Quasi-biennial modulation of the Northern Hemisphere tropopause height and temperature

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 113,, doi: /2007jd009765, 2008 Quasi-biennial modulation of the Northern Hemisphere tropopause height and temperature P. Ribera, 1 C. Peña-Ortiz, 1 J. A. Añel, 2,3 L. Gimeno, 3 L. de la Torre, 2,3 and D. Gallego 1 Received 27 December 2007; revised 4 March 2008; accepted 7 April 2008; published 18 July [1] The influence of the quasi-biennial oscillation (QBO) on the tropopause pressure and temperature is studied through the application of the multitaper-singular value decomposition method (MTM-SVD). Reanalysis data (ERA-40) from the European Centre for Medium-Range Weather Forecasts (ECMWF) and radiosonde data from the Integrated Global Radiosonde Archive (IGRA) covering the period are used. The results show a strong response of the height and temperature of the tropopause to the QBO not limited to the equatorial latitudes but affecting the entire Northern Hemisphere. A cooling (warming) of the tropopause temperature over polar (equatorial) latitudes during a QBO positive phase is observed, being particularly noticeable over polar latitudes. The anomalies in the tropopause height confirm these results, with the tropopause being at higher (lower) levels in polar (equatorial) latitudes during QBO positive phase. Results for the QBO negative phase are of opposite sign. We also found that the results obtained using raw radiosonde data and reanalysis are in very good agreement. Finally, the evolution of the mass stream function through a QBO cycle is used to justify the differences observed in the evolution of the tropopause characteristics at low and high latitudes through the QBO cycle. Citation: Ribera, P., C. Peña-Ortiz, J. A. Añel, L. Gimeno, L. de la Torre, and D. Gallego (2008), Quasi-biennial modulation of the Northern Hemisphere tropopause height and temperature, J. Geophys. Res., 113,, doi: /2007jd Introduction [2] The number of publications in recent years on the tropopause and in its characteristics and variability indicates an increasing interest in the topic. The tropopause is the boundary layer between the troposphere and the stratosphere and its position is determined by its location above the troposphere, whose structure is determined mainly by convection, and below the stratosphere, which is predominantly radiatively controlled, and it plays an important role in the exchange of water vapor, mass, and chemical compounds between the two layers [Holton et al., 1995]. [3] Recently, Pan et al. [2007] analyzed the results of the Stratosphere-Troposphere Analysis of Regional Transport (START) experiment and proposed that the tropopause at midlatitudes, equatorward of the jet, appeared to behave as a transport barrier between stratospheric and tropospheric air masses, while at higher latitudes this behavior was not so pronounced and mass transport between the two layers could take place across the tropopause. [4] At tropical latitudes, different authors have studied how the tropopause can affect deep convection over the 1 Departamento de Sistemas Fisicos, Quimicos y Naturales, Universidad Pablo de Olavide, Seville, Spain. 2 CESAM, Departamento de Fisica, Universidade de Aveiro, Aveiro, Portugal. 3 Facultad de Ciencias de Ourense, Universidad de Vigo, Ourense, Spain. Copyright 2008 by the American Geophysical Union /08/2007JD region and, consequently, the dynamics of the troposphere. Huesmann and Hitchman [2001] identified a correlation between a stratospheric oscillation, such as the quasi-biennial oscillation (QBO) [Baldwin et al., 2001], and the evolution of the pressure and temperature at the tropical tropopause, with the oscillation possibly affecting other tropospheric variables. The authors proposed that it would be of interest to determine the extent of the influence of the QBO on global weather. Collimore et al. [2003] continued to investigate the relationship between the QBO and tropospheric dynamics. They found that the different phases of the QBO were characterized by different heights and amounts of tropical deep convection. They suggested that these phenomena might be caused, at least partially, by the variations of the tropopause properties. They also proposed that a better understanding of the relationship between the QBO and tropical deep convection could help meteorologists and climatologist to forecast tropical rainfall and, possibly, weather around the globe. However, the impact of the QBO is not limited to tropical latitudes. Angell and Korshover [1964] had already described biennial and quasibiennial oscillations of different variables at extratropical latitudes, for example total ozone, temperature, or tropopause height, that occurred in phase or out of phase with respect to the equatorial QBO. [5] During the last decade, some authors have proposed different mechanisms by which the QBO signal is transmitted to middle and high latitudes. Baldwin et al. [2001], Huesmann and Hitchman [2001], or Ribera et al. [2004], among others, describe a secondary meridional circulation 1of10

2 that extends the impact of the QBO from the equator to approximately 40 into each hemisphere through the generation of cells of meridional circulation. Those cells propagate vertically, following the characteristic QBO descent of the zonal wind over the equator. [6] At higher latitudes and during the positive QBO phase, the polar vortex becomes stronger and the temperature over the area becomes colder than normal. To explain this relationship, the interaction between wave activity at extratropical latitudes and mean flow has been proposed, such that during the west (east) phase of the QBO the interaction weakens (intensifies) the Brewer-Dobson circulation, and thus favors upwelling (downwelling) in the Arctic region that has to be compensated by downwelling (upwelling) at lower latitudes [Baldwin et al., 2001; Salby and Callaghan, 2005; Calvo et al., 2007]. Given that wave activity is stronger during the hemispheric winter, the mechanism just described should be more evident in the Northern Hemisphere during December, January, and February. [7] In the past, most research about stratospheric variability has been based in the analysis of data from reanalysis or from output from models. While these data sources provide excellent resolution in space and time, their dependence on the assimilation model and model characteristics could introduce artificial biases in the results. Therefore, the use of direct measurements, such as those provided by radiosonde data, remains essential. Randel et al. [2000] studied the relationship between the QBO and the temperature and pressure at the tropopause level. They used NCEP reanalysis data covering the periods and , obtaining for these periods values of explained variance of 52% and 12%, respectively. In addition, they performed a comparison with radiosonde data from a subset of 26 tropical stations (22 in some cases). In general, their results showed good agreement with those from reanalysis. However, analysis using radiosonde data is particularly problematic, due to the shortage of data, time gaps, or uneven spatial coverage. Recently, Añel et al. [2007, 2008] studied the problem of data homogeneity in the Integrated Global Radiosonde Archive (IGRA) radiosonde database and proposed a subset of sites for climatic studies, the use of which will avoid many of the problems, at least partially. [8] The importance of analyzing the raw radiosonde in climatic studies is often dismissed. Although much of the IGRA radiosondes are included in reanalysis products, in a reanalysis the use of several radiosonde databases [Durre et al., 2006], the application of filters and the influence of the assimilation model [Haimberger, 2005] can potentially cause strong differences between the raw radiosondes and reanalysis derivatives. In addition, the use of the original radiosondes supplies information that is hardly accessible from reanalysis, as for example the capability for identifying multiple tropopauses or for a fine characterization of the thermal structure of the atmosphere. [9] The objective of this paper is double. First, to analyze the QBO effects on the tropopause characteristics (pressure and temperature) that is obtained isolating the QBO projection on several variables by using the multitaper-singular value decomposition method (MTM-SVD) [Mann and Park, 1999]. Second, to study the coherence of the results obtained by using simultaneously reanalyzed data from the European Centre for Medium-Range Weather Forecasts (ERA-40) and the raw observations from IGRA. [10] The paper is organized as follows: In section 2, the data used in the analysis and the method applied are described. In section 3, the main results of this study are presented and discussed in detail. In section 4, the main results are summarized and conclusions are presented. 2. Data and Methods [11] In order to characterize the quasi-biennial oscillation detected in the evolution of the values of pressure at the tropopause level, reanalyzed data from ERA-40 [Simmons and Gibson, 2000; Uppala et al., 2005] and pressure and temperature at the tropopause data directly extracted from a radiosonde data set was used. The period analyzed was from January 1979 to December [12] The following fields from the ERA-40 reanalysis were used: zonal wind at 30 hpa and pressure at the tropopause level, with a spatial resolution of 5 longitude by 5 latitude. Additionally, mass stream function and mean zonal temperature at 30 levels between 1000 hpa and 1.15 hpa, with a meridional resolution of 5, being the mass stream function an ERA-40 product computed from v* and omega* of the TEM equations for the primitive equations [Andrews et al., 1987, equation (3.5.1)]. [13] Radiosonde data was extracted from the sounding meteorological data contained in the IGRA [Durre et al., 2006]. Only data corresponding to 0000 and 1200 UTC were analyzed. Considering that the number of stations releasing sondes at times different of 0000 and 1200 UTC is appreciable, we included as 1200 UTC soundings those that correspond to launchings between 0900 UTC and 1500 UTC. For 0000 UTC, the same criterion was followed using 2100 UTC and 0300 UTC. [14] The sounding profiles were analyzed individually using the World Meteorological Organization [1957] definition of the tropopause (lapse rate tropopause): The first tropopause is defined as the lowest level at which the lapse rate decreases to 2 C/km or less, provided also the average lapse rate between this level and all higher levels within 2 km does not exceed 2 C/km. [15] Monthly means of pressure and temperature at the tropopause level were computed for each station. Only those months with data on more than half of the days were considered. Once these filters were applied, 187 series were obtained that covered the whole world, the same ones used by Añeletal.[2007] and proposed by Añeletal.[2008]. [16] A new filter was applied and only those series whose missing values constituted less than 5% of the total were retained and used in the analysis. In this way, we used a sufficiently homogeneous data series and ensured that the results obtained were representative. The final number of radiosonde series used in the analysis was reduced to 61 with a good spatial coverage over most of the Northern Hemisphere; this is particularly true for high latitudes, given that 46 of these observatories are to the north of 30 N (Figure 1 and Table 1). [17] The MTM-SVD method permits the identification of coherent narrowband oscillatory signals in a multiple variable data set [Mann and Park, 1999]. The application of the method begins with the transformation of each of the M 2of10

3 Figure 1. Location of the radiosonde stations used. original time series (M being the number of stations or grid points) from the time to the spectral domain by applying the MTM procedure and using three orthogonal tapers (as proposed by Mann and Park [1999]) for analyzing the climate data. The three independent spectral estimates Y(f) computed for each of the M time series are organized in a M x 3 matrix A(f) for which a complex singular value decomposition (SVD) is performed at each frequency f. The left and right singular vectors so obtained are used to reconstruct the temporal (local fractional variance (LFV) spectrum) and spatial patterns of the signal that are associated with a given frequency. [18] The LFV spectrum is used to identify the dominant timescales of any statistically significant patterns of variability in the underlying climate fields. It must be read as a classic Fourier spectrum, though it represents the joint spectrum of all the data sets included in the original data set. A Monte Carlo test is performed to determine significant oscillatory bands. [19] Once the significant frequencies are identified, the right singular vector obtained by applying the complex SVD can be used to reconstruct the evolution of the spatial pattern associated with those frequencies through a complete cycle. [20] In this study, the MTM-SVD method was applied to a data set that included the following items simultaneously: the zonal wind field at 30 hpa, pressure at the tropopause from reanalysis, pressure and temperature at the tropopause computed from the sounding data contained in the radiosonde data set, and the temperature and mass stream function data corresponding to 30 vertical levels of the ERA-40 reanalysis. [21] The MTM-SVD method was applied using deseasonalyzed monthly data for the annual analysis (both for the reanalysis and for the radiosondes) and winter anomalies for the winter analysis (using December, January, and February as representative winter months). The data was deseasonalyzed by subtracting the monthly long-term mean values to the original data at each grid point or radiosonde station. The zonal wind data at 30 hpa was used to define the evolution of the cycle. Phase 0 of a cycle is the one corresponding to the maximum intensity of west winds over the equator at 30 hpa. The evolution of the remaining variables follows the same cycle as that observed for the zonal wind. Further details of this method and its application can be found in the work of Ribera et al. [2004]. 3. Results [22] The application of the MTM-SVD method to the joint data sets of monthly data for the zonal wind at 30 hpa (extracted from the ERA-40 reanalysis), pressure at the tropopause (from the ERA-40 and computed from sounding data), temperature at the tropopause (computed from sounding data), and temperature and mass stream function from the ERA-40, led to the identification of a significant coherent band of oscillation with a broad maximum between 0.35 and 0.47 cycles per year, with peaks centered at 0.46 and 0.37 cycles per year (Figure 2). This band corresponds to an oscillation period slightly longer than 2 years, with peaks of approximately 26 and 32 months, which coincides with the band characteristic of the stratospheric QBO of the zonal wind, which is the dominant pattern of interannual variability of the equatorial strato- 3of10

4 Table 1. Radiosonde Stations Used, Showing WMO Station Code, Station Name, Latitude, Longitude, and Complete Period With Data for the Radiosonde Station WMO Code Station Name Latitude Longitude Period JAN MAYEN SODANKYLA LERWICK VALENTIA OBSERVATORY KEFLAVIK EGEDESMINDE NARSSARSSUAQ SCORESBYSUND AMMASSALIK LA CORUNA GIBRALTAR MÜNCHEN ANKARA SOJNA PECHORA MAGADAN VOLOGDA PETROPAVLOVSK KYIV CHKALOV BET DAGAN THIRUVANANTHAPURAM KING S PARK WAKKANAI SENDAI KAGOSHIMA CHICHI JIMA MARCUS IS BANGKOK SINGAPORE/CHANGI HAILAR KASHI BARROW ANCHORAGE ST. PAUL ISLAND ANNETTE ISLAND ALERT SABLE ISLAND ST. JOHNS GOOSE BAY MOOSONEE FROBISHER CAMBRIDGE BAY BAKER LAKE FORT SMITH INUVIK KEY WEST BROWNSVILLE SAN DIEGO DODGE CITY OAKLAND SALEM GREAT FALLS DAVENPORT SAN JUAN LIHUE AGANA HILO/LYMAN CHUUK MAJURO ATOLL KOROR sphere [Baldwin et al., 2001]. When winter mean values for zonal wind and pressure at the tropopause were analyzed, similar results were obtained, and, again, a significant quasibiennial band was identified (Figure 2). [23] Once the significant oscillation periods were identified, the evolution of the associated spatial patterns through a complete cycle was reconstructed. Figure 3 (top) includes the evolution of the spatial pattern of the Northern Hemisphere zonal wind through half a cycle (16 months) of this quasi-biennial oscillation with the 0.37 cycles/yr frequency, from phase 0 to phase 180, where phase 0 of the cycle corresponds to the initial stage of the oscillation and every 4of10

5 Figure 2. Annual and winter local fractional variance (LFV) spectrum of the joint zonal wind at 30 hpa + pressure and temperature at the Tropopause data set. The y axis corresponds to the relative variance explained by the first eigenvalue of the SVD obtained for every frequency (named local fractional variance). Dashed lines denote 90% and 95% confidence limits from Monte Carlo simulations. 45 represent approximately four months of delay. Results obtained with the 0.46 cycles/a frequency are very similar to those for the 0.37 cycles/a band and will not be presented in this paper. [24] From Figure 3, it becomes evident that the main characteristic of the initial phase is the existence of an intense positive zonal wind belt over the equator that decreases with the latitude until 35 N and then begins to Figure 3. Evolution of the spatial pattern of the zonal wind at 30 hpa through half a cycle (f = 0.37 cycles/a) at (top) annual and (bottom) winter timescales. 5 of 10

6 Figure 4. Evolution of the spatial pattern of pressure at the tropopause from ERA-40 data (color contours) and from radiosonde data (circles) through half a cycle (f = 0.37 cycles/a) at (top) annual and (bottom) winter timescales. Pressure anomalies are expressed in hpa, both for radiosonde and ERA data. Blue denotes negative anomalies both for ERA-40 and radiosonde data, while yellow and red denote positive anomalies for ERA-40 and radiosonde data, respectively. White areas correspond to null anomalies (lower than 0.5 hpa in absolute value). The same scale was used for annual and winter data. increase again until it reaches a secondary maximum at approximately 65 N. Spring, summer, and autumn analyses (figures not included) showed that the weak manifestation of the secondary maximum near 65 N in the annual cycle had its origin in the cold seasons (winter and spring), and that the annular character of this acceleration disappeared in summer and, specially, in autumn. The following phases of the oscillation are characterized by a deceleration of the equatorial zonal wind toward negative values and by the disappearance of the polar vortex acceleration. Phases 135 and 180 of the oscillation, 12 and 16 months after phase 0, are characterized by negative values for the zonal wind over the equator and an increasing deceleration of the polar vortex. The spatial patterns reconstructed for other frequencies, such as 0.46 cycles/a, are very similar to the one presented in Figure 3, with slightly different values in the anomalies of the zonal wind being characteristic during every phase. [25] The winter analysis of the evolution of the oscillation shows characteristics very similar to the annual one, but with the situation at high latitudes better defined. During phase 0, the positive anomaly of the zonal wind at high latitudes draws a complete circulation ring around the pole, which corresponds to an intensified polar vortex. In addition, the following phases show characteristics quite similar to those of the annual analysis, but with an intensified response over the higher latitudes. Phase 0 of the winter analysis should be interpreted as a winter when the QBO reaches its maximum positive phase, west phase (maximum zonal wind at 30 hpa over the equator), and phases 45, 90, and subsequent correspond to winters 4 months, 8 months, etc, after the maximum positive QBO phase. [26] Both the LFV spectra and the reconstruction of the spatial patterns resemble very much the results reported in two previous publications, in which the equatorial QBO and its effects in low and middle latitudes were characterized by applying the MTM-SVD method to data obtained from the NCAR-NCEP reanalysis [Ribera et al., 2003, 2004]. Ribera et al. [2003] showed that the acceleration of the polar vortex during the positive phase of the QBO was associated with colder than normal conditions for the stratosphere over the polar area, while Ribera et al. [2004] presented a reconstruction of the secondary circulation of the QBO and its evolution through a QBO cycle. [27] The effect of the QBO in zonal wind on tropopause pressure level is presented in Figure 4. We observe essentially an annular structure, in which an elevation of the tropopause level (negative anomalies of pressure) in high latitudes is opposed to a fall at lower latitudes and vice versa. The positive phase of the QBO (west phase or phase 0) is characterized by lower than normal values of the pressure at the tropopause over high latitudes of the Northern Hemisphere and higher than normal values over low latitudes. With the evolution of the phases, the situation 6 of 10

7 Figure 5. Evolution of the spatial pattern of the zonal wind at 30 hpa from ERA-40 data (color contours) and of temperature at the tropopause from radiosonde data (circles) through half a cycle (f = 0.37 cycles/a) at (top) annual and (bottom) winter timescales. Blue denotes negative anomalies both for ERA-40 and radiosonde data. White areas correspond to null anomalies (lower than 0.5 m/s in absolute value). Temperature anomalies are expressed in C. is reversed: during the negative phases of the QBO, the tropopause at high latitudes is characterized by higher than normal pressure values, which represents a lower level of the tropopause. Once again, this situation can be characterized better when the winter situation is analyzed. In this season, the annular character of the spatial pattern is better defined, as can be observed in Figure 4 (bottom). [28] It is worthwhile to note the good agreement between the qualitative results obtained when using data from the ERA-40 reanalysis and from radiosonde data. In phase 0, the area covered by negative anomalies over high latitudes in the ERA-40 reanalysis (blue areas) includes all the negative variations that were detected in the tropopause pressure level using radiosonde data (Figure 4). In addition, positive anomalies at lower latitudes that were detected using radiosonde data are located over yellow/orange areas, where positive anomalies regarding the pressure at the tropopause were identified using ERA-40 data. Both from the ERA-40 and from radiosondes, the anomalies detected for the pressure at the tropopause level are stronger at high than at low latitudes. This behavior is found both on the annual and winter timescales. [29] The quantitative results obtained from the two data sets are also similar. The maximum anomalies that were detected for the pressure at the tropopause are located over the polar region both in the winter and in the annual analysis, while anomalies at lower latitudes are smaller. At low latitudes, the modulation of the pressure at the tropopause produces low anomalies, below 10 hpa, and the values obtained both from the IGRA and from the ERA40 are equivalent. The magnitude of these anomalies remains constant for the annual and the winter analyses. By contrast, at high latitudes, there is a noticeable difference between the annual and the winter values of the anomalies. Anomalies in the tropopause level reach values near 30 hpa in the winter analysis, both in IGRA and in ERA-40 data, while for the annual analysis the observed anomalies remain near 15 hpa. These differences are due to the winter intensification of the interaction between wave activity and mean flow caused by the winter intensification of the wave activity in the Northern Hemisphere, as later in this paper will be shown. [30] The analysis of the spatial patterns of the temperature at the tropopause level from radiosonde data, together with the analysis of its quasi-biennial oscillation, served to identify positive (negative) tropopause temperature anomalies at tropical latitudes during the westerly (easterly) phase of the QBO (Figure 5). Maximum anomalies in the tropical region are below 1 C for both the annual and winter patterns, which is in agreement with the results obtained by Randel et al. [2000] using reanalyzed and radiosonde data. Our results also agree with those of Huesmann and Hitchman [2001], in which a positive correlation between the QBO and the temperature at the tropopause was detected using data from the NCEP reanalysis, and with those of Collimore et al. [2003], in which an elevation (lowering) of 7 of 10

8 Figure 6. QBO anomalies induced in the mass stream function (contour lines) and temperature (shaded). Contours are drawn at ±50, 100, 200, 500, 1000, 2000, Kg/s. Solid (dashed) lines represent clockwise (anticlockwise) circulation. The vertical axis represents the pressure level in hpa. 8of10

9 the tropopause was detected during east (west) phases of the QBO. [31] At high latitudes, Figure 5 shows a cooling (warming) of the polar tropopause during the west (east) QBO phase. In this case, temperature anomalies are higher in the winter (maximum anomaly near 3.5 C) than in the annual pattern (maximum near 2.7 C). Anomalies of temperature are stronger at high latitudes than in the tropics in both the annual and winter analyses. [32] Previous studies [Salby and Callaghan, 2004, 2005] showed that changes in the Brewer-Dobson circulation induce anomalies in the tropopause temperature and height. In the areas where the stratospheric downwelling is anomalously weak (strong), the tropopause is, therefore, anomalously cold and high (warm and low). The QBO induces anomalies in the mean meridional circulation of the stratosphere at tropical and middle latitudes, which gives rise to the secondary circulation of the QBO [Ribera et al., 2004]. It also modulates the Brewer-Dobson circulation at the winter polar stratosphere [Calvo et al., 2007], where it modulates the upward propagation of planetary waves that drive the stratospheric mean meridional circulation. [33] Figure 6 shows mass stream function and temperature anomalies that are associated with the QBO during winter (DJF). At tropical latitudes, the secondary circulation of the QBO can be distinguished in the stratosphere. Three circulation cells can be identified in the winter hemisphere. During the westerly QBO phase, anticlockwise circulation anomalies are found in the low tropical stratosphere. These anomalies induce downwelling and warm temperature anomalies at the equatorial latitudes, which is consistent with the increase in the pressure and temperature of the tropical tropopause shown in Figures 4 and 5 during the westerly phase of the QBO. By contrast, the easterly QBO phase is associated with weaker downwelling and cold temperature anomalies at the equatorial low stratosphere, which is consistent with the negative anomalies in the pressure and temperature of the tropical tropopause. [34] At high latitudes, the westerly (easterly) phase of the QBO is associated with a lower (higher) wave activity in the polar stratosphere [Calvo et al., 2007] that leads to a weaker (stronger) downwelling and, therefore, to a colder (warmer) polar vortex, as shown in Figure 6. These anomalies are again consistent with the anomalies in the pressure and temperature of the tropopause shown in Figures 4 and 5, where the westerly (easterly) phase of the QBO is associated with a colder and higher (warmer and lower) polar tropopause. The QBO modulation of the northern polar vortex is much stronger during winter [Baldwin and Dunkerton, 1998]. This explains why QBO modulation of the polar tropopause is also greater during these months, as shown in Figures 4 and 5. [35] These results are consistent with the notion that the QBO modulation of the pressure and temperature of the tropopause occurs through the QBO modulation of the mean meridional circulation of the stratosphere, but through two different processes. At tropical latitudes, the QBO induces a secondary circulation that apparently modulates the height and pressure of the tropopause in the equatorial region, while at polar latitudes, it is the QBO modulation of the upward propagating planetary waves what modifies the winter downwelling at these latitudes that seems to affect the polar tropopause. It has been proposed that similar processes, where changes in the stratospheric mean meridional circulation affect the tropopause, govern, for example, the seasonal evolution of the tropopause [Salby and Callaghan, 2004]. 4. Summary and Conclusions [36] We applied the MTM-SVD method to data from two different sources in order to characterize the QBO modulation of the temperature and the pressure at the tropopause over the Northern Hemisphere in the period 1979 to One of these sources, the ERA-40 reanalysis, has been used frequently to study dynamic processes in the stratosphere, while the IGRA database, particularly the S187 subset [Añel et al., 2007, 2008], has become available only recently and had not previously been used to study dynamic modulations of tropopause characteristics. [37] Radiosonde data permit a very good characterization of the tropopause, but its spatial coverage makes it difficult to identify spatially coherent patterns. By contrast, reanalysed data has good spatial coverage, but because the original data included in the reanalysis model was processed to produce the final data sets, the detailed characteristic of some atmospheric variables may include some distortion, as, in example, a softening in the vertical temperature gradients. The modulation exerted by the QBO over tropopause characteristics that were observed when the series of the 61 radiosonde stations distributed over the Northern Hemisphere were used show very good agreement with those obtained with the ERA-40 data. In fact, the results of the comparison of both data sets at low latitudes are very similar to those obtained by Randel et al. [2000] using the NCEP reanalysis and a set of 26 (or 22) radiosonde stations at tropical latitudes. [38] Two mechanisms are thought to be responsible for the modulation of the tropopause characteristics at low and high latitudes, respectively. At low latitudes, a secondary meridional circulation induced by the QBO modulates the upwelling in the low tropical stratosphere and therefore the tropopause height and pressure. However, at polar latitudes, it is the QBO modulation of the upward propagating planetary waves in the winter stratosphere that induces anomalies in the downward branch of the Brewer-Dobson circulation at polar latitudes and seems to affect tropopause evolution. These mechanisms are consistent with the winter intensification of the QBO effects over the tropopause at polar latitudes and with similar processes proposed by Salby and Callaghan [2004] to explain the seasonal evolution of the tropopause. [39] Considering that the results obtained in the analyses presented in this paper with both data sets are quite similar, we may conclude that in future analysis of tropopause characteristics, when the research is focused on the analysis of spatial patterns, the ERA-40 data set will provide a good data source; while when a more detailed analysis of tropopause characteristics is sought, as for example the existence of double or triple tropopause, the use of the S187 IGRA subset is recommended. [40] Acknowledgments. This work was partly funded by the Spanish National Research Project TRODIM MEC-CGL C05-04/01- CLI. 9of10

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