Contents Introduction Timescales of Climate Change Modern Analog Approaches in Paleoclimatology Paleoclimate History of the Arctic The Younger Dryas Climate Event
Introduction C J Mock, University of South Carolina, Columbia, SC, USA ã 2013 Elsevier B.V. All rights reserved. This article is reproduced from the previous edition, volume 3, pp. 1867–1873, ã 2007, Elsevier B.V.
Introduction, Why Study Paleoclimatology? The Earth’s climate constantly changes, exhibiting variations both temporally and spatially. In a shorter timeframe of every other year or so, climatic changes such as those resulting from El Nin˜o events, prominently affect regions throughout the globe. In much longer timeframes, such as tens of thousands of years ago, dramatic climatic changes have occurred, associated with environmental changes such as the equatorward expansion of large ice sheets and characteristics of vegetation assemblages much different than those seen today. A thorough understanding of the causes of climatic variations is important for society because of the effects of climate on human activities such as agriculture, water resources, energy, biological productivity, and environmental quality. These variations include not only present-day natural variability, such as periodically recurring droughts and floods, but also include future climatic changes. In particular, during the last few decades, scholars have shown increasing concern about human-induced climatic changes such as a doubling of carbon dioxide concentration, which may cause global warming (IPCC, 2001). Some future global warming scenarios from computer models predict potentially widespread catastrophic consequences for society, such as widespread drought at mid-latitudes and unprecedented rapid warming in the Arctic. Paleoclimatology is defined as the study of climates during any part of the geological past (Bradley, 1999), and specifically deals with climates prior to the period of modern instrumental records, using proxy data (natural phenomena that are climatedependent) to reconstruct past climates, and using computer models (hereafter referred to as general circulation models (GCMs)) to explain the causes of past climatic change (Kohfeld and Harrison, 2000; Figure 1). The Quaternary period, defined as encompassing the last 2.6 My, is unique in the field of paleoclimatology. This is due to the availability of copious
amounts of data by which to thoroughly understand the climate system at critical times of the past. The study of past climates can greatly help our understanding of climatic change by: 1. Providing a longer-term perspective than the modern instrumental record on understanding the controls, magnitudes, and spatial as well as temporal aspects of climatic change. For example, failure of the Asian monsoon may have occurred more frequently in the past, ranging from several centuries to many thousands of years ago, and the examination of many such cases may provide clues on how particular controls (e.g., El Nin˜o events, mountain uplift) govern monsoonal activity (An et al., 2001; Morrill et al., 2003). Paleoclimatology also provides a longer record of greenhouse gas concentrations and other phenomena linked to climatic forcing mechanisms, and assessment of these longer records, such as carbon dioxide concentrations, may provide different interpretations on the timing of global warming (Ruddiman, 2005). 2. Testing the accuracy of GCMs. Some paleoclimates have boundary conditions and forcing mechanisms that were much different than today and what is expected for the future (Figure 2), especially at longer time scales, such as the peak of the last glaciation around 21 000 years ago (Webb, 1998) and just before the onset of the Quaternary when tectonic uplift played a prominent role in climatic change (Berger, 1992; Ruddiman et al., 1997). However, the variability of forcing mechanisms also exhibits different characteristics within shorter time scales, such as pre-industrial carbon dioxide concentrations in the last 500 years (Robertson et al., 2001). Since the forecasting of future climate relies on the use of GCMs, if model simulations of paleoclimate correspond with those reconstructed from fossil data, we could place more confidence in using these GCMs for simulating and understanding future climatic changes, such as global warming.
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3. Providing a longer climate record of natural variability. We need a clear understanding of natural climatic variability, in order to delineate natural from anthropological variability. As a result of increased anthropogenic effects on climate, such as increasing population and urbanization, it is difficult to disentangle these two factors. The general rise in global mean temperature since the mid-1800s provides a clear example (Mann et al., 1998), but other prominent warm periods in the past provide valuable information on how the climate systems operate to further assess future climates (Webb et al., 1993). Scholars know that increased urban heat island effects and carbon dioxide concentrations may play important roles, but could the temperature rise also be a natural response from a colder period known as the Little Ice Age in the seventeenth to nineteenth centuries when carbon dioxide concentrations were lower than today?
The first three reasons for studying paleoclimate help to understand the controls of climatic change and how the climate system operates. However, paleoclimatology is multidisciplinary, benefiting from several fields to understand and reconstruct climates of the past, thus offering important information for paleoecologists. This leads to a fourth important reason for studying paleoclimatology. 4. To provide detailed paleoclimatic records to understand the role of climatic change on ecosystems and society. This importance is best illustrated through some examples. Paleoecologists interested in vegetation histories of a species need to incorporate the role of climatic change over time scales of thousands to millions of years (Overpeck et al., 2003). Archaeologists studying the changing lifestyles of past societies need detailed paleoclimatic records to assess the role of climatic changes (Weiss and Bradley, 2001). The latter example also proves useful for scholars studying climate impact assessment and reconstructing natural hazards, such as the effects of widespread severe drought (Figure 3; The North American Drought Atlas, 2004). Some paleoclimatic proxies possess subseasonal resolution that can sometimes detect specific meteorological events, such as hurricanes and severe flooding, that affected society (Figure 4; Mock et al., 2006). Although most societies functioned differently in the past than they do today, we can learn much from climate impact studies of the past and apply them to understand potential future impacts (Jones et al., 2001).
Basic fundamental approaches in paleoclimatic research (1) Modeling approach Boundary conditions
Numerical models (GCMs)
(2) Paleoclimatic reconstruction approach Proxy data
Some Recent Developments in Paleoclimatology
Insolation (cal cm–2 day–1)
Figure 1 The two basic fundamental approaches in paleoclimate research: (1) the modelling approach and (2) the paleoclimate reconstruction (‘data’) approach. A common theme that has emerged in paleoclimatology in the last three decades is the synthesis and analysis of ‘data/model’ comparisons.
Prior to 1970, much paleoclimatological research focused primarily on climatic reconstructions that described what happened, with studies involving a variety of different proxy data
June mid-month insolation at 60°N
525 500 475 450 1 000 000
Years BP 380 360 340 320 300 280 260 1500
Carbon dioxide concentrations
Year AD Figure 2 Some examples of boundary conditions of climate over time. Top: June mid-month insolation at 60 N in the last million years; note the cyclical behavior of insolation that represents variations in the Milankovitch orbital parameters. Reproduced from Berger A (1992) Orbital Variations and Insolation Database. IGBP PAGES/World Data Center-A for Paleoclimatology Data Contribution Series # 92-007. NOAA/NGDC Paleoclimatology Program, Boulder, CO. Bottom: Carbon dioxide concentrations since AD 1500. Reproduced from Robertson AD, Overpeck JT, Rind D, et al. (2001) Hypothesized climate forcing time series for the last 500 years. Journal of Geophysical Research: Atmospheres 106: 14783–14803. Paleoclimatic reconstruction data from the NOAA Paleoclimatology website at http://www.ncdc.noaa.gov/paleo/paleo.html.
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20 °N 140 °W
20 °N 120 °W
–6 –5 –4 –3 –2 –1 0 1 2 3 4 5 6
–6 –5 –4 –3 –2 –1 0 1 2 3 4 5 6
10.5 9.0 7.5 6.0 4.5 3.0 1.5 0.0 2000
NC tropical cyclones
Number of storms (annually)
4 3 3 2 2 1 1 0 1820
Number of storms (5-year running mean)
Figure 3 Geographical extent of Palmer Drought Severity Indices (PDSI) for two extreme drought years for the southern Great Plains, Mexico, and the Southeastern USA: 1752 and 1860. Negative indices represent the magnitude of severe drought. The drought maps were created from a network of 835 tree-ring sites. Reproduced from Cook ER and Krusic PJ (2004) North American Summer PDSI Reconstructions. IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2004-045. NOAA/NGDC Paleoclimatology Program, Boulder, CO.
Year Figure 4 Annual time series of the number of tropical cyclones affecting the coast of North Carolina, USA. General trends are indicated by a 5-year running mean. Tropical cyclone data were taken from the HURDAT database and archival collections owned and compiled by Mock and colleagues at South Carolina.
types (Wendland, 1991). Radiometric dating techniques, such as radiocarbon and potassium-argon dating, provided a quantitative means to date past climatic change. Paleoclimatic research was propelled by the establishment of numerous research centers that specialized in particular proxy data and dating methods. For example, dendroclimatology, the study of tree-rings, accelerated after the establishment of the Laboratory of Tree Ring Research at the University of Arizona, USA in 1937. Similar dendroclimatic laboratories were established later at Columbia University in New York, the University of Arkansas, the Climatic Research Unit, University of East Anglia, United Kingdom, and the Swiss Federal Institute for Forest, Snow, and Landscape Research, Switzerland, among many. Research centers focusing on other proxies such as palynology also emerged, including the University of Minnesota in the United States, University of Cambridge in England, Lund University in Sweden, the University of Bern in Switzerland, and the Russian Academy of Sciences, Institute of Geography in Moscow. Similarly, prominent research centers in Quaternary paleoceanography emerged as well, with some notable centers being based at Cambridge University, Brown University, and Columbia University. As time progressed, improvements and new techniques in data analysis were developed at
prominent research centers such as the Quaternary Research Center in the United States, and the Xian Laboratory of Loess and Quaternary Geology at the Chinese Academy of Sciences. Newly trained academics that graduated from these research centers started research centers of their own, building up paleoclimatic databases. Beginning in the early 1970s, the development of highspeed computers fostered a new type of paleoclimatology that specializes in analyzing large paleoclimatic datasets (Wright and Bartlein, 1993). Some interpretive tools in paleoclimatic analyses are qualitative in nature, which continue to this day and can involve analyses from local to hemispheric scales (Figure 1). Earlier quantitative studies applied basic transfer functions to convert proxy variables into climate variables, which also involved the calibration of modern climatic data with modern environmental data. The modern relationships were applied to fossil environmental data to quantitatively reconstruct past climate (Webb and Bryson, 1972). As the datasets grew, so did the sophistication of quantitative interpretive tools for analyzing large-scale paleoclimatic datasets (Mann et al., 1998; Prentice et al., 1991). For example, the recently compiled North American Drought Atlas, which provides geographical maps of drought severity by year, is based
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on a geographical network of 835 tree-ring sites (Figure 3; Cook and Krusic, 2004). Many paleoclimatic data networks are now available through the World Data Center-A for Paleoclimatology (WDC-A) at Boulder, CO (Webb et al., 1994), and other mirror sites around the world at Johannesburg in South Africa, Lanzhou in China, Mendoza in Argentina, Nairobi in Kenya, and Pune in India (Eakin et al., 2003). These data networks range from the regional to global scale, with examples being the International Tree Ring Database (GrissinoMayer and Fritts, 1997) and the Global Pollen Database. The computer revolution also created a paleoclimatic perspective for dealing with GCMs. These models are similar to those used in daily weather forecasting but instead the principles are applied to simulate large-scale climate patterns of the past. Earlier attempts focused mostly on the atmosphere, but paleoclimatic modeling has evolved to link atmospheric models with detailed feedbacks as they relate to processes in the biosphere, lithosphere, and hydrosphere (Kohfeld and Harrison, 2000; Kutzbach et al., 1998). Considerable attention has been paid to ocean-atmospheric feedbacks. GCMs have been used to simulate paleoclimates ranging from a few hundred to millions of years ago (Kutzbach, 1992), as well as selected timeframes and phenomena of interest in the past (LeGrande et al., 2006; Seager et al., 2005). As opposed to paleoclimatic proxy data, which independently reconstruct ‘what happened’ (Figure 1), GCMs explain ‘why things happened’ and thus are an extremely useful tool for paleoclimatologists to test hypotheses concerning the causes of climatic change by comparing simulation results with those derived from proxy data (Harrison and Prentice, 2003; Mahowald et al., 1999). Within the last two decades, many different paleoclimatic modeling groups have emerged and remain active; some of these include modeling activities at the National Center for Atmospheric Research in Boulder, CO, the Hadley Centre in the United Kingdom, the Canadian Centre for Climate Modeling and Analysis, the Max-Planck Institute for Meteorology at Bremen University, the Laboratoire de Me´te´orologie Dynamique in France, and the Goddard Institute of Space Studies in Maryland, USA. Increased resolution in dating techniques and the growing body of paleoclimatic evidence, particularly from ice cores and marine sediments from the North Atlantic, indicate that abrupt decadal-centennial scale changes in climate occurred in the distant past, that are much different in magnitude and character than those observed in the modern instrumental record (Clark et al., 1999; Labeyrie et al., 2003; Overpeck, 1996). These changes are significant for society, for we now know that such abrupt climatic changes may occur within a single human lifetime. Paleoclimatic records thus offer the only means to test whether our predictive models can simulate such future changes. Modeling attempts have been made to simulate the causes and nature of these abrupt changes. These model runs are enabling scientists to conduct detailed data-model comparisons at the hemispheric and global scales (Clark et al., 2002). However, to date, most modeling studies on these events are still focusing on providing sensitivity tests to assess potential forcing mechanisms. We are only beginning to document and understand the controls and causes of these abrupt changes, and such questions will continue to be important for the paleoclimatology community for years to come.
Organization of the Articles Numerous articles in this encyclopedia describe how paleoclimatology can contribute toward a further understanding of the climate system of the past. These articles represent the most up-to-date information from the paleoclimate research community. Bartlein provides an overview of the concepts on how climate varies at different time scales, ranging from interannual to pre-Quaternary, and how we can interpret some reconstructions from proxy data in relation to climate model simulations. Shuman further discusses the details of how Quaternary scientists use different data, methods, and tools for reconstructing past climates, including data/model comparisons as well as various geographical, quantitative, and qualitative approaches. Harrison describes the current status of data/ model comparisons in paleoclimatology. Several articles provide more details on important forcing mechanisms that affect feedbacks in the climate system, and these are important parts of climate model simulations. The importance of the thermohaline circulation on past climates is well-known, and Rahmstorf describes how changes of various fluxes in the oceanic environment may relate to glacial fluctuations and other rapid climatic changes. Brozkin illustrates that although climate is a prominent control on geographical aspects of the terrestrial biosphere, various other factors in the terrestrial biosphere may also alter feedbacks that affect the climate system. Tegen describes the importance of atmospheric dust on climate at different time scales, including attempts to quantify its magnitude. Shindell illustrates how solar and volcanic forcing are related to climatic variability at different time scales, also approaching this from a modeling perspective. Another group of articles describe specifics on the nature of climate variability at different time scales from throughout the Quaternary and back into the Pliocene. Poore provides an important review of pre-Quaternary climate and forcing mechanisms that helps assess the onset of paleoclimatic variations in relation to multiple glacial and interglacial cycles in the Quaternary. Owen also contributes valuable information on pre-Quaternary paleoclimate, focusing attention on tectonics and continental configurations, but also addressing several different aspects of tectonics. Berger describes an overview of the astronomical theory of Quaternary paleoclimate, discussing the prominent orbital cycles as well as the role of carbon dioxide in climate change. The late Pleistocene/Holocene timeframe of approximately the last 130 000 years has been the focus of many studies; some continuous, high-resolution proxies (e.g., ice cores) and climate modeling researchers have expressed a high degree of confidence in the prominent climate forcing mechanisms. Montoya illustrates the details of modeling simulations of the paleoclimate of the Last Interglacial (around 125 000 years ago), which is a time when orbital factors were conducive to widespread warmth in many parts of the world. Broccoli discusses the nature of research on model simulations of the Late Glacial Maximum (LGM) of 21 000 years ago, and demonstrates the importance of nonorbital factors such as ice-sheet size, dust, and greenhouse gases. Labeyrie illustrates that there are also more rapid, millennial-scale changes that occur within the orbital-induced changes and prominent glacial–interglacial
PALEOCLIMATE | Introduction
cycles. These events, commonly referred to as Dansgaard/ Oeschger and Heinrich events, are prominent in many highresolution paleoclimatic records but more work is needed on modeling efforts. Barber describes a regional example, illustrating how peatland records in northwest Europe can aid in multiproxy efforts of reconstructing past regional climate patterns through the Holocene. Another group of articles describes the nature of paleoclimatic records at time scales within the last 2000 years, as well as addressing their importance to contemporary climatic issues and societal impacts. Smith provides an overview of dendroclimatology, which is a prominent paleoclimate proxy with annual temporal resolution for many terrestrial regions. Chenoweth provides an overview of research on historical climate reconstruction from archival materials, some of which include data resolved at the daily level. These materials are mostly limited to the last several centuries, depending on the geographical area of interest. Mann elegantly describes how different high-resolution proxies, including tree-rings and historical evidence, can be combined to quantitatively reconstruct temporal and spatial patterns of high-resolution climate over the last millennium. These reconstructions capture many important, dominant climatic modes that are seen in the modern instrumental record, but they also reveal changes in the importance of these modes over time. Liu provides an overview on paleotempestology, the reconstruction of past hurricanes and typhoons that encompass time scales from the last few hundred years to most of the Holocene, based on several different proxies. He also provides discussion of some of the forcing mechanisms that govern past hurricane activity. C Mock provides two articles on paleo-ENSO (El Nin˜o-Southern Oscillation, Paleo-ENSO) and paleodrought, respectively. As with paleotempestology, both of these phenomena are climatic extremes of high interest to society that can be reconstructed from paleoclimatic proxies, also extending through the Holocene. Last, Schneider and Mastrandrea illustrate how longer records from paleoclimatology aid society in further understanding anthropogenic global climate change, particularly global warming, that may occur in the future.
See also: Dendroclimatology; Paleoclimate Relevance to Global Warming. Glacial Climates: Biosphere Feedbacks; Effects of Atmospheric Dust; Thermohaline Circulation; Volcanic and Solar Forcing. Glaciation, Causes: Astronomical Theory of Paleoclimates; Tectonic Uplift and Continental Configurations. Paleoclimate: Timescales of Climate Change. Paleoclimate Modeling: Data– Model Comparisons; Last Glacial Maximum GCMs; Paleo-ENSO; The Last Interglacial. Paleoclimate Reconstruction: Approaches; Historical Climatology; Paleodroughts and Society; Paleotempestology; Pliocene Environments; Sub-Milankovitch (DO/Heinrich) Events; The Last Millennium. Plant Macrofossil Methods and Studies: Mire and Peat Macros.
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