1 Introduction
For the last 11 700 years, human civilisation has developed under stable and warm climatic conditions in the interglacial period called the Holocene. During the Pleistocene (2 588 000 years before present up to theHolocene), there were many glacial periods, also known as ice ages, followed by shorter interglacials. There is little evidence that variation of solar irradiation output has played an important role in trigging the shifts between glaciations and interglacials, but changes in ir-radiation impinging on the Earth due to changes in the Earth’s orbit around the Sun definitely have (see Box 2.1). We do not know much about solar variability beyond the Holocene, with one important exception; the Sun has increased its irradiance by about 25% since the Earth was formed 4.5 billion years ago. This is calledthe faint young Sun paradox, since the young Sun with today’s atmospheric composition would leave the Earth frozen and unable to sustain life. The solution to the paradox obviously involves an evolution of theatmosphere, from one domi-nated by greenhouse gases to one rich in oxygen and only traces of carbon dioxide and methane. This transition was driven by the sudden evolution of microbes that obtain their energy from photosynthesis. These bacteria transform CO2and water into sugars and oxygen, and hence created anatmosphererich in oxygen with low concentrations of greenhouse gases.
It is believed that on time scales of billions of years, the combination of an increasingly intensive Sun, drifts and collisions of continents, and evolution of the biosphere have contributed to the variations of the climate. It has been shown by analysis of a variety of so-calledproxydata(to be defined below) that there is climatevariability on time scales from years up to hundreds of million years. There are different drivers of climate changeoperating on different time scales, but the climatestate is not just a simple function of the drivers, but rather the result of a
1Department of Mathematics and Statistics, UiT - The Arctic University of Norway, N-9037 Tromsø, Norway
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EDP Sciences 2015 DOI: 10.1051/978-2-7598-1733-7.c116
complex interplay between external forcing and internal processes in theclimate system. There is, for instance, no simple linear relation between slowly increasing solar irradiance and the global temperature over the lifetime of the Earth.
To learn more about this complex interplay, we need reliable quantitative proxy-based estimates of climates of the past. This chapter deals with the most used proxies involved in such studies, and the methods employed to extract climate-related information from them. Since this book is about the impact of solar activity, we will focus on reconstruction of global-scale surface temperature of theHolocene, and in particular the last two millennia. Beyond this time span, we do not at present have sufficiently accurate reconstructions of temperature and solar forcing to make meaningful inferences about their connection.
2 An overview of proxies
In the study of past climates, proxies are preserved physical characteristics of the past that stand in for direct measurements to the climatic conditions. Examples of proxies include ice cores, tree rings, sub-fossil pollen, boreholes, corals, lake and ocean sediments, and cave stalagmites. The character of deposition of theproxy material has been influenced by the climatic conditions of the time in which they were laid down or grew. Chemical traces produced by climatic changes, such as quantities of particular isotopes, can be recovered from proxies. Some proxies, such as gas bubbles trapped in ice, enable traces of the ancientatmosphereto be recovered and measured directly to provide a history of fluctuations in the com-position of the Earth’s atmosphere. Systematic cross-verification betweenproxy indicators is necessary for accuracy in readings and record-keeping. In general, proxies must be calibrated against modern instrumental records to yield a quan-titative reconstruction of pastclimate.
2.1 Ice cores
Ice cores are recovered by drilling through the Greenland and Antarctic ice sheets, glaciers in North American regions, islands of the North Atlantic and Arctic Oceans, and alpine, tropical and sub-tropical locations. Measuring oxygen iso-tope composition in water molecules allows estimation of past temperatures and snow accumulations. The heavier isotope (18O) condenses more readily as temper-ature decreases and falls as precipitation, while the lighter isotope (16O) can fall in even colder conditions. In addition to oxygen isotopes, water contains hydrogen isotopes,1H and2H, which are also used as temperature proxies. The best dated series are based on sub-annual sampling of ice cores and the counting of seasonal ice layers. Such series may have absolute dating errors as small as a few years in a millennium. Dating may be performed using for instance volcanic ash layers with assumed dates.
K. Rypdal and T. Nilsen: Observations on paleoclimatic time scales 131
2.2 Sediment cores
Marine sediment cores are widely used for reconstructing past climate. One of the common approaches is to extract and study the marine microfossils that are preserved in the sediments. Carbonate deposits from foraminifera and coccol-ithopores are examples of abundant microfossils that are good indicators of past environmetal conditions found in deep-sea sediments. Diatoms are also of great im-portance for reconstructing pastclimate, they are unicellular, photosynthetic algae with a siliceous shell. The general assumption is that the down-core composition of diatomic microfossil assemblages is related to past environmental conditions at the core site. A number of statistical techniques are elaborated to convert assemblages to past estimates of hydrographic conditions, including sea-surface temperature at the study site. In lake sediment cores, remains of microorganisms, such as diatoms, foraminifera, microbiota, and pollen within sediment can indicate changes in past climate, since each species has a limited range of habitable conditions.
2.3 Tree rings
Dendroclimatology is the science of determining pastclimates from properties of the annual tree rings. Rings are wider when conditions favor growth, narrower when times are difficult. Other properties of the annual rings, such as maximum latewood density have been shown to be better proxies than simple ring width.
Using tree rings, local climates can be reconstructed for hundreds to thousands of years. By combining multiple tree-ring studies, sometimes with other climate proxyrecords, one can make inferences about past regional and globalclimates.
2.4 Corals
Palaoclimate reconstructions from corals provide insights into the past variability of the tropical and sub-tropical oceans andatmosphere, prior to the instrumental period, at annual or seasonal resolutions, making them a key addition to terrestrial information. The corals used forpaleoclimatereconstruction grow throughout the tropics in relatively shallow waters, often living for several centuries. Accurate annual age estimates are possible for most sites using a combination of annual variations in skeletal density and geochemical parameters. Paleoclimate recon-structions from corals generally rely on geochemical characteristics of the coral skeleton, such as temporal variations in trace elements or stable isotopes.
2.5 Speleothems
Speleothems are mineral deposits formed from groundwater within underground caverns. Stalagmites, stalactites, and other forms may be annually banded or contain compounds that can be radiometrically dated. Thickness of depositional layers or isotopic records can be used to determine pastclimateconditions.
2.6 Borehole measurements
Borehole data are direct measurements of temperature from boreholes drilled into the Earth’s crust. Departures from the expected increase in temperature with depth can be interpreted in terms of changes in temperature at the surface in the past, which have slowly diffused downward, warming or cooling layers below the surface. Reconstructions show substantial sensitivity to assumptions that are needed to convert the temperature profiles to ground surface temperature changes, hence borehole data are most useful forclimate reconstructions over the last five centuries.
2.7 Uncertainties of proxy-basedpaleoclimate reconstructions
There are multiple sources to uncertainties when proxy data are being used to reconstruct past climate conditions. During field work, the sampling procedure itself may disturb the record of interest. Marine sediment cores may for instance be compressed by the coring equipment during sampling, and the stratigraphy could be slightly disturbed. Furthermore, when the desirableproxydata material has been extracted and processed, the assumptions that convert the raw proxy data to the final climatic variable or condition are of great importance. Transfer functionsare used to convert the climate-related variable to the desired quantity, and these functions describe the assumed relationship between the two quanti-ties. The relationship can be tested against present-day conditions, and often it is found that additional factors must be taken into consideration. For example, let us look at a proxy for paleoglaciation; the oxygen isotope ratios in marine carbonate deposits. The carbonate deposits are extracted from marine or lake sediment cores, and are microfossils of foraminifera which generally produce their carbonate shell from the surrounding ocean water. It is assumed that the oxygen isotope ratios in the carbonate reflect the oxygen isotope ratio in the ocean at the time the shell was formed. The oxygen isotope ratio in the ocean is dependent on temperature, salinity and effects related to uppwelling. The effect of the different components is difficult to isolate, and hence today such records are considered to reflect global paleoglaciation and not ocean temperature isolated. Meanwhile, studies have shown that certain types of foraminifera produce a shell which is not equivalent to the isotopic composition in the ocean, and that different species living in the same environment record different oxygen isotope values. Such differ-ences between species are called vital effects, and these effects are corrected before reconstructions are created. Yet another source of uncertainty is imperfections of the age model. Proxydata which are annually layered is not a problem, but e.g., marine sediments are virtually impossibly to date with high accuracy. A linear sedimentation rate is generally assumed, but this is in lack of better knowledge about the sedimentation rate in the area. Particular features in the sediments may help in the dating process, such as volcanic ash layers and dust. Each volcanic eruption produces ash and larger particles with a specific chemical “fingerprint”, so if the timing of the eruption is known, then the sediments where the ash is found can be dated accurately.
K. Rypdal and T. Nilsen: Observations on paleoclimatic time scales 133
2.8 Simulating proxies in climate models
State-of-the-artclimate modelsare not only used to predict futureclimate changes, but also to simulateclimatein the past and present. Modelling the presentclimate is important for validation of theclimate models, by comparison of model output with observations. The available proxy data material inpaleoclimatestudies in-dicate thatclimatehas varied considerably also earlier in Earth’s history, but the nature and mechanisms of such changes are in many cases poorly understood. Pa-leoclimate model simulations are therefore used to study pastclimate dynamics, but the validation of such simulations is difficult because direct measurements of the true climatic variables do not exist further back than a few centuries. We only have proxy-based reconstructions to rely on when studying longer time peri-ods, where climatic variables, such as temperature are estimated fromproxydata using transfer functions. As mentioned above, the transfer functions are based on assumptions and involve uncertainties. An alternative method for validating the paleoclimate simulations is called the “forward proxy modelling technique”.
This method involves simulating the actual proxy data in the model. The mod-elledproxy can be compared with true proxy data, and hence the problem with transfer functions is eliminated. A number of climate modelscurrently have sta-ble water isotope diagnostics implemented, which are useful both for validating experiments but also for testing the spatial relationship between changes in the heavy oxygen istotope (δ18O) and temperature. A model study by Sturm et al.
(2010) shows that the altitude effect makes δ18O decrease more with height than the temperature, and the same is true when moving from coastal to continental sites during winter (the continental effect).
3 Solar activity reconstructions from cosmogenic isotopes
Chapters2.1and2.2 in this book describe reconstructions ofsolar activity based onsunspotobservations combined with models that relate solar irradiance to such observations. Systematicsunspotobservations, however, have been recorded only after Galileo made his first telescopic observations in AD 1610. Reconstructions for the more distant past has been made feasible by the observation that the sunspot number (SSN) is strongly correlated with the concentration of certain cosmogenic isotopes in tree rings and ice cores. We consider two solar activity reconstructions, Solanki et al.(2004), which is based on14C in mid-latitude tree rings, andSteinhilber et al.(2009), which is based on10Be, measured in polar ice cores. Both proxies measure intergalactic cosmic ray flux, which is correlated with solar activity. The reason for this correlation is that the solar wind is stronger during high solar activity, and this increases the strength of the interplanetary magnetic field. This field deflects galactic cosmic rays (GCR) and reduces the GCR-flux impinging on the Earth’satmosphereand thus reduces the production of the radio-isotopes14C and 10Be. Solanki et al. (2004) reconstruct thesunspot number, while Steinhilber et al. (2009) reconstruct total solar irradiance (TSI), and are based on physical modelling of the whole chain of processes from activity
on the Sun to the accumulation of the isotopes in the tree rings and ice. This modelling is quite different for the two proxies. For instance, 14C production on mid-latitudes is strongly influenced by the almost horizontal Earth magnetic field, which has been increasing in strength throughout theHolocene. This influence can be corrected for, but more difficult is the complex biological interactions of Carbon, which make it problematic to relate the concentration in tree rings directly to the concentration in theatmosphereat a given time. 10Be deposited in polar ice cores, on the other hand, is less influenced by the almost vertical magnetic field at high latitudes and is directly washed out of the atmosphereand deposited as snow at the actual site.
The two reconstructions span most of the Holocene and are shown in Figure 1a. They are quite similar on the time scales of the millennial oscilla-tions, and many (but not all) of the century scale fluctuations are present in both curves, although sometimes with a phase shift of up to a century in one direction or the other. Power spectral analysis of time series like these has been used to detect cycles in thesolar activitybeyond the 11-yrsolar cycle(theSchwabe cycle).
Examples are a 70–90 year periodicity called the Gleissberg cycle and the 210-year de Vries cycle. The cycles are very weak, however, and very arcane spectral meth-ods are needed to detect the spectral peaks. The reality of many of these cycles are still subject to some controversy.
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Power spectra. Blue: SSN from14C. Red: TSI from10Be
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Fig. 1. (a) Blue curve: The reconstructed sunspot number from the isotope 14C as presented in Solanki et al. (2004). Red curve: The reconstructed solar irradiance from the isotope10Be as presented in Steinhilber et al. (2009). (b) The power spectral densities of the time series in (a). The slopes of the fitted straight lines are = 0.8.
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Fig. 2.(a) A temperature proxy from the GRIP ice core showing variations in Greenland temperatures during the last ice age and the Holocene. (b) Blue curve: the Moberg et al.
(2005) NH temperature reconstruction. Red curve: the NH temperature derived from the ECHO-G Erik1 simulation driven by solar and volcanic forcing. Black-dotted curve: the instrumental global temperature record. The temperatures are represented as anomalies relative to the mean of the Moberg curve over the period AD 0 – 500. All records have been smoothed by a 30-year low-pass filter.
Fig. 1. (a) Blue curve: The reconstructed sunspot number from the isotope 14C as presented inSolanki et al.(2004). Red curve: The reconstructed solar irradiance from the isotope10Be as presented inSteinhilber et al.(2009). (b) The power spectral densities of the time series in (a). The slopes of the fitted straight lines areβ= 0.8.
The power spectra contain interesting information beyond the cycles, as shown in Figure1a. Here, we have plotted on logarithmic axes a very simple estimate of the power spectral density called the periodogram for the two reconstructions. The rapid loss of power for frequenciesf >1/50 yr−1(periods shorter than 50 yr) just reflects that the reconstructions (which are given with 10-year resolution) really are smooth on time scales shorter than 50 yr. Forf <1/50 yr−1, both spectral
K. Rypdal and T. Nilsen: Observations on paleoclimatic time scales 135
plots can be fitted by a straight line with negative slope of β ≈0.8. Since both axes are logarithmic, this means that the power spectra on time scales slower than 50-years has the power-law formS(f)∼f−β. Time series with such spectra and β >0 are said to be long-range dependent since they exhibit stronger variability on the long time scales as compared to random noise.
Interestingly, the Northern hemisphere temperature reconstructions discussed in the next section also exhibit power spectra of this type withβ ≈0.8.This should perhaps indicate that the long-range dependence seen in the temperature reflects the dependence of the solar driver. However, paleoclimatic model simulations exhibit the same long-range dependence even in model runs without a solar driver, as shown byØstvand et al.(2014), suggesting that the long-range dependence in solar activityand globalclimateare properties of the internal dynamics in the Sun and the Earth’sclimate system, respectively.
4 Hemispheric and global reconstructions
Raw proxydata must be transferred into climatological quantities like tempera-ture, precipitation, ice cover, sea level and so on. Some of the methods are specific for eachproxy, but also rely heavily on general statistical methods like regression analysis (see Chapter 3.9). If we want to understand the climate impact of ex-ternal forcings like solar irradiance and volcanic aerosols, we cannot be satisfied with local reconstructions of the climateat the proxysites. It is necessary to re-construct a large-scaleclimatefield by employing multivariate regression methods, so-calledclimate field reconstructions. Such methods have been applied both to filling spatial gaps in early instrumental climate datasets and to the problem of reconstructing pastclimatepatterns. Independently, multiple temperature recon-structions for the past millenium have been produced, and they show the same evolution of the global or hemispheric mean surface temperature, namely a weakly cooling trend up to AD 1850, and an abrupt increase in temperature over the last century. The techniques for such reconstructions are diverse and rather arcane and disputes about their validity gave rise to the highly politicised “hockey-stick”
controversy.
4.1 Temperature reconstructions
In Figure 2a, we show a graph of theδ18Oproxyfor the Greenland temperature as recovered from the GRIP ice core. Prior to 11.7 kyr before present (BP), this graph shows a cold, but very unstable,climateridden by sudden warming events
In Figure 2a, we show a graph of theδ18Oproxyfor the Greenland temperature as recovered from the GRIP ice core. Prior to 11.7 kyr before present (BP), this graph shows a cold, but very unstable,climateridden by sudden warming events