# Assessing the long-term variability of acetylene and ethane in the
stratosphere of Jupiter

Henrik Melin  L. N. Fletcher  P. T. Donnelly  T. Greathouse  J. Lacy  G. S.
Orton  R. Giles  J. Sinclair  P. G. J. Irwin  University of Leicester,
Leicester LE1 7RH, UK  Southwest Research Institute, San Antonio, USA
University of Texas, Austin USA  Jet Propulsion Laboratory, Pasadena, USA
University of Oxford, UK

###### Abstract

Acetylene (C2H2) and ethane (C2H6) are both produced in the stratosphere of
Jupiter via photolysis of methane (CH4). Despite this common source, the
latitudinal distribution of the two species is radically different, with
acetylene decreasing in abundance towards the pole, and ethane increasing
towards the pole. We present six years of NASA IRTF TEXES mid-infrared
observations of the zonally-averaged emission of methane, acetylene and
ethane. We confirm that the latitudinal distributions of ethane and acetylene
are decoupled, and that this is a persistent feature over multiple years. The
acetylene distribution falls off towards the pole, peaking at $\sim$30∘N with
a volume mixing ratio (VMR) of $\sim$0.8 parts per million (ppm) at 1 mbar and
still falling off at $\pm 70^{\circ}$ with a VMR of $\sim$0.3 ppm. The
acetylene distributions are asymmetric on average, but as we move from 2013 to
2017, the zonally-averaged abundance becomes more symmetric about the equator.
We suggest that both the short term changes in acetylene and its latitudinal
asymmetry is driven by changes to the vertical stratospheric mixing,
potentially related to propagating wave phenomena. Unlike acetylene, ethane
has a symmetric distribution about the equator that increases toward the pole,
with a peak mole fraction of $\sim$18 ppm at about $\pm 50^{\circ}$ latitude,
with a minimum at the equator of $\sim$10 ppm at 1 mbar. The ethane
distribution does not appear to respond to mid-latitude stratospheric mixing
in the same way as acetylene, potentially as a result of the vertical gradient
of ethane being much shallower than that of acetylene. The equator-to-pole
distributions of acetylene and ethane are consistent with acetylene having a
shorter lifetime than ethane that is not sensitive to longer advective
timescales, but is augmented by short-term dynamics, such as vertical mixing.
Conversely, the long lifetime of ethane allows it to be transported to higher
latitudes faster than it can be chemically depleted.

###### keywords:

Jupiter, atmosphere
Spectroscopy
Abundances, atmospheres
Atmospheres, structure

††journal: Icarus

##  1 Introduction

The temperature of Jupiter’s stratosphere is determined by the balance between
solar heating via absorption of sunlight in the visible and near-infrared, and
radiative cooling by hydrocarbons, predominantly in the mid-infrared [Yelle et
al., 2001, Moses et al., 2004].

Photolysis of methane (CH4) produces acetylene (C2H2) and ethane (C2H6). And
all three of these species are efficient emitters in the mid-infrared and cool
the volume of gas that they inhabit by radiating energy to space [Moses et
al., 2004]. By observing the spectra of these species, we can retrieve the
vertical temperature profiles, and the acetylene and ethane abundances [Irwin
et al., 2008]. This gives us our primary means of diagnosing environmental
conditions in Jupiter’s stratosphere, revealing the dynamical and chemical
processes at work.

Acetylene and ethane were first discovered at Jupiter by Ridgway [1974] using
the 1.5 m McMath solar telescope at Kitt Peak. The first latitudinal profiles
were derived from Voyager-2 IRIS spectra by Maguire et al. [1984], showing
that the zonal abundances of acetylene and ethane were radically different:
the mixing ratio of the former decreased by a factor of three towards the
pole, whilst the latter increased by a factor of three towards the pole. This
was confirmed by Nixon et al. [2007], who analysed mid-infrared observations
taken with the CIRS instrument [Flasar et al., 2004a] during the Cassini flyby
of Jupiter in 2000. These two abundance distributions are surprising, given
that both species are photochemical products of methane, and have an expected
peak production rate about the equator, where the solar flux is the greatest
[Moses et al., 2004].

Very few studies constrain the long-term change in the abundance of ethane.
Kostiuk et al. [1987, 1989] analyzed data from 1982 to 1986 and observed no
change in the ethane abundance. More recently, Nixon et al. [2010] analysed
mid-infrared acetylene and ethane emissions from both the Voyager and Cassini
spacecraft, providing two snapshots of their distribution separated by 21
years, sampling northern fall equinox and northern summer solstice
respectively. They observed an ethane abundance that increased slightly and
became more symmetric between 1979 and 2000. In contrast, the acetylene
abundance went from being almost constant with latitude to having an abundance
distribution that fell sharply towards the pole. They concluded that there
could be seasonal changes in temperature, acetylene, and ethane at all
latitudes and pressure levels. Improvements in ground-based spectroscopic
mapping capabilities were exploited by Fletcher et al. [2016] to provide a
further snapshot of Jupiter’s stratospheric temperatures, ethane and acetylene
in 2014, finding very similar distributions to those seen by Cassini 14 years
earlier. In this work, we expand on the work of Fletcher et al. [2016] to
study stratospheric variability over a 6-year timescale, or half a jovian
year.

Nixon et al. [2010] modelled the lifetimes at 1 mbar to be hundreds of days
for acetylene and hundreds of years for ethane. The former is much shorter
than the jovian year ($\sim$12 years) whilst the latter is likely too long to
sense any short-term seasonal or dynamic behaviour. These two very different
timescales could explain why the distribution of ethane and acetylene appear
so different. If dynamic timescales are either much shorter or much longer
than these lifetimes we might expect the distributions to be identical. If,
however, the typical dynamical timescales are in-between the two lifetimes
then we may expect the two species to show different zonally averaged
meridional distributions [Zhang et al., 2013b, Medvedev et al., 2013, Kuroda
et al., 2014]. However, Liang et al. [2005] suggested that these arguments
based on chemical lifetimes alone were likely too simplistic. They used a
coupled photochemical and dynamical model of Jupiter’s stratosphere to show
that whilst different acetylene and ethane lifetimes could produce different
zonal distributions, they required stratospheric transport timescales at 5
mbar that were 100 times longer than those derived from the Shoemaker-Levy 9
impact observations [Friedson et al., 1999].

At the poles of Jupiter, methane chemistry is also driven by energetic auroral
precipitation [e.g. Sinclair et al., 2017]. This generates enhancements in
ethane and acetylene about the magnetic poles, which rotate at the System III
longitude rate. These components may contribute to the global distribution,
but the mechanisms for this remain unclear, and the present study will focus
on the equatorial and mid-latitudes away from the auroral regions.

One persistent long-term dynamic feature of Jupiter’s stratosphere is the
Quasi-Quadrennial Oscillation [QQO, Leovy et al., 1991, Orton et al., 1991,
1994], whereby the temperature of the equatorial stratosphere oscillates with
an approximate four-year cycle. This is observed as changes in the zonal mean
brightness temperature of methane at any particular pressure level. An
increase in stratospheric temperatures will increase the observed brightness
of acetylene and ethane, but it is unknown if the QQO has a direct role to
play in driving long-term changes in stratospheric abundances.

Here, we investigate how stratospheric temperatures and the distributions of
acetylene and ethane change over a period of six years, between September 2012
and January 2017. We describe our observations in Section 2, followed by the
testing of a variety of different plausible spatial distributions using
atmospheric retrievals in Section 3. The results are described in Section 4,
followed by a discussion, placing them in a broader context in Section 5. We
then summarise the results of this study in Section 6.

TEXES Run | Included? |  | Comment
---|---|---|---
2012 January |  | No |  | Poor weather
2012 September | Yes |  |  | Only methane band
2013 February | Yes |  |  |
2014 February |  | No |  | Poor weather
2014 December | Yes |  |  |
2015 March | Yes |  |  |
2015 November | Yes |  |  |
2016 January |  | No |  | Instrument issues
2016 April | Yes |  |  |
2016 December | Yes |  |  |
2017 January | Yes |  |  |
Table 1: The NASA IRTF TEXES observing runs used in this study. Note that the 2014 December observations were presented by Fletcher et al. [2016]. This usability implied by this table only applies to the medium resolution observations analysed in this study.  Observing run | 744 cm-1 scaling | 819 cm-1 scaling | 1247 cm-1
---|---|---|---
2012 September | N/A | N/A | 1.30
2013 February | 1.10 | 0.73 | 1.00
2014 December | 1.06 | 0.73 | 1.00
2015 March | 1.09 | 0.73 | 1.00
2015 November | 1.04 | 0.68 | 1.00
2016 January | 1.12 | 0.74 | 1.00
2016 April | 1.12 | 0.74 | 1.00
2016 December | 1.09 | 0.77 | 1.00
2017 January | 1.48 | 0.93 | 1.30
Table 2: The multiplicative scaling factor for the acetylene, ethane, and
methane bands for each observing run used in this study. This is derived by
comparing the mid-latitude tropospheric continuum emissions of NASA IRTF TEXES
and Cassini CIRS. This scaling factor was applied to the TEXES observations
and are plotted in Figure 2.

##  2 Observations

The Texas Echelon Cross Echelle Spectrograph [TEXES, Lacy et al., 2002] is a
mid-infrared spectrograph capable of observing at spectral resolutions between
$R=\lambda/\Delta\lambda\sim 2000$ to $R\sim 85$,000, used in a visitor mode
at the 3-m NASA Infrared Telescope Facility (IRTF) in Hawaii. The instrument
covers the wavelength range 5 – 25 $\mu$m at a variety of slit-lengths and
spectral resolutions – here we use the 45′′-long slit (1.4′′ wide in medium-
resolution mode), giving a spectral resolution up to $R\sim$10,000. The long
slit covers the entire diameter of Jupiter, which has an maximum angular size
at opposition of $\sim$45′′. The TEXES detector contains 256 $\times$ 256
pixels.

We use three medium-resolution settings: acetylene at 744 cm-1 (13.4 $\mu$m,
coverage between 742-747 cm${-1}$), ethane at 819 cm-1 (12.2 $\mu$m, coverage
between 815-823 cm-1), and methane at 1247 cm-1 (8.0 $\mu$m, coverage between
1243-1252 cm-1). The methane emissions sense stratospheric temperature, whilst
the acetylene and ethane bands enable the determination of stratospheric
hydrocarbon abundances. From 2013 onwards the TEXES observations fell into a
regular pattern of acquiring eight spectral channels in medium and low
resolution: 538 and 587 cm-1 in the Q-band, 745, 819 and 1248 cm-1 for
stratospheric emission; and 900, 960 and 1160 cm-1 for tropospheric structure.
The motivation for choosing these channels is explained in more detail by
Fletcher et al. [2016].

The slit was aligned along the north-south terrestrial meridian, and was
stepped across the disc of Jupiter, building up a spectral cube of two spatial
dimensions and one spectral dimension. At the beginning and end of each
spectral cube, calibration flat-field and black-body spectra were obtained by
moving a card of known temperature in front of the instrument aperture.
Typical exposure times are $\sim$4 s per spectrum, with a full scan of Jupiter
taking about 5 minutes.

These observations are wavelength calibrated using the telluric skylines and
flux calibrated using the calibration black body observations and the TEXES
‘pipe’ pipeline software [Lacy et al., 2002]. Once calibrated, the calculated
projection of the limb of Jupiter was fitted to the observations by eye,
enabling the allocation of planetographic latitude, System III longitude, and
emission angle to each pixel. This information can be used to project the
calibrated spectral cube onto a latitude and longitude grid, which in turn
enables us to average several spectral cubes together to build up complete
latitude–longitude maps for each wavelength.

We analyse the acetylene, ethane, and methane TEXES observations of Jupiter
obtained between 2012 and 2017, listed in Table 1. Because of weather and
technical issues, not all observing runs produced data usable for this study.
The September 2012 observations had very limited longitude coverage for the
acetylene and ethane bands, but we were able to construct a near-complete map
of methane, allowing us to retrieve temperature. The January 2016 observations
suffered from a partial obstruction of the light path of the instrument by
mylar, following a routine servicing of the instrument. The equatorial TEXES
spectra from the observing runs, averaged between 30∘N and 30∘S, are shown in
Figure 1. The longitude coverage is complete for all runs, apart from
September 2012 (see Figure 3).

Figure 1:  The equatorial spectra of Jupiter for the epochs listed in Table 1,
showing the three wavelength bands: 744 cm-1, 819 cm-1, and 1247 cm-1 (left to
right). The black line is the observed intensity, the grey shaded regions is
the uncertainty on the intensity and the purple line is the telluric
absorption. The dashed lines shows the wavenumber range used for the NEMESIS
retrievals. The spectra have been shifted to rest wavelengths. Figure 2:  The
intensity scaling factor used for the TEXES observations analysed here. Each
cross represents an individual acetylene data cube, whilst stars indicate
individual ethane cubes. The factor is approximately the same for all years,
apart from January 2017. These factors were derived by comparing the intensity
of the tropospheric mid-latitude emission to that of Cassini CIRS.

The TEXES detector displays non-linear behaviour that is a function of the
energy flux that falls on the detector. Since the energy flux is dependent on
the spectral resolution, this becomes a noticeable issue at medium and low
resolutions, and in spectral windows where the target has a large energy flux.
At Jupiter, the 744 cm-1 window is brighter than the 1247 cm-1 window by about
a factor of 10 per spectral pixel, which is why we need to introduce a larger
correction factor at 744 than at 1247 cm-1. Fletcher et al. [2016] addressed
this issue in the December 2014 data by introducing a scaling factor, and a
similar approach will be adopted here. In order to correct for this detector
behaviour we scale the TEXES spectra using the continuum emissions from the
troposphere, matching it to a TEXES forward model based on CIRS temperatures
and compositions. The Cassini CIRS instrument is one of the most accurately
calibrated mid-IR spectrometers [Jennings et al., 2017], and a comparison
between the two instruments can be illustrative of inconsistencies in the
TEXES calibration.

To determine the radiance of the tropospheric background, we select a region
void of any stratospheric emissions and telluric absorption features. For the
744 cm-1 band we use the region between 743.0 and 743.1 cm-1 (left of the
acetylene feature in Figure 1). For the 819 cm-1 band we use the region
between 817.4 and 818.1 cm-1 (between the ethane features in Figure 1). We
compare the latitude regions contained within 45∘N to 60∘N and 45∘S to 60∘S,
scaling the TEXES spectra to match the continuum of the CIRS spectrum. We
assume that this region of the troposphere has not changed over the seven
years covered in this study, or since the Cassini observations of 2000. The
obliquity of Jupiter is 3∘, which produces no discernible seasonal behaviour
in either the troposphere or stratosphere [e.g. Conrath et al., 1990]. This is
also outside of the range of tropospheric latitudes where belt/zone
variability is observed [Fletcher, 2017]. Table 2 lists the multiplicative
scaling factors used for each observing run. These are shown in Figure 2. The
TEXES observations in January 2017 stand out as particularly curious, as both
acetylene and ethane required a scaling inconsistent with the previous
observing runs. In addition, both September 2012 and January 2017 required a
scaling of the methane band – they were scaled to the mean methane radiance of
the other set of observations, which appeared well calibrated. The September
2012 data used a set of non-nominal detector bias and gain settings, producing
a strong non-linearity of response, whereas the January 2017 data anomaly was
caused by erroneous temperature readings for the flat-field card, producing
over-compensating flat-fields

Fletcher et al. [2016] did preform a scaling on the 1247 cm-1 channel, but
found it made only a small difference on the retrieved temperatures.
Additionally, the 1247 cm-1 band lacked continuum emission clear from
overlying methane emissions so we were unable to produce a scaling factor for
this band, and it is assumed to be 1.0, apart from at the dates mentioned.

Figure 2 shows that the calibration corrections are constant with time, apart
from January 2017, indicating that this is a systematic issue in the TEXES
calibration pipeline, related to the non-linear effect outlined above.

We also adopt a shift-and-stretch fit of the wavelength scale (i.e. a linear
fit: position and scale) to better match the rest wavelength of the
hydrocarbon emissions, subtracting the Doppler shift of the planet, in the
same manner as Fletcher et al. [2014, 2016]. Once the spectra are transformed
into the rest frame of the hydrocarbon emissions, they are interpolated so
that each observing run is on the same wavenumber scale as was observed on
December 2014.

Here, we used the telluric absorption as a measure of the quality of the data,
directly linking it to the uncertainty. When the telluric absorption is high,
the signal-to-noise becomes low, which produces a large uncertainty. The
telluric absorption is shown as purple in Figure 1. We estimate the error on
the observed intensity, $\Delta I$, by the following expression:

$\Delta I=0.08\times\frac{I_{max}}{S_{n}}$ (1)

where $I_{max}$ is the peak intensity in a particular wavelength band and
$S_{n}$ is the fractional telluric transmission, defined as unity when the
Earth’s atmosphere lets through all of the light emanating from Jupiter, and
zero when all of the light is absorbed. The 0.08 multiplier was determined by
measuring the noise floor away from the disk of Jupiter.

Figure 1 shows the mean equatorial spectrum for each wavelength band and each
epoch, with the scaling factors of Table 2 applied. The black lines are the
observed intensities, and the grey shaded regions indicate the uncertainty in
the emission. The purple lines indicate the telluric absorption, which ranges
from significant in the 744 cm-1 band to almost nonexistent in the 819 cm-1
band. When the telluric transmission is small, i.e. approaching 0%, the the
uncertainty in the observed radiances becomes large, as outlined above.

For our retrievals we picked a wavelength range for each band that was
relatively un-obstructed by telluric absorption (purple lines in Figure 1) for
all of the observing runs. For acetylene we used the wavelength range 743.1 to
743.5 cm-1, for ethane we used 816.5 to 820.0 cm-1, and for methane we used
1245.0 to 1247.5 cm-1. These wavelength regions are indicated by vertical
dashed lines in Figure 1. For each set of observations, we limit the latitude
range to $\pm$70∘, avoiding most of the polar aurora, regions with chemistry
driven by impact ionisation.

Figure 3: From left to right, maps of acetylene, ethane, and methane emissions
extracted from the 744, 819 and 1247 cm-1 medium spectral resolution channels
on the TEXES instrument, respectively. The latitudes are planetographic and
the longitudes are System III. All the channels have been scaled as to show
the observed intensity at all latitudes. The solar ecliptic longitude
$\psi_{SUN}$ is indicated, with $\Psi_{SUN}$ = 90∘ representing northern
summer solstice.

###  2.1 Maps of stratospheric hydrocarbons

Figure 3 shows longitude–latitude maps of acetylene, ethane and methane for
each of the usable observing dates listed in Table 1, between September 2012
and January 2017, with the scalings of Table 2 applied. The acetylene and
ethane maps have the tropospheric background subtracted, by subtracting the
continuum upon which the hydrocarbon features sit, and then summing the
discrete line features. In addition, in order better to show the observed
brightness across all latitudes, the ethane map has been flattened by
subtracting off a cosine curve that approximately follows the general trend in
the emission. This has the effect of removing the large-scale latitudinal
distribution and highlighting smaller changes over time.

There is a brightening in all three wavelength bands at about about 30∘N,
appearing in December 2014. This is above the tropospheric North Temperate
Belt, seen between $\sim$24∘ and $\sim$31∘ latitude [NTB, Fletcher et al.,
2016]. The enhancement subsequently dissipates over the following few years,
but still evident in January 2017, as previously noted by Fletcher et al.
[2017].

The maps in Figure 3 have been scaled to show the mid-to-low latitude
emissions, rendering the auroral emissions about the poles saturated. Still,
they show a remarkable degree of temporal variability. This set of
observations begin near northern summer solstice at Jupiter (March 2012), and
end near southern summer solstice (May 2018). This change in viewing geometry
is likely to contribute to the observed changes. Note that the correct
emission angles were used in the retrievals, outlined in the following
section. The analysis of the auroral emissions as observed by TEXES is outside
the scope of this study.

Figure 4: The spectra of acetylene, ethane, and methane from December 2014, at
latitude 25∘N for each of the four hypotheses. The first row is hypothesis A
(uniform distribution), second row is hypothesis B (symmetric distribution),
third row is hypothesis C (asymmetric distribution), and the bottom row is
hypothesis D (distributions change with latitude and time). The observations
have been scaled by the factors listed in Table 2.

###  2.2 NEMESIS

We invert the observed TEXES spectra to determine vertical profiles of
temperature and abundances, in order to investigate how these change over
time. To do this we use the NEMESIS radiative-transfer and retrieval code
[Irwin et al., 2008]. Inherent in the optimal-estimation process is an a
priori knowledge of the atmospheric system in the form of vertical profiles of
temperature and composition based on previous observations or model
predictions. The NEMESIS retrieval produces a best fit to the observed
spectra. In particular, the a priori uncertainty on the temperatures ensures
that the final retrieved profile is smooth and realistic. The strength of mid-
infrared emission from acetylene and ethane depend both on their abundance and
the temperature of the line-forming region, whereas methane is vertically
well-mixed below its homopause, and so we can use methane emission as a sensor
of stratospheric temperature.

The temperature and abundance measurements remain degenerate. The retrievals
can thus be done in either two stages, first temperature, then abundances, or
in a single stage. If we do the former we would rely on the fact that the
retrieved temperatures from the methane band were an accurate representation
of the temperatures in the ethane and acetylene line forming regions, which
may not be the case. By retrieving the temperature and abundance
simultaneously the degenerate effects are properly accounted for in the
resulting uncertainties on the retrieved profiles. Using NEMESIS we
disentangle the contribution of temperature, acetylene and ethane abundances.

We use the same a priori atmosphere as Fletcher et al. [2016], which is
derived from Cassini CIRS observations [Nixon et al., 2007, Fletcher et al.,
2009], in addition to the same set of spectral data and k-tables. For each
NEMESIS retrieval, the temperature was allowed to stray a maximum of 5 K from
the a priori temperature profile. This corresponds approximately to the range
of variability observed at the 1 mbar level in the stratosphere of Jupiter
[Nixon et al., 2010].

Fletcher et al. [2016] calculated the contribution functions for each of the
medium resolution TEXES channels used here. The methane band at 1247 cm-1
samples pressures between 1 and 10 mbar, the acetylene band at 744 cm-1
samples between 5 and 100 mbar, and the ethane band at 819 cm-1 samples the
stratosphere between 0.5 and 50 mbar. While our observations could contain
sufficient information to determine the vertical structure of acetylene and
ethane, we have chosen to fix the vertical structures to the a priori, and to
simply scale them in the retrievals.

At the poles, chemistry driven by auroral particle precipitation, centred
about the offset magnetic field, generates elevated temperatures and modified
hydrocarbon distributions that are highly localised in latitude and longitude
[e.g. Sinclair et al., 2017]. In order to exclude emission associated with the
auroral process, we limit the latitude range of our retrievals to be $\pm$70∘.

The observed TEXES acetylene, ethane, and methane spectra were used to
retrieve zonally-averaged atmospheric profiles of acetylene, ethane and
temperature to examine if and how these parameters change over time. Spectral
fits of acetylene, ethane and methane retrieved by NEMESIS from the December
2014 dataset are shown in Figure 4.

Figure 5: The acetylene and ethane volume mixing ratio (VMR) at 1 mbar for
each of the hypothesis tested in this study. For hypothesis A, B, and C, only
the temperature is retrieved, keeping the hydrocarbon distributions fixed,
where the solid line is hypothesis A, the dotted line is hypothesis B, and the
dashed line is hypothesis C. For hypothesis D, temperature is retrieved along
with acetylene and ethane.

##  3 Analysis

Previous examinations of Jupiter’s stratospheric emission have typically
allowed temperatures and chemical abundances to vary freely to produce good
fits to the data [e.g. Nixon et al., 2007, 2010]. Here, the TEXES data are
subject to calibration changes from run to run, weather changes on Earth,
degeneracies in the retrieval of temperature and composition, and the issue
that the abundance measurements are extremely sensitive to any systematic or
random uncertainties propagating through the temperature measurements.
Therefore, we simply don’t take the ‘full’ retrieval at face value, and
instead we develop four distinct hypotheses. One of these is the full
retrieval, whilst the others represent simplified scenarios for the
distribution of the hydrocarbons.

We will investigate whether the time-series of NASA IRTF TEXES observations
can distinguish between four distinct hypotheses that describe the zonally-
averaged distribution of both acetylene and ethane over time:

  * 1.

Hypothesis A: The abundance does not change with latitude or time, and is
therefore latitudinally uniform for all dates. If this were the case, then the
variable emission seen in Figure 3 would be generated by temperature changes
alone.

  * 2.

Hypothesis B: The abundance is symmetric about the jovigraphic equator and
does not change with time.

  * 3.

Hypothesis C: The abundance is asymmetric about the jovigraphic equator and
does not change with time.

  * 4.

Hypothesis D: The abundance changes with both latitude and time.

The zonally-averaged meridional profiles of the volume mixing ratio (VMR) for
acetylene and ethane at 1 mbar for each of these hypotheses can be seen in
Figure 5. The acetylene zonal profile for hypothesis A (uniform) is the
average value from all epochs and all latitudes of the profiles of hypothesis
D (time-variable). For hypothesis B (symmetric), the mean profile of Figure 5b
was added to the mirrored mean profile of Figure 5b, then averaged and
smoothed between 40∘N and 40∘S. The profile for hypothesis C (asymmetric) is
the mean of the profiles of hypothesis D (time-variable). For hypothesis D
(time-variable) we retrieve temperature, acetylene, and ethane for all years,
whilst for hypothesis A (uniform), B (symmetric), and C (asymmetric) we only
retrieve the temperature, keeping the acetylene and ethane distributions fixed
according to Figure 5a and Figure 5c. The same process was applied to derive
the hypotheses distributions for ethane – see Figure 5c and 5d.

Figure 6: The normalised goodness of fit parameter, $\chi^{2}$ as a function
of latitude for the acetylene channel (744 cm-1) from the NEMESIS retrievals
of the NASA IRTF TEXES data. The results for hypotheses A, B, C and D are
respectively shown in the 1st, 2nd, 3rd and 4th panels. The value of the
$\chi^{2}$ is largely driven by signal-to-noise, and a direct comparison of
the absolute $\chi^{2}$ is meaningless.

The dotted line in Figure 5a shows the average of the acetylene profiles in
Figure 5b, with a peak volume mixing ratio of about 0.8$\pm$0.2 ppm at 30∘N,
and a value of about $\sim$0.25$\pm$0.05 ppm at $\pm$70∘. Similarly, the
dotted line in Figure 5c shows the average of the ethane profiles in Figure
5d, showing a minimum VMR of $\sim$10$\pm$0.6 ppm at the equator, and
$\sim$18$\pm$1.1 ppm at $\pm$50∘.

The NEMESIS retrieval algorithm calculates fits to the observed spectra, from
which we can calculate the normalised goodness of fit, $\chi^{2}$, defined as:

$\chi^{2}=\frac{1}{N}\sum_{i=\lambda_{start}}^{\lambda_{end}}\frac{(fit_{i}-data_{i})^{2}}{data_{i}}$
(2)

where $N$ is the number of spectral bins, $\lambda_{start}$ and
$\lambda_{end}$ are the wavenumber bounds of interest, $fit_{i}$ and
$data_{i}$ is the fitted and observed radiance in wavelength bin $i$
respectively. Since we are interested in what the differences in $\chi^{2}$
are between our hypotheses in both the acetylene and ethane spectra,
individual $\chi^{2}$ are calculated for the 744 cm-1 and 819 cm-1 channels.
The $\chi^{2}$ parameter is strongly dependent on the signal-to-noise of the
observed spectrum, and larger $\chi^{2}$ means a larger discrepancy between
the observed spectrum and the retrieved model spectrum. In turn, the signal-
to-noise is dependent on a number of parameters, e.g. observing conditions,
dark currents, and readout noise. It is therefore difficult to compare
spectral fits from different observing runs which have different signal-to-
noise. This is illustrated in Figure 6, which shows the retrieved $\chi^{2}$
for each hypothesis and observing run for the acetylene channel. The March
2015 has almost always the highest $\chi^{2}$, meaning it was more challenging
to fit with our spectral model. In contrast, the April 2016 run has the lowest
$\chi^{2}$, indicating a good signal-to-noise. All of the $\chi^{2}$ profiles
in Figure 6 show an increase at about $\pm$15∘, and towards the poles – this
is also driven by signal-to-noise, as a noisier spectrum produces a larger
$fit-data$ residuals. These regions also appear much darker in the maps shown
in Figure 3, indicating a lower signal (brightness), and thus mismatches
between observed and modelled spectra form a larger proportion of the observed
spectra.

The spectra shown in Figure 4 highlight how the quality of fit changes
according to which hypothesis is used. We show retrieval models for acetylene
and ethane from December 2014, at a latitude of 30∘N, for each of the four
hypothesis. For acetylene, we see a general decrease in the $\chi^{2}$ as we
move from hypothesis A to D, indicating a better fit to our observed spectrum.

Figure 7: The percentage change in $\chi^{2}$ between the different NEMESIS
retrivals for both the acetylene and ethane wavelength channel. We compare the
quality of fit for each of the four different hypotheses shown in Figure 5.

In order to compare retrieved $\chi^{2}$ of different observing runs, we
define the change in the quality of the fit as a percentage difference of two
sets of retrieved $\chi^{2}$, $\Upsilon$:

$\Upsilon_{mn}=\frac{\chi^{2}_{m}-\chi^{2}_{n}}{\chi^{2}_{m}}\times 100\%$ (3)

where $\chi_{m}^{2}$ and $\chi^{2}_{n}$ represents the $\chi^{2}$ from NEMESIS
retrievals for hypothesis $m$ and $n$. Figure 7 shows the percentage
improvement in $\chi^{2}$, comparing the quality of the fit for each of the
hypotheses above. The different panels in Figure 7 will be discussed in the
following section.

Figure 8: The collapsed acetylene and ethane abundance profile at 1 mbar,
together with the zonal-mean temperature profiles at the same pressure. For
each observing run, the distribution was rescaled to have the same average
abundance equatorward of $\pm$60∘ latitude. In the right panels, for ease of
viewing, error bars are only given for the equatorial data, but are of equal
amplitude at all latitudes. Note that for the September 2012 data insufficient
acetylene or ethane data are available, and so only the temperature retrieved
from methane is shown.

##  4 Results

###  4.1 Temperature

Before discussing the distributions of the hydrocarbons, we begin by reviewing
the temperatures retrieved for each observing run. Figure 8c shows the ‘raw’
temperature retrievals versus latitude at 1 mbar, revealing variability at all
latitudes of about $\pm$5 K with an uncertainty of about $\pm$3 K, with Figure
8f showing the time-series. Note that the temperature from the September 2012
observations was retrieved using only the methane band at 1247 cm-1, rather
than all three spectral channels used in subsequent retrievals. There is a
clear heating event in December-2014 and March-2015 data at 25∘N. This heat
has mostly dissipated by November 2015, although remnants of this
meteorological event are still visible during later observations – see Figure
3. This heating at northern mid-latitudes may coincide with the expansion of
the North Equatorial Belt [NEB, Fletcher et al., 2017], confirming the
elevated 1 mbar temperatures identified by Fletcher et al. [2016] in the
December 2014 TEXES data. The consequences of this mid-latitude heating event
on the hydrocarbon distributions will be explored in the following sections.
In addition, the low latitudes show some temperature variability associated
with Jupiter’s Quasi-Quadrennial oscillation – this phenomenon, and the
impacts on the vertical hydrocarbon distributions, will be discussed in
Section 4.5.

###  4.2 Acetylene – C2H2

Figure 7a shows the percentage improvement in the goodness of fit,
$\Upsilon_{AB}$, for the acetylene channel at 744 cm-1, comparing a
latitudinally uniform distribution (A) to one that is symmetric about the
equator (B). There is a positive change in $\Upsilon_{AB}$ providing strong
evidence that hypothesis B better describes the observations than hypothesis
A: namely, that we must allow the abundances of acetylene to vary with
latitude in order to fit the data, and varying temperature alone is
insufficient.

At mid-latitudes in Figure 7, both in the northern and southern hemisphere,
the $\Upsilon_{AB}$ parameter tends towards zero. The reason for this is shown
in Figure 5a, showing the abundance of acetylene and ethane as a function of
latitude for each of the hypotheses: the volume mixing ratio of hypothesis A
and B, are the same at a latitude of $\pm$50∘.

Figure 7b shows the $\Upsilon_{AC}$ comparison between a flat (A) and
asymmetric (C) acetylene distribution. Similarly as above, the asymmetric
distribution is a much better fit to our observations. Hence, we can rule out
a distribution of acetylene that is constant with latitude.

Figure 7c shows the comparison between the symmetric (B) and asymmetric (C)
hypothesis. Here, a deviation from $\Upsilon_{BC}=0$ indicates that the
asymmetric model at some latitudes and epochs improves and at others worsens
the quality of the fit with respect to a symmetric model. The deviation from
zero occurs at latitudes where the two abundance profiles are different (see
Figure 5a). This indicates that at some latitudes, the distribution of
acetylene cannot be symmetric about the equator, and that the asymmetric
hypothesis is a better description of the data than the symmetric model.

We now compare the asymmetric model to the one where acetylene and ethane are
allowed to vary with latitude and with time, $\Upsilon_{DC}$. The NEMESIS runs
associated with hypothesis D retrieves temperature and scaled abundances of
ethane and acetylene, with the retrieved family of acetylene latitude profiles
being shown in Figure 5b. Figure 7d shows, unsurprisingly, that all epochs
benefit to some degree by having more degrees of freedom in the retrievals.
However, as seen in Figure 5b there remains a systematic offset in the VMR of
the retrieved acetylene abundance of each observing run. Given that these
offsets are systematic, they are likely related to changes in the radiometric
calibration from date to date, and the general spread may be a better
representation of our uncertainty in the absolute abundances being retrieved,
than the ones furnished by NEMESIS. We assume that the acetylene and ethane
abundances do not increase or decrease systematically at all latitudes over
these short timescales. Therefore, what could be interpreted as evidence for
temporal changes in Figure 7d may be just be a result of these offsets. An
attempt to rectify this is performed in Section 4.4.

###  4.3 Ethane – C2H6

Figure 7e shows $\Upsilon_{BA}$, the comparison between the uniform
distribution (A) and symmetric distribution (B) of ethane, with Figure 7f
showing the comparison between the flat (A) and the asymmetric model (C),
$\Upsilon_{CA}$. The positive improvements at all latitudes, apart from at the
ones where the three hypotheses have the same abundance, is evidence that we
can reject the hypothesis of an ethane abundance that is constant with
latitude.

Next, we compare the symmetric (B) to the asymmetric (C) hypotheses,
$\Upsilon_{BC}$, shown in Figure 7g. Here, there are very small improvements
to the quality of the fit, particularly at the equator and at $\sim$30∘N,
which is where the two ethane abundance profiles in Figure 5c are different.
However, these changes are small, and we are unable to state unequivocally
that an asymmetric hypothesis performs better than an symmetric one.
Therefore, from the TEXES data-set used here, a distribution of ethane
symmetric about the equator and invariant with time appears to be a good
representation of the data.

Lastly, we compare the asymmetric hypothesis (C) to the hypothesis where
ethane and acetylene are allowed to vary (D), $\Upsilon_{CD}$, shown in Figure
7h. These profiles show slightly larger departures from $\Upsilon=0$ than
$\Upsilon_{CB}$ in Figure 7h by virtue of having more degrees of freedom, but
they are essentially flat, and we see no evidence that ethane varies over
time.

In summary, this work shows that the TEXES dataset favours an asymmetric and
changing distribution of acetylene, but a symmetric and unchanging
distribution of ethane.

###  4.4 Temporal variability

The retrieved abundances of acetylene and ethane in Figure 5b and 5d shows
that individual retrievals for the same gases all share a common distribution
but have systematic offsets. For example, the acetylene abundance in December
2014 and March 2015 have a very similar shape, whilst being offset
approximately 0.3 ppm across all low- to mid-latitudes. Such a systematic
offset across the entire planet is unlikely to be physical, and masks smaller-
scale local variations in the gaseous composition (e.g., related to wind, wave
and atmospheric circulation). Such systematic biases are more likely due to
small errors in the absolute calibration in all of the TEXES channels, or that
our method of scaling the TEXES observations to Cassini CIRS is not entirely
sufficient. In order to assess how these abundances change over time we scale
the abundance profiles to compensate for these calibration offsets. We make
the assumption that the spatially averaged VMR equatorward of $\pm$60∘
latitude does not change significantly over time, and then scale each
observing run to have the same spatially averaged VMR. The scaled VMR of these
species at 1 mbar can be seen in Figure 8a and 8b plotted versus latitude.
Figure 8c shows the retrieved temperature at the same pressure level and
demonstrates some differences of the order of 5 K from date to date. Whether
this is real, or related to differences in the observing conditions, is hard
to say. The right column shows the temporal evolution of acetylene (8d),
ethane (8e) and temperature (8f) at three different latitudes, 25∘S, 0∘, and
25∘N. The red error bars shows the error associated with the retrievals at the
equator – the other latitudes have errors of similar magnitude.

The collapsed acetylene distribution in Figure 8a shows that there is
variability in the retrieved distributions with time, although error bars for
these retrievals are on the order of $\pm$0.15 ppm. The time-series in Figure
8d shows a distribution that starts off clearly asymmetric, and 2013-14, with
northern latitudes demonstrating higher acetylene abundances than southern,
but in moving towards the last set of observations in January 2017 the
distribution is clearly becoming more symmetric. The error bars are
substantial but the deviations over time are not random, instead appearing at
$+25^{\circ}$ to fall over the 6-year period of the dataset. This changing
acetylene asymmetry is consistent with our conclusions in Section 4.2.

The collapsed ethane distribution in Figure 8b shows less variability than the
acetylene, with an uncertainty of about $\pm$1 ppm. The time-series in figure
8e shows very little variability, apart from a suggestive increase in the
equatorial abundance between November 2015 and January 2017, which remains
inside the levels of uncertainty.

###  4.5 Quasi-Quadrennial Oscillation

Our data-set covers about half a jovian year, slightly longer than the 4-year
cycle of the QQO, and so we can examine to what extent the medium-resolution
TEXES data can address this cyclical behaviour in the stratosphere. Cosentino,
et al. [accepted] used higher-spectral resolution TEXES observations to show
that an alternating pattern of warm and cool thermal anomalies descends
downwards over the equator over time, with an amplitude of about $\sim$5 K.

The 1 mbar temperature time-series shown in Figure 8f does not readily reveal
the QQO cycle at the equator (solid line). This is because the temperature
differences seen at 0∘ latitude (Figure 8c) are mainly driven by the small
calibration offsets present in the TEXES medium-resolution dataset, generating
a temperature scatter that has a similar magnitude to the expected QQO
temperature amplitude. In an attempt to correct for this, we calculate the
temperature anomaly, as outlined below.

The temperature anomaly is calculated by first rescaling the temperature to a
common average, using only the temperatures contained within 10∘S to 10∘N. The
anomaly is then the difference between the rescaled temperature for a
particular observing run and the average rescaled temperature. This procedure
attempts to correct for the calibration offsets, in a similar manner as for
acetylene and ethane in Figure 8a and 8b. Figure 9 shows the the stratospheric
temperature anomalies over time, as a function of pressure and latitude. This
method shows that we still see similar temperature fluctuations as Cosentino,
et al. [accepted], even though the spectral resolution of our data is a factor
of 5-8 lower. Since we observe the QQO temperature oscillation to be present
in the medium-resolution TEXES data analysed here, we can now address to what
extent the QQO affects the abundances of acetylene and ethane. For example, in
a zonal time-series, if a minimum in temperature coincides with a minimum
abundance of acetylene, that would suggest an upwelling of cold acetylene-
depleted air, a secondary circulation pattern associated with the QQO cycle.

The collapsed acetylene and ethane abundances in Figure 8d, 8e are corrected
for the TEXES calibration offsets (see Section 4.4), and the time-series in
Figure 8d and 8e shows how these species vary over time. The acetylene
distribution in Figure 8 does show a minima at the equator in late 2014/early
2015, whilst ethane appears unchanging over time. This minimum in the 1 mbar
acetylene abundance may be connected to the temperature minimum in the QQO
temperature anomaly, consistent with an upwelling of cold acetylene deficient
air. However, the variability is completely contained within the retrieval
errors and so this dataset provides no concrete evidence that the QQO cycle
affects the acetylene and ethane abundances. This analysis is at the limit of
what we can do with these data, and in order to investigate to what extent the
QQO cycle modulates the hydrocarbon distributions we need to employ higher
spectral resolution observations.

Figure 9: The temperature anomalies for each epoch as a function of latitude
and pressure. These distributions are the difference from the mean temperature
for all epochs. We have normalised the temperature maps to account for
calibration offsets. The errors on the retrieved temperatures is $\sim$3 K.
The Quasi-Quadrennial Oscillation temperature anomaly can be seen moving
downwards at the equator at any particlar pressure over time, alternating
between positive and negative $\Delta T$.

##  5 Discussion,

###  5.1 Distributions of acetylene and ethane

In analysing the mid-infrared TEXES observations obtained between September
2012 and January 2017 we have confirmed that the two hydrocarbons are
decoupled from one another, with acetylene decreasing towards the pole, and
ethane increasing toward the pole. This decoupling is a permanent feature of
Jupiter’s stratosphere, persisting throughout the 6-year observing period and
was present also during Cassini’s flyby of Jupiter in 2000 [Nixon et al.,
2007]. Additionally, we have found that the distribution of acetylene is
asymmetric about the jovigraphic equator, being more abundant at mid-northern
latitudes than at mid-southern latitudes. The acetylene distribution moves
from being asymmetric in 2012 to being near-symmetric in 2017, although the
error bars accrued from the retrieval and subsequent scalings are on the same
order as the observed asymmetry.

The fact that the acetylene and ethane distributions are so different is
perplexing. The abundances of these hydrocarbons are governed predominantly by
the solar flux, which has the highest energy density about the equator.
Additional more complex sources and sinks, such as ion-neutral chemistry,
subsequently alters these distributions. The hydrocarbons are transported by
two principal means: 1) Diffusive processes, where molecular and turbulent
diffusion acts in the vertical direction, whilst meridional turbulent
diffusion act in the latitudinal direction [e.g. Lellouch et al., 2002] 2)
Advective processes, such as the movement of a global circulation cell. If
acetylene and ethane had very short lifetimes, say hundreds of days, we may
expect a poleward decrease for both species, following the daily averaged
meridional solar flux variation [Moses et al., 2004, Liang et al., 2005, Zhang
et al., 2013a]. If instead they had very long lifetimes, say hundreds of
years, then the global circulation of upwelling at the equator and downwelling
at the pole [Conrath et al., 1990, Liang et al., 2005], would form a
distribution increasing towards the pole. The peak production of ethane occurs
at $\sim$1 $\mu$bar [Moses et al., 2005], and it is transported to the lower
stratosphere via diffusion. The fact that ethane increases towards the pole
despite having a peak production rate at the equator indicates that the
depletion rates are slower than the rates at which ethane is transported
towards the pole. Observations of Jupiter’s stratosphere following the
Shoemaker–Levy 9 impact [e.g. Friedson et al., 1999, Lellouch et al., 2002,
Griffith et al., 2004] could be explained with only meridional diffusion,
although Lellouch et al. [2006] required both meridional diffusion and
advection to explain the abundance distributions of HCN and CO2. At Saturn,
turbulent diffusion has been shown to be insufficient to explain the increase
of ethane abundance with latitude [Moses et al., 2007]. Hydrocarbons in
Jupiter’s stratosphere are likely mixed by both advective and diffusive
processes, and future modelling work will be required to connect the
atmospheric chemistry with diffusion and general circulation in the
stratosphere.

Acetylene, on the other hand, has a distribution centred about the equator. If
acetylene has a lifetime much shorter than the advection time-scale, with
upwelling at the equator and downwelling at the pole, then we would expect it
to have high abundances close to where it is created [Liang et al., 2005,
Zhang et al., 2013b], which is what is observed. In addition, it seems likely
that these distributions are stable over long time periods given that the
distribution is similar to that observed by CIRS [Nixon et al., 2007]. Whilst
Liang et al. [2005] suggested that the lifetime argument in isolation is
likely too simplistic, the lifetimes calculated by Nixon et al. [2010] are
hundreds of days for acetylene, and hundreds of years for ethane. If the time-
scale for advecting these species globally is intermediate between the
acetylene and ethane chemical timescales, say a few years, then the long-lived
ethane could be showing the abundance redistributed by global scale advection,
meridionally transporting material from the equator, where the hydrocarbon are
produced, to the poles. The short-lived acetylene would not survive these long
dynamical cycles, and thus remaining predominantly about the equator.

It must also be noted that the poles of Jupiter are a rich source of methane
chemical products, due to the ion-neutral reactions driven by particle
precipitation from the magnetosphere [Sinclair et al., 2017]. This source of
both acetylene and ethane could be evident at latitudes greater than $\pm$70∘,
but it remains unclear whether the hydrocarbons produced at these high
latitudes can be advected equatorward to produce the distributions we observe.

###  5.2 Temporal evolution of acetylene

Since the axial tilt of Jupiter is small ($\sim$3∘) we do not expect any
extreme seasonal behaviour in the planet’s stratosphere [Conrath et al.,
1990]. However, Nixon et al. [2010] observed broad-scale abundance changes in
both acetylene and ethane between 1979 and 2000. Here, we are seeing small
changes over a period of 5 years, between 2013 and 2017. In particular, there
is a change in the symmetry of mid-latitude acetylene, beginning in November
2015, with the abundance at $+25^{\circ}$ decreasing and the abundance at
$-25^{\circ}$ increasing. This suggests that the distribution is becoming more
symmetric as we head towards January 2017. This can also be seen in Figure 7c,
where the December 2016 and January 2017 observing runs produce lines closest
to $\Upsilon_{CB}=0$, indicating that the asymmetric hypothesis offers no
improvement on the symmetric. This evolution of the acetylene, from asymmetric
to symmetric, starts when we see the temperature enhancement at 25∘N in
December 2014 and March 2015 (Figure 8f). The enhancement in mid-northern
latitude temperatures in 2014-15 was first observed in Fletcher et al. [2016].
It appears to be related to the significant longitudinal variability of the
NEB seen in Figure 3, suggestive of wave phenomena propagating in the
stratosphere. The localisation of the highest brightness temperature in
December 2014 near to a ragged northern edge of Jupiter’s NEB prompted
speculation that it could be related to dynamic activity in the troposphere,
particularly that related to an expansion of the NEB [Fletcher et al., 2017].
The stratospheric wave pattern was observable at higher spatial resolution
from VLT-VISIR [Lagage et al., 2004] throughout early 2016. This TEXES dataset
confirms that the wave tracked by Fletcher et al. [2017] had a lower amplitude
than that seen in 2014-2015 by TEXES: i.e., Fletcher et al. were likely seeing
the after-effects of the process that caused the thermal enhancement near
270∘W in 2014-15. The cooling of the perturbation over a $\sim$1-2 year
timescale could be caused both by radiative cooling from stratospheric
hydrocarbons, combined with mixing and homogenisation with longitude by the
propagation of the wave itself.

In this study we present data from 2012 to 2017. A longer time series is
beyond the present scope of the analysis, but a similar northern wave was
observed during Cassini [Flasar et al., 2004b, Li et al., 2006, Fletcher et
al., 2016] and at the same time acetylene was observed to be more asymmetric
[Nixon et al., 2007]. The acetylene asymmetry could be driven by a vertically
propagating wave, advecting acetylene-enriched air from higher stratospheric
levels to the 1-mbar level. In such a case, we would expect the acetylene
asymmetry to be more prominent during periods of strong wave activity near the
northern edge of the NEB.

A wave-generated bulk transport towards lower altitudes (and lower
temperatures) would also move ethane, suggesting that this too would have an
asymmetry. Yet the observed ethane distribution is inconsistent with an
asymmetric distribution. This could be a result of the fact that fact that
acetylene has a stronger vertical gradient in the region [Moses et al., 2005]
to which TEXES is sensitive. Thus, a small vertical displacement can have
substantial consequences for the VMR perturbation at the 1-mbar level. Ethane
has a shallower gradient than acetylene [Moses et al., 2005], so it would take
a far larger displacement to have any notable consequences on the ethane
emission.

In summary, the spatial variability in the hydrocarbons appears to have three
causes: 1) small-scale and short-lived variation caused by stratospheric
mixing (and potentially wave activity); which strongly affects species with
large vertical gradients in abundance; 2) large-scale upwelling at the equator
and downwelling at the poles generate gradients that are determined by the
balance between the chemical timescale and the global circulation timescale
[Conrath et al., 1990]; and 3) variable production via ion-neutral chemistry
in the polar regions as described by e.g. Sinclair et al. [2017], followed by
advection to lower latitudes.

##  6 Summary

We have analysed NASA IRTF TEXES observations obtained between 2012 and 2017.
We made four distinct hypotheses about the distribution and temporal evolution
of acetylene and ethane: three that are invariant with time, but have a flat
(A), symmetric (B) and asymmetric (C) distribution about the equator, with the
last hypothesis being that they vary across all latitudes with time.

The TEXES data supports the hypothesis that acetylene is best described by an
asymmetric distribution about the equator, that varies with time. Ethane, in
contrast, is symmetric about the equator and does not vary with significantly
with time, although there is some localised variability at mid-latitudes whose
source is uncertain.

We suggest that the change in the abundance distribution of acetylene is
driven by stratospheric waves that mix acetylene-rich air to lower altitudes.
The differences between the distributions of acetylene, which increases
towards the equator, and ethane, which increases towards the pole, is likely
linked to their different chemical lifetimes. Acetylene is only short lived
(hundreds of days), so does not serve as a tracer of longer timescale
dynamics. Ethane has a very long lifetime (hundreds of years), and is re-
distributed by equator-to-pole transport that occur over very long timescales.

##  7 Acknowledgements

This work was supported by the UK Science and Technology Facilities Council
(STFC) Grant ST/N000749/1 for Melin. Fletcher was supported by a Royal Society
Research Fellowship at the University of Leicester. Melin, Greathouse, Giles,
Fletcher and Orton are Visiting Astronomers at the Infrared Telescope
Facility, which is operated by the University of Hawaii under contract
NNH14CK55B with the National Aeronautics and Space Administration.

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