GC41A-0878 (8.4 MB, )

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Reconstructing 2000 years of Indian summer monsoon variability from high-resolution Tibetan lake sediments, eastern Himalaya
Broxton W.
1
Bird ,
Lonnie G.
1
Thompson ,
Tandong
2
Yao
1The
Ohio State University, Byrd Polar Research Center, 1090 Carmack rd. Columbus Ohio, 43210, USA
2Institute of Tibetan Plateau Research, Chinese Academy of Sciences, P.O. Box 2871, Beijing 100085, China
Abstract
Significance
This presentation outlines a joint United States and Chinese NSF funded research initiative to
investigate Indian summer monsoon (ISM) dynamics during the last 2000 years using high-resolution
lake sediment archives from the eastern Himalaya. Specifically, this work will examine the
relationships between ISM dynamics during the Medieval Climate Anomaly (MCA, AD 900 to 1300),
Little Ice Age (LIA, AD 1400 to 1800), and current warm period (CWP, the last 100 years) and 1)
radiative forcing, 2) ocean-atmosphere variability, and 3) other records of the Indian and Asian
monsoon. To address these questions, we will analyze the physical and geochemical characteristics of
sediment cores collected from small alpine lakes (~0.1 km2) in the Nyainqentanglha Mountains of the
southeastern Tibetan Plateau. This region is ideal for both ISM and Tibetan Plateau water resource
investigations because it is located at the point where ISM moisture from the Bay of Bengal is
transported into and westward across the Tibetan Plateau. As such, the hydrologic balances of lakes
in this region should be highly sensitive to changes in ISM rainfall and record variations in its strength
through time. Despite the Nyainqentanglha Mountain’s climatic significance, they are
underrepresented in the current body of paleoclimate research. By developing records of ISM
variability through time from this region, this research will provide new and valuable information
about ISM variability that can be used to explore how and why this system changes through time.
Here, we explore the current understanding of ISM variability, its significance, and future research
directions.
1998 El Niño SSTA
Photographs illustrating some of the
environmental and human systems
that ISM supports. Upper left: farmers
planting rice in the northwestern state
of Punjab. Upper right: The Khumbu
Glacier, Nepal. Lower left: Major rivers
originating on the Tibetan Plateau.
Research Objectives
Indian summer monsoon rainfall sustains water resources.
1) Glaciers
2) Regional groundwater
3) Rivers
4) Dry season water supplies
5) Agriculture
6) Municipal water supplies
1) Collect high-quality sediment cores from alpine lakes in the Nyainqentanglha Mountains.
2) Produce quantitative records of hydrologic variability using hydroclimate proxies.
3) Identify temporal patterns of mean state changes in regional ISMR variability for the last 2000
years.
4) Synthesize our results with other high-resolution paleoclimate records from Asia.
Research Questions
1) How has ISM intensity changed in the Nyainqentanglha Mountains during the last 2000 years?
2) Is there evidence for long-term reductions/intensifications of the ISM during the MCA, LIA, or CWP?
3) How does ISMR variability in the Nyainqentanglha Mountains compare with monsoon variability
across Asia?
4) To what extent do radiative forcing and ocean-atmosphere processes contribute to long-term, highfrequency ISMR variability?
Approach
This work will collect new lake sediment archives from small alpine lakes in the Nyainqentanglha
Mountains. This region was selected because it is a center of ISM activity, but is underrepresented by
instrumental and paleoclimate data.
Target lakes have been identified in three regions that represent areas most affected by the ISM (Fig.
1 & 2). By reconstructing changes in the hydrologic regimes of these lakes, we hope to identify mean
state changes in the strength of the ISM through time and their relationship with larger scale climate
phenomenon
Climatology
Images provided by the NOAA/ESRL Physical Sciences Division, Boulder Colorado from their
Web site at http://www.esrl.noaa.gov/psd/
2010 El Niño Modoki SSTA
1997 +IOD Event
Figure 2 (a) Vector winds associated with the ISM during June, July, and
August. (b) Spatial distribution of ISM precipitation.
Figure 3 Sea surface temperature anomalies (SSTA) during the (a) 1998 El Niño event, (b) the 2010 El
Niño Modoki event, and (c) 1997 positive IOD event.
Indian Summer Monsoon
The Boreal summer precipitation maximum that characterizes the ISM is
associated with a northward position of Intertropical Convergence Zone
(ITCZ) and reversal in seasonal wind direction. Although insolational
heating of the Tibetan Plateau has been long held as an important
driver of the onset of the ISM (e.g., Li and Yanai, 1996), new research
suggests that the ISM is initiated and sustained largely by the delivery of
warm moist air by the arrival of the ITCZ and its isolation from cool dry
air from the Tibetan Plateau by the Himalaya Mountains (Boos and
Kuang, 2010).
Influences on the ISM
ISMR is impacted by internal variability as well as large-scale ocean-atmosphere variability and global
teleconnections. Influences include the El Niño-Southern Oscillation (ENSO), the El Niño Modoki, and the
Indian Ocean Dipole (Krishnamurthy and Kirtman, 2009; Kumar et al., 2009). Reduced ISMR is associated
with warm ENSO events, particularly the Modoki mode, and negative phases of the IOD. Warm ENSO phases
are shown above (reduced ISMR) along with a negative phase of the IOD (increased ISRM). These modes
dominate interannual ISMR variability. Decadal trends are less well understood because of the paucity of
long-term instrumental records. A shift in the secular nature of the Indian summer monsoon occurred at the
time of the AD 1976 Pacific and Indian ocean regime shift, however (Clark et al., 2000) , which suggests that
decadal and longer-scale ocean atmosphere forcing contributes to ISM variability.
Isotopes in Precipitation
a.
b.
- Southern Tibetan Plateau is source of several large rivers (e.g., the
Brahmaputra River).
- Rainfall from the ISM contributes to Tibetan Plateau water supplies (Tian
et al., 2003).
- Some work suggests that ISMR is decreasing while intense intervals are
increasing (Dash et al., 2009).
Methodology
Age Control
- 210Pb, 137Cs, 226Ra
- 14C
Sedimentology
- Total organic carbon
- Total carbonate
- Grain size
- Bulk density
- Magnetic susceptibility
We choose to utilize lake sediments for reconstructing ISMR because 1) lakes are geographically welldistributed across the Himalaya and Tibetan Plateau, 2) are sensitive to climate change at the timescales with which this work is concerned, and 3) they often have sedimentation rates equal to, or
greater than, 1 mm yr-1 in alpine settings, which justifies sampling sediment cores at annual, or near
annual, resolution.
Figure 1 Map of the Tibetan
Plateau and surrounding
region. Lake records are
represented by circles (Table
1) and ice cores by triangles.
The target region for this work
is shaded in dark gray and
numbered with roman
numerals I-III. The thick
dashed lines demarcate the
region of Tibet influenced by
the ISM with the Himalaya to
the south and the Tanggula
Mtns. to the north (Tian et al.
2003). The direction of
moisture influx to the Tibetan
Plateau is shown with grey
arrows.
I.
II.
Sediment geochemistry
- Trace and major elements
- Ca, Fe, Mg, Si, Ti, Al
- Stable carbonate isotopes
- δ18O, δ13C
Limnology
-Modern lake hydrology
- δ18O, δD
- pH, DO, temperature, conductivity
- Alkalinity
Figure 4 Annual relationship between δ18O
and air temperature in recent precipitation
events at four meteorological stations on the
Tibetan Plateau (Tian et al., 2003).
Figure 5 Seasonal distribution of δ18O in
recent precipitation at four meteorological
stations on the Tibetan Plateau (Tian et al.,
2003).
Figure 6 (a) Correlation between monthly anomalies of temperature and δ18O based on
IAEA station data. Significant correlations at p < 0.05 are indicated by white crosses. (b)
as in (a) but for correlation between monthly anomalies of precipitation and δ18O (Vuille
et al., 2005).
Isotopes in precipitation (δ18O, δD) in regions affected by the ISM, or downstream from those regions, are influenced most significantly by the amount of precipitation that occurs during the
monsoon season. Lakes in regions affected by the ISM that contain a sedimentary archive suitable for measuring δ18O trends may therefore be useful in reconstructing past hydrologic
variability related to mean state changes in the ISM.
Regional Records
Ice Cores
Speleothems
6
4
(Zhang et al., 2008)
(Thompson et al., 1989)
2
(Cai et al., 2010)
(Thompson et al., 2000)
(Cosford et al., 2009)
Field Plan
Supported by US National Science Foundation and the
Institute of Tibetan Plateau Research (Chinese Academy of
Sciences) , an expedition to recover sediment cores from
alpine lakes in the Nyainqentanglha Mountains will be
conducted during May and June of 2011.
This expedition will spend 1 to 2 weeks at each of the target
sites to perform coring and watershed assessment.
Initial sediment core analysis will be performed at the
Institute of Tibetan Plateau Research.
III.
Table 1 List of lake-based paleoclimate studies from the Tibetan Plateau identified in
1 showing the length and resolution of the climate record.
Acknowledgements
This research is funded by the National Science Foundation Grant # EAR-1023547. Support
is also provided by the Chinese Academy of Science and the Institute of Tibetan Plateau
Research.
LIA
MCA
(Berkelhammer et al., 2010)
(Tan et al., 2009)
(Hu et al., 2008)
(Dykoski et al., 2005)
(Thompson et al., 1997)
7
5
Figure 7 Comparison of regional monsoon
records from speleothems (1-7) and ice core
records from the Tibetan Plateau. Also shown is
a lake record of the South American summer
monsoon from Pumacocha, an alpine lake in the
Peruvian Andes. It is apparent from this
comparison that late Holocene monsoon
variability in Asia is complex. Speleothems from
the Dandak cave in India and the Wanxiang cave
in China, however, show some noteworthy
similarities. This may suggest that western China
and India experience similar spatiotemporal
patters in monsoon variability. This work will
help test this idea.
3
Dun
Gul
DasIII.
7
II.
I.
65 4
3
2
1
1
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