Spatial Variability of Climate and Past Atmospheric Circulation Patterns from Central West Antarctic Glaciochemistry
Atmospheric circulation patterns and the spatial variability of atmospheric chemistry and moisture transport in central West Antarctica are investigated using new 40 year long (1954–1994 A.D.) glaciochemical and accumulation rate records developed from four firn cores from this region. The core site...
Main Authors: | , , , , |
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Format: | Text |
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DigitalCommons@UMaine
1999
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Online Access: | https://digitalcommons.library.umaine.edu/ers_facpub/245 https://digitalcommons.library.umaine.edu/cgi/viewcontent.cgi?article=1250&context=ers_facpub |
Summary: | Atmospheric circulation patterns and the spatial variability of atmospheric chemistry and moisture transport in central West Antarctica are investigated using new 40 year long (1954–1994 A.D.) glaciochemical and accumulation rate records developed from four firn cores from this region. The core sites lie on a 200 km traverse from 82° 22′ S, 119° 17′ W to 81° 22′ S, 107° 17′ W. The glaciochemical records represent the major ionic species present in Antarctic snow: Na+, K+, Mg2+, Ca2+, Cl−, NO3−, and SO42−. High spatial variability appears in comparisons of full record averages and poor intersite linear correlation results. Accumulation rates show 50–100% changes over distances of 50–100 km and sea-salt concentrations drop by 50% between the middle two sites. One likely contributor to the high variability seen at this spatial scale is variability in synoptic- and finer-scale meteorology. Empirical orthogonal function (EOF) analysis shows that 80% or more of the variance in site chemistry can be attributed to two types of air masses: winter season air (50–70% of site variance) with a strong marine signature (heavy loading of sea-salt species) and summer season air (21% of the variance), marked by marine biogenic non-sea-salt SO4 plus NO3. This pattern of winter and summer regimes appears at other West Antarctic sites suggesting it may apply to the entire region. We show that a general picture of the patterns of variability in West Antarctica can best be drawn by using an analysis technique that fully exploits high resolution, multiparameter, multisite data sets. |
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