Upper mantle dynamics and quaternary climate in cratonic areas (DynaQlim)—Understanding the glacial isostatic adjustment

Upper mantle dynamics and quaternary climate in cratonic areas (DynaQlim)—Understanding the glacial isostatic adjustment

Journal of Geodynamics 50 (2010) 2–7 Contents lists available at ScienceDirect Journal of Geodynamics journal homepage: http://www.elsevier.com/loca...

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Journal of Geodynamics 50 (2010) 2–7

Contents lists available at ScienceDirect

Journal of Geodynamics journal homepage: http://www.elsevier.com/locate/jog

Upper mantle dynamics and quaternary climate in cratonic areas (DynaQlim)—Understanding the glacial isostatic adjustment Markku Poutanen a,∗ , Erik R. Ivins b a b

Finnish Geodetic Institute, Geodeetinrinne 2, 02430 Masala, Finland Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109-8099, USA

a r t i c l e

i n f o

Article history: Received 12 January 2010 Received in revised form 18 January 2010 Accepted 20 January 2010

Keywords: GIA Crustal dynamics Climate Glaciation Data combination

a b s t r a c t A substantial material flow, deep within the solid Earth, is caused by the periodic ocean-continent water transport of the Quaternary ice ages. That lateral transport is enormous, causing 120–135 m of equivalent global sea-level rise and fall, or about 45–50 Peta tonnes (1 Peta tonne = 1018 kg) of surface mass transfer. The global manifestation of the slow mantle flow response to this surface load is glacial isostatic adjustment (GIA). Measurements of this phenomenon offer a unique opportunity to retrieve information pertaining to both the Earth’s upper mantle and the changing mass of glaciers and ice sheets during the past. The waxing and waning of ice mass is driven by long-term variations in climate. DynaQlim (upper mantle dynamics and quaternary climate in cratonic areas), a regional coordination committee of the International Lithosphere Program (ILP) since 2007, is focused on studying the relations between upper mantle dynamics, its composition and physical properties, temperature, rheology, and Quaternary climate. Combining historical and modern terrestrial and space-borne geodetic observations with seismological investigations, studies of the postglacial faults and continuum mechanical modelling of GIA, the research goal of DynaQlim is to offer new insights into properties of the lithosphere and upper mantle. The joint inversion of different types of observational data is an important step toward providing a better understanding of GIA on all levels of Earth sciences. A primary regional focus of DynaQlim is the study of cratonic areas of northern Canada and Scandinavia. Greenland and Antarctica are also of great interest, as they represent observational examples of ice sheet dynamics and mass change in response to relatively strong present-day climate forcing. © 2010 Elsevier Ltd. All rights reserved.

1. Introduction Measurement of glacial isostatic adjustment (GIA) offers a great opportunity in geosciences to retrieve unique information about Earth climate and interior. The surface expressions of GIA provide data that are critical to a host of studies on fundamental internal Earth dynamics and that have direct application to crustal, lithospheric and mantle Earth rheology (e.g., Lambeck and Johnston, 1998; Karato, 2003). GIA also is a primary cause of long-term Earth rotation variability (Sabadini and Vermeersen, 2004). Past ice sheet dynamics are only partially constrained by their connection to the deformation of the viscoelastic solid Earth. All of the overarching challenges for understanding the variability of the Quaternary land, ocean, atmosphere and climate are both data intensive and highly multidisciplinary. Attempting to incorporate many of the putative nonlinear feedback mechanisms into any robustly performing cou-

∗ Corresponding author. E-mail address: Markku.Poutanen@fgi.fi (M. Poutanen). 0264-3707/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.jog.2010.01.014

pled model of ocean heat/salinity transport, atmospheric dynamics, while correctly accounting for CO2 and other greenhouse gas constituents, is a major challenge to understanding the process of climate variability, ice sheets dynamics and solid Earth loading. During the period of geologic history known as the Pleistocene (0.01–2.6 Myr), quasi-periodic variations between glacial and interglacial intervals prevail, and these play key roles for both shaping the landscape and driving the geodynamic evolution of cratonic regions like Laurentia, Fennoscandia, Antarctica, Greenland and northernmost Eurasia. Laurentia and Fennoscandia have broadly similar glaciation histories during the Quaternary, though their tectonic histories are quite different. In Antarctica the nature of ice fluctuation appears to be distinctly different, as are the likely climate forces that cause waxing and waning of the vast ice masses (Raymo et al., 2006). Our understanding of the glacial history of northern Europe and Eurasia has advanced during last two decades, as access to new field data has produced substantial steps forward in our on-land, coastal and off-shore knowledge of glacial, glacial transition and interglacial phases (e.g., Siegert and Dowdeswell, 2002).

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The improvements allow our model-based inferences for the Last Weichselian and Holocene ice loading–unloading sequence to be better constrained over the last decade (Svendsen et al., 2004). In parallel, new developments in numerical modelling of glaciations have shed light on the processes involved, as well as the importance of their environmental couplings (Forsström, 2005; Zweck and Huybrechts, 2005; Näslund et al., 2005). Extensive and diverse sets of observations exist, including geodetic 3D crustal movement measurements, regional and local gravity data, geological observations of past sea-level changes, lateglacial faults, terminal moraines and other glacial deposits, deep borehole heat flow data, mantle tomographic imaging, as well as various palaeoclimatological proxies. However, there still exist open questions related to upper mantle dynamics and composition, rebound mechanisms and uplift models, including the role of tectonic forces. 2. Observational data There are systematic postglacial uplift observations over the last 100 years based on geodetic methods using repeated precise levelling, tide gauges, gravity change and monitoring postglacial fault activity. Maps of vertical motion have been based on time series encompassing several decades of observation. Horizontal motions could not be observed accurately over large areas without modern GNSS (global geodetic observing systems, including GPS) techniques. GNSS observations are accurate enough to allow the construction already of 3D motions in a few year time series (e.g., Bouin and Wöpplemann, 2010). As an example, the project BIFROST (baseline inferences for Fennoscandian rebound observations, sea level, and tectonics), initiated in 1993, is using tens of permanent GPS stations in Finland and Sweden to produce maps of the 3D crustal veloc-


Fig. 2. Vertical rates of Fennoscandian rebound as a function of distance to the uplift maximum. GPS data (diamonds) are based on latest BIFROST results of Lidberg et al. (this volume), tide gauge data (open circles) are from Ekman and Mäkinen (1996), and GIA model (crosses) is based on revised model constructed by Glenn Milne (Lidberg et al., this volume). All fitted trend lines show similar slope (solid line: GPS; double line: GIA model; dashed line: tide gauges). Difference between GPS and tide gauge uplift values amounts the eustatic rise of the Baltic Sea; GPS uplift values are relative to the mass center of the Earth. Most of the scatter in data are due to the fact that the uplift area is not circular, as assumed in this simple model.

ity field of improved spatial fidelity and accuracy (Milne et al., 2001; Johansson et al., 2002; Lidberg, 2007; Lidberg et al., 2010) (Figs. 1 and 2). A more recent European effort, launched in 2008, is the COST Action ES0701 “Improved Constraints on Models of Glacial Isostatic Adjustment” with the aim of providing improved constraints on GIA models and on contemporary ice mass balance estimates for Antarctica, Greenland and Earth’s smaller ice caps and ice fields (COST, 2010). With a strong alignment with the goals of DynaQlim,

Fig. 1. GIA in Fennoscandia. Left: The upside-down triangles on the map are permanent GNSS stations, triangles stations where absolute gravity is regularly measured, and dots with joining lines are the land uplift gravity lines, measured since the mid-1960s. Contour lines show the apparent land uplift relative to the Baltic mean sea level 1892–1991, based on Nordic uplift model NKG2005LU (Vestøl, 2006; Ågren and Svensson, 2007). Right: Diagram of the observed relative gravity change between Vaasa and Joensuu in Finland during 40 years of measurement on the land uplift gravity lines (Mäkinen et al., 2005).


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Fig. 3. GIA in the Northern Hemisphere as delivered by GRACE trend and shown here as water-equivalent height change. The GRACE signal is unfiltered by either hydrological modeling or destriping. The GRACE Level 2 product employed is from Release 4.1 of the Jet Propulsion Laboratory (JPL). The trend uses the months January 2003 to May 2009, excluding June 2003. The harmonics are truncated at degree and order 120 and employ an isotropic Gauss filter of 575-km radius. (Compare to Ivins and Wolf, 2008, figures 1a and 2a, therein, which uses a 3.4 yr shorter time series).

COST ES0701 is coordinating research done under the umbrella of DynaQlim. In North America several hundred continuous GPS stations have been used to compute contemporary velocities (e.g., Calais et al., 2006; Wolf et al., 2006; Sella et al., 2007). GNSS observations in Antarctica are sparse, but an ever-increasing number of permanent geodetic stations and repeated episodic campaigns will permit a more detailed analysis in the future. In Greenland repeated GPS campaigns have been carried out over a period of close to 10 years (e.g., Dietrich et al., 2005). It has recently been demonstrated that such bedrock-based data are useful for determining recent interannual mass changes in the interior of the Greenland ice sheet (Khan et al., 2007). Alternatively, should ice loss accelerate from the Little Ice Age, as is the case with Patagonia, Alaska and Iceland, viscoelastic models of the crustal motions must be included in the analysis (e.g., Dietrich et al., 2010). The gravitational uplift signal can be detected by absolute and relative gravimetry (e.g., Ekman and Mäkinen, 1996; Mäkinen et al., 2005; Amalvict et al., 2009) or by the GRACE satellite mission data (e.g., Wahr and Velicogna, 2003; Peltier, 2004; Tamisiea et al., 2007). Recent studies have demonstrated that the GRACE data clearly show temporal gravity variations both in Fennoscandia and North America (Tamisiea et al., 2007; Ivins and Wolf, 2008; Steffen et al., 2008; Tregoning et al., 2009). The temporal trends and the uplift pattern retrieved from these data are in good agreement with previous studies and independent terrestrial data (Fig. 3). Groundbased gravity observations must be accompanied with GPS time series to allow the separation of the geometric uplift rate from the gravity change. Gravity changes due to postglacial rebound are about −2 ␮gal/cm of uplift, or about −2 ␮gal/year at the centre of the uplift area in Fennoscandia (Mäkinen et al., 2005; Ekman and Mäkinen, 1996, see Fig. 1).

High-resolution gravity data with spatial scales of 100 km or better and with nearly uniform quality will become available from the GOCE satellite mission launched March 2009. The data are expected to reveal detailed 3D information on Earth rheology and Late Pleistocene ice sheet evolution (Vermeersen and Schotman, 2008). While ancient shorelines may reveal both the uplift history and pattern, the accuracy of shoreline timing is a limiting factor (e.g., Lambeck et al., 1998; Tikkanen and Oksanen, 2002). Over the last several decades attempts have been made to reconstruct palaeoshorelines worldwide. In the periglacial regions the palaeo-sea level is dominated by regional lithospheric flexure due to glacial loadings. Therefore, in such coastal regions there is a close link between GIA and reconstructions of palaeoclimate. Regions along the margins of the rebound area in Fennoscandia and Laurentia reveal complex stress fields. While a connection to GIA is often hypothesized, it is not entirely clear that the residual rebound stresses are responsible for present-day seismicity. The intraplate seismicity in Fennoscandia is low to moderate and the epicentres are concentrated along ancient tectonic deformation zones in areas which are favourably orientated with respect to the regional stress field, and are thus capable of being reactivated (e.g., Slunga, 1991; Arvidsson, 1996; Uski et al., 2003; Gregersen and Voss, this volume). Rebound processes may play a role in triggering seismicity in intraplate areas of northern America (e.g., James and Bent, 1994; Wu and Johnston, 2000; Grollimund and Zoback, 2001; Ma et al., 2008). Using a simple flexure argument, Chung and Gao (1997) and Chung (2002) proposed a similar connection for Greenland seismicity, and Antarctic earthquakes have been analyzed using viscoelastic mantle response modelling by Ivins et al. (2003) and Kaufmann et al. (2005). Recent studies also examine the possibility that during glacial transition times, when global sea-level rise rates are at their maximum (synchronous with Meltwater Pulses 1A and 1B) large interplate faults, such as the San Andreas in southern California, experience coeval enhancement of the shear loading rates that lead to large-scale rupture events (Lutrell and Sandwell, submitted for publication). The viscoelastic response of the solid Earth and regional palaeotopography are influenced by the rheological behaviour of the lithosphere and its lateral variations. Our knowledge of the rheology and structure of the lithosphere is based on rock deformation experiments, petrophysical inference from seismology and heat flow. The surface heat flow will impact the flow dynamics of the ice sheet (Näslund et al., 2005) and thus the deglaciation history. Inversion of temperature data in deep boreholes provides direct access to ground temperature histories during glaciation times (Kukkonen and Jõeleht, 2003; Pollard et al., 2005).

3. GIA models and DynaQlim Current solid Earth GIA models, although 3D in their very nature, assume 1D radial stratification with linear viscoelastic rheology (e.g., Sabadini and Vermeersen, 2004). During the last few years, progress has been made in the development of global, 3D Earth modelling (Martinec, 2000; Wu and van der Wal, 2003; Whitehouse et al., 2006; Klemann et al., 2008). An important step has been the joint inversion of different types of geodetic and gravimetric data related to GIA and connected with geological and geophysical information. Kollo and Vermeer (2010) used the vertical and horizontal postglacial motion in order to determine the lithospheric thickness from observed rates. Paulson et al. (2007) have noted that the collective global GIA data that currently constrain vertical viscosity structure with more than two mantle layers might be subject to greater model-errors than previously recognized owing to the effects of lateral varia-

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tions. Klemann et al. (2008) demonstrated that lateral variation in lithospheric rheology generates toroidal crustal motions at geodetically measurable rates. This rotational motion can mimic plate tectonic rotations. The toroidal GIA solutions cannot be generated in 1D earth models. Milne et al. (2001) solved for Earth rheology using 3D crustal motion observations from the BIFROST continuous GPS network and the Australian National University-derived ice history as synthesized by Kurt Lambeck. Current unexplained GIA model residuals are at the level of 0.2–0.5 mm/year (compared to the observed values) and can be seen in Fig. 2 (Lidberg et al., this volume). Realistic regional modelling needs considerable improvement in the reconstruction of the palaeotopography, and better assessment of the observational uncertainties in the key data sets (e.g., Klemann and Wolf, 2007). Scherneck et al. (2010) analyzed the crustal strain determined by a network of permanent GPS stations. They found that the strain generated by flexure due to GIA is important with maximum strain rates of 5 nano/year in the interior of the rebound area. Recent models of glacially induced faulting are based on glacially induced stresses in the down-warped elastic lithosphere, using increasingly complex numerical models of the glacial history, earth rheology, rock mechanics and pore pressure (e.g., Wu et al., 1999; Hetzel and Hampel, 2005; Lund, 2005; Lund and Näslund, 2008). Emerging as an important aspect of GIA is its impact on palaeotopography and the evolving routes of major rivers and drainage systems, controlling sediment pathways, flood events and the formation and evolution of lake systems over the past 100,000 years of the last glacial cycle (e.g., Svendsen et al., 2004; Krinner et al., 2004; Ivins et al., 2007; Mangerud et al., 2008; Clark et al., 2008; Lemieux et al., 2008). Cyclic changes in eccentricity (400 and 100-kyr), obliquity (41-kyr) and rotational precession (23-kyr) of the Earth, known as the Milankovitch periodicities, control the summer insolation variability in the northern hemisphere. The climate system has numerous nonlinear feedback mechanisms, connected with the variability of many other factors (e.g., Alley et al., 2003). In sum, the large number of potential feedback mechanisms and their poorly controlled model parameterizations, translates into a tenuous scientific understanding how the climate and oceans reorganize during the growth and collapse phases of the great continental glaciations. (A more extended discussion of the topic is given in Poutanen et al., 2009.) Mantle time scale responses to loading have broad viscoelastic relaxation spectra, and for phenomena with low spherical degree order, and for polar-wander responses, continental-scale loading cycles are quite important. An optimum response time scale for the upper mantle is in the range of 500–5000 years for craton-like Earth structure. There are examples of plate boundary responses to Little Ice Age climate changes in which low viscosity parameters are demonstrated to be sensitive to the last 400 years of loading–unloading sequences (e.g., Larsen et al., 2005). Apparently the coupling between atmospheric CO2 and glacier/ice cap growth and diminution also occurs during the waxing and waning of the global Little Ice Age (Cox and Jones, 2008), with temperature leading CO2 by 50 years. One conclusion from this connection might be that ocean and atmospheric temperature changes, now exacerbating the acceleration of global ice loss, will be accelerating for next 50–100 years, regardless of anthropogenic attempts to limit the CO2 growth.

4. Conclusion Advances in studies of the glacial history of northern Europe and Eurasia have significantly improved our understanding of the


ice history during the Late Weichselian (∼100–21 kyr BP), glacial transition times and during the Holocene (11 kyr to present-day) (Svendsen et al., 2004). Connection of the glacial-to-transition and Holocene climates however is complex, and only a longterm, sustained, inter-disciplinary science effort will allow GIA, as observed geodetically, to be connected appropriately to global ocean-atmosphere reorganizations. This connection, none-theless, is very much a part of the ‘holy-grail’ of GIA studies (Broecker, 1966), for without these climate changes the GIA phenomenon would simply not exist. There is the potential to revisit the question of ice thickness at last glacial maximum (LGM) (at 26–21 kyr BP) and during glacial transition time (21–11 kyr BP). Improved models of the evolution of ice thickness would most certainly improve our understanding of climate prior to and during these times. Connection of rheology, sea-level rise and uplift rate is discussed, e.g., in van der Wal et al. (2010). The DynaQlim initiative aims to integrate existing data and models of GIA processes, including geological and geodetic observations combined with climatology and other relevant geodata, such as seismological or sea-level data. The two formerly glaciated regions, Fennoscandia and Laurentia, are expected to be most promising for our model development. One of the objectives of the DynaQlim is to produce better models both of the glacial history and of the Earth response in order to enhance our understanding of the phenomenon of glacially induced faulting and to better predict where and when it occurs. Understanding behaviour of such faults is needed for the safety assessment for future nuclear waste repositories (e.g., Vidstrand et al., 2008). The need to find crustal rock regimes that will safely store carbon with a minimum of pre-existing fractures that may potentially leak dangerous gases to the surface (Zang et al., 2009) is also a possible of practical application of GIA faulting relationships. Acknowledgements The authors want to thank the DynaQlim community for the support of the project and joint effort to promote the GIA related research. The research of Markku Poutanen was partly funded by the Academy of Finland, grant 120212. The research of Erik Ivins is funded by NASA’s Earth Science Program, Solid Earth and Surface Processes Focus Area at the Jet Propulsion Laboratory, California Institution of Technology. References Ågren, J., Svensson, R., 2007. Postglacial land uplift model and system definition for the new Swedish height system RH 2000. Reports in Geodesy and Geographical Information Systems Rapportserie, LMV-Rapport 2007:4, Lantmäteriet, Gävle. Alley, R.B., Marotzke, J., Nordhaus, W.D., Overpeck, J.T., Peteet, D.M., Pielke Jr., R.A., Pierrehumbert, R.T., Rhines, P.B., Stocker, T.F., Talley, L.D., Wallace, J.M., 2003. Abrupt climate change. Science 299, 2005–2010. Amalvict, M., Willis, P., Wöppelmann, G., Ivins, E.R., Bouin, M.-N., Testut, L., Hinderer, J., 2009. Isostatic stability of the East Antarctic station Dumont d’Urville from long-term geodetic observations and geophysical models. Polar Res. 28 (2), 193–202, doi:10.1111/j.1751-8369.2008.00091.x. Arvidsson, R., 1996. Fennoscandian earthquakes: whole crust rupturing related to postglacial rebound. Science 274, 744–746. Bouin, M.-N., Wöpplemann, G., 2010. Land motion estimates from GPS at tide gauges: a geophysical evaluation. Geophys. J. Int. 180, 193–209. Broecker, W.S., 1966. Glacial rebound and deformation of the shorelines of proglacial lakes. J. Geophys. Res. 71, 4777–4783. Calais, E., Han, J.Y., DeMets, C., Nocquet, J.M., 2006. Deformation of the North American plate interior from a decade of continuous GPS measurements. J. Geophys. Res. 111, B06402, doi:10.1029/2005JB004253. Clark, J.A., Befus, K.M., Hooyer, T.S., Stewart, P.W., Shipman, T.D., Gregory, C.T., Zylstra, D.J., 2008. Numerical simulation of the paleohydrology of glacial Lake Oshkosh, eastern Wisconsin, USA. Quaternary Res. 69, 117–129. COST, 2010. COST Action ES0701: Improved Constraints on Models of Glacial Isostatic Adjustment., http://w3.cost.esf.org/index.php?id=205&action number=ES0701.


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