Journal of Atmospheric and Solar-Terrestrial Physics 161 (2017) 64–75
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Transport of water vapour over the Tibetan Plateau as inferred from the model simulations S. Jain *, S.C. Kar National Centre for Medium Range Weather Forecasting (NCMRWF), Ministry of Earth Sciences (MoES), Noida, 201309, Uttar Pradesh, India
A R T I C L E I N F O
A B S T R A C T
Keywords: Water vapour Temperature Tropopause WRF model Tibetan Plateau
This paper discusses the transport of water vapour in the tropopause region over the Tibetan Plateau, where high water vapour mixing ratio is observed during the Northern Hemisphere (NH) summer-monsoon period. The Weather Research and Forecasting (WRF) model has been used to study the two contrasting cases i.e. when water vapour is high and low at 100 hPa (close to tropopause). The composite distribution of water vapour shows two key results (a) the water vapour appears be transported to the Tibetan plateau region from the extra-tropics under the influence of stronger northwesterly winds and (b) the vertical water vapour flux is relatively higher over the Tibetan Plateau region during the period when water vapour amount at this level is higher. This suggests that in addition to the horizontal transport from the extra-tropics, the local convection occurring over the Tibetan Plateau also contributes to the increase in the water vapour over this region. The differences in the circulation during high and low water vapour cases suggest that a cyclonic circulation difference over the central Indian region limit the transport of water vapour from the Bay of Bengal to the Tibetan Plateau region.
1. Introduction The water vapour is the largest natural contributor to the global warming. It absorbs strongly in the infra-red and microwave region and therefore traps the outgoing long wave radiations (OLR) emitted from the Earth's surface. The increase in stratospheric water vapour heats the troposphere but radiatively cools the stratosphere and thus affects the total radiative forcing (Forster and Shine, 1999). The water vapour in the upper troposphere also gives rise to the formation of thin cirrus clouds which influence the upper tropospheric energy budget by reflecting the UV radiations of the sun and absorbing the infrared radiations emitted from the Earth's surface. Therefore, it is important to study the changes in water vapour in upper troposphere and lower stratosphere (UTLS) in order to understand the dynamical, chemical and radiative processes occurring in the both troposphere as well as stratosphere (SPARC Report, 2000). An increasing trend in the stratospheric water vapour is observed for almost two decades from the year 1980–2000 as shown by Solomon et al. (2010). After the year 2000, a sharp decrease in stratospheric water vapour is observed for almost six years (Randel et al., 2006) followed by an overall increasing trend till date. The increase in stratospheric water vapour has affected the green house radiative forcing (Forster and Shine, 1999, 2002; Smith et al., 2001). Dessler et al. (2013) have shown that
* Corresponding author. E-mail addresses:
[email protected] (S. Jain),
[email protected] (S.C. Kar). http://dx.doi.org/10.1016/j.jastp.2017.06.016 Received 9 March 2017; Received in revised form 23 May 2017; Accepted 26 June 2017 Available online 27 June 2017 1364-6826/© 2017 Elsevier Ltd. All rights reserved.
there exists a stratospheric water vapour feedback in the atmosphere under which stratospheric water vapour increases in response to the tropopause temperatures. The complex processes related to the stratospheric-tropospheric exchange of water vapour are still not properly understood and therefore are not well represented in climate models (Jiang et al., 2012, 2015). Water vapour feedback is a major source of uncertainty in most of the climate models. Furthermore, the distribution of water vapour is associated with the radiative properties and evolution of clouds, which represent a significant source of error in climate simulations and weather prediction (IPCC report 2007). Therefore, it is important to study the sources of upper tropospheric and lower stratospheric water vapour in order to predict the future global climatic conditions. The main process responsible for the water vapour transport from the surface to the tropopause and lower stratospheric region is tropical convection (Holton et al., 1995; Jiang et al., 2010). Due to relatively higher temperatures, intense evaporation occurs over the tropics as compared to the mid-latitudes and poles. The water vapour is transported vertically in the atmosphere due to the convection over the tropics. The main convective outflow of water vapour occurs much below the tropopause level (which is at ~100 hPa pressure level) but some overshooting convective turrets penetrate the tropopause and reach the lower stratosphere. Most of the water vapour enters the stratosphere through
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Journal of Atmospheric and Solar-Terrestrial Physics 161 (2017) 64–75
Fig. 1. Spatial distribution of mean WVMR (ppmv) for July 2015 and August 2015 over the Asian monsoon region at 100 hPa level from (a) EOS Aura MLS satellite and (b) ERAInterim reanalysis.
The large scale hydration of the tropopause is observed over the Asian monsoon region during the Northern Hemisphere (NH) summermonsoon season i.e. June to September. The region of hydration and deep convection is not collocated over the Asian monsoon region. The deepest penetrating convection during the NH summer-monsoon season is observed over the Bay of Bengal but the maximum moisture is observed over the Tibetan Plateau (Jain et al., 2013). The moistening of the tropopause over the Tibetan Plateau region could be because of the quasi-
the tropical tropopause layer (Fueglistaler et al., 2009). In addition to the deep convection, the distribution of water vapour in the tropopause and lower stratosphere is largely influenced by the horizontal advection and mixing. The vertical transport of water vapour in the tropopause and lower stratosphere is slow (Mote et al., 1996) and the stratospheric humidity is determined by the horizontal transport of air passing through the areas of low tropopause temperatures (Brewer, 1949; Mote, 1995; Holton and Gettelman, 2001; Jiang et al., 2015).
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Fig. 2. Spatial distribution of mean WVMR (ppmv) from EOS Aura MLS satellite for 26 July 2015 to 10 August 2015 over the Asian monsoon region at (a) 82 hPa (b) 100 hPa (c) 121 hPa (d) 146 hPa (e) 177 hPa and (f) 216 hPa pressure level.
Fig. 3. Vertical cross section of WVMR (ppmv) from ERA-Interim reanalysis with respect to time from 26 July 2015 to 10 August 2016 over the Tibetan Plateau region (30–40 N, 80–100 E).
Plateau region are collocated with upper level Asian monsoon anticyclone. It is also possible that the other minor constituents such as water vapour could also be trapped by the similar transport mechanism by the Asian monsoon anticyclone. Therefore, this study examines the transport pathways of the water vapour to the tropopause level over the Tibetan Plateau region. To study this, simulations using the Weather Research and Forecasting (WRF) model have been carried out for July and August 2015. The two different cases are selected when the water vapour is high or low in the WRF model simulations. More details related to the WRF model and data used in this study is given in section 2. Section 3 discusses
horizontal transport of water vapour from the Bay of Bengal (BOB) to the Tibetan Plateau region or extra-tropical convection occurring over the south China (Gettelman et al., 2004). In addition, the Tibetan Plateau is a source of elevated surface heating and therefore the local convection occurring over the Tibetan Plateau can also transport water vapour vertically into the tropopause and lower stratosphere (Fu et al., 2006; Li et al., 2005). The exact cause of hydration over the Tibetan Plateau is still debated. The role of BOB in the moistening process over the Tibetan Plateau is also not clear. Li et al. (2005) have shown that the high CO pollutant concentrations in the upper troposphere over the Tibetan 66
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Fig. 4. Vertical cross section of the WVMR (ppmv) with respect to time over the Tibetan Plateau region for each 3-day WRF simulation from 26 July 2015 to 10 August 2015.
the key results of this study and the main findings of this paper are concluded in section 4.
used for the shortwave radiation (Dudhia, 1989). The radiation schemes are called at every 10 min. For surface physics, the NOAH land surface model and for planetary boundary layer physics, Yonsei University (YSU) scheme is used (Hong and Kim, 2008). The Grell-Devenyi ensemble scheme (Grell and Devenyi, 2002) has been used for convective parameterization over the domain of study. Jain and Kar (2017) have carried out sensitivity experiments of the UTLS moisture to the convective and cloud microphysics parameterization schemes. They have shown that the Grell-Devenyi convective scheme and WSM-6 cloud microphysics scheme simulate the UTLS moisture relatively well and therefore these schemes are used in this study. It has also been noted by these authors that after the day 3 forecast, the drying tendency of the WRF model dominates any other feature of the moisture distribution particularly at 100 hPa pressure level. Therefore, the model integration time is constrained to 3 days and fresh simulation is carried out for each day with 3-day forecast period. The 3-day integration time may not be sufficient for the lower stratospheric water vapour to reach equilibrium stage. However, the main objective of this paper is to study the instantaneous increase in the UTLS moisture over the Tibetan region. There are several other studies which have utilized the WRF model for short period simulations to examine the various processes (including water vapour changes) in the UTLS. Mahalov et al. (2011), while studying the mountain waves in the UTLS for two intensive observational periods (IOPs) of the Terrain-induced Rotor Experiment, carried out numerical simulations using the WRF model for
2. Data and methodology For the present paper, the WRF model version 3.7 has been used to study the transport of water vapour over the Asian monsoon region. The model domain covers 5 N–50 N and 60 E–120 E and the spatial resolution of the domain is 12 km. The initial and boundary conditions at every 6 h interval are taken from the ERA-Interim reanalysis data. The ERA-Interim data are one of the latest global atmospheric reanalysis dataset which uses Integrated Forecasting System (IFS) data assimilation system with 4D-Var analysis and 12 h analysis window (Dee et al., 2011). The spatial resolution of this dataset is ~75 km with 60 vertical levels from surface to 0.1 hPa. The details about the data assimilation system, observational data assimilated in the product and errors in the ERAInterim dataset are given by Dee et al. (2011). The WRF model simulations for 3-days are carried out with initial conditions for each day starting from 26 July 2015 at 00 UTC to 10 August 2015 at 00 UTC. The time step used for the WRF model is 30 s and the pressure top is set at 10 hPa. The WSM-6 scheme (Hong and Lim, 2006) which is suitable for high-resolution simulations is used in this study for cloud microphysics. The Rapid Radiative Transfer Model (RRTM) scheme is used for longwave radiations and Dudhia scheme is
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Fig. 5. Composite diagram of the vertical cross section of the WVMR (ppmv) for the cases when (a) WVMR is low at 100 hPa i.e. 26 July-30 July 2015 and (b) WVMR is high at 100 hPa i.e. 01 August 2015 to 05 August 2015 in the WRF model.
Therefore, this period is suitable for studying the mechanism of water vapour transport to UTLS using model simulations. Fig. 4 shows the distribution of the WVMR as a function of pressure and time over the Tibetan Plateau region for simulations carried out for 26 July 2015 to 10 August 2015. It is seen that over the Tibetan Plateau, the maximum drying is observed at the 100 hPa in the WRF model. The values of the WVMR decrease to less than 1 ppmv in the model. The drying is mainly observed from 26 July to 31 July at 36 h simulation time and continues till the end of simulation. In contrast, the increase in WVMR (ppmv) is observed in the model at 100 hPa at 48 h forecast for 01 August 2015 and 36 h forecast for 02 August 2015 to 08 August 2015. The magnitude of water vapour is comparatively higher, ~ 4–6 ppmv, at 100 hPa in the model. In order to understand as to what contributes to the rise in water vapour in the WRF model, composite diagrams of water vapour for pressure versus time is plotted for 5-day period when water vapour decreases at 100 hPa in the WRF model (26 July 2015 to 30 July 2015) and similarly for 5-day period when water vapour increases in the model (01 August 2015 to 05 August 2015) at this level. Fig. 5 (a) and 5 (b) shows the composite diagrams for low and high water vapour cases respectively. It is apparent from Fig. 5 (a) that reduction in the WVMR in the model for composite cases is centered at the 48 h forecast time. The water vapour amount is less than 1 ppmv at about 100 hPa in low WVMR cases, whereas, it is more than 3ppmv in high WVMR cases at this level. Therefore, the spatial distribution of the simulated WVMR (ppmv) is examined after 48 h simulation for each case (high water vapour and low water vapour) over the Asian monsoon region at the 100 hPa.
the two IOPs. These simulations were each for 48 h. Le and Gallus Jr. (2012) have used the WRF model to carry out 24-hr integration to examine the amount of water vapour transported in the UTLS during the most active period of a mesoscale convective system. Homeyer (2015) have also carried out WRF model simulation of few hours for an observed case of overshooting convection. Therefore, in this paper the WRF model is run for the 3-day forecast period with initial conditions for each day starting from 26 July 2015 to 10 August 2015. 3. Results and discussion 3.1. Distribution of water vapour mixing ratio over the Tibetan Plateau Fig. 1 shows the spatial distribution of water vapour mixing ratio (WVMR) for July and August from the Aura Microwave Limb Sounder (MLS) satellite and ERA-interim data. Though there are some differences in the magnitude of water vapour due to the coarse resolution of ERAInterim, it is seen that both the datasets agree well with each other. Fig. 2 shows the mean WVMR for 26 July 2015 to 10 August 2015 obtained from Aura MLS satellite at 82 hPa, 100 hPa, 121 hPa, 146 hPa, 177 hPa and 216 hPa levels. It is seen that for pressure levels close to the tropopause (~100-82 hPa pressure level), the highest WVMR is observed over the Tibetan Plateau. At higher pressure levels (i.e. at lower heights), maximum hydration is seen over the Bay of Bengal region. It is noted that there is a spatial shift in the maxima of the WVMR from 216 to 100 hPa for this particular case. Therefore, this case can be used to examine the increase in the WVMR over the Tibetan region. Fig. 3 shows the vertical cross-section of the WVMR (ppmv) obtained from Era-Interim reanalysis dataset over the Tibetan Plateau region (30 N–40 N, 80 E–100 E). This figure shows that there is an increase in the WVMR (>6 ppmv) from 01 August 2015 to 07 August 2015. The WVMR is observed to be relatively low (<6 ppmv) in the UTLS region before and after this period.
3.2. Horizontal transport of water vapour in the WRF model Fig. 6 (a) and (b) show the composite spatial distribution of water vapour at 100 hPa for low and high water vapour cases, respectively. The 68
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Fig. 6. Composite spatial distribution of the WVMR (ppmv) at 100 hPa at 48 h forecast time. The black arrows show the horizontal wind vectors (a) for low WVMR cases and (b) for high WVMR cases. 69
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Fig. 7. (a) Spatial distribution of the difference in WVMR at 100 hPa for composite high and low water vapour cases at 48 h forecast time. The black arrows show the difference of horizontal wind between high and low cases and (b) same as Fig. 7 (a) but for the difference in temperatures (K) at 100 hPa pressure level (c) same as Fig. 7 (a) but for 700 hPa.
horizontal wind vectors at this level are also shown in these figures. It is noted from Fig. 6 (a) that the low water vapour appears over the Tibetan region covering 30–40 N, 80–100 E. The Asian summer monsoon anticyclone is elongated with respect to longitude and the water vapour is lower on the eastern flank of the anticyclone. In contrast, the anticyclone is relatively more symmetric along latitude and longitude for high water vapour composite as compared to the low water vapour composite. The high water vapour is not observed at the centre of the anticyclone but appears on the northern flanks of the anticyclone as shown in Fig. 6 (b). The difference between the WVMR and winds for the high and low
water vapour composites is plotted in Fig. 7 (a). The difference in the WVMR (and horizontal winds) is obtained by subtracting the average WVMR (and horizontal winds) for low water vapour cases from the average WVMR (and horizontal winds) for the high water vapour cases. It is apparent from Fig. 7 (a) that the water vapour is relatively higher over the Tibetan Plateau during the selected cases of high water vapour. Over the region of high WVMR, strong northwesterly wind differences are observed. This suggests that the water vapour is transported to this region horizontally from the region northwest of it during high WVMR cases. In other words, during the period of low WVMR cases, these 70
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Fig. 8. Spatial distribution of the horizontal water vapour flux (kg km2 s1) at 100 hPa. The black arrows show the horizontal water vapour flux vectors.
between high water vapour and low water vapour composites at 100 hPa. The difference in the composite horizontal wind vectors at 100 hPa pressure level are also shown in this figure. It can be seen from Fig. 7 (b) that during the high WVMR period, temperatures are relatively higher over eastern and northeastern China whereas the temperatures are relatively lower over net anti-cyclonic system over the central Indian region as compared to the low WVMR cases. The Tibetan Plateau has relatively higher tropopause temperatures as compared to the Bay of Bengal and central Indian region during high WVMR period. The relatively higher temperatures near the tropopause (~100 hPa in this case) suggest the tendency of air to hold more moisture and therefore there is a possibility of enhancement of water vapour in the proximity of the areas of high temperatures during high WVMR cases. Fig. 7(c) shows the spatial distribution of the difference in the WVMR for high water vapour and low water vapour cases at 700 hPa level. At 700 hPa, there are two net anti-cyclonic system differences over east and west coast of central Indian region. The water vapour is low at the centre of the anticyclone during high WVMR cases. There is convergence zone in between the two anti-cyclonic systems and water vapour is observed to be higher over this region at the lower heights for higher WVMR cases as compared to lower WVMR cases. The horizontal water vapour flux at 100 hPa is calculated in this study over the WRF domain. The water vapour flux is given as:
northwesterly winds are weaker transporting less water vapour to this region from northwest. Over the central Indian region, the circulation difference is anti-cyclonic which limits the horizontal transport of water vapour from the equatorial as well as Bay of Bengal region to the Tibetan Plateau during the period of high WVMR cases. Therefore, the possibility of the transport of water vapour from the Bay of Bengal region for these high WVMR cases appears to be very unlikely and can be demarcated in the WRF model simulations. Many studies have shown that the air masses are transported to upper troposphere from the north of Tibetan region by convective lifting followed by the entrapment of pollutants within the Asian monsoon anticyclone (Fu et al., 2006; Park et al., 2007, 2008; Li et al., 2005). Another feature in Fig. 7 (a) is the presence of a cyclonic circulation difference between high and low WVMR cases centered at around 45 N and 105 E and anti-cyclonic circulation difference over the central Indian region (25 N and 85 E). There is a convergence zone over the Tibetan Plateau and water vapour appears to be higher over this region, under the influence of circulations over the central Indian and south China region. This convergence zone seen in the difference plot indicate that during the high WVMR period, net inflow of water vapour is relatively more over this region as compared to the net outflow leading to the increase in water vapour over this region. The differences in composite water vapour and winds have also been plotted for other forecast times and similar features have been obtained (Figures not shown). It is apparent from Fig. 7 (a) that the prevailing winds are either weak northwesterlies or north easterlies for low water vapour cases as compared to high water vapour cases. The northwesterly wind difference plays the key role in the transport of water vapour from the extra-tropical tropopause to the Tibetan Plateau during high WVMR period. Fig. 7 (b) shows the spatial distribution of temperature difference
Water vapour flux, Qx ¼ q*x where Qx given in kg km2s1, q is mass concentration of water vapour and x is the zonal or meridional component of the wind. The q has been calculated from the model simulated WVMR using ideal gas law equation. The composite horizontal water vapour flux is calculated for high and low water vapour cases separately. The difference in the horizontal
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Fig. 9. (a) Spatial distribution of the difference in the instantaneous water vapour vertical flux between composite high and low water vapour cases over the part of the Asian monsoon region. The Tibetan Plateau region is shown by the thick black contour line and the black arrows show the residual horizontal wind vectors. The instantaneous values of flux for the initial conditions of the WRF model are shown and (b) same as Fig. 9 (a) but for 48 h forecast time.
flux is then calculated by subtracting the horizontal component for low cases from the high cases. Fig. 8 shows the magnitude of the zonal and meridional component of the difference in horizontal water vapour flux at 100 hPa. The black arrows represent the horizontal water vapour flux difference in vector form. It is seen that the water vapour flux increases in WRF model for high water vapour cases. The main difference is the transport of water vapour from the north of Tibetan Plateau under the influence of strong north westerly wind pattern during high WVMR cases.
lower stratospheric moisture over the Tibetan Plateau, it is necessary to calculate the vertical water vapour fluxes over this region. The instantaneous water vapour flux passing through the 100 hPa surface is calculated by the method given by Halland et al. (2009) for the selected high and low water vapour cases, separately. Composite plots water vapour flux for these high and low WVMR cases were then prepared. The spatial distribution of the difference in water vapour vertical flux between composite high and low water vapour cases over Tibetan Plateau (thick black line) region is shown in Fig. 9 (a)-(b). The black arrows show horizontal wind vectors. The difference in flux values shown in Fig. 9 (a) are for the initial condition of the WRF model whereas the values shown in Fig. 9 (b) are for the 48 h simulations from each initial condition. It can
3.3. Vertical transport of water vapour over the Tibetan Plateau To study the influence of convection on the upper tropospheric and 72
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Fig. 10. Tropopause height (hPa) obtained from the NCEP Reanalysis data for (a) low water vapour cases (26 July 2015–30 July 2015) and (b) high water vapour cases (01 August 2015–05 August 2015).
(b) that the water vapour vertical flux is relatively higher for high water vapour cases as compared to the low water vapour cases over the Tibetan Plateau region after 48 h simulation. The net water vapour flux appears to be positive over the Tibetan Plateau region. Heath and Fuelberg
be seen from Fig. 9 (a) that over the Tibetan Plateau region the forecasted vertical water vapour fluxes increase considerably from the initial values. Fig. 9 (a) suggest that the initial water vapour flux for high as well as low cases is almost same over the Tibetan Plateau. It can be noted from Fig. 9
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Fig. 11. Time series of the composite vertical velocity (ms1) and water vapour flux (kgkm2s1) simulated by the WRF model as a function of forecast hour during high water vapour (red line) and low water vapour (black line) cases at 100 hPa pressure level over the Tibetan Plateau region (30–40 N, 80–100 E) for (a) vertical velocity (ms1) and (b) water vapour flux (kgkm2s1). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
(2014) have also calculated the water vapour flux diurnal cycle at 150 hPa and 100 hPa levels. They have also shown that the net positive flux over the Tibetan Plateau region suggests the greater water vapour content at these levels. Fig. 10 (a) and (b) shows the tropopause pressure (hPa) obtained from NCEP reanalysis data (Kalnay et al., 1996) for low water vapour and high water vapour composites, respectively. It can be seen from Fig. 10 (a) and (b) that the average tropopause pressure is between 100 and 120 hPa over the Tibetan region (30–40 N, 80–100 dE). The 100 hPa level lies within the tropopause over the selected region for all the cases considered (high as well as low WVMR). Therefore, there are no mid-latitude tropopause jump locations over Tibet during the study period. The time series of the average vertical velocity of air (ms1) over the Tibetan Plateau (30–40 N, 80–100 E) is shown in Fig. 11 (a). The X-axis shows the forecast time (hours) from the initial condition. The red and black line shows the values for composite cases of high water vapour and low water vapour, respectively. It is seen in the figure that the vertical velocities are positive which represents the net ascent of air at 100 hPa level over the Tibetan Plateau. The vertical velocity is relatively higher for the selected cases with high water vapour. This suggests that local vertical ascent of air is also a cause of enhancement of water vapour in the upper troposphere and tropopause over this region. The existence any of artificial gravity waves in the present set of simulations could not be found. No particularly high vertical velocity values have been simulated which could be associated with these kind of waves. There are several studies which have used the WRF models to simulate convective or/and orographic gravity waves in UTLS realistically. Costantino et al. (2015) have very high-resolution configuration of the WRF model to simulate convective gravity wave propagation and breaking in the stratosphere. Spiga et al. (2008) have identified the sources of inertia-gravity waves in the Andes Cordillera region using observed radiosonde and WRF model simulations. Fig. 11 (b) shows the similar plot as Fig. 11 (a) but for the instantaneous vertical water vapour flux (kgkm2s1) over the Tibetan Plateau at
100 hPa pressure level. It must be noted from Fig. 11 (b) that the vertical water vapour flux is much higher for the high WVMR cases and relatively lower for the low water vapour cases. This suggests that the local vertical transport of water vapour also contributes to the occurrence of high water vapour over the Tibetan Plateau region. The magnitude of horizontal water vapour fluxes is around 103 times higher than the vertical water vapour flux. This suggests that horizontal transport and mixing contributes largely to the water vapour over the Tibetan Plateau region. 4. Conclusions The present paper discusses the transport pathways of the water vapour to the tropopause and lower stratosphere over the Tibetan Plateau region. The deepest penetrating convection is observed over the Bay of Bengal during the NH summer-monsoon period, whereas, the maximum water vapour in the tropopause region is observed over the Tibetan Plateau. The ~2-week period selected for this study was chosen after analyzing the WVMR data obtained from Era-Interim reanalysis and the MLS data. Both the data showed that the maximum hydration occurred over the Tibetan Plateau region during August, 2015. An increase in the WVMR over the Tibetan Plateau is seen from 01 August to 07th August 2015. The WVMR was relatively lower before and after this period. However, the case selected for the present study may not be representative for all the years. A comparison of the WRF simulations with that from observations showed that short-range simulations did not have any unrealistic trend or oscillation. The WRF model simulations suggest that the moistening of the Tibetan Plateau near the tropopause level can occur due to the southward horizontal transport of water vapour from the extra-tropics or the vertical transport of water vapour occurring over the Tibetan Plateau due to local convection or adiabatic processes. The ascending motions of air and relatively higher temperatures (~7–10 K higher than Bay of Bengal) near the tropopause favor the increase in the WVMR over the Tibetan region. This is in consensus to what many previous studies have shown (Li et al.,
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2005; Fu et al., 2006 and references therein) though the high water vapour is not observed at the centre of the Asian monsoon anticyclone but appears on the northern flanks of the anticyclone. The possibility of the transport of water vapour from the Bay of Bengal region to the Tibetan Plateau during the study period is limited by the presence of an anti-cyclonic circulation difference during high WVMR cases in the model simulations over the central Indian region. The water vapour flux from the WRF model suggests that the vertical transport of water vapour is higher during the high water vapour cases. This study shows that large enhancement or reduction in stratospheric moisture can occur without any contribution from deep convection occurring over the Bay of Bengal.
Holton, J.R., Haynes, P.H., McIntyre, M.E., Douglass, A.R., Rood, R.B., Pfister, L., 1995. Stratosphere-troposphere exchange. Rev. Geophys. 33 (4), 403–439. Homeyer, C.R., 2015. Numerical simulations of extratropical tropopause-penetrating convection: sensitivities to grid resolution. J. Geophys. Res. Atmos. 120, 7174–7188. http://dx.doi.org/10.1002/2015JD023356. Hong, S.Y., Kim, S.W., 2008. Stable boundary layer mixing in a vertical diffusion scheme. In: Proc. Ninth Annual WRF User's Workshop, 3.3. National Center for Atmospheric Research, Boulder, CO. Available online at: http://www.mmm.ucar.edu/wrf/users/ workshops/WS2008/abstracts/3–03.pdf. Hong, S.Y., Lim, J.O.J., 2006. The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteorol. Soc. 42, 129–151. IPCC AR4 SYR, Climate Change, 2007. Synthesis Report, Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, ISBN 92-9169-122-4. Jain, S., Kar, S.C., 2017. Sensitivity of upper tropospheric and lower stratospheric water vapour to the convective and cloud microphysics schemes: a case study. Meteorol. Appl. Under revision. Jain, S., Jain, A.R., Mandal, T.K., 2013. Role of convection in hydration of tropical UTLS: implication of AURA MLS long-term observations. Ann. Geophys. 31, 967–981. http://dx.doi.org/10.5194/angeo-31-967-2013. Jiang, J.H., Su, H., Pawson, S., Liu, H.C., Read, W.G., Waters, J.W., Santee, M.L., Wu, D.L., Schwartz, M.J., Livesey, N.J., Lambert, A., Fuller, R.A., Lee, J.N., 2010. Five year (2004–2009) observations of upper tropospheric water vapor and cloud ice from MLS and comparisons with GEOS-5 analyses. J. Geophys. Res. Atmos. 115 (D15). Jiang, J.H., Su, H., Zhai, C., Perun, V.S., Del Genio, A., Nazarenko, L.S., Donner, L.J., Horowitz, L., Seman, C., Cole, J., Gettelman, A., Ringer, M.A., Rotstayn, L., Jeffrey, S., Wu, T., Brient, F., Dufresne, J.L., Kawai, H., koshiro, T., Watanabe, M., Lecuyer, T.S., Volodin, E.M., Iversen, T., Drange, H., Mesquita, M.D.S., Read, W.G., Waters, J.W., Tian, B., Teixeira, J., Stephens, G.L., 2012. Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA “A-Train” satellite observations. J. Geophys. Res. Atmos. 117 (D14). Jiang, J.H., Su, H., Zhai, C., Wu, L., Minschwaner, K., Molod, A.M., Tompkins, A.M., 2015. An assessment of upper troposphere and lower stratosphere water vapor in MERRA, MERRA2, and ECMWF reanalyses using Aura MLS observations. J. Geophys. Res. Atmos. 120, 11468–11485. http://dx.doi.org/10.1002/2015JD023752. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., 1996. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77 (3), 437–471. Le, T.V., Gallus Jr., W.A., 2012. Effect of an extratropical mesoscale convective system on water vapor transport in the upper troposphere/lower stratosphere: a modeling study. J. Geophys. Res. 117, D03111. http://dx.doi.org/10.1029/2011JD016685. Li, Q., Jiang, J.H., Wu, D.L., Read, W.G., Livesey, N.J., Waters, J.W., Zhang, Y., Wang, B., Filipiak, M.J., Davis, C.P., Turquety, S., 2005. Convective outflow of South Asian pollution: a global CTM simulation compared with EOS MLS observations. Geophys. Res. Lett. 32, 14. Mahalov, A., Moustaoui, M., Grubisic, V., 2011. A numerical study of mountain waves in the upper troposphere and lower stratosphere. Atmos. Chem. Phys. 11, 5123–5139. Mote, P., Rosenlof, K., Mclntyre, M., Carr, E., Gille, J., Holton, J., Kinnersley, J., Pumphrey, H., Russell III, J., Waters, J., 1996. An atmospheric tape recorder: the imprint of tropical tropopause temperatures on stratospheric water vapor. J. Geophys. Res. 101 (D2), 3989–4006. Mote, P.W., 1995. The annual cycle of stratospheric water vapor in a general circulation model. J. Geophys. Res. 100 (D4), 7363–7379. http://dx.doi.org/10.1029/ 94JD03301. Park, M., Randel, W.J., Emmons, L.K., Bernath, P.F., Walker, K.A., Boone, C.D., 2008. Chemical isolation in the Asian monsoon anticyclone observed in Atmospheric Chemistry Experiment (ACE-FTS) data. Atmos. Chem. Phys. 8, 757–764. http:// dx.doi.org/10.5194/acp-8-757-2008. Park, M., Randel, W.J., Gettelman, A., Massie, S.T., Jiang, J.H., 2007. Transport above the Asian summer monsoon anticyclone inferred from Aura microwave Limb sounder tracers. J. Geophys. Res. 112 (D16). Randel, W.J., Wu, F., Vomel, H., Nedoluha, G.E., Forster, P., 2006. Decreases in stratospheric water vapor after 2001: links to changes in the tropical tropopause and the Brewer-Dobson circulation. J. Geophys. Res. 111, D12312. http://dx.doi.org/ 10.1029/2005JD006744. Smith, C.A., Joanna, D.H., Toumi, R., 2001. Radiative forcing due to trends in stratospheric water vapour. Geophys. Res. Lett. 28 (1), 179–182. Solomon, S., Rosenlof, K.H., Portmann, R.W., Daniel, J.S., Davis, S.M., Sanford, T.J., Plattner, G.K., 2010. Contributions of stratospheric water vapor to decadal changes in the rate of global warming. Science 327 (5970), 1219–1223. SPARC report 2, 2000. Assessment of Water Vapour in the Upper Troposphere and Lower Stratosphere. Spiga, A., Teitelbaum, H., Zeitlin, V., 2008. Identification of the sources of inertia-gravity waves in the Andes Cordillera region. Ann. Geophys. 26, 2551–2568.
Acknowledgements The initial and boundary conditions to run the WRF model has been obtained from ECMWF ERA-Interim reanalysis. The WRF model setup is obtained from the National Centre for Atmospheric Research (NCAR)/ University Corporation for Atmospheric Research (UCAR). The tropopause pressure data is obtained from NCEP reanalysis 1. The WVMR given by EOS Aura MLS and ERA-Interim is used in this study. This work is funded by Ministry of Earth Sciences (MoES) under the project ‘Modeling changes in water cycle and climate’. The authors are thankful to the Head, NCMRWF for his support in carrying out this research work. The authors are also thankful to the two anonymous reviewers for their suggestions on this paper. References Brewer, A.W., 1949. Evidence for a world circulation provided by the measurements of helium and water vapor distribution in the stratosphere. Q. J. R. Meteorol. Soc. 75, 351–363. Costantino, L., Heinrich, P., Mze, N., Hauchecorne, A., 2015. Convective gravity wave propagation and breaking in the stratosphere: comparison between WRF model simulations and lidar data. Ann. Geophys. 33, 1155–1171. Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Vitart, F., 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137 (656), 553–597. Dessler, A.E., Schoeberl, M.R., Wang, T., Davis, S.M., Rosenlof, K.H., 2013. Stratospheric water vapor feedback. Proc. Natl. Acad. Sci. U. S. A. 110 (45), 18087–18091. Dudhia, J., 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci. 46, 3077–3107. Forster, P.M.D.F., Shine, K.P., 1999. Stratospheric water vapour changes as a possible contributor to observed stratospheric cooling. Geophys. Res. Lett. 26, 3309–3312. Forster, P.M.D.F., Shine, K.P., 2002. Assessing the climate impact of trends in stratospheric water vapor. Geophys. Res. Lett. 29 (6). Fu, R., Hu, Y., Wright, J.S., Jiang, J.H., Dickinson, R.E., Chen, M., Filipiak, M., Read, W.G., Waters, J.W., Wu, D.L., 2006. Short circuit of water vapour and polluted air to the global stratosphere by convective transport over the Tibetan Plateau. Proc. Natl. Acad. Sci. U.S.A. 103 (15), 5664–5669. Fueglistaler, S., Dessler, A.E., Dunkerton, T.J., Folkins, I., Fu, Q., Mote, P.W., 2009. Tropical tropopause layer. Rev. Geophys. 47 (1) http://dx.doi.org/10.1029/ 2008RG000267. Gettelman, A., Kinnison, D.E., Dunkerton, T.J., Brasseur, G.P., 2004. Impact of monsoon circulations on the upper troposphere and lower stratosphere. J. Geophys. Res. 109, D22101. http://dx.doi.org/10.1029/2004JD004878. Grell, G.A., Dev enyi, D., 2002. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett. 29 (14). Halland, J.J., Fuelberg, H.E., Pickering, K.E., Luo, M., 2009. Identifying convective transport of carbon monoxide by comparing remotely sensed observations from TES with cloud modeling simulations. Atmos. Chem. Phys. 9 (13), 4279–4294. Heath, N.K., Fuelberg, H.E., 2014. Using a WRF simulation to examine regions where convection impacts the Asian summer monsoon anticyclone. Atmos. Chem. Phys. 14 (4), 2055–2070. Holton, J.R., Gettelman, A., 2001. Horizontal transport and the dehydration of the stratosphere. Geophys. Res. Lett. 28 (14), 2799–2802.
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