globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2235
论文题名:
Evolution of the Southern Annular Mode during the past millennium
作者: Nerilie J. Abram
刊名: Nature Climate Change
ISSN: 1758-1311X
EISSN: 1758-7431
出版年: 2014-05-11
卷: Volume:4, 页码:Pages:564;569 (2014)
语种: 英语
英文关键词: Palaeoclimate ; Atmospheric dynamics
英文摘要:

The Southern Annular Mode (SAM) is the primary pattern of climate variability in the Southern Hemisphere1, 2, influencing latitudinal rainfall distribution and temperatures from the subtropics to Antarctica. The positive summer trend in the SAM over recent decades is widely attributed to stratospheric ozone depletion2; however, the brevity of observational records from Antarctica1—one of the core zones that defines SAM variability—limits our understanding of long-term SAM behaviour. Here we reconstruct annual mean changes in the SAM since AD 1000 using, for the first time, proxy records that encompass the full mid-latitude to polar domain across the Drake Passage sector. We find that the SAM has undergone a progressive shift towards its positive phase since the fifteenth century, causing cooling of the main Antarctic continent at the same time that the Antarctic Peninsula has warmed. The positive trend in the SAM since ~AD 1940 is reproduced by multimodel climate simulations forced with rising greenhouse gas levels and later ozone depletion, and the long-term average SAM index is now at its highest level for at least the past 1,000 years. Reconstructed SAM trends before the twentieth century are more prominent than those in radiative-forcing climate experiments and may be associated with a teleconnected response to tropical Pacific climate. Our findings imply that predictions of further greenhouse-driven increases in the SAM over the coming century3 also need to account for the possibility of opposing effects from tropical Pacific climate changes.

Warming of the polar regions has global implications for sea-level rise and climate change feedback processes such as decreased planetary albedo and the release of naturally stored carbon reservoirs. High-latitude amplification of global warming trends is clearly observed across the Arctic4, 5. In contrast, Antarctica is the only continental region where long-term cooling over the past 2,000 years has not yet been reversed to climate warming5. Yet some regions of Antarctica have warmed significantly over the past ~50 years, with the Antarctic Peninsula and parts of west Antarctica displaying the most rapid temperature increases in the Southern Hemisphere6, 7. Understanding these regional responses of Antarctic temperature to recent climate change requires an improved characterization of natural and anthropogenically driven changes in Southern Hemisphere climate variability.

Here we use the James Ross Island (JRI) ice core from the northern Antarctic Peninsula7, 8, 9 (64.2° S, 57.7° W; Fig. 1), along with other published temperature-sensitive proxies5, to reconstruct Southern Annular Mode (SAM) variability since AD 1000. The SAM can be defined as the zonal mean atmospheric pressure difference between the mid-latitudes (~40° S) and Antarctica (~65° S; ref 1). The positive phase of the SAM is associated with low pressure anomalies over Antarctica and high pressure anomalies over the mid-latitudes, and this enhanced atmospheric pressure gradient results in strengthening and poleward contraction of the Southern Hemisphere westerly jet stream1. The mountainous geographic barrier of the Antarctic Peninsula makes temperature variability in this region particularly sensitive to the strength of the westerly winds passing through Drake Passage. As such, JRI is a key location for documenting SAM-related climate variability (Fig. 1b) and previous work8, 9 has demonstrated that the water-isotope-derived temperature record from the JRI ice core is significantly correlated with observational indices of the SAM1, 10.

Figure 1: Regional temperature histories.
Regional temperature histories.

a, James Ross Island (JRI) temperature reconstruction7, 9 (green) alongside continent-scale temperature reconstructions5 for South America (red) and Antarctica (blue; excludes JRI). Anomalies shown as 7 yr (thin grey lines) and 70 yr (thick lines and grey shading) moving averages, relative to AD 1961–1990 means (dashed lines). b, Location of JRI (green cross) and proxies used in the South America (red crosses) and Antarctica (blue crosses) temperature reconstructions. Shading shows spatial correlation coefficient (r; p < 0.1) of the annual SAM index1 with 2 m air temperature in the ERA-Interim reanalysis16 (January–December averages; AD 1979– 2012).

Proxy records.

We use the deuterium isotope record from the JRI ice core as a temperature proxy for the Antarctic Peninsula region8, 9. Full details of the ice core site and isotope analysis can be found in ref. 7. We use the JRI1 age model with annual layer chronology since AD 1807, as in ref. 9. Deuterium isotope measurements made at 10 cm resolution along the upper 300 m of the ice core correspond to better than annual resolution since AD 1111 and were binned to produce annual (~ January–December) averages. The 111 years between AD 1000 and 1110 comprise 85 isotope measurements and interpolation was used to generate a pseudo-annual resolution record over this interval.

We also use temperature-sensitive proxy records for the Antarctic and South America continental regions5 to capture the full mid-latitude to polar expression of the SAM across the Drake Passage transect. The annually resolved proxy data sets compiled as part of the PAGES2k database are published and publically available5. For the South American data set we restrict our use to records south of 30° S and we do not use the four shortest records that are derived from instrumental sources. Details of the individual records used here and their correlation with the SAM are given in Supplementary Table 1.

Data are available at http://www.nature.com/nclimate/journal/v4/n7/full/ftp://ftp.ncdc.noaa.gov/pub/data/paleo/icecore/antarctica/james-ross-island/ and http://www.nature.com/ngeo/journal/v6/n5/full/ngeo1797.html

SAM reconstruction.

The proxy records from the South America, Antarctic Peninsula and Antarctic continent regions (where SAM has a significant influence on temperature; Fig. 1b) were used to reconstruct an annual average SAM index since AD 1000. We employ the widely used composite plus scale (CPS) methodology5, 11, 12 with nesting to account for the varying length of proxies making up the reconstruction. For each nest the contributing proxies were normalized relative to the AD 1957–1995 calibration interval, which represents the interval of maximum overlap between the annual (January–December) Marshall–SAM index (http://www.antarctica.ac.uk/met/gjma/sam.html) and most of the proxy network (Supplementary Table 1). The normalized proxy records were then combined with a weighting12 based on their correlation coefficient (r) with the SAM during the calibration interval (Supplementary Table 1). The combined record was then scaled to match the mean and standard deviation of the instrumental SAM index during the calibration interval. Finally, nests were spliced together to provide the full 1,008-year SAM reconstruction. Alternate methods for carrying out the CPS reconstruction were explored and the primary findings discussed here are shown to be robust across different methodologies (Supplementary Figs 1 and 2).

For each proxy nest a 95% confidence interval was defined as 1.96 times the standard deviation of the residuals of the SAM reconstruction from the Marshall–SAM index during the calibration interval. The reduction of error statistic was also calculated to test the performance of the reconstruction. The brevity of Antarctic instrumental records limits the ability to cross-validate the SAM reconstruction using separate calibration and verification intervals18. Instead, we assess the significance of reduction of error values by repeating 1,000 CPS simulations where the proxy network was replaced by AR(1) time series matching the length and lag-1 autocorrelation of the proxies and we use the upper 95th percentile to determine the critical reduction of error level (REcrit) for each proxy nest. We further verify the SAM reconstruction against the extended Fogt–SAM index10 (http://polarmet.osu.edu/ACD/sam/sam_recon.html). To carry out this assessment the four seasonal reconstructions were averaged to estimate an annual (December–November) Fogt–SAM index, which was then scaled to match the variance of the Marshall–SAM index from 1961 to 1990.

Model output.

We use multimodel output from the subset of CMIP5 climate models that ran transient Last Millennium simulations since AD 85021, 22. Historical simulations from the same ensemble were used to extend the model output from AD 1850. The CMIP5 Last Millennium and Historical experiments use transient radiative forcings that include orbital, solar, volcanic, greenhouse and ozone parameters as well as land use changes21, 22. All data was accessed from the Earth System Grid Federation node (http://pcmdi9.llnl.gov/esgf-web-fe/), with the exception of the historical portion of the HadCM3 Last Millennium simulation (provided by A. Schurer, Edinburgh University) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk3L simulations (http://www.nature.com/nclimate/journal/v4/n7/full/ftp://ftp.ncdc.noaa.gov/pub/data/paleo/gcmoutput/phipps2014/). To assess the importance of different radiative-forcing mechanisms, we used multiple simulations of the past 1,500 years carried out with the CSIRO Mk3L coupled climate model, as described in ref. 23. Supplementary Table 2 gives further details on the climate model data sets.

We use monthly resolution mean sea-level pressure fields to calculate the zonal mean at 40° S and 65° S. The model-generated data were averaged into January–December annuals to match the proxy data, normalized relative to the AD 1961–1990 interval and differenced to generate a SAM index1. We also use surface air temperature model output to examine SAM–temperature relationships at our proxy sites in the Last Millennium climate simulations (Supplementary Fig. 4).

Data archive.

The SAM reconstruction developed here is archived with the World Data Center for Paleoclimatology (http://hurricane.ncdc.noaa.gov/pls/paleox/f?p=519:1:0::::P1_STUDY_ID:16197).

  1. Marshall, G. J. Trends in the Southern Annular Mode from observations and reanalyses. J. Clim. 16, 41344143 (2003).
  2. Thompson, D. W. J. et al. Signatures of the Antarctic ozone hole in Southern Hemisphere surface climate change. Nature Geosci. 4, 741749 (2011).
  3. Gillett, N. P. & Fyfe, J. C. Annular mode changes in the CMIP5 simulations. Geophys. Res. Lett. 40, 11891193 (2013).
  4. Screen, J. A. & Simmonds, I. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature 464, 13341337 (2010).
  5. PAGES 2k consortium Continental-scale temperature variability during the past two millennia. Nature Geosci. 6, 339346 (2013).
  6. Bromwich, D. H. et al. Central west Antarctica among the most rapidly warming regions on Earth. Nature Geosci. 6, 139144 (2013).
URL: http://www.nature.com/nclimate/journal/v4/n7/full/nclimate2235.html
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/5133
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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Nerilie J. Abram. Evolution of the Southern Annular Mode during the past millennium[J]. Nature Climate Change,2014-05-11,Volume:4:Pages:564;569 (2014).
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