Seasonal and monthly zonal medians of water vapour in the upper troposphere
and lower stratosphere (UTLS) are calculated for both Atmospheric Chemistry
Experiment (ACE) instruments for the northern and southern high-latitude
regions (60–90
The Arctic oscillation (AO), also known as the northern annular mode (NAM),
explains 64 % (
Water vapour is the most important greenhouse gas in the atmosphere (Lacis et
al., 2010), playing an important role in climate change by magnifying changes
in radiative forcing by longer-lived greenhouse gases through the water
vapour feedback (Dessler and Sherwood, 2009). A variety of observations have
shown that, at near-global scales, specific humidity in the troposphere has
been increasing along with atmospheric temperatures in a manner consistent
with that predicted by the Clausius–Clapeyron equation –
approximately 7 % K
In order to understand and attribute long-term changes, internal modes of
variability, particularly those with longer periods, should be considered
simultaneously. In the extratropics, the annular modes explain more of the
month-to-month and year-to-year variance of the atmospheric flow than any
other climatic phenomenon (Thompson and Wallace, 2000;
The AO exhibits the largest variability during the cold season (Thompson and
Wallace, 2000). Groves and Francis (2002) related TOVS (TIROS Operational
Vertical Sounder) precipitable water vapour net fluxes across 70
Here, the relationship between water vapour in the upper troposphere and
lower stratosphere (UTLS) at northern and southern high latitudes (60–90 and
60–90
SCISAT was launched in 2003, carrying a suite of solar occultation
instruments to carry out the mission named the Atmospheric Chemistry
Experiment (ACE) (Bernath et al., 2005). The ACE instruments measuring water
vapour are Measurements of Aerosol Extinction in the Stratosphere and
Troposphere Retrieved by Occultation (MAESTRO, McElroy et al., 2007) and the
Fourier Transform Spectrometer (FTS, Bernath et al., 2005). The ACE data sets
begin in February 2004. The measurements provide a unique combination of high
vertical resolution and the ability to measure the water vapour profile from
the mid-troposphere to the lower stratosphere, where the volume mixing ratio
(VMR) is < 10 ppm (parts per million), below the lower detection
limit of the nadir-sounding AIRS (Gettelman et al., 2004). HIRS
(High-Resolution Infrared Radiation Sounder) is the nadir sounder used in the
last two Intergovernmental Panel on Climate Change (IPCC) assessments (e.g.
Hartmann et al., 2013) for long-term trend studies of upper tropospheric
humidity (Soden et al., 2005; Shi and Bates, 2011). However, the trend
analysis of the HIRS data set is confined to the region 60
The MAESTRO water vapour retrieval method follows the one used previously
(Sioris et al., 2010). Data are available at
POAM III has been validated down to 8 km or
Besides the validation results, it is also valuable to look at retrieval
uncertainties to understand the expected data quality. Based on an analysis
of 1 year of southern high-latitude data, the MAESTRO water vapour retrieval
relative uncertainty is found to be best at the lowest retrieval altitude of
5 km and is typically
For the Northern Hemisphere, the monthly tropopause height is defined as the
height above 5 km that is the lower of the lowest local minimum or the
lowest height at which the lapse rate is < 2 K km
To arrive at water vapour anomalies, there are three steps: creation of the
time series (e.g. monthly or seasonal), compilation of the climatology, and
deseasonalization. Monthly time series are created at northern and southern
high latitudes using occultation profiles in the 60–90
Vertically, the binning is done in 1.0 km intervals centered between 5.5 and
22.5 km (above 23 km, the MAESTRO water vapour absorption signal tends to
be below the lower detection limit). A month is included in the climatology
and anomaly data set at any altitude where
The monthly climatology, used to deseasonalize the time series, is generated
by averaging the monthly medians and means over the available years. Figure 1
illustrates the relative difference between MAESTRO and ACE-FTS water vapour
climatologies at both high-latitude bands. At southern high latitudes,
monthly means are preferred for Fig. 1 and for the illustrated time series
(Fig. 2) instead of medians which, for MAESTRO, have a dry bias in the widely
dehydrated winter lower stratosphere. However, systematic and seasonally
dependent biases cancel out given the sensor-specific deseasonalization as
discussed at the end of this section, so only medians are used in the
regression analyses (Sect. 2.5). An ACE-FTS high bias of
(Orange) Relative differences between ACE-FTS and MAESTRO climatological medians averaged over the 8 months of sampling the northern high-latitude region and their standard deviation; (blue) relative differences between ACE-FTS and MAESTRO climatological means averaged over the 8 months of sampling the southern high-latitude region and their standard deviation. The horizontal bars show the standard deviation of the differences between the two climatologies over the 8 available months. To account for vertical resolution differences, the MAESTRO climatology was vertically smoothed with a 3 km boxcar.
The monthly water vapour VMR time series are shown for the Southern and
Northern Hemisphere in Figs. 2 and 3, respectively. At each height, the
monthly climatology (e.g. Fig. 4) is subtracted from the time series (e.g.
Fig. 2) to give the absolute deseasonalized anomaly. Dividing the monthly
absolute anomaly by the monthly climatology gives the relative anomaly. Note
that July and August 2011 were omitted from the MAESTRO southern
high-latitude climatology at 6.5–9.5 km due to a
Time series of the MAESTRO monthly mean water vapour volume mixing
ratio (VMR) vs. altitude (5.5–22.5 km) at southern high latitudes
(60–90
Note that, because conclusions below about the importance of the annular modes are reached based on water vapour anomalies and the fact the deseasonalization is sensor-specific (i.e. the time series observed by each instrument is deseasonalized using its own climatology), constant biases and seasonally dependent biases are actually inconsequential. Relevant biases are discussed in Sect. 2.5.
Time series of the MAESTRO monthly median water vapour volume mixing
ratio (VMR) vs. altitude (km) at northern high latitudes
(60–90
We use a multiple linear regression analysis to determine the contribution of
the appropriate annular mode to the variability in deseasonalized water
vapour at high latitudes as a function of altitude. The set of available
basis functions includes a linear trend, the monthly AAO (Mo, 2000) and AO
(Larson et al., 2005) indices
(
When determining the response of water vapour to the AO, the AO index plus a
constant are used, and the linear trend is included if it is significant at
the 1 standard error (
The types of biases that could affect the analysis of water vapour
variability are due to
interannual variation in latitudinal sampling, and interannual biases in retrieved water vapour profiles.
Regarding the non-uniform sampling of latitudes by the ACE orbit mentioned in
Sect. 2.4, the correlation between monthly time series of average sampled
latitude in the northern high-latitude region and the Arctic oscillation
index is 0.19, and similarly the correlation between the monthly time series
of average sampled latitude in the southern high-latitude region and the
Antarctic oscillation index is 0.12. Given these very low correlations, ACE's
latitudinal sampling should have a negligible impact on any conclusion about
the response of the observed water vapour anomaly to the annular modes,
although this is tested below using the latitude sampling anomaly as a basis
function. Toohey et al. (2013) estimated monthly mean sampling biases in the
UTLS to be
The MAESTRO water vapour record (Fig. 2) at southern high latitudes is similar to the records of contemporary limb sounders as shown in Fig. 13 of Hegglin et al. (2013).
The dehydration in September that extends downward into the upper troposphere at southern high latitudes (Fig. 4) is clearly observed by MAESTRO annually (Fig. 2).
The variability in the UTWV at southern high latitudes on a monthly timescale
is dominated by the seasonal cycle. The observed seasonal variation is a
factor of
MAESTRO mean climatology (2004–2012) of the vertical distribution
of the water vapour volume mixing ratio in the Antarctic (60–90
The stronger seasonal cycle at northern high latitudes (e.g. at 5.5 km, Fig. 6) is partly due to the non-uniform latitudinal sampling differences in the months of maximum and minimum water vapour VMR, particularly in the Southern Hemisphere. The Northern Hemisphere seasonal cycle amplitude vertical profile (Fig. 6) is thus a truer reflection of the amplitude of the seasonal cycle at high latitudes. Figures 5 and 6 illustrate that the seasonal cycle amplitude of observed water vapour VMR in the lower stratosphere departs from the seasonal cycle amplitude of the saturation vapour VMR due to the isolation of this overlying atmospheric region from large sources of water vapour. According to GEM temperature analyses, the amplitude of the seasonal cycle in temperature is 18 K with a sharp peak in mid-summer (e.g. July), and is generally sufficient to explain the seasonal variation of water vapour VMR and its vertical dependence in the upper troposphere (Fig. 6).
Vertical profile of the seasonal cycle amplitude of Antarctic water vapour observed by three instruments. The amplitude is calculated by taking the ratio of climatological monthly means at maximum (January or December) and minimum (August or September). Note that POAM III has a different orbit that tends to sample consistently at higher latitudes (Nedoluha et al., 2002) and thus tends to have stronger seasonality at 8 km (driven by the larger temperature range). The saturation vapour pressure climatology is obtained using GEM analysis temperatures sampled at ACE measurement locations.
In spite of the large tropospheric seasonality at high latitudes, it is possible to deseasonalize the water vapour records from the ACE instruments and investigate the remaining sources of temporal variability, as shown next.
At 8.5 km, where the largest anti-correlations exist between MAESTRO water
vapour at 8.5 km and the AAO index, it is observed that the relative
standard error on the AAO fitting coefficient is reduced when the regression
is performed using a seasonal timescale rather than a monthly timescale.
Thus, in Fig. 7, the MAESTRO and ACE-FTS seasonal median relative anomalies
for 8.5
Analogous to Fig. 5 but for northern high latitudes. Profiles are presented at their respective native vertical resolutions.
Seasonal median water vapour anomaly time series from MAESTRO (8.5 km) and ACE-FTS (7.5 km) in the Antarctic troposphere and the response of each to AAO determined by linear regression. Seasons with missing data are removed to avoid discontinuities. The markers on the response curves indicate the sampled seasons.
At 8.5 km, where the response of water vapour to AAO has the smallest
relative uncertainty for both ACE-FTS and MAESTRO, the response ranges
between
Vertical profile of response to AAO, using southern high-latitude
water vapour relative anomalies based on monthly medians (2004–2012).
Horizontal bars are
Figure 9 shows the altitude dependence of observed water vapour response to
the Arctic oscillation using all 8 months that sample the northern
high-latitude region. There is a coherent and statistically significant
response (up to the 4
Analogous to Fig. 8, but for northern high-latitude water vapour in
response to the Arctic oscillation. Error bars display
The spatiotemporal sampling of ACE (Bernath et al., 2005) is quite non-uniform on monthly timescales, whereas on seasonal timescales the spatial coverage of the entire high-latitude region becomes more complete. When the latitudinal sampling anomaly is used as a basis function in fitting monthly water vapour anomaly time series, it is generally not a significant term in either hemisphere. Fig. 9 shows that the inclusion of this term does not change the response to the AO, reinforcing the same finding for the response to the AAO (Fig. 8). Clearly, water vapour at high latitudes responds with high fidelity to the local annular mode.
Using the MAESTRO water vapour anomalies, a seasonal time step, and all
seasons, 45 % of the variability is explained at 6.5
The most active season for the AO is from January to March based on monthly
standard deviations of the AO index in the period from 1950 to 2015. This
3-month period was used by Thompson and Wallace (2000). Figure 10 shows a
water vapour anomaly time series for an altitude of 6.5 km, composed only of
January, February, and March (2004–2013). The wintertime anti-correlation
between the ACE-FTS water vapour anomaly and the AO index peaks at 6.5 km
with
Time series of water vapour relative anomalies observed by
ACE-MAESTRO (“MAE”) and ACE-FTS at 6.5
Polar regions have a strong seasonal cycle in UTWV, which is consistent with the seasonality of the local temperature. The importance of the seasonal cycle in local temperature for UTWV seasonality at high latitudes has been stated previously (Chen et al., 1999). On the basis of general circulation model simulations, Del Genio et al. (1994) demonstrated that small-scale moist convection and the mean meridional circulation have a minor role in the seasonal cycle of polar UTWV, and that the primary mechanism is eddy moisture fluxes.
In the Arctic upper troposphere, condensation and precipitation play a minor
role in governing the water vapour abundance on monthly timescales. Near the
Arctic tropopause (250–350 mb), cloud fractions are < 35 %
(Treffeisen et al., 2007) and MAESTRO monthly median relative humidity at
9.5 km is < 40 % in all 63 months in which this instrument has
observed the northern high-latitude region. However, dynamical variability
via the annular modes has been shown here to strongly affect UTWV at high
latitudes. Apart from the seasonal cycle, the Antarctic oscillation is a
dominant mode of variability in upper tropospheric (
As stated in Sect. 1, the AO is most active in the winter, when the surface
is coldest. Therefore less infrared (IR) radiation is emitted and trapped by
AO-related increases in atmospheric water vapour. Over Antarctica, the AAO
instead shows strength in late spring (Thompson and Wallace, 2000) at a time
when there is increased IR radiation emitted by the surface, possibly making
AAO-related water vapour changes more likely to lead to increases in
temperature at the surface and to reduce outgoing longwave flux at the top of
the atmosphere (TOA). The impact of AAO-induced variability of upper
tropospheric water vapour on surface climate and outgoing longwave flux at
the top of the atmosphere is assessed for November 2009 and November 2010, 2
months when the AAO was of opposite phase (see Appendix A for details of the
method). The cooling rate differences at the surface between these negative
and positive phases of the AAO are trivial (< 0.07 K) in late
spring (November). The outgoing longwave flux is reduced by 0.7 W m
In the most recent IPCC report, Hartmann et al. (2013) review the literature
on trends in UTWV observed from satellite instruments. Only one such
publication is cited, namely Shi and Bates (2011). This work uses HIRS data
between 85
The amplitude of the response by water vapour to annular mode oscillations
does not change significantly (1
There is some observational evidence for two mechanisms that could explain how UTWV at high latitudes responds to the annular modes. The first is through annular-mode-related air temperature fluctuations (Thompson and Wallace, 2000), which impact UTWV by changing the saturation vapour mixing ratio. For changes in the saturation vapour mixing ratio to have an impact, there needs to be an available supply of upper tropospheric water vapour.
The second mechanism is through changes to the mean meridional flux itself (e.g. Boer et al., 2001; Devasthale et al., 2012; Thompson and Wallace, 2000), given the latitudinal gradient in water vapour between high and mid latitudes at all upper tropospheric heights. Boer et al. (2001) have already demonstrated the response of mean meridional flux of UTWV to the annular modes using climate model simulations. However, poleward isentropic transport may involve ascent, which may lead to condensation when RH reaches 100 %. If sufficient water vapour condenses, precipitation may occur, which would lower the local VMR of water vapour. But evaporation and condensation play a minor role in the polar tropospheric water budget (Boer et al., 2001), with water vapour representing 99 % of the total water content (Jakobson and Vihma, 2010, and references therein). There are many additional, related arguments in favour of the Eulerian mean meridional circulation as a plausible mechanism to account for the response of high-latitude UTWV to the annular modes. Firstly, the high-latitude upper troposphere has low RH (< 50 %), with the exception of autumn (e.g. March–April in the Southern Hemisphere). Secondly, in this autumnal period of higher RH (e.g. 60 % below 8 km), the annular mode activity is low for either hemisphere and, conversely, the active period for either annular mode falls in a season of low RH. Thirdly, the vertical component of the meridional circulation tends to shift downward during the negative phase of the local annular mode in either hemisphere (Fig. 7 of Thompson and Wallace, 2000), thereby reducing the likelihood of condensation. Fourth, ice crystals formed during poleward ascending motion will tend to return to the vapour phase before precipitating, given the dry, surrounding air (e.g. Prospero et al., 1983). Finally, precipitation may evaporate before descending into the lower troposphere given the vertical gradient in ambient temperature. These five additional arguments suggest that the meridional flux mechanism could be effective in transporting water vapour to the high-latitude upper troposphere on a monthly timescale during the negative phase of the annular mode. Boer et al. (2001) showed that there is an increased poleward upper tropospheric moisture flux via the meridional mean circulation at high latitudes during the negative phase of the annular mode in either hemisphere. According to the analysis of Boer et al. (2001), the mean meridional flow mechanism appears to be of greater relative importance in the high-latitude upper troposphere in the Southern Hemisphere. The effectiveness of the mean meridional flux mechanism in increasing UTWV VMR during negative AAO periods is amplified by the large latitudinal gradients in UTWV between southern mid and high latitudes. Note that these two mechanisms are not correlated spatially with each other to a high degree. This has been verified using the latitude and altitude dependence of their responses to the annular modes (Thompson and Wallace, 2000). The two mechanisms are complementary in that they both increase UTWV at high latitudes during the negative phase of the local annular mode.
There are other mechanisms that are considered, such as tropopause variations (discussed below) and meridional eddy moisture fluxes (Boer et al., 2001). As mentioned above, eddies are primarily responsible for the seasonal cycle of UTWV (Del Genio et al., 1994). However, Boer et al. (2001) clearly show for both hemispheres that annular-mode-related moisture fluxes via eddies are small (relative to the mean meridional flux) and of the wrong sign to explain the poleward transport of moisture in the high-latitude upper troposphere. However, only the meridional eddy flux term was considered, whereas Del Genio et al. (1994) point out that large-scale eddies transport moisture upward as well as poleward.
We see no evidence in either high-latitude region of a fourth mechanism
whereby the UTWV anomalies are simply explained by annular-mode-driven
tropopause variations: the correlation between tropopause height or
tropopause pressure anomalies and the relevant annular mode is not
significant in either high-latitude region
(
We proceed in this discussion considering only the first two mechanisms since they are supported by previous studies. The response profile of saturation vapour VMR relative anomalies (from analyses of the GEM assimilation system) to the AAO (Fig. 8) is studied in order to isolate and gain insight into the contribution of the first proposed mechanism.
Below 9 km, the response of saturation vapour VMR tends to be weaker than
the response by deseasonalized water vapour observed by the ACE instruments,
implying that the temperature mechanism cannot fully explain the strong
observed response of water vapour to the AAO at southern high latitudes
(Fig. 8). Near the tropopause (9.5–10.5 km), the response of saturation
vapour VMR to the AAO becomes effectively zero (within 1
At northern high latitudes (Fig. 9), saturation vapour VMR responds to the AO in a similar fashion to its response to the AAO at southern high latitudes. The response of saturation vapour VMR to the AO at northern high latitudes tends to be smaller in magnitude than the response by water vapour inferred from ACE observations, but the difference is not statistically significant at all altitudes compared to the ACE-FTS water vapour response. The water vapour anomalies from the two ACE instruments show a decreasing response to the AO with increasing altitude at northern high latitudes, but generally differ in the magnitude of the response, as is the case as well at southern high latitudes. Thus, no general conclusion can be unequivocally drawn about the sufficiency of the first proposed mechanism in the northern high-latitude upper troposphere.
The relative contributions by the different mechanisms involved in the response of water vapour to the annular modes remain uncertain partly due to significant intersensor differences (Figs. 8–9). Longer data sets and further analysis would be helpful to understand the contribution by the proposed mechanisms.
Cooling rate vertical profiles are calculated using MODTRAN5.2 (e.g.
Bernstein et al., 1996) assuming an Antarctic surface altitude of 2.5 km, a
subarctic summer temperature profile, free tropospheric aerosol extinction
(visibility of 50 km), and two water vapour cases
using MAESTRO climatological median water vapour between 6.5 and 9.5 km
increased by the vertically resolved water vapour response to AAO determined
by multiple linear regression (with AAO and constant as the only predictors)
for November 2009, when the AAO was in its negative phase (index of same as (1), except for November 2010, when the AAO index was
The availability of the NOAA annular mode indices is appreciated. The ACE mission is supported primarily by the Canadian Space Agency. POAM III data were obtained from the NASA Langley Research Center Atmospheric Science Data Center. C. E. Sioris is grateful to Frédéric Laliberté (Environment Canada) for a helpful discussion on separating the contributions by the two mechanisms proposed in Sect. 4.3. The three referees and the editor are thanked for greatly improving the article. Edited by: T. von Clarmann