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Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information

[1] The Asian summer monsoon (ASM) is an important component of the global climate system. We investigate the relationship that exists between it and the snow accumulation record from an ice core drilled on the Dasuopu glacier in the Himalayas. This ice core record has been proposed as a proxy to study variability in the ASM. We argue that there is a weak direct expression of the ASM in the snow accumulation time series from the ice core. This is the result of the extreme elevation of the ice core site and the surface-trapped characteristic of the atmospheric moisture transport associated with the ASM. We will present evidence of a coupling between Dasuopu snow accumulation (DSA) and the Hadley and Walker circulations. In particular, we argue that the recent reduction in snow accumulation at the site is the result of an intensification of the regional Hadley circulation.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information

[2] The Asian summer monsoon (ASM) exerts an influence on a large region stretching from Africa to the western North Pacific Ocean. It is one of the most important components of the global climate system and has a direct impact on the livelihood of over half of the world's population [Webster et al., 1998; Trenberth et al., 2000]. The societal and economic activities in the ASM region are strongly affected by variability of the monsoon. Traditionally, the defining characteristic of the ASM was the reversal of winds in the region [Ramage, 1971]. Recently, it has become apparent that the ASM is a complex phenomena with differing regional manifestations that are the result of the interaction of a variety of meridional and zonal circulations [Webster et al., 1998; Wang and LinHo, 2002].

[3] The Qinghai-Tibetan Plateau with a mean elevation in excess of 4000 m is one of the most imposing topographic features on the Earth's surface. Along its southern flank are the Himalayas that are associated with the most extreme changes in elevation anywhere on the earth's surface. This plateau plays an important role in the ASM by acting as the heat source that drives the regional monsoon circulations [Ye, 1981].

[4] Observational records of climate span only the most recent years of the Earth's history. Long term time series such as oxygen isotope, snow accumulation, and chemistry and dust concentration extracted from ice cores provide records of past climate that are exceedingly important to the development of scientific understanding of the regional and global climate systems [Bradley, 2002]. In 1997, a 156.9 m long ice core was extracted at a high elevation site (7,020 m asl) from the Dasuopu Glacier (28°23′N, 85°43′E) on the south central rim of the Himalayas. The Dasuopu site is located within the footprint of the ASM and it has been proposed that the ice core data from the site is a suitable proxy to study variability in ASM [Thompson, 2000; Thompson et al., 2000].

[5] In this paper, we assess the relationship that exits between the ASM and DSA. This will be accomplished through a comparison of the dynamical processes associated with the ASM and DSA.

2. Data and Methods

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information

[6] In 1997, three ice cores were extracted from the Dasuopu glacier in the Himalayas. Snow accumulation in the region is sufficiently high as to allow for the recovery of annually resolved snow accumulation time series through the stratigraphic analysis of various tracers [Thompson et al., 2000]. These cores have the potential to provide valuable information on annually resolved climate variability in the region over the past 600 years. In this paper, we will make use of the annual snow accumulation time series from ice core C1 covering the period 1956 to 1993 [Thompson, 2000]. Snow accumulation at the site is thought to occur most often during the summer months [Thompson et al., 2000; Thompson, 2000].

[7] We will use several indices that have been developed to characterize variability of the ASM. The All Indian monsoon rainfall (AIMR) index is an area-weighted summer mean (June–September) of rainfall as measured by a homogeneous network of 306 raingauges throughout India [Parthasarathy et al., 1992]. The index is generally recognized as a reliable index of the ASM although strictly speaking it represents regional variability of the ASM over India [Wang and LinHo, 2002]. Goswami [1999] developed a meridional wind shear index to characterize the atmospheric circulation associated with the ASM. This index was defined as the summer mean (June–September) difference of the 850 mb meridional wind minus the 250 mb meridional wind over the domain from 70E–110E and from 10N–30N. In addition to the meridional shear index, we also investigate the relationship between the summer mean meridional wind at various levels over the Goswami domain and the ASM and DSA. To test the sensitivity of these so-called V-indices to the choice of domain, we also use an extended domain that went from 5S–30N. The NCEP reanalysis [Kalnay et al., 1996] will be used to calculate the V-indices.

[8] We use a compositing technique [Gershunov and Barnett, 1998; Moore et al., 2002] to extract the information on the climate signal associated with anomalously heavy snow accumulation at the Dasuopu site and with anomalously heavy ASM precipitation. For an identified set of anomalous years, composites of summer mean (June–September) atmospheric fields are computed from the NCEP reanalysis. The composites are displayed as anomalies with respect to the underlying climatology based on the years 1948–2000. Their statistical significance is assessed through the use of the Student's t-test. In this paper, we will use the vertically integrated moisture transport [Peixoto and Oort, 1993] as well as the horizontal moisture transport on the 400 mb pressure surface, the approximate height of the ice core site, to characterize the circulation associated with DSA and the ASM.

3. Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information

3.1. Dynamics of the Flow in the Vicinity of the Dasuopu Site

[9] In Figure 1, a meridional cross-section of the topography through the ice core site is shown. The aspect ratio for this cross-section is 100:1 which is appropriate for large-scale atmospheric flow [Cushman-Roisin, 1994]. With this scaling, the extreme elevation change that occurs to the south of the ice core site is evident. Superimposed on the cross-section is the summer mean (June–September) meridional component of the atmospheric water vapor transport to the south of the ice core site. As one can see, the atmospheric moisture transport during the summer monsoon season is confined to the lower troposphere and there is no significant transport at the elevation of the ice core site. The Froude number provides a measure of the tendency for airflow to be blocked by a topographic barrier. A Froude number less than 1.0 implies that there is insufficient kinetic energy available to supply the work required to lift an air parcel over the topographic barrier [Cushman-Roisin, 1994]. For summer mean conditions, the Froude number for the Dasuopu site is on the order of 0.1. The smallness of the Froude number suggests that there is no significant flow over the barrier.

image

Figure 1. Meridional cross-section of the topography at the longitude of the Dasuopu glacier (located at x = 0). The vectors indicate the height dependence of the summer (JJAS) mean meridional transport of water vapour in the region to the south of the glacier (10–20N, 72E–96E).

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3.2. Correlation Between DSA, AIMR and V-Indices

[10] Over the period of 1956–1993, the correlation coefficient between DSA and the AIMR is only 0.16, a correlation which is not statistically significant at the 95% confidence level. Table 1 gives the correlation coefficients between the V–indices (at various levels) and both DSA and the AIMR. With regards to the Goswami domain, we see that the AIMR has a positive correlation with V-index at the 700 mb and a negative correlation at upper level 250 mb. This results in a large and positive correlation with 700–250 mb wind shear index that reflects the presence of a regional Hadley circulation associated with the ASM. The correlations between the V-indices and DSA tend to have the opposite sign to those with the AIMR resulting in a negative correlation with 700–250 mb wind shear index. With regard to the sensitivity to the choice of domain, the AIMR correlations tend to be larger over the original, smaller, Goswami domain while the DSA correlations tend to be larger over the extended domain.

Table 1. The Correlation Coefficients Between V-Indices and DSA and AIMR
 DSA1DSA2AIMR1AIMR2
  1. a

    Note that DSA1 and AIMR1 are calculated over the domain 10N–30N; DSA2 and AIMR2 are calculated over the domain 5S–30N.The row titled 700–250 mb represents the vertical shear of the meridional wind between the 700 mb and 250 mb levels. Bold correlations are significant at 95% level while the bold underlined ones are significant at 99.9% level.

250 mb0.410.66−0.320.00
500 mb0.380.110.440.15
700 mb0.340.310.550.28
1000 mb0.460.290.290.29
700–250 mb−0.120.550.620.10

3.3. Trend Analysis

[11] The DSA, 250 mb V-index (defined over the extended domain), and AIMR time series are shown in Figure 2. As discussed by Thompson [2000], snow accumulation at the Dasuopu site has been decreasing over the period of interest. A similar trend appears to be present in the 250 mb V-index. This represents an intensification in the magnitude of the southward airflow in the region. Unlike these two time series, there appears to be no trend present in the AIMR.

image

Figure 2. The time series and trend statistics of: (a) DSA; (b) 250 mb V-index and (c) the AIMR. The years in which snow accumulation and the AIMR are anomalously high or low are indicated by ‘o’ and ‘x’ on the respective time series. For convenience, heavy and light AIMR years are also indicated by long and short arrows on the DSA time series.

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[12] We tested the validity of the null hypothesis that the trends in these time series, obtained with the standard least squares linear regression method, are indistinguishable from zero. Geophysical time series typically exhibit temporal autocorrelation that results in a tendency for elevated power at lower frequencies [Allen and Smith, 1994]. This characteristic was incorporated into the analysis by assuming that the regression residuals are not statistically independent but rather are temporally correlated. As a result, we used a reduced effective sample size, which is a function of the lag-1 (year) autocorrelation of the regression residuals, in the calculation of the standard error in the trend and in the application of the t-test [Santer et al., 2000]. With regards to the DSA and V-index time series, the null hypothesis can be rejected at the 95% confidence level. The trend lines for these two time series are indicated in Figure 2. For the AIMR time series, the null hypothesis cannot be rejected at the 95% confidence level.

[13] Superimposed on the DSA time series are significant wet or dry monsoon years, defined as those years in which the AIMR exceeds its long term (1871–1999) by ±10%. It can be seen that only two out of the seven wet years are also heavy snow accumulation years at the Dasuopu site. In addition, only three of the ten dry years are also light snow accumulation years at the Dasuopu site.

3.4. Moisture Transport

[14] We seek to identify the atmospheric circulation patterns associated with heavy snow accumulation years at the Dasuopu site and heavy precipitation years over India. The significant negative trend in the DSA time series makes the identification of anomalous years problematic. Accordingly, this time series was detrended prior to the selection of anomalously heavy years. The eight heavy snow accumulation and heavy AIMR years selected are indicated in Figure 2. With these years, we created composites of the summer mean geopotential height and moisture transport fields through the technique described in section 2.

[15] Figure 3 shows the composites of the anomalous vertically integrated moisture transport and 700 mb geopotential height fields associated with heavy rainfall years over India and heavy snow accumulation years at the ice core site. Heavy rainfall over India is seen to be associated with an intensification of the monsoon trough over northwest India and the concomitant increase in the cyclonic moisture transport over the subcontinent. In the vicinity of Dasuopu, there is no evidence of a statistically significant transport. Over southeast Asia, there is also evidence of an intensification of the moisture transport associated with the Walker circulation. With regard to heavy snow accumulation at the Dasuopu site, there is no evidence of a monsoonal circulation anomaly. There is however some evidence of an intensification and northward movement of the Walker circulation over southeast Asia.

image

Figure 3. Composites of the anomalous 700 mb height and vertically integrated anomalous horizontal moisture transport fields for: (a) the years in which AIMR was high and (b) the years in which snow accumulation at the ice core site (indicated by ‘+’) was high. The horizontal moisture transport field is only shown at those locations where at least one of its components is significant at the 95% level. The shaded region indicates the Tibetan Plateau at 700 mb.

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[16] Figure 4 shows the composites of the anomalous moisture transport and geopotential height fields on the 400 mb surface associated with heavy rainfall years over India and heavy snow accumulation years at the ice core site. With regards to the anomalies associated with heavy Indian rainfall, there is evidence of an intensification of the upper-level branches of the transverse monsoonal and Walker circulations. Heavy snow accumulation at the Dasuopu site is associated with an upper-tropospheric anticyclonic circulation that may be associated with the Walker circulation. This anomaly results in the easterly transport of moisture towards the ice core site.

image

Figure 4. Same as Figure 3 except for the 400 mb surface.

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4. Conclusions and Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information

[17] Ice core data from the Dasuopu glacier along the southern rim of the Qinghai-Tibetan Plateau represents an annually resolved record of climate variability over the past 600 years. The plateau plays an important role in the ASM and it has been suggested that this data provides a record of variability in the ASM. In this paper we provide a critical examination of this evidence for a relationship between the snow accumulation time series from the ice core and the ASM.

[18] Over the period from 1956–1993, a small correlation coefficient (0.16) between DSA and the AIMR suggests a weak direct coupling between the two. This low correlation does not imply that there are not localized regions influenced by the ASM where there exists a correlation with the ice core. For example, Thompson et al. [2000] found a statistically significant negative correlation between dust concentration in the core and summer precipitation in the region immediately south and west of the glacier. However, this region comprises less than 10% of the landmass of the Indian subcontinent and over the period 1871–2000 there is no statistically significant correlation between the summer precipitation in this region and the AIMR. Furthermore, the low correlation that we have identified between the AIMR and DSA does not imply that there will not be years in which the two are strongly correlated. For example, the Dasuopu ice core shows high levels of dust concentration during the catastrophic monsoon failures of 1790–1796 and 1876–1877 [Thompson et al., 2000]. As these extreme events were most likely associated with widespread and persistent circulation anomalies, it is unclear at this time the coupling between the environmental conditions on the Dasuopu glacier that resulted in high dust accumulation and those associated with the failure of the monsoon. For the limited period under investigation in this paper, we found no significant overlap between extreme monsoon years and extreme snow accumulation years.

[19] We have shown that the atmospheric moisture transport during the summer monsoon season is confined to the lower troposphere. In addition, the low Froude number for the flow implies that monsoonal flow is blocked by the Himalayas. Additional evidence of a weak expression of the ASM in the DSA record is found in the differing characteristics of their correlation with the V-indices. In particular, the correlations with DSA tend to have the opposite sign to those with the AIMR. Furthermore, we find no evidence of an intensification of the monsoonal circulation pattern over India during heavy snow accumulation years at the ice core site. Rather we find that in these years, there is an upper-level anti-cyclonic circulation anomaly that advects moisture from the North Pacific towards the ice core site. This anomaly may be associated with changes in the Walker circulation. Finally, snow accumulation at the ice core has been decreasing over the period of interest. We have shown that this trend is statistically significant at the 95% level. Similar behaviour has also been identified in the 250 mb meridional wind in the region. Given the anti-correlation that exists between the two, it is possible that the observed reduction of snow accumulation is the result of an intensification of the regional Hadley circulation.

References

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information
  • Allen, M. R., and L. A. Smith, Investigating the origins and significance of low-frequency modes of climate variability, Geophysical Research Letters, 21, 883886, 1994.
  • Bradley, R. S., Paleoclimatology (Second Edition), pp. 613, Harcourt Academic Press, 2002.
  • Cushman-Roisin, B., Introduction to Geophysical Fluid Dynamics, pp. 320, Prentice-Hall, 1994.
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  • Goswami, B. N., V. Krishnamurthy, and H. Annamalai, Indian summer monsoon variability, A broad scale circulation index for interannual variability of the Indian summer monsoon, Quart. J. Roy. Met. Soc., 125, 611633, 1999.
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  • Santer, B. D., et al., Statistical significance of trends and trend differences in layer-average atmospheric temperature time series, Journal of Geophysical Research, 105(D6), 73377356, 2000.
  • Thompson, L. G., Ice Core evidence for climate change in the Tropics: Implications for our future, Quaternary Science Reviews, 19, 1935, 2000.
  • Thompson, L. G., et al., A high-resolution millennial record of the South Asian monsoon from Himalayan ice cores, Science, 289, 19161919, 2000.
  • Trenberth, K. E., D. P. Stepaniak, and J. M. Caron, The global monsoon as seen through the divergent atmospheric circulation, Journal of Climate, 13, 39693993, 2000.
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Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data and Methods
  5. 3. Results
  6. 4. Conclusions and Discussion
  7. References
  8. Supporting Information

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