situ measurements in the deep tropics over western Africa
(Khaykin et al., 2009; Schiller et al., 2009), northern Australia (Kley et
al., 1982; Corti et al., 2008), South America (Khaykin et al., 2013),
Central America (Sargent et al., 2014), and the western Pacific (Jensen et al.,
2020), as well as at midlatitudes over the North American monsoon (Hanisco et
al., 2007; Weinstock et al., 2007; Smith et al., 2017) and Asian monsoon
(Vernier et al., 2018; Brunamonti et al., 2018; Krämer et al., 2020). We
note that the reported cases represent a small fraction of in situ
measurements acquired; there is typically no more than one case of water
vapour enhancement above the tropopause detected during a given field
campaign.
Compared to other field campaigns, the StratoClim aircraft deployment in
Nepal provided an ample sampling of moist layers above the tropopause. Their
convective overshooting origin is unambiguously supported by both the
enhanced isotopic ratios in the moist plumes and by their traceability to
convective events. Notably, the occurrence of lower stratospheric moist
plumes above the monsoon regions is also supported by satellite observations
(Fu et al., 2006; Schwartz et al., 2013; Werner et al., 2020), whereas the
enhanced water isotopic ratios observed over these regions (Hanisco et al.,
2007; Randel et al., 2012) support the role of overshooting convection in
maintaining the water vapour maximum in the North American and Asian monsoon
anticyclones. This process adds to the radiatively driven slow ascent of wet
air through the warm tropopause in the northern part of the AMA. Another
possible pathway of water into the CLS in addition to the slow ascent and
overshooting may be the isentropic transport across the CPT from the Tibetan
Plateau (characterized by highest CPT) to the southern slopes of the Himalayas.
Using MLS observations and OLR data, Randel et al. (2015) concluded that
stronger convection in the Asian monsoon region leads to colder and drier
lower stratosphere, whereas the opposite is true for the weaker convection.
They also pointed out the importance of subseasonal variations of deep
convection driving the water vapour amount near the tropopause.
Interestingly, the composite maps of OLR anomalies for wet and dry modes
(Fig. 5 in Randel et al., 2015) reveal an east–west dipole, and in both
cases this dipole is centred exactly on the StratoClim flight domain.
Furthermore, the evolution of the UTLS conditions in the flight domain,
switching from warm/wet to cold/dry mode over the course of the campaign,
allowed for sampling the opposite-sign effects of deep convection on the
water vapour above the tropopause.
The warm/wet mode sampled during the early flights revealed substantial
enhancements of the water vapour mixing ratio reaching above 10 ppmv (twice the
background) and as high as the 400 K (18.2 km) level, but it revealed very little evidence for dehydration upstream. By contrast, the second (cold/dry mode) period of the
campaign with organized large-scale convection inside and close to the
flight domain led to synoptic-scale CPT cooling and a drastic drop of water
vapour by ∼30 % near the tropopause. We note though that
the dehydration layer did not extend above 395 K, whereas in the upper
layers, the excess of water vapour was subject to a transient phase
transition, resulting in an outbreak of cirrus at levels up to 415 K (18.9 km). A similar inference was made by Brunamonti et al. (2018) on the basis of
balloon soundings of water vapour and ozone in Nepal as part of StratoClim
campaign in 2017. They argued that overshooting convection is responsible
for an isolated maximum of H2O in the CLS observed in July 2017,
whereas the water vapour minimum at the CPT level is caused by
synoptic-scale cold anomaly above the southern slopes that maximized around
9 August.
Our trajectory analysis suggests that convective origin is characteristic of
the wettest and the driest parcels (Fig. 4a), which points out the dual role
of overshooting convection on the AMA water vapour. With that, we note that
the probability of dehydration decreases with the age of convective outflow,
ascending within the AMA at an average 1.1 K d-1 rate in potential temperature
(Legras and Bucci, 2020). This way, a hydrated air mass, circulating within
the confined anticyclone, progressively moves up and away from the
tropopause and becomes less likely to encounter permanent dehydration. A
similar inference was made by Ueyama et al. (2018) on the basis of
trajectory-based microphysical simulations. Although, as we showed here, the
secondary clouds can form as high as the 410–415 K level, their lifetime is
limited to a fraction of day, which does not enable a permanent removal of
water vapour from the CLS. Thus, a hydrated plume that survived a full
turnover within the AMA would retain its moisture and eventually loft it into
the free stratosphere.
The question on the role of different AMA sub-regions in the
cross-tropopause transport of water has been addressed by a number of
studies quoted in the introduction. With that, there appears to be no
consensus regarding the dominance of a particular sub-region. In this study,
the majority of the observed wet plumes in the CLS are traced back to
convective events in the northeastern part of the AMA, which influenced the
flights during the first (warm/wet) period of the campaign. The other
flights have sampled wet air originating from convection above the Tibetan
Plateau as well as northeastern and northwestern India. Given the limited
time period of the campaign and the large subseasonal variability of the
Asian monsoon, this inference may not be fully representative of the
climatological convective source regions. Nevertheless, it can be concluded
that convection occurring in the northern and northeastern parts of the AMA,
characterized by a warmer tropopause, is more likely to produce persistent
moistening of the lower stratosphere.
The airborne measurements in the AMA within StratoClim have revealed the
abundance of moist convective plumes in the CLS. In this respect, the Asian
anticyclone is very similar to its North American counterpart. Indeed, both
anticyclones extend well into the extratropics, where a warmer tropopause
enables unimpeded transport of large amounts of water vapour. An important
finding of our study is the persistence and recirculation of moist
convective plumes in the confined LS of the AMA. To our knowledge, such
phenomena were never before observed in the deep tropics. The recirculation
of water-vapour-enhanced air masses was reported in the Antarctic and Arctic
vortices (Vömel et al., 1995; Khaykin et al., 2013) where the hydration of
the lower stratosphere occurs through sedimentation of ice polar stratospheric clouds (PSCs).
Overall, our results suggest a complexity of processes controlling water
abundance and its aggregate state in the lower stratosphere of the AMA. The
strong isotopic enhancements specific to the moist layers in the CLS and
their traceability to convective events consistently suggest that
overshooting convection is an important contributor to the seasonal maximum
of water vapour in the AMA lower stratosphere. At the same time, the
large-scale organized convection in the southern part of the AMA is shown to
cause synoptic-scale dehydration around the tropopause through radiative
cooling. Another mechanism of dehydration is the overshooting of ice
crystals into the supersaturated environment above the tropopause, which
leads to their rapid growth and sedimentation. The evidence of such a
process was obtained in a particular flight (F8) and will be a subject of a
separate study.
Further insights into the AMA gaseous/particular composition and dynamics
will be provided by an upcoming airborne campaign within the Asian summer
monsoon Chemical and Climate Impact Project (ACCLIP;
https://www2.acom.ucar.edu/acclip, last access: 28 February 2022), which will sample the western Pacific
mode of the monsoon and eastward eddy shedding using NASA WB-57 and NCAR GV
aircraft. The stratospheric impact of overshooting convection in the North
American monsoon is a primary target of the Dynamics and Chemistry of the
Summer Stratosphere (https://dcotss.org/, last access: 28 February 2022) project, involving ER-2 high-altitude aircraft.
Data availability
The airborne data will be available from the HALO database
at https://halo-db.pa.op.dlr.de/mission/101 (last access: 30 July 2021)
(DLR, 2021). In the meantime they may be provided by
the respective principal investigator upon request. TRACZILLA data are available upon request. MLS data are publicly available
at http://disc.sci.gsfc.nasa.gov/Aura/data-holdings/MLS (last access: 28 February 2022; Lambert et al., 2015), GNSS-RO data
at https://www.romsaf.org/product_archive.php (last access: 28 February 2022; EUMETSAT, 2022), CALIOP data
at 10.5067/CALIOP/CALIPSO/LID_L1-STANDARD-V4-10 (NASA/LARC/SD/ASDC, 2016), and CATS data at
10.5067/ISS/CATS/L1B_N-M7.2-V3-00 (NASA/LARC/SD/ASDC, 2019).
Video supplement
The animation showing the hourly evolution of back trajectories released at the B7 point of StratoClim Geophysica flight F7 is available at: 10.5281/zenodo.5168703 (Khaykin et al., 2021).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-22-3169-2022-supplement.
Author contributions
SMK performed the airborne and satellite data analysis and wrote the draft. EM and BC provided airborne water isotope data. SB and BL performed the
trajectory calculation and geostationary satellite data analysis. AL, IF and
VY provided airborne water vapour data. MK, AA, CR and NS provided airborne
total water and ice particle size data. FC provided airborne particle
backscatter in situ data. VM and RM provided airborne lidar data. VV
provided airborne temperature data. EM, CES, BC, MK, CR, BL and FS provided
useful comments and participated in the redaction of the paper.
Competing interests
The contact author has declared that neither they nor their co-author has any competing interests.
Disclaimer
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Special issue statement
This article is part of the special issue ”StratoClim stratospheric and upper tropospheric processes for better climate predictions (ACP/AMT inter-journal SI)”. It is not associated with a conference.
Acknowledgements
We gratefully thank the StratoClim coordination team and the Myasishchev
Design Bureau for successfully conducting the field campaign. Meteorological analysis data are
provided by the European Centre for Medium-Range Weather Forecasts. ERA-5
trajectory computations are generated using Copernicus Climate Change
Service information. We also thank the AERIS/ICARE Data and Services Center
for providing access to the MSG1 and Himawari data as well as computer resources
for the production of the cloud top product using the NWC SAF GEO-v2018.1
algorithm. Last but certainly not least, we sincerely thank the three
anonymous referees for their constructive remarks.
Financial support
This research has been supported
by the StratoClim project of the European Community’s Seventh
Framework Programme (FP7/2007–2013) under grant agreement
no. 603557 and by the Agence Nationale de la Recherche TTL-Xing ANR-17-CE01-0015 projects.
Review statement
This paper was edited by Corinna Hoose and reviewed by three anonymous referees.
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