1. Introduction
There is continued interest in the impact of stratospheric water vapor (SWV) trends on climate (Forster and Shine 1999, 2002; Smith et al. 2001; Solomon et al. 2010). This has been motivated by the observed increase in SWV of ~30% over the late twentieth century (Scherer et al. 2008; Hurst et al. 2011) and the rapid and persistent decrease of ~15% after 2000 (Randel et al. 2006; Rosenlof and Reid 2008). Furthermore, SWV has been projected to increase by up to a factor of 2 over the coming century in response to increasing long-lived greenhouse gas (LLGHG) concentrations (Gettelman et al. 2010). However, the projections of future SWV trends are highly uncertain. The Chemistry–Climate Model Validation Activity (CCMVal-2) multimodel mean change in tropical lower stratospheric water vapor by 2100 is 1.3 ppmv for a medium LLGHG emissions (REF-B2) scenario, but the changes in individual models range from 0.5 to 4 ppmv. It is therefore important to explore the impacts of changes in SWV on climate.
Trends in SWV may arise via changes in the transport of water vapor into the stratosphere, which occurs predominantly in the tropics, and/or via changes in the production of SWV from the oxidation of methane. It is worth noting that SWV can therefore have a role in climate feedbacks (e.g., in response to changes in the strength of tropical convection; Rosenlof and Reid 2008), climate forcings [e.g., in response to volcanic eruptions (Joshi and Shine 2003) and changes in the production of SWV via methane oxidation (Rohs et al. 2006)], and modes of “unforced” internal climate variability [e.g., the quasi-biennial oscillation (QBO; Randel et al. 1998), the El Niño–Southern Oscillation (ENSO; Considine et al. 2001) and variations in the strength of the Brewer–Dobson circulation (Randel et al. 2006)].
Most of the existing literature on climate impacts has focused on the radiative forcing associated with SWV trends (Forster and Shine 1999, 2002; Smith et al. 2001; Solomon et al. 2010). However, there is now compelling evidence that the stratosphere and troposphere act as a two-way dynamically coupled system, such that changes in stratospheric wind and temperature have an impact on the extratropical tropospheric circulation [for an overview, see, e.g., Gerber et al. (2012)]. This study therefore considers an additional mechanism—specifically, that trends in SWV will cause changes in stratospheric temperature and wind, which may impact the tropospheric circulation.
There has been considerable interest in how the stratosphere influences the tropospheric response to climate forcings and processes, most notably increases in LLGHGs (e.g., Scaife et al. 2012), stratospheric ozone depletion and recovery (e.g., Son et al. 2008; Polvani et al. 2011; McLandress et al. 2011), ENSO (Cagnazzo and Manzini 2009; Ineson and Scaife 2009), and the 11-yr solar cycle (Haigh et al. 2005). However, relatively little attention has been paid to the impact of SWV trends on the coupled stratosphere–troposphere system. Rind and Lonergan (1995) conducted an experiment in which SWV was uniformly doubled from 3 to 6 ppm in a middle atmosphere general circulation model (GCM). Although they found evidence of there being changes in both the stratospheric and tropospheric circulation in response to the increase in SWV, the model’s radiation code did not correctly simulate the vertical structure of the stratospheric temperature response to SWV (Oinas et al. 2001). In their model [the Goddard Institute for Space Studies Global Climate-Middle Atmosphere Model (GISS GCMAM)], the maximum stratospheric cooling occurred in the upper stratosphere, whereas in more complete radiation codes the maximum is in the lower stratosphere (e.g., Forster and Shine 2002). Furthermore, their GCM had, by modern standards, a relatively poor horizontal (8° × 10°) and vertical (23 layers) resolution. MacKenzie and Harwood (2004) examined the impact of SWV changes due to projected future methane trends on the stratosphere. They found that the associated increase in SWV modified the stratospheric circulation response due to LLGHGs and aerosols alone, particularly over the Northern Hemisphere winter pole. However, partly because the effect of methane oxidation on SWV is largest in the upper stratosphere, the lower stratospheric temperature changes in their experiment were small.
The lower stratosphere is a key region for stratosphere–troposphere interaction, and is also where a given change in SWV has the greatest impact on temperature (e.g., Maycock et al. 2011). Joshi et al. (2006) investigated the dynamical impact of an increase in SWV using an atmospheric GCM with considerably higher horizontal resolution (1.875° × 1.25°) than used by Rind and Lonergan (1995), but with a relatively low model lid at ~40 km. A 20% increase in SWV was imposed in the model as an estimate of the 1980–2000 trend. This perturbation resulted in changes in the large-scale extratropical tropospheric circulation that were consistent with a more positive northern annular mode (NAM) index (Thompson and Wallace 2000). However, it was not clear whether the change in SWV in the upper or lower stratosphere had the greatest impact on the troposphere; this point is addressed later in this paper. In a more recent study, Tandon et al. (2011) used a simplified GCM to investigate the tropospheric response to idealized stratospheric heating perturbations with a structure resembling the cooling pattern due to a uniform increase in SWV. The response in their model consisted of a poleward shift in the tropospheric eddy-driven jet and a widening and weakening of the Hadley cell. The results of these studies suggest that trends in SWV may be an important driver of changes in stratospheric and tropospheric temperature and wind. The aim of this study is to investigate for the first time the circulation response to SWV perturbations in a comprehensive stratosphere-resolving atmospheric GCM. The following questions will be addressed:
What is the impact of uniformly doubling SWV on the stratosphere?
Is there evidence of changes in the tropospheric circulation in response to increasing SWV?
Are uniform changes in SWV in the upper or lower stratosphere more important for driving circulation changes in the troposphere?
The remainder of this paper is structured as follows: Section 2 describes the setup of the model and the experiments carried out, section 3 presents our results, and section 4 discusses our findings in the context of understanding the links between SWV trends and climate.
2. Method
We use the vertically extended atmospheric component of the Hadley Centre Global Environmental Model version 1 (HadGAM1) described by Hardiman et al. (2010) and Osprey et al. (2010). The model is similar to the core of the Met Office’s Unified model that participated in the coupled chemistry–climate model validation exercise (CCMVal-2) (UMUKCA-METO). There are 60 levels in the vertical domain and the model is run at N48 horizontal resolution (2.5° × 3.75°). The model is forced at the lower boundary over ocean grid points by time-varying monthly-mean sea surface temperatures (SSTs) and sea ice taken from the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST; Rayner et al. 2003) dataset. The land surface is allowed to evolve self-consistently. Ozone is imposed as a zonal-mean monthly-mean climatology created from merged satellite datasets covering the period 1979–2003 [see Dall’Amico et al. (2010) for further details]. Observed time-varying concentrations of carbon dioxide and methane for the period 1980–2002 are included, as well as fixed concentrations of nitrous oxide and chlorofluorocarbon (CFC)-11 and -12 at 1993 values. The model does not explicitly include anthropogenic or volcanic aerosols or a solar cycle. However, some component of the effect of such processes will be indirectly included in the simulations through the use of observed SSTs and sea ice.
The model includes additional modifications compared to the version described by Hardiman et al. (2010), which improve the representation of surface exchange processes at coastal grid points (Ackerley et al. 2012). These modifications negatively impact on the climatology and variability of the Northern Hemisphere winter stratospheric polar vortex. Specifically, they result in a weaker stratospheric westerly jet and a relatively high frequency of major sudden stratospheric warmings (SSWs) (1.2 yr−1) compared to the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) dataset (0.66 yr−1; Charlton and Polvani 2007). However, the simulated climatology and variability lie within the spread of the current generation of stratosphere-resolving GCMs (Butchart et al. 2010a).
HadGAM1 uses the Edwards and Slingo (1996) radiative transfer scheme (ESRTM), updated to use the correlated-k method to calculate transmittances for absorbing species (Cusack et al. 1999). There has been considerable debate in the literature about the suitability of broadband radiation codes for representing the radiative effects of trends in SWV (e.g., Oinas et al. 2001). Codes based on the ESRTM have been shown to consistently overestimate the radiative forcing and instantaneous change in heating rate for SWV perturbations by up to ~50% (e.g., Maycock and Shine 2012). However, the qualitative structure of the stratospheric temperature response to SWV in the ESRTM is consistent with more detailed radiation codes (Forster and Shine 2002; Maycock et al. 2011). This study will therefore provide an upper estimate of the magnitude of the response to a given SWV perturbation.
Each experiment consists of a three-member ensemble run for 23 years from January 1980 to December 2002. Unless otherwise stated, all figures in section 3 should be assumed to show results for 23 × 3 = 69 yr of data.
Since the configuration of the model used here includes prescribed SSTs, the effect of the radiative forcing due to perturbing SWV is not fully captured in the simulations (see, e.g., Forster and Shine 2002). The difference in the global-mean annual-mean surface temperature between the UNI and CTL experiments is negligible (~0.02 K), whereas with interactive SSTs the change may be expected to be around 1.4 K, assuming a stratosphere-adjusted radiative forcing of 1.2 W m−2 (calculated offline using the ESRTM) and a climate sensitivity of 1.15 K (W m−2)−1 for HadGEM1 (Solomon et al. 2007). This study therefore focuses on the atmospheric circulation response to SWV perturbations in the absence of changes in SSTs. The impact of including changes in SSTs on the response to SWV will be considered in a follow-up study. The effects of changing SWV on ozone concentrations either via changes in temperature, circulation, or chemical processes are also neglected.
3. Results
a. The response to uniformly doubling SWV
1) Stratospheric changes
Figure 1 shows from left to right: the seasonal-mean zonal-mean temperature (
Plots of 
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
The climatology of the model shows a warm bias in the polar lower stratosphere (~50 hPa) of ~5 K in both the northern and southern winter hemispheres compared to ERA-40 reanalysis data (Uppala et al. 2005). The warm bias in the SH in JJA is similar to that reported by Hardiman et al. (2010). However, the bias in the NH in DJF does not appear in Hardiman et al. (2010), so it appears largely attributable to the additional modifications to the model described in section 2.
The change in stratospheric 
Figure 2 shows the zonal-mean zonal wind (
Plots of 
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
Figure 2 also shows that significant changes in 
Having looked at the changes in the mean flow, we will now examine the response of eddies to the increase in SWV. The breaking of upward propagating planetary-scale Rossby waves makes an important contribution to the pseudomomentum budget of the winter stratosphere and leads to variations in the zonal-mean flow. The divergence of the Eliassen–Palm flux (EP flux) can be used as a measure of the zonal force per unit mass due to resolved wave breaking (e.g., Andrews et al. 1987). Figure 3 shows the EP flux divergence (∇ · F; m s−1 day−1) in the same layout as Fig. 2. In the climatology, more negative values are found in the midstratosphere in the NH in DJF (~−2 m s−1 day−1) than in the SH in JJA (~−1 m s−1 day−1), which indicates that more planetary waves are generated in the NH than in the SH. In the UNI experiment, the EP flux convergence in the NH in DJF increases in magnitude by 10%–15% in the mid and upper stratosphere. Conversely, in the SH in JJA the magnitude of ∇ · F decreases by ~25%. The opposite sign of the change in upper stratospheric EP flux divergence in the winter hemispheres may be related to differences in the background climatology, since the vertical wind profile is important for the propagation and refraction of planetary waves traveling from the troposphere into the stratosphere (Charney and Drazin 1961). In the SH, there is a significant decrease in the meridional eddy heat flux 
As in Fig. 2 but for the EP flux divergence (∇ · F; m s−1 day−1). The contour interval is 2 and 0.5 m s−1 day−1 in the left and right panels, respectively.
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
In the transformed Eulerian mean (TEM) framework (Andrews et al. 1987), it is clear that the effect of an increase in wave drag in the upper stratosphere will be twofold: first, it will directly impact 
The seasonal cycle in F↑ (kg s−1) at 70 hPa calculated from Eq. (3) for the four experiments: CTL (solid black), UNI (solid gray), LS (dashed gray), and US (dashed black). The contributions from F↓,NH and F↓,SH for the UNI and CTL experiments are shown by the dashed and dash-dot lines respectively. Note that the x axis is centered about the boreal winter season.
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
The strength of the BDC is important for the transport of trace species, including water vapor and ozone, into and out of the stratosphere (e.g., Butchart and Scaife 2001). It is therefore important to understand how the BDC changes in response to different climate forcings and feedbacks, and the role that different atmospheric waves play in driving these changes. A ubiquitous feature of the circulation response to increased LLGHG concentrations is an increase in the strength of the BDC, which is typically largest in DJF (Butchart et al. 2006, 2010b). A recent study by Shepherd and McLandress (2011) has shown that this can largely be explained by an increase in lower stratospheric wave drag associated with a lifting of the critical layers for wave breaking owing to the increased westerlies on the upper flanks of the subtropical jets. The fact that F↓ increases in the summer season in both hemispheres in Fig. 4 indicates that changes in lower stratospheric wave drag must play a role in the strengthening of the BDC in the UNI experiment, since westerly winds (i.e., winter conditions) are required for planetary waves to propagate into the mid and upper stratosphere. This is also evident by examining the seasonal cycle in mass flux higher up in the stratosphere (e.g., at 30 hPa; not shown) which, through downward control arguments (Haynes et al. 1991), will be largely determined by planetary wave drag in the mid and upper stratosphere. At higher altitudes, F↑ only increases in boreal winter in the UNI experiment, due to an increase in F↓,NH, and therefore changes in lower stratospheric wave drag must make a significant contribution to the increase in F↑ evident in Fig. 4; this is therefore consistent with the mechanism described by Shepherd and McLandress (2011).
There has also been considerable debate in the literature regarding the contribution of resolved waves (i.e., EP flux divergence) and parameterized waves (i.e., orographic and nonorographic gravity drag) to changes in the BDC. The study by McLandress and Shepherd (2009) highlighted the importance of changes in both the EP flux divergence and parameterized orographic gravity wave drag (OGWD) close to the turnaround latitudes for a strengthening of the BDC in response to increased LLGHGs in the Canadian Middle Atmosphere Model (CMAM) [see also Li et al. (2008), who find a similar result in the GFDL chemistry–climate model]. In this version of HadGAM1, the contribution of OGWD to the residual circulation at 70 hPa is considerably smaller than in CMAM and the dominant contribution comes from the resolved wave drag (Hardiman et al. 2010). Downward control calculations (not shown) indicate that the change in mass flux in the UNI experiment is also dominated by the change in resolved wave drag, and that the contributions from parameterized wave drag are small. Understanding these differences therefore remains an important area for future research, particularly given the uncertainties in observed gravity wave drag in the stratosphere.
Finally, the above results highlight a possible negative feedback for SWV transport. A uniform increase in SWV leads to a strengthening of the BDC, which would cause a lifting and cooling of the tropical tropopause. This is consistent with the pressure at the tropical tropopause being 5–10 hPa lower in the UNI experiment compared to the CTL experiment throughout the year. To first order, this would act to reduce the amount of water vapor entering the stratosphere, which is again consistent with the changes in SWV simulated by the model in response to the radiatively imposed SWV perturbation.
2) Tropospheric changes
Figure 2 shows that the increase in SWV results in north–south dipole changes in 
Figure 5 shows the differences in mean sea level pressure (MSLP; hPa) between the UNI and CTL experiments for (left) 20°–90°N and (right) 20°–90°S in (top) JJA and (bottom) DJF seasons. For clarity, the gray shading now indicates where the differences are found to be statistically significant at the 95% confidence level. In both hemispheres, and in both seasons, there is a relatively zonally symmetric decrease in MSLP over the polar cap, and a more zonally asymmetric increase in MSLP in the extratropics. These changes correspond to north–south dipoles over the extratropical ocean basins, which is consistent with the structure of the tropospheric annular modes (Thompson and Wallace 2000). The MSLP dipole over the North Atlantic has a peak-to-peak amplitude of 2 and 6 hPa in JJA and DJF, respectively, which can be compared to an amplitude of ~7–8 hPa associated with a 1 standard deviation departure of the North Atlantic oscillation (NAO) index in DJF (Greatbatch 2000). There is evidence of smaller MSLP changes over the North Pacific in DJF. In the SH, the peak-to-peak amplitude of the MSLP dipole is 4 and 6 hPa in JJA and DJF, respectively. The positive anomalies peak to the southwest of Australia, which coincides with the region of maximum intensity of the SH storm track (e.g., Hoskins and Hodges 2005). The changes in the tropospheric circulation due to the increase in SWV are associated with regional changes in surface temperature and precipitation over North America and western Europe, as well as over the Antarctic continent, which are consistent with annular mode variability found in observations and climate models (not shown; e.g., Marshall et al. 2001; Thompson and Wallace 2000).
Polar stereographic projections of the UNI-CTL differences in mean sea level pressure (MSLP; hPa) for (a) 20°–90°N in JJA and (b) 20°–90°S in JJA. (c),(d) As in (a),(b), but for DJF. The contour interval is 1 hPa. Note that for clarity the gray shading indicates where the response is statistically significant at the 95% confidence level.
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
Polar stereographic projections of the DJF UNI-CTL differences in (a),(b) zonal wind (m s−1) at 850 hPa, (c),(d) the standard deviation (Δσ) of the 2–6-day bandpass filtered 500-hPa geopotential height (m), and (e),(f) the maximum Eady growth rate (σmax; day−1) from Eq. (4) for (left) 20°–90°N and (right) 20°–90°S. The contour intervals are 1 m s−1, 2 m, and 0.02 day−1 in the top, middle, and bottom panels, respectively. Note that the gray shading indicates where the differences are statistically significant at the 95% confidence level.
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
Figures 6a and 6b show that there is a strengthening of the westerly low-level zonal wind of up to ~2 m s−1 on the poleward side of the storm tracks between 45° and 60°N and 55° and 65°S in the NH and SH, respectively, and a corresponding smaller decrease at lower latitudes. The low-level zonal wind changes over the North Atlantic peak downstream of the maximum baroclinic zone and extend into the Mediterranean and eastern Europe.
The climatology of the standard deviation of 2–6-day bandpass filtered Z500 shows maxima over the extratropical ocean basins, which are collocated with the baroclinic storm tracks (not shown). The Δσ of Z500 in Figs. 6c and 6d also show dipole changes, with increased variance on the poleward sides of the storm tracks and reduced variance at lower latitudes. This is consistent with the synoptic eddy activity being located further poleward on average.
Finally, the differences in σmax are shown in Figs. 6e and 6f. In the North Atlantic, the differences in σmax peak slightly upstream of the largest changes in the low-level zonal wind. Interestingly, there is also an increase in σmax on the western side of the North Pacific basin, which is not evident in the other diagnostics. The change in σmax is predominantly due to a change in the vertical wind shear across the troposphere, 
The relationship between the position of the tropospheric eddy-driven jet and the extratropical lower stratospheric temperature in each hemisphere is now considered, following a similar method to Polvani et al. (2011). In Fig. 7, the seasonal-mean latitude of the midlatitude jet at 850 hPa is plotted against the polar cap average (|φ| > 60°) 
The seasonal-mean latitude of the jet maximum at 850 hPa (°) plotted against the polar cap average (|φ| > 60°) 
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
There is a large amount of scatter in the points, particularly in the winter seasons. The correlation between the two variables within each of the datasets is quite weak (|r| < 0.4). In all cases, the difference in the polar cap 
The largest difference in Δφ is in the NH in DJF, with a poleward shift of 2.8°. In this case, the mean difference in 
To summarize, the overall poleward shift in the eddy-driven jets in both hemispheres in response to the increase in SWV agrees with the response to stratospheric polar cooling in simplified GCMs (e.g., Simpson et al. 2009; Tandon et al. 2011). However, there are distinct seasonal variations in the tropospheric response in both hemispheres, which we have been able to evaluate through the use of a more complex GCM that includes a seasonal cycle.
b. The impact of SWV changes in the upper versus lower stratosphere
The results so far have shown that a uniform doubling in SWV causes circulation changes in both the stratosphere and troposphere. This raises the question as to whether changes in SWV in the upper or lower stratosphere are more important for driving changes in the circulation. For example, it would be useful to know in which regions it is most important for GCMs to correctly simulate SWV, and also whether SWV trends due to changes in transport or changes in stratospheric chemistry are likely to have a bigger dynamical impact.
Figure 8 shows the DJF seasonal-mean differences in (top) 
Plots of the DJF differences in (a)–(c) 
Citation: Journal of Climate 26, 2; 10.1175/JCLI-D-12-00155.1
The vertical residual mass flux in the tropics, F↑, at 70 hPa in the LS and US experiments is plotted in Fig. 4. The vertical mass fluxes in the LS and US experiments almost exactly match those in the UNI and CTL experiments, respectively. There is virtually no change in the mass flux in the US experiment, and almost all of the increase in the UNI experiment is reproduced in the LS experiment. This suggests that the changes in stratospheric wave drag, and therefore the residual circulation, in the UNI experiment are almost entirely due to the changes in temperature and wind associated with the increase in SWV in the lower stratosphere.
The MSLP response in the LS experiment is also very similar to the UNI experiment (not shown). Conversely, no statistically significant changes in MSLP occur in the US experiment. Water vapor trends in the lower stratosphere (e.g., due to changes in tropical lower stratospheric transport) are therefore likely to be more important for the global circulation than equivalent trends in the upper stratosphere (e.g., due to methane oxidation).
4. Conclusions
This study has investigated the stratospheric and tropospheric circulation response to a uniform doubling in SWV from 3 to 6 ppmv in a comprehensive stratosphere-resolving atmospheric GCM. This represents an idealized SWV perturbation that is more akin to the effects of a long-term trend, such as those simulated for the future period by the CCMVal-2 models under increased long-lived greenhouse gas concentrations (Gettelman et al. 2010), than to the variations found in the observational record (e.g., Hurst et al. 2011). A future paper will consider the impact of changes in SWV derived from past observations (A. C. Maycock et al. 2012, unpublished manuscript).
A uniform increase in SWV causes stratospheric cooling, which is largest in the extratropical lower stratosphere throughout the year. This causes a more westerly zonal-mean zonal wind on the upper flanks of the subtropical jets. In the Northern Hemisphere (NH), there is an increase in the resolved wave drag in the mid and upper stratosphere from September to April, and a weaker westerly jet at pressures less than 10 hPa. Conversely, in the Southern Hemisphere (SH) there is a decrease in upper-stratospheric wave drag of ~25% from July to September, an increase in the strength of the stratospheric jet by up to 14 m s−1, and a delay in the final warming by ~13 days. This is similar to the impact of Antarctic ozone depletion on the stratosphere from November to February (e.g., Thompson et al. 2011; Polvani et al. 2011). There is an increase of ~10% in the vertical mass flux in the tropical lower stratosphere associated with the residual circulation throughout the year. This is mainly related to an increase in wave drag in the suptropical lower stratosphere in both hemispheres, and is consistent with studies of the residual circulation response to increases in long-lived greenhouse gas (LLGHG) concentrations (e.g., Butchart et al. 2006; Shepherd and McLandress 2011). In boreal winter, the increase in the residual circulation is also partly due to the increase resolved wave drag in the mid and upper stratosphere in the NH. The increase in the residual circulation is largely due to changes in the resolved wave drag, with the parameterized orographic and nonorographic gravity wave drag playing only a minor role. This is in contrast to other studies that show a significant role for both resolved and parameterized wave drag in the response to increased LLGHGs (e.g., Li et al. 2008; McLandress and Shepherd 2009). Understanding such differences between models remains an area of future research interest. The changes in wave drag and the related increase in the residual circulation occur almost exclusively in response to the increase in SWV in the lower stratosphere (p > 50 hPa).
The changes in the lower stratospheric state impact the large-scale extratropical tropospheric circulation. There are north–south dipole changes in mean sea level pressure over the extratropical ocean basins, which are concurrent with a poleward shift in the eddy-driven jets and a more positive annular mode index. The largest changes in the tropospheric circulation occur from December to February in both hemispheres. The changes in the tropospheric circulation are also almost entirely due to the increase in SWV in the lower stratosphere (p > 50 hPa). A uniform change in SWV in the upper stratosphere (p < 50 hPa) has virtually no impact on the atmospheric circulation in our model. The results of this study represent the climate response to an SWV perturbation in the absence of changes in sea surface temperatures (SSTs). The effect of coupling to SSTs is likely to be more important for SWV than for changes in other stratospheric constituents, such as ozone, for which the global-mean radiative forcing is quite small. A follow-up study will therefore consider the role of SST changes in the circulation response to SWV perturbations.
The tropospheric circulation changes due to uniformly increasing SWV are consistent with those found by Tandon et al. (2011). However, the use of a more comprehensive GCM with a well-resolved stratosphere has highlighted important changes in the stratospheric circulation which will not be captured in a simplified GCM without topography and in the absence of an annual cycle, such as that used by Tandon et al. (2011). These different experimental approaches should therefore be considered mutually complementary, and demonstrate that the nature of the tropospheric response appears robust across GCMs of varying complexity and differing configurations.
The results of this study indicate that trends in SWV may be an important driver of extratropical climate variability on interannual to multidecadal time scales. For example, it has been shown that the positive trend in the North Atlantic oscillation (NAO) from 1960 to 2000 can be almost entirely explained by the observed trend in lower stratospheric wind over this period (Scaife et al. 2005). The observed increase in SWV over this period may therefore have contributed to the NAO trend (Joshi et al. 2006). Furthermore, simulations under increasing LLGHG concentrations show increases in SWV of up to a factor of 2 over the twenty-first century (Gettelman et al. 2010). Trends in SWV should therefore be considered alongside LLGHGs and stratospheric ozone recovery as an important mechanism for driving temperature and circulation changes in both the troposphere and stratosphere in future climate projections. However, since the limited evidence available suggests past variations in SWV are generally not well reproduced in models (e.g., Oman et al. 2008), the sign and magnitude of future trends remains a source of uncertainty for future climate variability and change.
Acknowledgments
A. C. Maycock was supported by a NERC PhD studentship and a CASE award from the UK Met Office. M. M. Joshi was funded by NCAS-climate. A. A. Scaife was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). The authors would like to thank the detailed comments from the three anonymous reviewers which greatly helped to improve the manuscript.
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The geopotential height is bandpass filtered with a Lanczos filter following Duchon (1979) using a window of ±15 days.