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M. Eby, K. Zickfeld, A. Montenegro, D. Archer, K. J. Meissner, and A. J. Weaver

-down Representation of Interactive Foliage and Flora Including Dynamic vegetation model; Meissner et al. 2003 ). Land carbon fluxes are calculated within MOSES and are allocated to vegetation and soil carbon pools ( Matthews et al. 2004 ). Ocean carbon is simulated by means of an Ocean Carbon-Cycle Model Intercomparison Project type inorganic carbon cycle model and a nutrient–phytoplankton–zooplankton–detritus marine ecosystem model ( Schmittner et al. 2008 ). Sediment processes are represented using an oxic

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Alex S. Gardner, Martin J. Sharp, Roy M. Koerner, Claude Labine, Sarah Boon, Shawn J. Marshall, David O. Burgess, and David Lewis

1. Introduction Mass loss from glaciers and ice caps is likely the second largest contribution to global sea level rise after ocean thermal expansion ( Meier et al. 2007 ). Quantifying past contributions from this source is challenging because of the limited availability of measurements of glacier surface mass balance and rates of iceberg calving. Glacier surface mass balance models are widely used to compensate for this lack of measurements and can be used to predict how climate change will

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Garry K. C. Clarke, Etienne Berthier, Christian G. Schoof, and Alexander H. Jarosch

earth’s mountain glaciers and yield estimates that are completely independent of those obtained by conventional volume–area scaling analysis. Our use of ice masks underscores the importance of collecting accurate information on glacier outlines, one of the objectives of the Glacier Land Ice Measurements from Space (GLIMS) program (additional information is available online at ). The neural network estimators perform best during deglacial phases (like the present one) when the

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Martin Sharp and Libo Wang

consecutive days, or (ii) σ 0 dropped below M 2 for 1 day were categorized as melt days. In previous work, a and b were determined by tuning using air temperature measurements from on-ice weather stations to indicate when melt was occurring ( Wang et al. 2007 ). Becacuse we did not have access to such measurements for this study, we used daily MODIS level 3 (V0004) 1-km-resolution land surface temperature (LST) products (cf. Hall et al. 2006 , 2008 ) for tuning purposes. The errors in the MODIS

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Guido Vettoretti, Marc d’Orgeville, William R. Peltier, and Marek Stastna

McPhaden et al. 2006 ). There exists considerable evidence that ENSO has exhibited markedly different behaviors throughout the recent geologic past. A recent Holocene reconstruction of ENSO variability using deep sea sediments in the ENSO source region has provided some indication as to how the equatorial Pacific thermocline has evolved ( Koutavas et al. 2006 ). Although this record is not reliable during the YD, it suggests that the recorded “La Niña–like” mid-Holocene mean thermocline evolved

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J. Paul Spence, Michael Eby, and Andrew J. Weaver

. Conclusions are presented in section 5 . 2. Model description and experimental design a. The University of Victoria Earth System Climate Model This study uses version 2.7 of the intermediate complexity University of Victoria Earth System Climate Model (UVic ESCM). The UVic ESCM couples a 3D ocean general circulation model, a 2D atmospheric model, a thermodynamic–dynamic sea ice model, and a simple land surface model, described in detail in Weaver et al. (2001) . The UVic ESCM has a global domain, and

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Stephen D. Griffiths and W. Richard Peltier

rapid climate change events. On the northwest European shelf, postglacial changes in tidal amplitudes, currents, and mixing were examined by Uehara et al. (2006) . They, and others (e.g., Shennan and Horton 2002 ), have shown that changes in tidal amplitudes over the Holocene need to be accounted for when interpreting sedimentary records used to construct relative sea level history. We note that a corresponding analysis of changes in tidal range is needed for the east coast of North America, where

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Michael S. Pritchard, Andrew B. G. Bush, and Shawn J. Marshall

horizontal resolution limited by rhomboidal truncation at zonal wavenumber 30, whereas the oceanic component has 15 variably spaced vertical levels with a horizontal resolution of 2° latitude and 3.62° longitude. Oceanic vertical mixing is parameterized using the Richardson number scheme of Pacanowski and Philander (1981) and sea ice is modeled after Fanning and Weaver (1996) . Carbon dioxide is set to 200 ppm, and reconstructed ice sheet topography is from Peltier (1994) . The land surface albedo is

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Shawn J. Marshall and Martin J. Sharp

be a consequence of local continental and marine influences at these marginal sites. The western margins experience warm air advection from the adjacent land, whereas fog and cloud cover on the east coast reduce summer temperatures and lower PDD relative to the model. The climate forcing is a simple temperature extrapolation that neglects these meteorological influences. The PDD model is likely inappropriate to this site. We use literature values for the melt factors, derived from Greenland

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Garry K. C. Clarke, Andrew B. G. Bush, and John W. M. Bush

icebergs. The Agassiz–Ojibway megaflood presents an exceptional opportunity for testing these ideas because the volume of released freshwater and rate of delivery are well constrained. Several previous efforts to model the ocean response to the Lake Agassiz outburst can be faulted for either overestimating the volume of lake water released in the flood (e.g., Renssen et al. 2001 , 2002 , 2007 ; Wiersma and Renssen 2006 ) or for using a zonally averaged ocean model ( Bauer et al. 2004 ), which

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