Past Climate Variability and Change in the Arctic and at High Latitudes

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52 The U.S. Climate Science Program Chapter 3 Organic biomarkers can usually be recovered from Arctic sediments that do not preserve carbonate or siliceous microfossils. the δ/T slope produced by many of the large changes recorded in GreenlAnd ice cores was considerably less (typically by a factor of 2) than the spatial value, probably because of a relatively larger reduction in winter snowfall in colder times (Cuffey et al., 1995; Werner et al., 2000; Denton et al., 2005). The actual temperature changes were therefore larger than would be predicted by the standard calibration. In summary, water isotopes in polar precipitation are a reliable proxy for mean annual air temperature, but for quantitative use, some means of calibrating them is required. They may be calibrated either against instrumental data by using an alternative estimate of temperature change, or through modeling, even for ice deposited during the Holocene (Schmidt et al., 2007). 3.3.1f fossil assEmblagEs and sEa- surfacE tEmPEraturEs Different species live preferentially at different temperatures in the modern ocean. Modern observations can be used to learn the preferences of species. An inherent assumption is that species maintain their preferences through time. With that assumption, the mathematical expression of these preferences plus the history of where the various species lived in the past can then be used to interpret past temperatures (Imbrie and Kipp, 1971; CLIMAP, 1981). This line of reasoning is primarily applied to nearsurface (planktic) species, and especially to foraminifers, diatoms, and dinoflagellates. The presence or absence and the relative abundance of species can be used. Such methods are now commonly supported by sea-surface temperature estimates using emerging biomarker techniques outlined below. 3.3.1g biogEochEmistry Within the past decade, two new organic proxies have emerged that can be used to reconstruct past ocean surface temperature. Both measurements are based on quantifying the proportions of biomarkers—molecules produced by restricted groups of organisms—preserved in sediments. In the case of the “U k′ 37 index” (Brassell et al., 1986; Prahl et al., 1988), a few closely related species of coccolithophorid algae are entirely responsible for producing the 37-carbon ketones (“alkenones”) used in the paleotemperature index, whereas crenarcheota (archea) produce the tetra-ether lipids that make up the TEX 86 index (Wuchter et al., 2004). Although the specific function that the alkenones and glycerol dialkyl tetraethers serve for these organisms is unclear, the relationship of the biomarker U k′ 37 index to temperature has been confirmed experimentally in the laboratory (Prahl et al., 1988) and by extensive calibrations of modern surface sediments to overlying surface ocean temperatures (Muller et al., 1998; Conte et al., 2006; Wuchter et al., 2004). Biomarker reconstructions have several advantages for reconstructing sea surface conditions in the Arctic. First, in contrast to δ 18O analyses of marine carbonates (outlined above), the confounding effects of salinity and ice volume do not compromise the utility of biomarkers as paleotemperature proxies (a brief discussion of caveats in the use of U k′ 37 is given below). Both the U k′ 37 and TEX 86 proxies can be measured reproducibly to high precision (analytical errors correspond to about 0.1°C for U k′ 37 and 0.5°C for TEX 86), and sediment extractions and gas or liquid chromatographic detections can be automated for high sampling rates. The abundances of biomarkers also provide insights into the composition of past ecosystems, so that links between the physical oceanography of the high latitudes and carbon cycling can be assessed. And lastly, organic biomarkers can usually be recovered from Arctic sediments that do not preserve carbonate or siliceous microfossils. It should be noted, however, that the harsh conditions of the northern high latitudes mean that the organisms producing the alkenone and tetraethers possibly were excluded at certain times and places; thus, continuous records cannot be guaranteed. The principal caveats in using biomarkers for paleotemperature reconstructions come from ecological and evolutionary considerations. Alkenones are produced by algae that are restricted to the region of abundant light (the photic zone), so paleotemperature estimates based on them apply to this layer, which approximates the sea surface temperature. In the vast majority of the ocean, the alkenone signal recorded by sediments closely correlates with mean annual sea-surface temperature (Muller et al., 1998; Conte et al., 2006; Figure 3.17). However, in the case of highly seasonal high-latitude oceans,
U K’ 37 U K’ 37 U K’ 37 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 A Atlantic (451) B Pacific (131), Indian (5) and Southern (42) Oceans C Global dataset (629) Past Climate Variability and Change in the Arctic and at High Latitudes 0.0 –2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 WATER TEMPERATURE (°C) 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 –2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Norwegian Fjord Nordic Sea North Atlantic Bermuda NE Atlantic upwelling Equatorial Atlantic (5N-5S) South Atlantic NE Atlantic-low salinity Mediterranean Caribbean W. Argentine Basin (anomalous) data excluded from regression Bering Sea NE Pacific/California margin Peru upwelling Equatorial Pacific Hawaii Western Pacific Western Pacific (G. oceanica bloom) Indian Ocean/Arabian Sea S. Ocean (N of front) S. Ocean (S of front) S. Ocean (Fe enriched patch) data excluded from regression Atlantic Pacific Arabian Sea/S. Indian Ocean Southern Ocean (N of front) Southern Ocean (S of front) data excluded from regression WATER TEMPERATURE (°C) 0.0 –2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 WATER TEMPERATURE (°C) Emiliania huxleyi Figure 3.17 Biomarker alkenone. U K' 37 versus measured water temperature for ocean surface mixed layer (0–30 m) samples. A) Atlantic region. Empirical third-order polynomial regression for samples collected in >4°C waters is U K' 37 = –1.004 × 10 –4T 3 + 5.744 × 10 –3T 2 – 6.207 × 10 –2T + 0.407 (r 2 = 0.98, n = 413). (Outlier data from the southwest Atlantic margin and northeast Atlantic upwelling regime is excluded.) B) Pacific, Indian, and Southern Ocean regions: the empirical linear regression of Pacific samples is U K' 37 = 0.0391T – 0.1364 (r 2 = 0.97, n = 131). Pacific regression does not include the Indian and Southern Ocean data. C) Global data: the empirical third-order polynomial regression, excluding anomalous southwest Atlantic margin data, is U K' 37 = –5.256 × 10 –5T 3 + 2.884 × 10 –3T 2 – 8.4933 × 10 –3T + 9.898 (r 2 = 0.97, n = 588). + = sample excluded from regressions (Conte et al, 2006). [Copyright 2006; reproduced by permission of American Geophysical Union.] 53
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Past Climate Variability and Change
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Past Climate Variability and Change
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AUTHOR TEAMS FOR THIS REPORT Execut
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ACKNOWLEDGMENTS Many individuals ma
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TABLE OF CONTENTS Executive Summary
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102 The U.S. Climate Science Progra
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The U.S. Climate Science Program Ch
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CHAPTER 6 ABSTRACT Past Climate Var
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second, and the Transpolar Drift, t
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EXTENT, IN MILLION SQUARE KILOMETER
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Until recently, and for logistical
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1990; Fyles et al., 1994), the nort
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FREQUENCY 50 45 40 35 30 25 20 15 1
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Seas around icelAnd provide a rare
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at least 14 Ma (Darby, 2008). Sever
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T. quinqueloba, IN SPECIMENS PER GR
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7 6 5 4 3 2 1 Past Climate Variabil
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SEA-ICE COVERAGE, IN NUMBER OF MONT
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QUARTZ WEIGHT, IN PERCENT 6 5 4 3 2
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6.5 SUMMARY Geological data indicat
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GLOSSARY GLOSSARY 8 ka cold event A
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CAPE Project Circum-Arctic PaleoEnv
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Eccentricity Out of roundness (elli
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Innuitian sector The ice sheet that
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Moraine Landforms (typically ridges
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Positive feedback In climate studie
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Trough-mouth fans Undersea deposits
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The U.S. Climate Change Science Pro
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