ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-7003-2015Simulation of the isotopic composition of stratospheric water vapour –
Part 2: Investigation of HDO / H2O variationsEichingerR.roland.eichinger@dlr.dehttps://orcid.org/0000-0001-6872-5700JöckelP.https://orcid.org/0000-0002-8964-1394LossowS.https://orcid.org/0000-0003-2833-0522Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Physik der Atmosphäre, Münchner Straße 20, Oberpfaffenhofen, 82234 Weßling, GermanyKarlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Hermann-von Helmholtz-Platz 1, 76344 Leopoldshafen, GermanyR. Eichinger (roland.eichinger@dlr.de)29June201515127003701522September201428November201424April201503June2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/15/7003/2015/acp-15-7003-2015.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/15/7003/2015/acp-15-7003-2015.pdf
Studying the isotopic composition of water vapour in the lower stratosphere
can reveal the driving mechanisms of changes in the stratospheric
water vapour budget and therefore help to explain the trends and variations
of stratospheric water vapour during recent decades.
We equipped a global chemistry climate model with a description of the water isotopologue
HDO, comprising its physical and chemical fractionation effects throughout
the hydrological cycle.
We use this model to improve our understanding of the processes
which determine the patterns in the stratospheric water isotope composition and
in the water vapour budget itself.
The link between the water vapour budget and its isotopic composition in the tropical stratosphere
is presented through their correlation in a simulated 21-year time series.
The two quantities depend on the same processes; however, they are influenced
with different strengths.
A sensitivity experiment shows that fractionation effects during the oxidation of methane have a damping effect on
the stratospheric tape recorder signal in the water isotope ratio.
Moreover, the chemically produced high water isotope ratios
overshadow the tape recorder in the upper stratosphere.
Investigating the origin of the boreal-summer signal of isotopically enriched water vapour
reveals that in-mixing of old stratospheric air from the extratropics and the intrusion of
tropospheric water vapour into the stratosphere complement each other
in order to create the stratospheric isotope ratio tape recorder signal.
For this, the effect of ice lofting in monsoon systems is shown to play a crucial role.
Furthermore, we describe a possible pathway of isotopically enriched water vapour through the
tropopause into the tropical stratosphere.
Introduction
Variations in stratospheric water vapour alter the radiative heat budget
and the ozone mixing ratios .
The processes which control the stratospheric water vapour budget, however, are
poorly quantified .
These processes are temperature-controlled dehydration, convective
activity,
methane oxidation and isentropic transport.
Due to their physical and chemical properties, water isotopologues have the potential
to answer the open questions concerning the origin of stratospheric water vapour.
The small mass difference between H2O and HDO (16O; the
hydrogen isotope deuterium D denotes 2H) leads to different vapour pressures
and zero-point energies. This causes equilibrium and kinetic fractionation effects
during phase changes and chemical reactions. Each process which controls the
stratospheric water vapour budget can be associated with certain fractionation
effects and therefore leaves a specific isotopic signature in the water vapour
compound see. This isotopic fingerprint
allows us to comprehend the history of stratospheric water vapour
and, in this way, can assist to explain the trends and variations in its budget.
In addition to in situ and remote-sensing measurements, the comprehensive
simulation of the physical and chemical processes of water isotopologues on the global
scale is needed to gain an improved understanding of the basic structure
of the water isotope ratios in the stratosphere.
Model studies of water isotopologues in the upper-troposphere–lower-stratosphere (UTLS)
include approaches from conceptional
to one-dimensional and two-dimensional models.
applied the general circulation model (GCM)
GISS-E, in order to study stratospheric entry values of the isotope ratios of water vapour.
However, this model has a comparatively low resolution in the
stratosphere and accounting for methane oxidation is prescribed with
a fixed production rate.
In Part 1 of this article , an extension of
the global climate chemistry model (CCM) EMAC (ECHAM MESSy Atmospheric
Chemistry; MESSy stands for “Modular Earth Submodel
System”) was presented and evaluated. This extension, namely the
H2OISO (H2O ISOtopologues) submodel, comprises an additional hydrological cycle, including the water
isotopologues H218O and HDO and their physical fractionation effects,
based on previous studies by, e.g., and
. Besides a vertical resolution resolving the tropical
tropopause layer (TTL) and simulating the stratospheric dynamics explicitly,
this expanded model system also includes the computation of the methane
isotopologue CH3D and its chemical contribution to HDO through oxidation.
Results of an EMAC simulation showed good agreement in stratospheric HDO and
δD(H2O) with measurements from several satellite instruments:
δD(H2O)=[HDO]/[H2O]RVSMOW-1⋅1000.
The Vienna Standard Mean Ocean Water VSMOW; HDO standard is
RVSMOW=155.76×10-6see. Moreover,
the results revealed a stratospheric tape recorder which ranges between the
pronounced signal of MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) observations see and
the missing upward propagation of the seasonal signal in the ACE-FTS (Atmospheric Chemistry Experiment Fourier transform
spectrometer)
retrieval see.
The results of these simulations are now further analysed, with the aim of identifying the processes
which determine the patterns of the isotopic signatures in stratospheric water vapour.
The connection between the water vapour budget and its isotope ratio
in the tropical stratosphere over the two simulated decades is presented in Sect. .
The influence of isotope effects during methane oxidation on the δD(H2O)
tape recorder signal is investigated in Sect. .
In Sect. the origin of the Northern Hemisphere (NH) summer signal
of the δD(H2O) tape recorder is examined.
Its generation exclusively in the NH is shown to be connected with in-mixing of extratropical air and
ice lofting in association with clouds in monsoon systems.
Furthermore, a possible pathway of isotopically enriched water vapour from the NH troposphere
into the tropical stratosphere is presented.
These analyses also reveal a possible underestimation of ice overshooting in the
applied convection scheme which can have a significant effect on δD(H2O)
in the lower stratosphere.
This study constitutes the first application of the isotopic composition of water
vapour in order to explore the reasons for
changes in the stratospheric water vapour budget with global atmosphere chemistry–climate models.
Model description and simulation set-up
The MESSy submodel H2OISO, now part of the EMAC model
, comprises an additional hydrological cycle, separate from the
actual cycle and including tracers for the
water isotopologues H216O, HDO and H218O in the three phases
vapour, liquid and ice, respectively. These tracers are treated identically
to the standard state variables for water in the regular hydrological cycle
of EMAC, with the addition of the physical fractionation effects for the
isotopologues during phase transitions. The representation of these effects
follows the water isotopologue-enabled ECHAM (ECMWF
Hamburg) model see.
Equilibrium and kinetic fractionation during the evaporation of water from
oceans is described by the bulk formula of . Due to the
limitations of the applied land surface scheme, we neglect any isotope
fractionation from land surfaces for details, see. The
implementation of the cloud and convection parameterisations (CLOUD and
CONVECT) in EMAC follows the study of . For condensation
within clouds and for the evaporation of cloud water, a closed system is
assumed. An open system is used for the deposition of water vapour to ice.
Due to the low diffusivities of the isotopologues in the ice phase, no
exchange happens between ice and vapour. During the melting of ice and the
freezing of water, as well as for the sedimentation of ice, autoconversion,
accretion and aggregation, no fractionation is assumed. The representation of
the fractionation during the reevaporation of raindrops follows the study by
, who assume an isotopical equilibration of 45 % for
large drops from convective rain and 95 % for small drops falling from
stratiform clouds. Supplementary to this, an explicit accounting function
for the contribution
of CH3D oxidation to HDO, including a parameterisation of the deuterium
storage in molecular hydrogen, has been developed in order to achieve
realistic HDO mixing ratios and δD(H2O) values in the stratosphere.
In Part 1 of this article , the model
system and the implementation of HDO throughout the hydrological cycle,
including its chemical representation, are presented in detail.
An EMAC simulation in the T42L90MA (∼ 2.8∘×2.8∘,
90 layers in the vertical up to 80 km (0.01 hPa), explicit middle
atmospheric dynamics) resolution was carried out. The simulation was
performed with specified dynamics (i.e. “nudged” towards ERA-Interim
reanalysis data ECMWF; up to 1 hPa). The
“Tiedtke–Nordeng” convection scheme was
applied to the simulation. After starting from steady-state initial
conditions in 1982, the simulation was evaluated during the 21 years from
1990 to the end of 2010. A detailed description of the simulation set-up and a
description of the applied MESSy submodels are presented in Part 1 of this article . An evaluation of the model's
hydrological cycle itself can be found in , who assess the
EMAC base model ECHAM5. state that the modifications
introduced by the MESSy system, as well as by the application of the T42L90MA
resolution and nudging, produce a hydrological cycle similar to the results
in and consistent with observations. An extensive
evaluation of the isotopic composition of water vapour and of its chemical
precursor CH3D in this EMAC simulation in the troposphere and the
stratosphere is presented in Part 1 of the article
. Overall, a reasonable representation of stratospheric
HDO is reached, although with some systematic, but explainable,
discrepancies.
Time series of H2O and δD(H2O)
Temporal variations in stratospheric water vapour during the last decades
have been observed by various instruments. The reasons for these variations
are much discussed see,
e.g.,. Before analysing
these changes with the EMAC model using the newly implemented HDO, it has to
be ensured that the EMAC simulation features the main characteristics of the
changes in stratospheric water vapour from 1990 to the end of 2010.
Therefore, the equatorial water vapour mixing ratios at 30 km altitude of
the simulation are compared with a combined HALOE (HALogen Occultation
Experiment) and MIPAS data set in Fig. . A
detailed description of the combination of the satellite data time series is
given in the Supplement. A 2-year running mean was calculated for both time
series in order to make the trends more visible by eliminating the signal of
the quasi-biennial oscillation (QBO).
Time series of stratospheric water vapour at 30 km averaged between
10∘ S and 10∘ N.
Combined HALOE and MIPAS data and the EMAC simulation. Both time series are processed with
a 2-year running mean.
The combined HALOE–MIPAS data show an increase in stratospheric water vapour
in the first half of the 1990s and a plateau hereafter until the year 2000.
The water vapour mixing ratio drops by around 0.3 µmol mol-1
between 2000 and 2002 and stays at this lower level until the middle of the
first decade of the 21st century. Hereafter, a slow increase can be observed
until the end of the time series in 2010. This behaviour of stratospheric
water vapour during the previous decades has also been reported and
discussed, e.g. by , who analysed a combined HALOE and MLS (microwave
limb sounder) data set, and is strongly connected to tropopause temperatures.
The EMAC simulation generally reproduces these variations, although with a
constant offset and a few differences. The general dry bias in EMAC has
already been discussed by and in Part 1 of this article . Its main reasons are the slightly too cold
hygropause in the nudging data see, e.g., and the coarse
horizontal resolution of the model. In contrast to the satellite
observations, in the EMAC simulation the drop around the year 2001 is
preceded by an increase in water vapour. Moreover, the level of the water
vapour mixing ratio after the drop does not fall below the level of the early
1990s. The Pearson's correlation coefficient between the observed and
simulated time series is R2=0.50.
In order to estimate the correlation between the changes of water vapour and
its isotopic composition, the monthly anomalies with regard to the 21-year monthly
averages of the tropical water vapour mixing ratios and δD(H2O) are
shown in Fig. for the 21 years of the EMAC
simulation at 18 km and at 30 km altitude. Again, the data
were processed with a 2-year running mean, in order to obtain a better
visibility of the trends. The anomaly of δD(H2O) is divided by 30
for better comparability.
Time series of EMAC-simulated monthly stratospheric water vapour (black) and δD(H2O) (red)
anomalies with regard to the 21-year monthly average at 18 km and at 30 km altitude,
averaged between 15∘ S and 15∘ N and processed with a 2-year running mean filter.
The δD(H2O) anomalies were divided by 30 for better comparability.
At 18 km altitude, the Pearson's correlation coefficient between the two
time series is R2=0.57, and this correlation decreases to R2=0.28 at
30 km. At 18 km altitude, both quantities are dominated by
troposphere–stratosphere exchange processes. At 30 km altitude, the chemical
effects, induced by CH4 oxidation for H2O and the different lifetimes
of CH4 and CH3D for δD(H2O), become important. An
interdependence of the two quantities can be observed at both altitudes,
although, during certain periods, the development of the two time series is
anticorrelated. The drop around the year 2001 can be seen in water vapour and
in δD(H2O) at both altitudes. At 18 km, the more pronounced
feature in δD(H2O), however, is the steep increase before the drop.
The amplitude of this increase in δD(H2O) exceeds the amplitude of
the drop almost by a factor of 2. Even though most of the variations in the
two quantities are in phase, the signs of the anomalies are sometimes
inverted. At 18 km altitude, δD(H2O) is generally at a lower level
at the end of the 1990s compared to the early 2000s, after the drop. The
short-term changes, in particular, seem to be different between the two
quantities. This suggests that the processes that control stratospheric
δD(H2O) are related but not equal to those that control the
stratospheric water vapour budget. The tropopause temperatures, methane
oxidation, convective activity and other processes determining water vapour in
the stratosphere thus affect stratospheric H2O and
δD(H2O) with different strengths. Knowledge of this behaviour can
therefore help to connect the origin of certain variations and trends to
changes in specific processes. The next sections thus aim to reveal the influence of individual processes on stratospheric δD(H2O),
with a special focus on the tape recorder, since the strength of this
phenomenon largely determines the intrusion of water vapour into the
stratosphere.
Sensitivity of the δD(H2O) tape recorder to methane oxidation
In order to analyse the impact of the contribution of CH4 and CH3D
oxidation on the δD(H2O) tape recorder signal, an additional EMAC
simulation was conducted. The only difference in this simulation is a
modified chemical tendency for HDO. The concept for this sensitivity
simulation is an artificial deactivation of the chemical fractionation
effects. In other words, δD(H2O) is not influenced by
chemical isotope effects; CH3D oxidation alters always HDO in relation to
CH4 oxidation, as if there was no isotope fractionation. A detailed
description of this modification is given in the Supplement.
For the analysis of the impact of isotope effects during methane oxidation on
the δD(H2O) tape recorder signal, the simulation with the modified HDO
tendency is compared to the simulation with regular methane isotope
chemistry. The set-up is the same for both simulations.
Figure shows the tropical tape recorder signals from
2004 to 2009 for the two simulations from 15 to 30 km.
Tropical (15∘ S–15∘ N) δD(H2O) tape
recorder signal from 2004 to 2009 in the
simulation including (upper panel) and without (lower panel) the effect of methane oxidation
on δD(H2O).
Between 15 and 25 km, the δD(H2O) values are similar in both
panels. In the tropical tropopause layer and the lower stratosphere,
δD(H2O) is only weakly affected by methane oxidation. From 25 km
upwards, increasingly higher δD(H2O) values can be observed in the
simulation with regular methane isotope chemistry (upper panel). The effect
of the chemistry on δD(H2O) increases with altitude in the
stratosphere. This can be observed for the increased δD(H2O)
values, which emerge during the NH summer, as well as for the low
δD(H2O) values from the boreal-winter signal. The tape recorder
signal in the simulation with the modified methane isotope chemistry (lower
panel) extends further up. It is still present, although weak, at the top of
this panel at around 30 km altitude. In the upper panel the
δD(H2O) tape recorder signal above 25 km becomes increasingly
overshadowed by high δD(H2O) values, which are generated by the
different lifetimes of CH4 and CH3D, i.e. chemical isotope effects.
The upward-propagating signatures fade out or, more specifically, mix with the high
δD(H2O) values. These high δD(H2O) values show variations
with a phase of around 2 years, which can be associated with the QBO.
For a better quantification of the differences between the two tape recorder signals,
Fig. shows the annually averaged difference in the δD(H2O)
maximum and minimum as a function of altitude for the time period of Fig. .
The black line denotes the simulation with, and the red line the
simulation without, the methane effect.
Annually averaged difference between the maximum and the minimum of
δD(H2O) as function of altitude, with (black) and
without (red) the effect of methane oxidation on δD(H2O).
The tape recorder amplitudes are equal below 20 km. As expected, further
above, the amplitude of the simulation with chemistry effect on
δD(H2O) decreases more quickly with altitude than the amplitude of the
simulation without this effect. The high δD(H2O) values from the NH
summer signal are not affected as strongly by methane oxidation as the low
values from the NH winter signal are. To explain this, constant temperatures, and
hence fractionation factors, and a constant background δD(CH4) are
assumed, which is reasonable here. The isotope ratios of isotopically
different reservoirs show different sensitivities to the addition of a
compound with a certain isotope ratio. This means that the smaller the
differences between the δ values are, the smaller is the modification.
Since the high δD(H2O) values from the NH summer signal are closer
to the δD(CH4) values (δD(CH4) is also based on VSMOW),
which are around -50‰ here, compared to the low δD(H2O)
values from NH winter, the summer signal is altered less. Additionally, the water vapour mixing ratios are also different here. The δD(H2O)
values of the low water vapour mixing ratios from the NH winter signal are
therefore again affected more strongly by the addition of (a similar amount
of) isotopically enriched water vapour from methane oxidation. This leads to
the conclusion that
the production of H2O and HDO by the oxidation of CH4 and CH3D
reduces the amplitude of the δD(H2O) tape recorder and overshadows
the upward propagation of the signal.
Between 24 and 28 km, the amplitude of the δD(H2O) variations in
the simulation with chemistry effect on δD(H2O) are similar, and
above 28 km the amplitude in the simulation with the chemistry effect
exceeds the amplitude of the simulation without. This, however, is not due to
the tape recorder effect anymore but is caused by the QBO. The QBO also has an
effect on the stratospheric water vapour budget and on the water vapour tape
recorder see. As stated above, the cycle of the QBO can
be seen in the high δD(H2O) values between 25 and 30 km in
Fig. . Temperature and hence chemical fractionation
factor variations and also dynamical differences between the QBO phases which
mix in more or less strongly enriched water vapour lead to this cycle and
hence to this increase in amplitude.
The origin of the δD(H2O) tape recorder
Both the water vapour mixing ratio and δD(H2O) exhibit enhanced values in the
lower stratosphere during JJA (June, July, August). The underlying processes for this, however, may
differ in some ways for the two quantities. In order to demonstrate this and to analyse
the origin of the tape recorder signal, the water vapour
mixing ratios and δD(H2O) in the
UTLS for JJA are shown in Fig. .
H2O mixing ratio (left panel) and δD(H2O) (right panel) in the UTLS in JJA
averaged over the 21 years of the EMAC simulation. The black lines denote the tropopause.
Differences in the distribution of the enhanced values can be observed when comparing the two panels.
In the left panel, enhanced H2O mixing ratios can be seen
within almost the entire TTL, although decreasing with altitude and towards the southern latitudes.
At the northern edge of the TTL, the high H2O mixing ratios
exceed the tropopause and penetrate into the stratosphere. Some water vapour, however,
also intrudes into the stratosphere in the central and the southern TTL.
Isotopically enriched water vapour (see right panel) exclusively enters the
stratosphere at the northern edge of the TTL. δD(H2O) values of
above -650‰ can be observed, crossing the tropopause and entering
the tropical pipe here. Note that the enhancement of δD(H2O)
between 17 and 18 km is an artefact caused by the seasonal averaging. The
signal originates from the northern edge of the TTL and remains in the
tropical pipe during summer while being mixed with surrounding air masses
comparatively quickly between 16 and 17 km. In the Supplement, zonal
δD(H2O) across all latitudes is also presented for the other
seasons (DJF – December, January, February; SON – September, October,
November; MAM – March, April, May) from 10 to 30 km altitude. There, the
high δD(H2O) values in the tropical pipe can still be seen during
SON and DJF. In the central and southern parts of the TTL, the water vapour
is isotopically strongly depleted, exhibiting values below -700‰.
Low δD(H2O) values can be observed down to 14 km altitude in the
central and southern TTL, while relatively high water vapour mixing ratios
extend up to almost 16 km altitude in this region.
This shows that, in contrast to H2O, the enhanced isotope ratios in the
tropical lower stratosphere during JJA originate exclusively from the NH.
However, it is not clear if it originates from the
intrusion of tropospheric water vapour into the stratosphere or from
in-mixing of old stratospheric air from the extratropics. During DJF a
similar signal of isotopically enriched water vapour at the edge of the TTL
at around 40∘ S can be observed (see Supplement). In contrast to the
situation in JJA, here this signal is at considerably lower altitudes and does not
penetrate into the stratosphere.
In the lower stratosphere, air experiences rapid horizontal transport between
the tropics and the midlatitudes above the subtropical jets
. The region between the 380 and the 400 K isentrope is
therefore crucial for the properties of stratospheric air. To provide an
insight into the horizontal dynamics of this region, the average of
δD(H2O) between the 380 and the 400 K isentrope is shown in a
latitude–longitude representation for JJA in Fig. .
Again the other seasons are presented in the Supplement.
Seasonally averaged δD(H2O) (colours), horizontal
wind vectors (arrows) averaged from the 380 to the 400 K isentrope
and the tropopause height in kilometres (blue contour lines) in JJA, averaged over the
21 years of the EMAC simulation.
In general, the image features a pattern with low δD(H2O)
in the tropics and increasing values with higher latitudes.
In the Northern Hemisphere, patterns can be observed which
are associated with the Asian summer monsoon (ASM) and the North
American monsoon (NAM). High δD(H2O) values can be seen over the entire North
American continent. Over southern Asia, in contrast, very low values are dominant.
Around this isotopically depleted centre of the ASM anticyclone, the water
vapour is isotopically enriched. Over the West Pacific, at the outflow of the ASM anticyclone,
the wind vectors indicate
a considerable southward component, which drags isotopically enriched air from the
extratropics towards the tropics and then westwards.
This air may originate from in-mixing of old stratospheric air from the extratropics.
show a similar pattern for ozone which, according to ,
can also result in a stratospheric-tape-recorder-like signal.
However, state that this process is largely dependent on the species
itself, or, more specifically, on its meridional gradient.
The study shows that in-mixing plays a role in the annual ozone variations in the tropics but not
for carbon monoxide, nitrous oxide or water vapour.
Another possible explanation for these patterns is the intrusion of tropospheric air into the
stratosphere.
focus especially on slow ascent and dehydration through in situ cirrus
formation, which can generate the δD(H2O) tape recorder signal, and
point out the importance of ice overshooting convection on the pattern.
In the remainder of this section we will examine some of these mechanisms in order to obtain a better
understanding of their relative importance for the δD(H2O) tape recorder.
Relation between H2O and δD(H2O) from 14 to 18 km in JJA (left)
and DJF (right) between 20 and 40∘ N (black crosses) and between
40 and 20∘ S (red crosses), averaged over the 21 years of the EMAC simulation.
In-mixing vs. lofted ice
At first, we will examine whether in-mixing of old stratospheric air from the
extratropics alone can suffice to explain the δD(H2O) tape
recorder. Water vapour from the extratropical stratosphere has been
isotopically enriched through isotope effects during methane oxidation. These
effects are relatively even throughout the year and broadly consistent with
the chemical production rate of water vapour. A consistent relation between
H2O and δD(H2O) would therefore be expected if in-mixing was
the sole factor for this effect. In order to show that this is not the
case in the UTLS during JJA, the relation between the water vapour mixing
ratios and its isotope ratio is presented in Fig.
for JJA and DJF. The black crosses denote this relation in the NH (20 and
40∘ N) and the red crosses in the Southern Hemisphere (SH) (40 and
20∘ S), both from 14 to 18 km.
In JJA, the red crosses can be found in a δD(H2O) range between
roughly -700 and -660‰ with water vapour mixing ratios of up to
10 µmol mol-1. A relationship between increasing δD(H2O)
and increasing H2O mixing ratios is recognisable. The black crosses cover
the range of the SH relations as well, but also spread out to higher water
vapour mixing ratios and higher δD(H2O) values. Higher water vapour
mixing ratios generally feature enhanced δD(H2O) here too, but the
black crosses are much more widely distributed, especially for the same water
vapour mixing ratios. In DJF, the black crosses cover roughly the range of
the red crosses in JJA. The red crosses in DJF, however, hardly spread out to
higher H2O mixing ratios and δD(H2O); thus, the relation differs
only slightly between the hemispheres in DJF. The wider distribution of the
relation between H2O and δD(H2O) in the NH during JJA suggests
that several processes are important here because a single effect
would lead to a rather compact picture in the H2O to δD(H2O)
relation. In particular, this involves the combination of in-mixing of extratropical stratospheric air
and the intrusion of tropospheric air into the stratosphere.
Crucial tropospheric processes are connected with cloud and convection
effects, partly in association with the monsoon systems. As mentioned above,
upper-tropospheric water vapour penetrating from the troposphere into the
stratosphere could be crucial here. Also, the much discussed influence of ice
overshooting convection see, e.g., may have a
considerable effect on these patterns.
In order to provide a deeper insight into the ice water content and its
isotopic signature, the mixing ratios of ice in the UTLS for JJA (left panel)
and DJF (right panel) are shown in Fig. .
Additionally, δD(ice) (the deuterium isotope ratio of the ice water
content) is contoured in the figure and the height of the tropopause is
marked. The white regions denote ice water mixing ratios below
0.1 µmol mol-1.
Ice water content (colours) and δD(H2O) in ice (dashed contour lines)
in the UTLS in JJA (left) and DJF (right) and tropopause height (solid black line),
averaged over the 21 years of the EMAC simulation. The white regions denote
ice water mixing ratios below 0.1 µmolmol-1.
The ice water mixing ratios in JJA show two local altitude maxima between
roughly 12 and 15 km in this illustration: one in the inner tropics and
another one between 30 and 35∘ N. The latter maximum additionally
features high δD(ice) at high altitudes up to the tropopause. Ice
features δD values of up to -300‰ in this area, while the
isotope ratio of water vapour lies around -600‰ here (see
Fig. ). For DJF, a comparable maximum of lofted ice
with high isotopic signatures at these latitudes (in the SH) is not
simulated. Lofted ice which resublimates in the upper troposphere could
therefore be responsible for the isotopic enrichment of water vapour in this
region. The intrusion of this isotopically enriched water vapour into the
tropical pipe could then considerably amplify the δD(H2O) tape
recorder signal.
Effects of convective and large-scale clouds
The possible influence of ice lofting into the upper troposphere and an
associated isotopic enrichment of the tropical stratosphere during the NH summer
will be examined next. For this analysis, we carried out two additional
sensitivity simulations with the EMAC model. Analogously to the additional
simulation in Sect. with a modified HDO tendency for
methane oxidation, we now modified the HDO tendency for large-scale clouds
(submodel: CLOUD) and for convection (submodel: CONVECT).
These processes control ice lofting and its influence on δD(H2O) in
water vapour. Again, the tendency is modified in the manner that
δD(H2O) is not altered through the respective process. This enables
us to assess the stratospheric δD(H2O) patterns without the
influence of either of these two processes and thus to determine their respective
contribution on the δD(H2O) tape recorder. Since both of these
processes operate almost exclusively in the troposphere, this analysis also
allows the separation of the two above-mentioned factors that are thought to
control the δD(H2O) tape recorder signal: the in-mixing of old
stratospheric water vapour from the extratropics and the intrusion of
tropospheric water vapour through the tropopause.
Analogously to Fig. , the annual amplitudes of
δD(H2O) as a function of altitude are shown in
Fig. . The black line denotes the standard
simulation, the red line the simulation with the modified HDO tendency for
CLOUD and the green line with the modified HDO tendency for CONVECT.
Averaged annual amplitudes of δD(H2O) with altitude,
for the standard simulation (black), the simulation without large-scale
cloud effect on δD(H2O) (red) and the simulation without
the effect of convection on δD(H2O) (green).
Around the tropopause, the amplitude of δD(H2O) without the influence of large-scale clouds is
smaller and the amplitude without the influence of convection is larger than in the standard
simulation. This result is somewhat surprising because, in general, convection
is thought to isotopically enrich water vapour, especially during JJA and therefore increase
the annual δD(H2O) amplitude. In contrast, the stratosphere is generally isotopically
enriched in this simulation compared to the standard simulation, which means that in our model,
convection leads to isotopic depletion of the stratosphere. This is likely to be due to the
underrepresentation of overshooting convection in the convection scheme applied here.
Studies by and have shown that overshooting convection
increases δD(H2O) in the UTLS.
By contrast, isotopic depletion through dehydration during the ascent of water vapour seems to
dominate in the convection scheme.
This process affects HDO more strongly than H2O and therefore leads to isotopic depletion.
The simulation without the effect of large-scale clouds shows a smaller
δD(H2O) amplitude from the tropopause up to around 25 km. In other
words, it shows a weaker tape recorder with an earlier fade-out. The stratosphere is
generally depleted compared to the standard simulation here, and hence the
chemistry affects the pattern more strongly. The smaller δD(H2O)
amplitude below 25 km in this simulation shows that the isotopic enrichment
during JJA is strongly influenced through large-scale clouds. Hence, ice
lofting and the isotopic enrichment of water vapour through resublimation are
caused by large-scale clouds in our simulation. A possible mechanism for its
influence on the tropical stratosphere will be presented in the following
section. In conclusion, the in-mixing of old stratospheric air from the
extratropics alone can possibly generate a tape-recorder-like signal for
δD(H2O), although strong influences from tropospheric transport
induced by large-scale and convective clouds do have a significant impact on
the pattern.
A possible pathway through the tropopause
In order to depict a possible pathway for the isotopically enriched water
vapour, which complements the δD(H2O) tape recorder through
the effect of ice lofting, the ice water content (left panel) and
δD(ice) (right panel) in JJA at 14 km altitude are shown in
Fig. . The altitude of 14 km was chosen because, as
can be seen in Fig. , at this altitude the inner
tropical and the northern subtropical altitude maxima of the ice water
content are still pronounced. This provides information about the source of
the influence of ice lofting on the δD(H2O) tape recorder. Regions
with ice water mixing ratios below 0.1 µmol mol-1 are again
shaded white.
Ice water content (left) and δD(ice) (right) at 14 km altitude in JJA,
averaged over the 21 years of the EMAC simulation. The white regions denote
ice water mixing ratios below 0.1 µmolmol-1.
The left panel shows several spots of enhanced ice water mixing ratios around
the convective zones in the tropics. Especially high ice water mixing ratios
can be seen in Southeast Asia and Central America, but by far the highest
values are found over the Tibetan Plateau. δD(ice) exhibits a rather
uniform picture around the tropics, with values mostly between -500 and
-400‰. Only one single spot with isotopically enriched ice above
the Tibetan Plateau with values above -200‰ is noticeably different. This
corresponds with the latitude of the altitude maximum in
Fig. and suggests that ice lofting over the Tibetan
Plateau during the ASM season and associated isotopic enrichment of upper-tropospheric water vapour can possibly account for the major part of this
effect. The westerly wind regime in these latitudes (see
Fig. ) can transport the isotopically enriched
water vapour from the continent over the West Pacific, where it can enter the
stratosphere in the outflow of the ASM anticyclone. Here the tropopause is
especially low and crossed by isentropic surfaces. The zonal cross section of
δD(H2O), averaged from 30 to 40∘ N and presented in
Fig. , can provide additional evidence for this
possible mechanism. Additionally, the tropopause and the isentropes are shown
in the figure.
Zonal cross section of δD(H2O), averaged from 30∘ N to
40∘N for JJA (averaged over the 21 years of the
EMAC simulation). The black line denotes
the tropopause height; the red contour lines indicate levels of constant
potential temperatures (isentropes) in kelvin.
Here, the highest tropospheric δD(H2O) values can be found at
around 100∘ E, i.e. above the Tibetan Plateau and corresponding
with the ASM. Another, weaker maximum lies at around 100∘ W, which is the location of the Mexican High Plateau and the NAM. A third, even
weaker maximum at 0∘ E can be associated with the North African
monsoon. The lowest values are found where the tropopause is highest, i.e.
at around 16 km altitude at 50∘ E. This is also where the
temperatures are lowest (not shown). The tropopause height exhibits two
minima: one around 160∘ W and one around 10∘ W. Around
these minima, the highest stratospheric δD(H2O) values are
simulated. The underlying westerly wind regime (shown in
Fig. ) and the tropopause-crossing isentropes in
the subtropics thus support the suggestion of an ice lofting effect in
association with the monsoon systems contributing to the
δD(H2O) tape recorder.
Summary and discussion
As a first application of the new H2OISO submodel within the EMAC model,
stratospheric water vapour isotope ratios were investigated. The time series
of water vapour in the nudged EMAC simulation analysed here reproduces the
major variations in the recent decades. The time series of δD(H2O)
shows similarities with H2O but differs mainly regarding short-term
changes. This suggests that the processes controlling these two quantities
coincide, but their effect on the respective value is of different quantity.
The impact of methane oxidation on the stratospheric δD(H2O) tape
recorder signal was investigated by comparing the evaluated EMAC simulation
with an additional simulation with a suppressed chemical isotope effect of
methane oxidation on δD(H2O). Methane oxidation mainly affects
water vapour and its isotopic signature above 25 km, where the
δD(H2O) tape recorder signal fades out faster through this chemical
effect. Additionally, the amplitude of the δD(H2O) tape recorder is
reduced because methane oxidation influences the low δD(H2O) values
and the low water vapour mixing ratios much more strongly than the higher ones. This
result is not surprising, but it reveals the impact of the isotope
chemistry on the tape recorder. also applied a correction
for the methane effect on δD(H2O) to the ACE-FTS satellite
retrieval. This led to the removal of the increase in δD(H2O) with
altitude in the stratosphere as well. Moreover, it generated enhanced isotope
ratios in the lower stratosphere during JJA and SON, compared to the simulation without the
methane correction. However, the δD(H2O) tape recorder is still not
clearly visible in the ACE-FTS satellite retrieval.
The determining processes for the generation of enhanced δD(H2O)
during JJA in the tropical lower stratosphere were shown to take place
exclusively in the NH. This is in contrast to water vapour itself, which is
also influenced by direct transport through the TTL see, e.g.,. showed that
for some species a tape-recorder-like signal can be generated through the
in-mixing of old stratospheric air alone. However, and , for example, focus mostly on the slow ascent of
tropospheric water vapour and convective ice overshooting when evaluating the
reasons for the generation of the δD(H2O) tape recorder. In order
to investigate the role of the individual processes, we first assessed the
H2O to δD(H2O) ratio in the different hemispheres and seasons. A relationship between H2O and δD(H2O) that is much more spread out during JJA in the NH
(compared to the SH and to DJF) suggested that both the intrusion of
tropospheric water vapour and the in-mixing of old stratospheric air influence δD(H2O) here. In particular, due to extreme
interhemispheric differences in the ice water content and its isotopic
signature during the different seasons, the lofting of ice crystals is assumed
to enrich water vapour in the NH upper troposphere during JJA. Confirmation
is achieved through the results of sensitivity simulations with the modified HDO
tendency for large-scale clouds and for convection. The
averaged annual difference between the maximum and the minimum of
δD(H2O) shows a clear reduction in the UTLS up to 23 km for the
simulation without large-scale clouds affecting δD(H2O) and an
enhancement for the simulation without convection affecting HDO. The isotopic
enrichment during JJA is therefore not generated by convective events, which, in contrast, deplete the water vapour in the simulation, but by large-scale
clouds in association with monsoon systems. However, this shows that the
δD(H2O) tape recorder is strongly affected by tropospheric effects
through clouds and convection and not only by the in-mixing of extratropical air
masses.
Augmented ice lofting, especially in the ASM over the Himalayas, has
been shown to isotopically strongly enrich the water vapour in the upper
troposphere. In the outflow of the monsoonal anticyclones, this isotopically
enriched water vapour is transported into the stratosphere on isentropic
surfaces. Numerous studies,
e.g. have
shown that this sideways transport into the tropics in particular from the
ASM also contributes significantly to the stratospheric water vapour budget. By analysing MIPAS satellite data, suggest that a slow dehydration through cirrus cloud
formation plays a key role for the δD(H2O) tape recorder. However, the separation of this particular
process within the individual parts of the model, i.e. large-scale and
convective clouds, is not easily resolvable. In the model, convective
clouds isotopically deplete stratospheric water vapour. However, the relative
importance of this individual process for the annual signal has to be further
investigated. present a somewhat different pattern
of δD(H2O) in the UTLS by analysing ACE-FTS satellite data. In this
retrieval, enriched δD(H2O) at 16.5 km altitude can mostly be
found over America, and the patch of high δD(H2O) associated with
the ASM, as seen in the EMAC data, is considerably weaker. It is still a matter of debate as to whether convective ice
overshooting has a significant effect on
the stratospheric water vapour budget see, e.g.,.
According to and , however, it has a
substantial effect on the stratospheric δD(H2O) signature. This ice
overshooting occurs mostly in the inner tropics and has the potential to
isotopically enrich the tropical lower stratosphere. However, the NAM is also
associated with strong convective ice overshooting see,
e.g.,. The direct intrusion of ice crystals into the stratosphere
is known to be represented rather sparsely by the convection scheme applied here and taken from , and it has been shown to not affect
stratospheric δD(H2O) in this simulation. Therefore, this
discrepancy between model and observations may be due to the
underrepresentation of convective ice overshooting in the applied convection
scheme. The NAM region as well as the inner tropics could show considerably
higher δD(ice) values in the UTLS. Furthermore, this is possibly also
the cause for the too low δD(H2O) values in the lower tropical
stratosphere in EMAC compared to satellite observations during NH summer, as
shown in Part 1 of this article . A more
detailed evaluation of this effect can be conducted through the
implementation of water isotopologues into other convection schemes of EMAC.
Future sensitivity studies can then also resolve the robustness of the patterns discovered here and possibly explain the differences between model
results and observations more precisely.
Conclusions
The temporal variations in stratospheric δD(H2O)
reveal connections to those in water vapour,
but they show differences regarding the amplitudes.
This provides additional information about the underlying processes of the changes
and therefore can help to gain a better understanding of the
reasons for the trends and variations in the stratospheric water vapour budget.
First, however, this requires an understanding and quantification
of the influence of the individual processes that are responsible for the patterns
of δD(H2O) in the stratosphere.
Isotope fractionation effects during methane oxidation blur the δD(H2O) tape recorder
signal by damping its amplitude and overshadowing it at higher altitudes.
This explains the weaker tape recorder signal in δD(H2O) compared
to those in H2O and HDO.
The in-mixing of old stratospheric water vapour with high isotope ratios from the extratropics
alone does not suffice to describe the δD(H2O) tape recorder.
Instead, the influence of the intrusion of tropospheric water vapour through
clouds and convection contribute significantly to this pattern.
The isotopic enrichment of upper-tropospheric water vapour through ice lofting in association
with monsoon systems and further transport of these air masses into the tropical
stratosphere in the outflow account for this influence.
However, a quantification of the contributions of the respective processes and also
of the individual monsoon systems is yet to be established
and first requires further analyses of the discrepancies between the model results
and satellite retrievals.
These discrepancies indicate possible insufficiencies
in the model, i.e. the underrepresentation of overshooting convection.
This study has laid the foundations for further analyses in order to determine the connection between
the patterns and changes in stratospheric H2O and δD(H2O).
The additional information provided by the water isotope ratio
is of significant support in unravelling the factors which
contribute to trends and variations
in the stratospheric water vapour budget.
Acknowledgements
The authors thank the DFG (Deutsche Forschungsgemeinschaft) for funding the
research group SHARP (Stratospheric Change and its Role for Climate
Prediction, DFG Research Unit 1095); the study presented here was conducted as
part of R. Eichingers PhD thesis under grant number BR 1559/5-1. We
acknowledge support from the Leibnitz Supercomputing Center (LRZ), the German
Climate Computing Center (DKRZ) and thank all MESSy developers and submodel
maintainers for their support. Moreover, we thank H. Garny for an important
suggestion and S. Brinkop for important comments on the manuscript. Last but not
least, we acknowledge the constructive comments of two anonymous referees, who helped to significantly improve this manuscript.
The article processing charges for this open-access
publication were covered by a Research Centre of the
Helmholtz Association.Edited by: P. Haynes
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