quantifying paleoclimate dynamics using isotopes ...

            QUANTIFYING PALEOCLIMATE DYNAMICS USING ISOTOPES IN PRECIPITATION

A DISSERTATION SUBMITTED TO THE DEPARTMENT OF EARTH SYSTEM SCIENCE AND THE COMMITTEE ON GRADUATE STUTIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

Matthew Jacob Winnick August 2015

ABSTRACT 1. Motivation As anthropogenic emissions continue to alter the Earth’s climate system, understanding the range of potential consequences has become a question of paramount importance for human society. Over the past few years, atmospheric pCO2 has risen above 400 ppm to levels that the Earth has not experienced since the Pliocene epoch, roughly 3 million years ago (Pagani et al., 2010). While general circulation models (GCM’s) are our primary means for projecting climate change into the future, it remains an open question as to whether or not they are able to accurately simulate dynamics under radically different climate states. The hydrologic cycle, in particular, is subject to considerable uncertainty due to the control of relatively complex dynamic changes in atmospheric circulation on top of thermodynamic forcing (Shepherd, 2014; Trenberth et al., 2015), especially in the mid-latitudes. Past climate reconstructions may therefore play a vital role in testing the ability of GCM’s to accurately simulate climate dynamics under high pCO2 scenarios (Bony et al., 2015). The Cenozoic era, covering the past 65 Ma, offers a number of unique windows into climate systems that were equilibrated with modern to near-future projections of atmospheric pCO2 levels and with comparable geographic boundary conditions relative to earlier times in Earth’s history. Over the course of the Cenozoic, atmospheric pCO2 decreased from peak levels of 400 to >2000 ppm in the Early Eocene (52 Ma) to pre-industrial levels of 190-280 ppm in the mid-Pleistocene (1 Ma) (Beerling and Royer, 2011). Consequently, global temperatures have decreased from 10-15º C warmer-than-modern in the Early Eocene to ~4º C colder-than-modern

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during Pleistocene glacial times, with attendant reorganizations of the Earth system including the separate initiations of large-scale glaciation in the Southern and Northern Hemispheres (Zachos et al., 2001). Paleoclimate dynamics throughout the Cenozoic have been reconstructed using a number of different physical and chemical proxies that provide insights into their formation conditions, which can then be compared to GCM experiments to test hypotheses of causality and model performance. In this dissertation, I focus specifically on isotopes in precipitation, which are commonly used as proxies for changes in the hydrologic cycle. The goal of this work is to develop and apply mechanistic frameworks to isotope reconstructions in order to provide quantitative inferences and better understand climate dynamics during key times throughout the Cenozoic era.

2. Isotopes in Precipitation Ratios of stable isotopes in precipitation are one of the more ubiquitous proxy tools for elucidating past hydrologic conditions and have been utilized extensively over the last half-century. Specifically, changes in the ratios of water isotopologues containing the less-abundant stable isotopes of hydrogen and oxygen (D and

18

O) to

those without are controlled by equilibrium and kinetic fractionation processes that occur during phase transformations. As such, measurements of these ratios (δD and

δ18O) in meteoric water and in authigenic minerals and biomarkers that incorporate meteoric water into their chemical structure in predictable ways can provide unique insights into the global hydrologic cycle.

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Isotopes in precipitation are sensitive to a wide range of hydro-climatic factors. For example, δD and δ18O co-vary strongly with temperature in the high latitudes (Dansgaard, 1964; Rozanski et al., 1993); precipitation amount and atmospheric residence time of water vapor in the tropics (Risi et al., 2008; Aggarwal et al., 2012; Moore et al., 2014); and changes in moisture source location and conditions (Pausata et al., 2011), topography (Poage and Chamberlain, 2001), evapotranspiration (ET) (Gat and Matsui, 1991), synoptic-scale air mass interactions (Liu et al., 2010), and mixing by transient eddies (Eriksson, 1965) in terrestrial environments, to name a few. While this sensitivity allows for the potential characterization of complex hydrologic dynamics, separating out these disparate effects from isotope measurements remains a major challenge. Compounding this difficulty is the fact that the majority of preQuaternary terrestrial paleoclimate studies are restricted to a single proxy locality due to the intensive nature of sampling and analysis; as a result, single records have often been interpreted in the context of a specific variable of interest (i.e. temperature, topography, etc.) rather than in a holistic manner. Only in the past decade have enough records emerged to begin to examine large-scale spatial patterns of isotopes in precipitation in the past, facilitated in part by the development of biological proxies allowing for measurements in coastal localities. Additionally, the recent widespread availability of paleoclimate GCM output and the incorporation of isotopes into GCM’s have opened the door to more mechanistic interpretations of these spatially extensive reconstructions. The research presented herein is built off this general trajectory, and explores the methods with which proxy

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compilations and physical models can be combined to better quantify paleoclimate dynamics. This dissertation is a collection of four separate studies arranged in chronological order by completion date, as detailed below. Chapter 1 examines the migration of the Pacific storm track in response to changes in the structure of tropical Pacific sea surface temperatures (SST’s) and initiation of Northern Hemisphere glaciation through the Plio-Pleistocene using new and previously published paleosol carbonate records. In Chapter 2, I develop a reactive transport model to simulate isotopic gradients over terrestrial environments and explore the variables controlling the isotopic ‘continental effect’ globally. Chapter 3 compares a reactive transport model of latitudinal isotopic gradients with a proxy compilation to better understand global isotopic variability and latent heat transport under Early Eocene hothouse conditions. Finally, Chapter 4 presents an isotope mass-balance model for the Pliocene ocean-ice system that is then used to quantify peak eustatic sea level from the benthic foraminifera record.

3. Summary of Research In Chapter 1, I investigate the regional temporal evolution of isotopes in precipitation recorded in paleosols across the western US through the Plio-Pleistocene (4 – 1 Ma). Major Earth system shifts occurred across the Plio-Pleistocene including a decrease in pCO2 from modern to pre-industrial values (Pagani et al., 2010), the establishment of modern tropical Pacific SST patterns (Wara et al., 2005), and the large-scale initiation of Northern Hemisphere (NH) glaciation (Zachos et al., 2001).

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All of these transitions are thought to exert both thermodynamic and dynamic controls on western US hydrology (e.g. Seager et al., 2007; Trenberth et al., 1997; Oster et al., 2015), which also saw a massive reorganization with the desiccation and subsequent re-establishment of large lake systems across the now-arid region (Thompson, 1991). Specifically, I test the hypothesis that wetter-than-modern Pliocene conditions across the western US were the result of increased SST’s in the East Equatorial Pacific (EEP) which caused a southward shift in the Pacific storm track despite globally warmer temperatures, similar to modern El Nino dynamics (Molnar and Cane, 2002). To test this hypothesis, I compare the temporal trends in two new and three previously published paleosol δ18O records across the late Pliocene with modern spatial patterns of El Nino precipitation δ18O anomalies. When seasonality of soil carbonate formation is taken into account, all proxy trends through the late Pliocene match the modern transition from El Nino to neutral climate states in both direction and magnitude. This suggests that cooling of the EEP resulted in the northward shift in the Pacific storm track, and is consistent with compilations of proxy data that indicate large-scale aridification throughout the region. Furthermore, all proxy records display a characteristic ‘V’ shape where δ18O approaches mid-Pliocene values in the early to mid-Pleistocene, coincident with the initiation of NH glaciation and a return to wetterthan-modern conditions across the western US. We suggest that this return to midPliocene δ18O values indicates the subsequent southward migration of the Pacific storm track, consistent with the establishment of the Laurentide ice sheet. This chapter was published in Climate of the Past in 2013 with coauthors Dr. Jeffrey M. Welker and Dr. C. Page Chamberlain (Winnick et al., 2013). I co-designed

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this study, led fieldwork to collect San Timoteo, CA paleosol samples, conducted laboratory prep and stable isotope analyses, compiled previously published sections, and wrote the manuscript. Dr. Jeffrey M. Welker contributed USNIP data and the modern ENSO anomalies figure. Dr. C. Page Chamberlain co-designed the study, conducted fieldwork and isotope analyses on Hagerman, ID paleosols, and assisted in preparing and editing the manuscript. In Chapter 2, I explore the factors that control isotopic gradients in precipitation across terrestrial environments. Since the earliest monitoring efforts of isotopes in precipitation in the early 1960’s, it has been recognized that δD and δ18O tend to decrease with increasing distance inland, an observation typically referred to as the ‘continental effect’ (Dansgaard, 1964; Rozanski et al., 1993). Despite this general observation, actual isotopic gradients have been found to vary by at least two orders of magnitude across the globe (Rozanski et al., 1993). Additionally, previous efforts to characterize these gradients have shown that Rayleigh distillation is unable to capture the range of global variability (Liu et al., 2010). To better understand the ‘continental effect’, I adapt a one-dimensional reactive transport model of isotopes in precipitation (Hendricks et al., 2000) for transport over terrestrial environments that includes the well-described processes of ET and eddy transport that affect isotope gradients (Gat and Matsui, 1991; Erikkson, 1965) and compare model results to global observations. I demonstrate that while rainout is the dominant control on isotopic gradients, deviation from Rayleigh distillation is controlled by the competing effects of ET and eddy transport that increase and decrease the sensitivity of gradients to rainout, respectively. These variables become increasingly important at short length scales of

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specific humidity (i.e. high degrees of rainout) such as in orographic environments. The analysis presented in Chapter 2 provides a mechanistic framework for interpreting reconstructions of isotopic gradients and provides strategies to test hypotheses of change with the goal of unraveling the competing effects of vegetation, circulation, and topography. This chapter was published in Earth and Planetary Science Letters in 2014 with coauthors Dr. C. Page Chamberlain, Jeremy K. Caves, and Dr. Jeffrey M. Welker (Winnick et al., 2014). I designed the study, conducted modeling experiments, and wrote the manuscript. Dr. Jeffrey M. Welker collected and processed observational data from the USNIP. Dr. C. Page Chamberlain and Jeremy K. Caves assisted with manuscript preparation and editing. Chapter 3 analyzes the mechanistic controls on low latitudinal gradients of isotopes in precipitation during the Early Eocene (55 – 49 Ma) and explores the dynamics of latent heat transport under hothouse climate conditions. During this time, reconstructed atmospheric pCO2 was between 400 to >2000 ppm (Beerling and Royer, 2011); as a result, global temperatures were 10-15º C warmer than modern (Zachos et al., 2001; Huber and Caballero, 2011). This warming was concentrated in the high latitudes, with largely ice-free poles and crocodiles and palm trees ringing the artic circle (Markwick, 1994; Sluijs et al., 2009), resulting in reduced latitudinal temperature gradients (Wolfe, 1995). Despite the widespread use of reconstructed δD and δ18O in Early Eocene climate studies, very little work has been done to examine global variability of isotopes in precipitation under hothouse conditions from a geophysical perspective, with the exception of one isotope-enabled GCM experiment

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that matched broad-scale patterns of isotope econstructions with the implementation of Eocene boundary conditions (Speelman et al., 2010). To address this, I use a reactive transport model, modified from the model in Chapter 2 to simulate global latitudinal patterns of isotopes in precipitation (Hendricks et al., 2000), implemented with a novel Monte Carlo routine and forced with previously published Eocene GCM experiments (Huber and Caballero, 2011). Low latitudinal gradients of isotopes in precipitation are controlled primarily by increased high-latitude length scales of specific humidity, potentially amplified by an increase in transient eddy-driven moisture fluxes. Reduced high-latitude length scales are driven by polar amplification of global warming, so that in the absence of polar amplification, global warming produces no change in precipitation isotopes, as demonstrated by comparisons of Eocene simulations forced with pCO2 of 2240 and 4480 ppm. I suggest, therefore, that observed increases in latitudinal δD gradients during Early Eocene hyperthermal events (Krishnan et al., 2015) may instead reflect theorized reductions in latent heat transport by mid-latitude transient eddies (Caballero and Hanley, 2012). This chapter is currently under review at Geophysical Research Letters with coauthors Jeremy K. Caves and Dr. C. Page Chamberlain. I co-designed this study, conducted modeling analyses, and wrote the manuscript. Jeremy K. Caves compiled and analyzed the Eocene proxy compilation and assisted with manuscript preparation and editing. Dr. C. Page Chamberlain co-designed this study and assisted with manuscript preparation and editing.

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Finally in Chapter 4, I present a quantitative isotope mass-balance model for calculating Pliocene sea level from the benthic oxygen isotope (δ18Ob) record and rectify a long-standing discrepancy between ice sheet models and Pliocene sea level reconstructions. Despite a wealth of sophisticated research aimed at de-convolving temperature and ice volume signals from the δ18Ob record, every δ18Ob-based Pliocene sea level reconstruction in the literature applies an LGM-calibrated linear relationship between global sea level and δ18O to estimate global sea level. Chapter 4 argues that this relationship, based on melting of the Laurentide and Fenno-Scandinavian ice sheets, is inappropriate for the Pliocene epoch and instead, presents a detailed boxmodel based on Pliocene climate and ice sheet configurations. This model includes two well-established, though previously unconsidered processes: (1) the isotopic evolution of terrestrial ice with changing climate (Dansgaard, 1964), and (2) the melting of submarine terrestrial ice (Fretwell et al., 2013). Both of these processes contribute to the δ18Ob record without contributing to global sea level, effectively amplifying signals of terrestrial ice sheet growth and ablation in the δ18Ob record. I then apply this model to the Lisiecki and Raymo (2005)

δ18Ob stack along with a detailed sensitivity analysis to Pliocene boundary conditions, and conclude that Pliocene sea level was likely 9-13.5 m above modern and very likely 5-17 m above modern. These new sea level estimates, in concurrence with dynamic ice sheet models forced with Pliocene boundary conditions, are substantially lower than previous δ18Ob-based estimates, and suggest that the East Antarctic Ice Sheet is much less sensitive to radiative forcing than previously inferred from the geologic record.

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This chapter is accepted at Geology with coauthor Jeremy K. Caves. I codesigned this study, contributed to quantitative analyses, and wrote the manuscript. Jeremy K. Caves co-designed the study, contributed to quantitative analyses, prepared the figures, and assisted in manuscript preparation and editing.

4. References Aggarwal, P.K., Alduchov, O.A., Froehlich, K.O., Araguas-Araguas, L.J., Sturchio, N.C., Kurita, N. (2012) Stable isotopes in global precipitation: A unified interpretation based on atmospheric moisture residence time. Geophysical Research Letters 39, L11705, doi:10.1029/2012GL051937. Beerling, D.J., and D.L. Royer (2011) Convergent Cenozoic CO2 history. Nature Geoscience 4, 418-420. Bony, S., Stevens, B., Frierson, D.M.W., Jakob, C., Kageyama, M., Pincus, R., Shepherd, T.G., Sherwood, S.C., Siebesma, A.P., Sobel, A.H., Watanabe, M., Webb, M.J. (2015) Clouds, circulation and climate sensitivity. Nature Geoscience 8, 261-268. Caballero, R. and J., Hanley (2012) Midlatitude eddies, storm-track diffusivity, and poleward moisture transport in warm climates. Journals of the Atmospheric Sciences 69, 3237-3250. Dansgaard, W. (1964) Stable isotopes in precipitation. Tellus 16, 436-468. Eriksson, E. (1965) Deuterium and oxygen-18 in precipitation and other natural waters: Some theoretical considerations. Tellus 17, 498-512.

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Fretwell, P., Pritchard, H.D., Vaughan, D.G., Bamber, J.L., Barrand, N.E., Bell, R., Bianchi, C., Bingham, R.G., Blankenship, D.D., Casassa, G., Catania, G., Callens, D., Conway, H., Cook, a. J., et al. (2013) Bedmap2: Improved ice bed, surface and thickness datasets for Antarctica. Cryosphere, v. 7, p. 375–393, doi: 10.5194/tc-7-375-2013. Gat, J.R. and Matsui, T. (1991) Atmospheric water balance in the Amazon Basin: an isotopic evapotranspiration model. J. Geophys. Res. 96, 13179-13188. Hendricks, M.B., DePaolo, D.J., Cohen, R.C. (2000) Space and time variation of δ18O and δD in precipitation: Can paleotemperature be estimated from ice cores? Global Biogeochem. Cy. 14, 851-861. Huber, M., and R. Caballero (2011) The early Eocene equable climate problem revisited. Clim. Past 7, 603-633. Krishnan, S., M. Pagani, and C. Agnini (2015) Leaf waxes as recorders of paleoclimatic changes during the Paleocene-Eocene Thermal Maximum: Regional expressions from the Belluno Basin. Organic Geochemistry 80, 8-17. Lisiecki, L.E., and Raymo, M.E. (2005) A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography, v. 20, no. PA1003, doi: 10.1029/2004PA001071. Liu, Z., Bowen, G.J., Welker, J.M. (2010) Atmospheric circulation is reflected in precipitation isotope gradients over the conterminous United States. J. Geophys. Res. 115, D221210. Markwick P (1994) “Equibility,” continentality, and Tertiary “climate”: The crocodilian perspective. Geology 22, 613-616.

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Molnar, P. and Cane, M.A. (2002) El Niño’s tropical climate and teleconnections as a blueprint for pre-Ice Age climates. Paleoceanography 17, PA1021. Moore, M., Kuang, Z., Blossey, P.N. (2014) A moisture budget perspective of the amount effect. Geophys. Res. Lett. 41, 1329-1335. Oster, J.L., Ibarra, D.E., Winnick, M.J., Maher, K. (2015) Steering of westerly storms over western North America at the Last Glacial Maximum. Nature Geoscience 8, 201-205. Pagani, M., Liu, Z., LaRiviere, J., and Ravelo A. C. (2010) High Earth-system climate sensitivity determined from Pliocene carbon dioxide concentrations. Nature Geosci. 3, 27-30. Pausata, F. S. R., Battisti, D. S., Nisancioglu, K. H., Bitz, C. M. (2011) Chinese stalagmite δ18O controlled by changes in the Indian monsoon during a simulated Heinrich event. Nature Geosci. 4, 474-480. Poage, M.A. and Chamberlain, C.P. (2001) Empirical relationships between elevation and the stable isotope composition of precipitation and surface waters: considerationsfor studies of paleoelevation change. Am. J. Sci. 301, 1-15. Risi, C., Bony, S., and Vimeux, F. (2008) Influence of convective processes on the isotopic composition (δ18O and δD) of precipitation and water vapor in the tropics: 2. Physical interpretation of the amount effect. J. Geophys. Res. 113, D19305. Rozanski, K., Araguas-Arrguas, L., and Gonfiantini, R. (1993) Isotopic patterns in modern global precipitation, in: Climate Change in Continental Isotopic Records, edited by: Swart, P.K., Lohmann, K.C., McKenzie, J., and Savin, S.,

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American Geophysical Union Geophysical Monograph, 78, 1-37. Seager, R., Ting, M., Held, I., Kushnir, Y., Lu, J., Vecchi, G., Huang, H.-P., Harnik, N., Leetmaa, A., Lau, N.-C., Li, C., Velez, J., and Naik, N. (2007) Model projections of an imminent transition to a more arid climate in Southwestern North America. Science 316, 1181–1184. Shepherd, T.G. (2014) Atmospheric circulation as a source of uncertainty in climate change projections. Nature Geoscience 7, 703-708. Sluijs A., S. Schouten, T.H. Donders, P.L. Schoon, U. Rohl, G. Reichart, F. Sangiorgi, J. Kim, J.S. Damste, and H. Brinkhuis (2009) Warm and wet conditions in the Arctic region during Eocene Thermal Maximum 2. Nature Geoscience 2, 777780. Speelman, E.N., Sewall, J.O., Noone, D., Huber, M., von der Heydt, A., Damste, J.S., Reichart, G.-J. (2010) Modeling the influence of a reduced equator-to-pole sea surface temperature gradient on the distribution of water isotopes in the Early/Middle Eocene. Earth Planet. Sc. Lett. 298, 57-65. Thompson, R. S. (1991) Pliocene environments and climates in the western United States. Quaternary. Sci. Rev. 10, 115–132. Trenberth, K. E., Branstator, G. W., Karoly, D., Kumar, A., Lau, N.-C., and Ropelewski, C. (1998) Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J. Geophys. Res. 103, 14291-14324. Trenberth, K.E., Fasullo, J.T., Shepherd, T.G. (2015) Attribution of climate extreme events. Nature Climate Change, doi: 10.1038/NCLIMATE2657.

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Wara, M. W., Ravelo, A. C., and Delaney, M.L. (2005) Permanent El Niño-like conditions during the Pliocene warm period. Science 29, 758-761. Winnick, M.J., Welker, J.M., Chamerblain, C.P. (2013) Stable isotopic evidence of El Nino-like atmospheric circulation in the Pliocene western United States. Clim. Past 9, 903-912. doi:10.5194/cp-9-903-2013 Winnick, M.J., C.P. Chamberlain, J.K. Caves, and J.M. Welker (2014) Quantifying the isotopic ‘continental effect’. Earth Planet. Sci. Lett. 406, 123-133. Wolfe, J. (1995) Paleoclimatic estimates from Tertiary leaf assemblages. Annu. Rev. Earth Planet. Sci. 23, 119-142. Zachos, J., Pagani, M., Sloan, L., Thomas, E., and Billups K. (2001) Trends, rhythms, and aberrations in global climate 65 Ma to present. Science 292, 686-693.

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ACKNOWLEDGEMENTS First and foremost I would like to thank my advisor C. Page Chamberlain whose mentorship and support have been invaluable throughout my graduate career. More than anything, Page taught me the value of pursuing the scientific questions that are inspiring on a personal level and of the importance of maintaining a fluidity of thought. I am forever indebted to him for his guidance and for the science, camping, and music that have made my time at Stanford so memorable. I would also like to thank Kate Maher who has essentially been a second advisor to me. Her mentorship as both a scientific collaborator and a teacher has been a constant source of inspiration, and I am thrilled to have the opportunity to continue working with her as a postdoctoral scholar next year. I am very grateful for the guidance from and helpful discussions I’ve had with Noah Diffenbaugh; in particular, welcoming me into his research group meetings early in my graduate education helped to shape my understanding of climate dynamics. I would also like to thank my defense chair Stephen A. Graham and committee member C. Kevin Boyce for their invaluable insights and suggestions through the dissertation process. I would especially like to thank my research group – Jeremy Caves, Daniel Ibarra, Hari Mix, and Annie Ritch – who have been like a family during my time at Stanford, and I look forward to the years of friendship and collaboration ahead. I am also grateful for the incredibly helpful discussions and collaborations I’ve had with Andreas Mulch, Jessica Oster, Christopher Skinner, Rob Dunbar, Jerry X. Mitrovica, Jeffrey M. Welker, and the Stanford Earth History Group of Support (EHGOS). I thank my friends and family for all of their support and the much-needed doses of

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sanity. Finally I’d like to thank my parents, Martha Jacobs and Steve Winnick, without whose love and support I would not be here.

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TABLE OF CONTENTS ABSTRACT ............................................................................................................... iv ACKNOWLEDGEMENTS ................................................................................. xviii TABLE OF CONTENTS ......................................................................................... xx LIST OF TABLES................................................................................................. xxiv LIST OF FIGURES................................................................................................ xxv CHAPTER 1: Stable isotopic evidence of El Niño-like atmospheric circulation in the Pliocene Western United States .......................................................................... 1 ABSTRACT ................................................................................................................. 2 INTRODUCTION ........................................................................................................ 3 METHODS ................................................................................................................... 6 Pedogenic carbonates ....................................................................................... 6 Modern isotopes in precipitation ...................................................................... 8 RESULTS ..................................................................................................................... 8 Pedogenic carbonates ....................................................................................... 8 Modern isotopes in precipitation .................................................................... 10 DISCUSSION ............................................................................................................ 12 Seasonality of carbonate formation ................................................................ 12 Comparison of Pliocene and modern isotope signals ..................................... 14 Comparison of Pliocene and Pleistocene isotope signals ............................... 15 CONCLUSIONS ........................................................................................................ 17 ACKNOWLEDGEMENTS ....................................................................................... 18 REFERENCES ........................................................................................................... 19 FIGURES ................................................................................................................... 30 CHAPTER 2: Quantifying the isotopic ‘continental effect’ ................................. 35 ABSTRACT ............................................................................................................... 36 INTRODUCTION ...................................................................................................... 37 ISOTOPE MODEL .................................................................................................... 40

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Model derivation ............................................................................................ 40 Model sensitivity ............................................................................................ 42 Continental isotopic gradients ........................................................................ 45 DATA ......................................................................................................................... 46 Isotope data..................................................................................................... 46 Global Damköhler and Peclet numbers .......................................................... 47 DISCUSSION ............................................................................................................ 49 Data-model comparison ................................................................................. 49 Implications for paleoclimate and paleoaltimetry studies .............................. 55 Implications for large-scale monitoring of modern terrestrial ET ................. 57 CONCLUSIONS ........................................................................................................ 58 ACKNOWLEDGEMENTS ....................................................................................... 60 REFERENCES ........................................................................................................... 60 TABLE AND FIGURES ............................................................................................ 69 CHAPTER 3: A mechanistic analysis of Early Eocene latitudinal gradients of isotopes in precipitation ........................................................................................... 77 ABSTRACT ............................................................................................................... 78 INTRODUCTION ...................................................................................................... 78 METHODS ................................................................................................................. 80 Isotope model ................................................................................................. 80 Data ................................................................................................................ 83 RESULTS ................................................................................................................... 84 Modern data-model ........................................................................................ 84 Eocene data-model ......................................................................................... 85 Eocene simulation comparison ....................................................................... 87 DISCUSSION ............................................................................................................ 87 Early Eocene δ18O gradients .......................................................................... 87 Insensitivity of δ18O to temperature in hothouse climates ............................. 89 Implications for δD signals of Early Eocene hyperthermals .......................... 91 CONCLUSIONS ........................................................................................................ 92

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ACKNOWLEDGMENTS .......................................................................................... 93 REFERENCES ........................................................................................................... 94 FIGURES ................................................................................................................. 101 CHAPTER 4: Isotope mass-balance constraints on Pliocene sea level and East Antarctic Ice Sheet stability................................................................................... 104 ABSTRACT ............................................................................................................. 105 INTRODUCTION .................................................................................................... 106 ANTARCTIC PLIOCENE TEMPERATURES AND δ18O .................................... 108 METHODS ............................................................................................................... 109 RESULTS AND DISCUSSION .............................................................................. 111 IMPLICATIONS ...................................................................................................... 113 ACKNOWLEDGEMENTS ..................................................................................... 114 REFERENCES ......................................................................................................... 114 FIGURES ................................................................................................................. 122 APPENDIX A: Supporting information for CHAPTER 1 ................................. 125 MODERN ENSO δ18O SIGNALS ........................................................................... 126 PLIOCENE TOPOGRAPHY ................................................................................... 127 REFERENCES ......................................................................................................... 130 TABLES AND FIGURES........................................................................................ 133 APPENDIX B: Supporting information for CHAPTER 2 ................................. 139 TABLES ................................................................................................................... 140 APPENDIX C: Supporting information for CHAPTER 3 ................................. 145 TABLES AND FIGURES........................................................................................ 146 APPENDIX D: Supporting information for CHAPTER 4 ................................. 149 SENSITIVITY TO ENHANCED WARMING OVER GIS AND WAIS ............... 150

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CALCULATION OF MASSES OF THE MARINE-BASED AND NON-MARINEBASED WAIS SECTORS ....................................................................................... 150 SENSITIVITY TO PLIOCENE BOTTOM WATER TEMPERATURES ............. 151 REFERENCES ......................................................................................................... 152 TABLES AND FIGURES........................................................................................ 159

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LIST OF TABLES CHAPTER 2 Table 1 ........................................................................................................................ 69 APPENDIX A Table 1 ...................................................................................................................... 135 APPENDIX B Table 1 ...................................................................................................................... 140 APPENDIX C Table 1 ...................................................................................................................... 146 Table 2 ...................................................................................................................... 147 APPENDIX D Table 1 ...................................................................................................................... 163

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LIST OF FIGURES CHAPTER 1 Figure 1....................................................................................................................... 30 Figure 2....................................................................................................................... 31 Figure 3....................................................................................................................... 32 Figure 4....................................................................................................................... 33 Figure 5....................................................................................................................... 34 CHAPTER 2 Figure 1....................................................................................................................... 70 Figure 2....................................................................................................................... 71 Figure 3....................................................................................................................... 72 Figure 4....................................................................................................................... 73 Figure 5....................................................................................................................... 74 Figure 6....................................................................................................................... 75 Figure 7....................................................................................................................... 76 CHAPTER 3 Figure 1..................................................................................................................... 101 Figure 2..................................................................................................................... 102 Figure 3..................................................................................................................... 103 CHAPTER 4 Figure 1..................................................................................................................... 123 Figure 2..................................................................................................................... 124 APPENDIX A Figure 1..................................................................................................................... 133 Figure 2..................................................................................................................... 134

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APPENDIX C Figure 1..................................................................................................................... 148 APPENDIX D Figure 1..................................................................................................................... 159 Figure 2..................................................................................................................... 160 Figure 3..................................................................................................................... 161 Figure 4..................................................................................................................... 162

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CHAPTER 1 Stable Isotopic Evidence of El Niño-like Atmospheric Circulation in the Pliocene Western United States Matthew J. Winnick1, Jeffery M. Welker2, and C. Page Chamberlain1 1

Environmental Earth System Science, Stanford University, Stanford, CA 94305, USA

2

Environment and Natural Resources Institute and Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK 99508, USA

Reproduced with permission from Winnick, M.J., Welker, J.M., and Chamberlain, C.P., Climate of the Past. Copyright Authors 2013, Creative Common Attribution 3.0 License

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ABSTRACT Understanding how the hydrologic cycle has responded to warmer global temperatures in the past is especially important today as concentrations of CO2 in the atmosphere continue to increase due to human activities. The Pliocene offers an ideal window into a climate system that has equilibrated with current atmospheric pCO2. During the Pliocene the western United States was wetter than modern, an observation at odds with our current understanding of future warming scenarios, which involve the expansion and poleward migration of the subtropical dry zone. Here we compare Pliocene oxygen isotope profiles of pedogenic carbonates across the western US to modern isotopic anomalies in precipitation between phases of the El Niño Southern Oscillation (ENSO).

We find that when accounting for seasonality of carbonate

formation, isotopic changes through the late Pliocene match modern precipitation isotopic anomalies in El Niño years. Furthermore, isotopic shifts through the late Pliocene mirror changes through the early Pleistocene, which likely represents the southward migration of the westerly storm track caused by growth of the Laurentide Ice Sheet. We propose that the westerly storm track migrated northward through the late Pliocene with the development of the modern Cold Tongue in the East Equatorial Pacific, then returned southward with widespread glaciation in the Northern Hemisphere – a scenario supported by terrestrial climate proxies across the US. Together these data support the proposed existence of background El Niño-like conditions in western North America during the warm Pliocene. If the Earth behaves similarly with future warming, this observation has important implications with regard to the amount and distribution of precipitation in western North America.

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1. INTRODUCTION As the Earth’s climate continues to respond to the anthropogenic input of greenhouse gasses to the atmosphere, understanding potential regional responses of the hydrologic cycle becomes vital for effective freshwater resource management and natural hazard mitigation policies. This problem is particularly relevant in watervulnerable areas such as the southwest United States where the amount of water used is similar to the amount of water available (Meehl et al., 2007). The current suite of Earth system models predicts an intensified hydrologic cycle with increasing global temperatures (Meehl et al., 2007). For many regions, this temperature increase is associated with increased precipitation.

However, in the mid-latitudes where

evaporation currently dominates precipitation such as in the southwest US, a temperature increase results in decreasing precipitation due to the poleward expansion and enhanced aridification of the Hadley cell margin (Seager et al., 2007; O’Gorman and Schneider, 2010). This predicted regional response conflicts with reconstructed wetter-than-modern conditions in the southwest during pre-Quaternary warm periods, particularly in the Pliocene epoch. It is then of great importance to study the mechanisms behind increased precipitation during pre-Quaternary warm periods in regions that are projected to dry over the coming decades as a result of modern climate change. Herein, we examine terrestrial stable isotope records for the Pliocene of western North America in order to better understand the causes of these wetter-than-modern conditions despite higher global temperatures and a potentially strengthened hydrologic cycle.

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The Pliocene epoch (5.33 – 2.58 Ma), with similar-to-modern boundary conditions including atmospheric pCO2 of ~400 ppm (Pagani et al., 2010) and global geography (Zachos et al., 2001; Haug et al., 2001), affords us a unique view of a globally warmer equilibrium state of the Earth system (Jansen et al., 2007). During the Pliocene, global temperatures were 3-4ºC higher than today (Ravelo et al., 2005), and major ice sheets were absent from the Northern Hemisphere (Zachos et al., 2001). In addition, much of the western and southern US were characterized by wetter-thanmodern conditions, while a few areas in the Pacific Northwest were drier than modern (FIG 1). A number of studies have suggested that these anomalous wet conditions may have been the result of the temperature structure of the tropical Pacific. In the Pliocene, sea surface temperatures (SSTs) in the West Equatorial Pacific were similar to modern, while SSTs in the East Equatorial Pacific (EEP) were 3-5ºC warmer with evidence of a much deeper thermocline (Wara et al., 2005; Dekens et al., 2007; Etourneau et al., 2010). In the modern climate, this temperature structure characterizes the El Niño phase of ENSO. This observation has led many studies to conclude that the Pliocene was characterized by a background El Niño-like state, though the nature of interannual variability is poorly constrained (Ravelo et al., 2004; Wara et al., 2005). During modern El Niño years, North America is particularly affected by atmospheric teleconnections, as anomalous atmospheric conditions propagate poleward from the equatorial Pacific via planetary waves. Major changes in North American hydrology are primarily facilitated by a deeper Aleutian low, which forces the subtropical jet and westerly storm track equator-ward (Bjerknes, 1969; Trenberth

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et al., 1998).

Qualitative spatial patterns of reconstructed Pliocene precipitation

(wetter/drier) based on terrestrial proxy records match modern El Niño teleconnection patterns (Molnar and Cane, 2002) (FIG 1), and GCM experiments have shown that forced permanent El Niño-like SSTs result in a south-shifted subtropical jet and increased moisture convergence across the western and southern US (e.g.: Barreiro et al., 2006; Shukla et al., 2009; Brierly and Federov, 2010; Vizcaíno et al., 2010; Goldner et al., 2011). It has also been suggested that these wet conditions may have been the result of lower topography in the North American Cordillera (Bonham et al., 2009) based on PRISM 2 (Pliocene Research, Interpretation and Synoptic Mapping) boundary conditions. The assumption of lower topography, however, is not supported by paleoaltimetry studies of the US, which show that large-scale topography reached modern elevations by the early Miocene (e.g.: Mulch et al., 2006; Mix et al., 2011; Chamberlain et al., 2012). More recently, Pliocene boundary conditions provided by PRISM 3 and used as part of the PlioMIP (Pliocene Model Intercomparison Project) have been amended to include near-modern topography across the western US (Sohl et al., 2009; Bragg et al., 2012). Results of PlioMIP ensembles using these updated boundary conditions indeed show enhanced precipitation rates over the western US likely resulting from the reduced zonal temperature gradient across the tropical Pacific, though there appear to be discrepancies with proxy-based reconstructions of precipitation across the southeastern US (Haywood et al., 2012). In this study, we seek to test the hypothesis that wetter-than-modern Pliocene conditions in the western US were the product of a background El Niño-like state. To

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accomplish this, we compare two new and three previously published Plio-Pleistocene oxygen isotopic profiles across the western US measured in pedogenic carbonates with modern observations of isotopes in precipitation across two phases of ENSO (Neutral and El Niño) at 77 stations across the country (Welker, 2012). Unlike floral-, faunal-, and sediment-based reconstructions that record only local environmental conditions, isotopes in precipitation recorded in authigenic minerals are controlled by a combination of local conditions and upstream processes such as rainout and moisture transport (e.g.: Pausata et al., 2011; Poulsen et al., 2010). While separating local signals from upstream signals is often challenging, oxygen isotopes therefore have the potential to offer unique insights into synoptic-scale atmospheric circulation.

2. METHODS 2.1 Pedogenic carbonates We sampled two well-dated sections composed of Pliocene paleosols and fluvial deposits that contain abundant pedogenic carbonate: 1) the San Timoteo Badlands of southern California (CA) (Albright, 1999) on the windward corner of the intersection of the Transverse and Peninsular ranges, and 2) the sections located at Hagerman, Idaho (ID) from the Glenns Ferry, Tuana Gravels, and Bruneau formations (Hart et al., 1999; Sadler and Link, 1996; Amini et al., 1984). We collected calcareous sand- and mudstones showing no physical signs of re-precipitation of carbonate such as weathered surfaces or calcite veins. Milled carbonate samples were reacted with phosphoric acid through a Kiel III carbonate device. Carbon and oxygen isotope ratios were then measured on a Thermo Finnigan Delta Plus. Precision of carbonate δ18O

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values is ~0.06‰ based on repeated analyses of NBS-19 and M-2 carbonate standards. These isotope values are given in APPENDIX A Table 1. In addition to these new isotope records, we compiled three previously published isotopic profiles of pedogenic carbonates that are found in Plio-Pleistocene sections in the western US. These profiles were collected from Camp Rice, New Mexico (NM) (Mack et al., 1994), Meade, Kansas (KS) (Fox and Koch, 2003), and St David, Arizona (AZ) (Wang et al., 1993) (FIG 1). Taken together, these locations allow us to compare isotopic signals across a broad spatial range of the western US, which has not previously been attempted. These sites represent a range of seasonal climates as shown in Figure 2. In San Timoteo, CA, the majority of precipitation occurs during the winter months via the westerly storm track with very little precipitation during the summer months. The sites in St David, AZ and Camp Rice, NM receive the majority of their precipitation from the North American Monsoon during the summer months. They also receive moisture from the westerly storm track during the winter months, with spring being the driest time of the year. Hagerman, ID experiences relatively dry conditions throughout the year with reduced seasonality and the majority of precipitation coming from the Pacific. Finally, precipitation in Meade, KS occurs primarily in the spring and early summer months with moisture delivered from the Gulf of Mexico via the Great Plains Low Level Jet. Measured isotope values are left as δ18Ocarbonate for analysis rather than converting to δ18Oprecip, as regional temperature evolution over this time period is poorly constrained. As a result, our comparisons between paleo and modern data are

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limited to relative changes rather than absolute values. We correct for changing δ18O of seawater due to the initiation of terrestrial Northern Hemisphere glaciation. This correction involves a linear increase in δ18Osea of 0.39‰ between 3.6 and 2.4 Ma based on mean ocean records (Mudelsee and Raymo, 2005). 2.2

Modern isotopes in precipitation Weekly precipitation samples collected as part of the National Atmospheric

Deposition Network were analyzed for δ18O and δD values as part of the United States Network for Isotopes in Precipitation (USNIP) (Welker, 2012; Welker, 2000). We use this dataset in our analysis as it represents over 10,000 samples of weekly precipitation collected from 77 sites across the US between 1989 and 1995 (Welker, 2012). We binned these samples into El Niño and Neutral Phases based the Southern Oscillation Index.

We then subdivided these phases into JFM (winter), AMJ (spring), JAS

(summer), and OND (autumn) seasons. Seasonal average δ18O was calculated for each site using precipitation amount-weighted averages of raw weekly isotopic values. The El Niño isotopic anomalies given in this paper are the difference between El Niño and Neutral seasonal averages at each site (Dδ18O). Finally, we used a twelve-point spherical kriging interpolation in ArcGIS to generate seasonal maps of precipitation

δ18O anomalies.

3. RESULTS 3.1 Pedogenic carbonates Oxygen isotopic records are presented in FIG 3a-e. These records show two contrasting trends that are dependent upon geographic location. First, in the southwest

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US we observe a decrease in δ18O of carbonate through the late Pliocene followed by an increase through the early Pleistocene. For example, in the section located at St David, AZ, δ18O decreases by 3‰ through the late Pliocene, then increases by 2‰ through the early Pleistocene. Similarly, δ18O decreases by 4‰ through the late Pliocene in sections at San Timoteo, CA, and increases by 3‰ through the early Pleistocene in Camp Rice, NM. In contrast, δ18O values in the Great Plains and Northwest Interior increase through the late Pliocene and decrease through the early Pliocene. The δ18O values of pedogenic carbonates from Meade, KS, increase by 2‰ through the late Pliocene, then decrease by 2‰ through the early Pleistocene. Three δ18O values of carbonate from this section are excluded at ~2.4 Ma, as these values are anomalously high (by 6-9‰) and clearly represent extensive evaporative enrichment that mask changes in precipitation (Fox and Koch, 2003). Finally, though temporal coverage is relatively poor, δ18O values in Hagerman, ID increase by as much as 4‰ across the late Pliocene and decrease by ~1‰ across the early Pleistocene. One feature that is consistent between all of the locations that span both the late Pliocene and early Pleistocene is a characteristic ‘V’ shape with a local min/max within estimated dating errors of the Pliocene-Pleistocene boundary. Consequently, carbonate δ18O values in the mid-Pleistocene (ca. 1 Ma) approach mid-Pliocene (ca. 4.0 Ma) values in these sections regardless of the direction of change. Isotopic trends in the San Timoteo, CA and Camp Rice, NM sections also reverse initially around the Plio-Pleistocene boundary. The structure of the isotope records and the fact that the direction of changes is

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regionally dependent strongly suggests that oxygen isotope signals are primarily affected by atmospheric circulation changes rather than changes in temperature or local rainfall amount. Regional temperature evolution through this time period is not well-constrained, though global reconstructions show temperature decreased across the late Pliocene on the order of 1.1 – 1.6 ºC (see Pagani et al., 2010). The temperature effects on δ18Ocalcite values are approximately 0.35 per mil / °C, based on the combined relationships between temperature of precipitation and its oxygen isotope composition (Rozanski et al., 1993) and the equilibrium isotopic fractionation between carbonate and water (Kim and O’Neil, 1997). Assuming a liberal 2º C of cooling across the late Pliocene, this should translate into a decrease in δ18O values of ~0.7‰ at all sites, which if present, is masked under the larger observed signals. Additionally, terrestrial proxy-based climatic reconstructions show similar decreases/increases in rainfall amount at or in the vicinity of all isotope localities through the Pliocene/Pleistocene (Fig 1; Thompson, 1991). While there is likely spatial heterogeneity in the magnitude of these changes, we would expect to observe increasing/decreasing δ18O through the Pliocene/Pleistocene at all locations based on the local ‘amount effect.’ As we do not observe this, we eliminate local rainfall amount as a dominant driver of isotopic change across this time interval. In addition, we do not believe these records are responding to changes in orography (see APPENDIX A for full discussion). 3.2 Modern isotopes in precipitation Modern seasonal precipitation δ18O anomalies during El Niño years as compared to Neutral years from 1989-1995 are shown in Figure 4 (Welker, 2012). During the

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fall months (OND), negative δ18O anomalies occur primarily in the Southwest and Great Plains, and are on the order of -4‰ to -3‰. During El Niño winters (JFM), negative anomalies on the order of -3‰ to -2‰ occur over the West coast and around the Great Lakes. Large positive anomalies on the order of 3-6‰ characterize the Southwest, while small negative anomalies occur over the eastern US in the Spring (AMJ).

Anomalies are minimal during the summer (JAS) with small positive

anomalies over southern Idaho/northern Utah and small negative anomalies over North Dakota.

It is important to note that for specific regions, isotopic anomalies are

seasonally distinct. For example, the Southwest experiences large negative anomalies in the fall and large positive anomalies in the spring. The fact that the largest anomalies are located in the Southwest is consistent with the region’s sensitivity to changes in the position of the Pacific jet as shown in the modern climate (Ropelewski and Halpert, 1986) and in the past via forcing from the North Atlantic (Wagner et al., 2010; Asmerom et al, 2010).

There are small

correlations between site elevation and δ18O anomalies in the spring and fall (r2 = 0.16 and 0.24, respectively), as the largest anomalies occur in the high-elevation Southwest. However, we believe this is due to the region’s sensitivity to ENSO rather than elevation itself. While we incorporate over 10,000 separate weekly measurements of isotopes in precipitation in our analysis of modern ENSO signals, the time interval of observations is only 6 years and does not include large El Niño events such as took place in 1997-8. In order to validate these observed signals as robust features of ENSO teleconnections, we compared observations to reanalysis-driven isotope-

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tracking model data from 1950-2003 and found modeled ENSO signals over the past half-century largely match those observed from 1989-1995 (see APPENDIX A for full discussion).

4. DISCUSSION 4.1 Seasonality of carbonate formation In order to compare modern observations of isotopes in precipitation with isotopes of pedogenic carbonates, we must consider seasonal biases of pedogenic carbonates at each locality, as modern soil carbonates have been shown to form during discreet seasonal intervals that are regionally distinct (Breecker et al., 2009; Stevenson et al., 2010; Peters et al., 2013). Accounting for the seasonal bias in the soil carbonate records presented is of particular importance considering regional δ18O anomalies in El Niño precipitation are seasonally dependent. Pedogenic carbonate formation occurs as soils dry, both through the associated decrease in soil pCO2 as microbial respiration rates slow and as carbonate becomes increasingly saturated in soil water through evapotranspiration, following the wet season and peak primary productivity (Breecker et al., 2009; Peters et al., 2013; McFadden and Tinsley, 1985; McFadden et al., 1991; Retallack, 2005). Evidence for carbonate formation during times of drying of soils is supported by depth profiles of oxygen isotopes in soils. Typical soil profiles show increasing d18Ocarbonate values near the soil surface (Quade et al., 1989; Liu et al., 1996), an effect caused by the upward wicking of soil water and downward diffusion of the isotopically heavier water as a soil dries (Barnes and Allison, 1983). We therefore assign carbonate growth to occur

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as average monthly precipitation reaches a minimum and soil moisture decreases. In the Southwest region including the San Timoteo, CA, St David, AZ, and Camp Rice, NM localities, monthly precipitation reaches a minimum and soil moisture decreases dramatically in the spring (AMJ) following the winter westerly storms (FIG 2). This observation is consistent with the empirical finding of Breecker et al. (2009) that carbonate formation in the Southwest occurs primarily in the spring. In the Great Plains including the Meade, KS locality, minimum monthly precipitation and decreasing soil moisture occurs primarily in the fall (OND) following the wet summer growth season (FIG 2). Finally in the Northwest Interior including the Hagerman, ID locality, soil moisture decreases as monthly precipitation reaches a minimum in the summer (JAS) (FIG 2). However, an empirical study of this region found that dry areas (MAP < 400mm) with weak seasonality of rainfall form carbonates in the winter as well (Stevenson et al., 2010). We then model the season of carbonate formation at Hagerman, ID as both summer and winter as two possible end-member scenarios. In this analysis, we make the assumption that Pliocene seasonality was not significantly different from the modern. While there were undoubtedly changes in precipitation in the western US during the Pliocene, a survey of Pliocene GCM studies suggest that the overall patterns of precipitation seasonality were similar to today in the regions relevant to our study. In the Southwest, models predict wetter winter conditions, while spring-summer conditions were similar to or drier than modern (Barreiro et al., 2006; Vizcaino et al., 2010; Goldner et al., 2011), resulting in a strengthened version of the modern seasonality pattern (FIG 2). In the Great Plains region, models predict increases in summer precipitation with little to no change in

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fall-winter precipitation (Barreiro et al., 2006; Haywood et al., 2007; Shukla et al., 2009; Vizcaino et al., 2010; Goldner et al., 2012), again strengthening the modern pattern of seasonality (FIG 2). In all cases, these changes may have acted to shift carbonate formation to later in the season, though the quantification of this shift is not possible. 4.2

Comparison of Pliocene and modern isotope signals A comparison of the observed Plio-Pleistocene changes in carbonate δ18O with

calculated changes in δ18O between El Niño and Neutral years (Δδ18O) at each locality based on observed seasonal El Niño anomalies and the estimated season of soil carbonate formation is shown in Figure 5. Observed Δδ18O of pedogenic carbonates across the late Pliocene matches calculated changes associated with a shift from El Niño to Neutral circulation in the modern climate at three of the four analyzed localities - Meade, KS, St David, CA, and San Timoteo, CA. The Hagerman, ID site presents a more complicated scenario, however. If carbonate δ18O is representative of winter precipitation, as it most likely is in the modern climate based on regional empirical analyses of carbonate formation in this region (Stevenson et al., 2010), then the change in δ18O at the Hagerman, ID site is consistent with the observed change from El Niño to Neutral background circulation across the late Pliocene. If carbonate

δ18O is representative of summer precipitation, potentially due to higher Pliocene mean annual precipitation, however, the observed shift does not support the transition from El Niño to Neutral circulation at the Hagerman site. These results suggest that the evolution of atmospheric circulation through the Pliocene resembled the modern transition from El Niño to Neutral phases of ENSO.

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This is consistent with both modeling studies that show El Niño-like conditions across the US forced with reconstructed tropical Pacific SST’s and with the reconstructed development of the modern EEP Cold Tongue through the late Pliocene (FIG 3f). Local environmental signals may have interacted with those of changing atmospheric circulation as well. Specifically, increases in local soil evaporation with regional aridification may have led to increasing δ18O values through the Pliocene. This signal would act to amplify the El Niño signals at the KS locality and dampen the El Niño signals at the AZ and CA localities. In addition, a potential shift of carbonate formation to earlier in the season through the Pliocene as mentioned above may have amplified El Niño signals at the CA, AZ, and KS sites: in CA and AZ with a shift towards the incorporation of isotopically lighter winter precipitation, and in Kansas through a shift towards the incorporation of isotopically heavy summer precipitation. The potential contributions of these local conditions to observed signals are speculative and cannot be quantified. 4.3

Comparison of Pliocene and Pleistocene isotope signals In addition to this line of evidence, comparisons between carbonate δ18O values

from mid-Pliocene and mid-Pleistocene paleosols also support the idea that wetterthan-modern Pliocene conditions in the western US were a product of El Niño-like circulation. The Plio-Pleistocene boundary is characterized by the initiation and rapid expansion of glaciation in the Northern Hemisphere (Zachos et al., 2001). Northern Hemisphere glaciation, independent of the longitudinal location of ice sheet growth, causes a series of atmosphere-ocean teleconnections that propagate to the tropics resulting in a south-shifted ITCZ (Intertropical Convergence Zone) in all three major

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ocean basins (Chiang and Bitz, 2005). A south-shifted ITCZ in turn creates a deeper Aleutian low and shifts the Pacific jet southwards across the western US (Trenberth et al., 1998; Chiang and Bitz, 2005), similar to El Niño circulation. Studies that reconstruct climate during periods of Northern Hemisphere glaciation caused by orbital and North Atlantic freshwater forcing in the Quaternary with both proxy data and models observe a deeper Aleutian low and subsequent southward shifted Pacific jet, which enhances moisture delivery to the Southwest (e.g.: Clark et al., 1999; Wagner et al., 2010; Asmerom et al., 2010). The fact that mid-Pliocene δ18O values are similar to mid-Pleistocene values at all sites that span this time interval suggests that atmospheric circulation in the midPliocene resembled that of the mid-Pleistocene. Specifically, the Pacific subtropical jet was displaced farther south allowing the enhanced delivery of moisture to the Southwest. In the absence of large-scale glaciation during the mid-Pliocene, the observed El Niño-like SST structure of the equatorial Pacific provides a wellunderstood mechanism that causes this circulation regime over the western US. In our proposed scenario, the ‘V’ pattern of δ18O observed in Plio-Pleistocene pedogenic carbonates represents the poleward migration of the subtropical jet with the decay of El Niño-like SSTs and development of the EEP Cold Tongue through the late Pliocene, followed by a southward redirection of the subtropical jet beginning at the Plio-Pleistocene boundary by the large-scale expansion of glaciation in the Northern Hemisphere. This scenario is consistent with the timing of previous reconstructions of the EEP Cold Tongue (Lawrence et al., 2006; FIG 3f) and Northern Hemisphere glaciation (Maslin et al., 1995; FIG 3g).

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This scenario is also consistent with

compilations of faunal-, floral-, pollen-, and sediment-based reconstructions of climate evolution, as well. Across the western US, there is a general pattern of wetter-thanmodern conditions through the Pliocene, followed by a period of increased aridity around the Pliocene-Pleistocene boundary, and finally a return to wetter-than-modern conditions by the mid-Pleistocene (Thompson, 1991; FIG 3).

5. CONCLUSIONS In summary, we have compared δ18O values from pedogenic carbonates at multiple sites across the western US through the Plio-Pleistocene with modern δ18O changes in precipitation between phases of the El Niño Southern Oscillation to test the hypothesis that reduced zonal SST gradients in the tropical Pacific resulted in El Niñolike circulation – specifically in a south-shifted Pacific jet. The isotopic signals we observe match modern differences between El Niño and Neutral phases of ENSO and are consistent with the predicted response of the Pacific jet to the development of modern zonal SST gradients through the late Pliocene in terms of direction, magnitude, and timing. In addition, convergence on mid-Pliocene δ18O values during the midPleistocene in pedogenic carbonates at localities that cover the interval suggests similar circulation conditions during these two time intervals. Circulation during the mid-Pleistocene is currently better constrained and was characterized by a deep Aleutian low and south-shifted Pacific jet, similar to El Niño circulation. Together, we see these as strong evidence that reconstructed wetter-than-modern conditions in the Pliocene western US despite warmer global temperatures, were in fact a product of the background El Niño-like temperature structure of the tropical Pacific.

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This finding is also broadly consistent with the initial results of PlioMIP ensemble data run with PRISM 3 boundary conditions, which show increased precipitation over the western US as a result of the reduced zonal temperature gradient across the tropical Pacific (Haywood et al., 2012). Future work addressing the nature of tropical Pacific teleconnections encapsulated in these ensemble data along with the use of isotope-enabled GCM’s run with PlioMIP boundary conditions will allow for an unprecedented level of data-model comparison. Finally, while idealized GCM experiments have demonstrated the dynamical effects of a background El Niño-like tropical Pacific on Pliocene climate (e.g.: Barreiro et al., 2006; Shukla et al., 2009; Brierly and Federov, 2010; Vizcaíno et al., 2010; Goldner et al., 2011), the mechanisms leading to this state are still debated (e.g.: Federov et al., 2006; Federov et al., 2010). The identification of these mechanisms and their relevance to modern climate change is of the utmost importance to freshwater resource management in the western US as well as other regions affected by atmospheric teleconnections from the tropical Pacific.

6. ACKNOWLEDGEMENTS We would like to acknowledge Dr.’s Peter Blisniuk, Rob Dunbar, and David Mucciarone for laboratory assistance and space as well as Dr.’s Rob Dunbar, Kate Maher, and Noah Diffenbaugh for useful comments and suggestions on this project. We would like to thank Walter Torres, Jeremy Caves, and Hari Mix for fieldwork and laboratory assistance. We also thank two anonymous reviewers for suggestions and edits that improved an earlier version of this paper. This research has been supported

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in part by NSF grants DBI 0923517 and AGS 0080952 awarded to J.M.W. and EAR 1019648 awarded to C.P.C.

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Remeika, P., Fischbein, I. W., and Fischbein, S. A. (1988) Lower Pliocene petrified wood from the Palm Springs Formation, Anza Borrego Desert State Park, California. Rev. Palaeobot. Palyno. 56, 183-198. Repenning, C.A. (1987) Biochronology of the microtine rodents of the United States, in: Cenozoic Mammals of North America, edited by: Woodburne, M. O., University of California Press, 236-267. Retallack, G. J. (2004) Late Miocene climate and life on land in Oregon within a context of Neogene global change. Palaeogeogr. Palaeocl. 214, 97–123. Retallack, G. J. (2005) Pedogenic carbonate proxies for amount and seasonality of precipitation in paleosols. Geology 33, 333-336. Ropelewski, C. F., and Halpert, M. S. (1986) North American precipitation and temperature patterns associated with the El Niño-Southern Oscillation (ENSO). Mon. Wea. Rev. 114, 2352-2362. Rozanski, K., Araguas-Arrguas, L., and Gonfiantini, R. (1993) Isotopic patterns in modern global precipitation, in: Climate Change in Continental Isotopic Records, edited by: Swart, P.K., Lohmann, K.C., McKenzie, J., and Savin, S., American Geophysical Union Geophysical Monograph, 78, 1-37. Sadler, J. L. and Link, P. K. (1996) The Tuana Gravel: Early Pleistocene response to longtitudinal drainage of a late-stage rift basin, western Snake River Plain. Northwest Geology 26, 46-62. Seager, R., Ting, M., Held, I., Kushnir, Y., Lu, J., Vecchi, G., Huang, H.-P., Harnik, N., Leetmaa, A., Lau, N.-C., Li, C., Velez, J., and Naik, N. (2007) Model

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8. FIGURES FIGURE 1. Modern El Niño precipitation anomalies, isotope localities, and reconstructed Pliocene conditions. Anomalous annual El Niño precipitation calculated with CMAP precipitation data from 1979– 2008; CMAP precipitation data provided by the NOAA/OAR/ESRL PSD, Boulder, CO, USA, from their website at http://www.esrl.noaa.gov/psd/. Purple stars show isotope record localities used in this study. Blue circles represent reconstructions of wetter-than-modern Pliocene conditions, and red circles represent reconstructions of drier-than-modern Pliocene conditions.

El Niño Annual Precipitation Anomaly

6! 8!

7! 11! 10! 3! 6!

9! 6!

12! 13! 14! 1! 15!

18!

21! 20!

4!

16! 17! 2!

5! 19! 21! 20!

cm/year -8

-4

0

4

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8

Isotope ! Locality!

Pliocene! Wet!

Pliocene! Dry!

Pliocene! Same!

1.  This Study 2.  Wang et al., 1993 3.  This Study 4.  Fox and Koch, 2003 5.  Mack et al., 1994 6.  Wolfe, 1990 7.  Retallack, 2004 8.  Cheney, 1938 9.  Adam et al., 1990 10.  Thompson, 1991 11.  Smith, 1987 12.  Forester and Bradbury, 1981 13.  Hay et al., 1986 14.  Smith, 1984 15.  Remeika et al., 1988 16.  Nations et al., 1981 17.  Gray, 1961 18.  Hager, 1974 19.  Repenning, 1987 20.  Litwin and Andrle, 1992 21.  Willard, 1993

FIGURE 2. Average monthly precipitation rates (right) and soil moisture (left) at each site. Precipitation data calculated from CMAP 1979– 2000 (ref. in Fig. 1) and soil moisture calculated from NOAA Climate Prediction Center 1971–2000 (van den Dool et al., 2003) at each of the isotope localities.

0.6

0.8

Time

1.2 0.0

0.2

0.4

0.6

Time

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100 200 250 270 290100 140 180110 130 150120 160

Meade HagermanCamp.Rice St.David Timoteo

200 100 160 150 120 130 180 110 140 250 270 290100

1.0

Ja n Fe b Ma r Ap r Ma y Ju n Ju l Au g Se p Oc t No v De c

0.2 0.2 1.5 1.5 1.5 1.5 0.5 0.5 0.5 1.5 0.5 0.5 1.5 2.5 2.5 0.4 0.60.8 1.0 1.20.5

Meade HagermanCamp.Rice St.David Timoteo 0.4

0.8

1.0

1.2

Soil Moisture (mm)

0.2

290 270 250

0.0

120

Meade KS

160

Hagerman ID

140 120

Camp Rice NM

140

St David AZ

100 180

San Timoteo CA

Ja n Fe b Ma r Ap r Ma y Ju n Ju l Au g Se p Oc t No v De c

0.8 0.8

1.4

1.4

s 200

Meade Hagerman Camp.Rice St.David Timoteo Precipitation Rate (mm/day)

p

0.0

0.2

-6 -10 -9 -8 -7 -6 -5 -4 -6 -7 -7

2.5

3.5

4.0

3.0

3.5

4.0

3.0

3.5

4.0

3.0

3.5

4.0

3.0

3.5

4.0

3.0

3.5

4.0

-8 -8 -9 -9

4 4

b 2.0

2.5

3

1.5

0 -15-14.50

1

2 2

az[, 2]

1.0

1.5

2.0

d 1.0

1.5

2.0

-9 -9 -10 21 22 23 24 25 26 27-10 300 300

2.5 id[, 2]

e f 1.0

1.5

2.0

2.5 ks[, 2]

g1.0

1.5

2.0

200 -6 200 0 -8 100 100 -90 -7

2.5 nm[, 2]

-8 -8

-7 -7

c

2.5 eep[, 3]

WET

DRY

1.0

1.5

2.0

2.5

3.0

1.0

1.5

2.0 mag[, 2.51] 3.0

WET 3.5

4.0

3.5

4.0

Age az[,(Ma) 2]

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North Pacific EEP ODP Site 846 ODP Site 882

3.0

ca[, 2]

1.0

-17.5 -17 -16.0 -16

δ18O ca[, 3] (‰ VPDB) δ18O az[, 3] (‰ VPDB) δ18O 3] (‰ nm[, VPDB) δ18O id[, 3] (‰ VPDB)

2.0

Meade Kansas

Δδ18O ks[, 3] (‰)

1.5

Camp Rice Hagerman Idaho New Mexico

SST eep[, (°C)2]

1.0

St David Arizona

Magnetic Susceptibility 2] az[, mag[, 3] (Ice-rafted Debris)

San Timoteo California

a

FIGURE 3. Isotope stratigraphies from (a) San Timoteo, CA, (b) St David, AZ (Wang et al., 1993), (c) Camp Rice, NM (Mack et al., 1994), (d) Hagerman, ID, and (e) Meade, KS (Fox and Koch, 2003). Open circles in (a–d) represent individual samples, filled circles binned averages, and error bars bin ranges. Camp Rice, NM, values normalized to sub-locality minimum values, and circles, triangles, squares represent sublocalities Hatch Siphon, Rincon Arroyo, Lucero Arroyo, respectively. (f) Reconstructed SSTs in the east equatorial Pacific ODP Site 846 show development of the modern cold tongue (Lawrence et al., 2006). (g) Magnetic susceptibility at ODP Site 882 in the North Pacific shows ice-rafted debris and expansion of NH glaciation through the Pleistocene (Maslin et al., 1995). Climatic conditions (wet/dry) in the western US are shown at the bottom and in blue and red background based on compilation of proxy-based reconstructions (Thompson, 1991).

FIGURE 4. Modern seasonal El Niño isotope anomalies. Black circles represent USNIP station sites. Figure modified from Welker (2012).

JFM

AMJ

JAS

OND

-3 -2 -1 0 1 2 3 4 5 δ18O (‰ VSMOW)

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FIGURE 5. Comparison of observed Pliocene Δδ18O with modern El Niño Δδ18O anomalies. Error bars in observed Δδ18O values show 95% confidence intervals in differences between relevant sample bins. Error bars in modern El Niño anomalies show 95% confidence intervals from calculated kriging prediction errors. Numbered stars correspond to labeling in Fig. 1. 4#

2#2#

2#

0#0#

0#

!2# !2#

!4# !4#

Δδ18O (‰)

4#4#

4#

4#

St David 2# AZ

2#

0#

0#

!2#

!2#

1!

2!

San Timoteo CA AMJ

AMJ

!2# !4#

!6# !6#

!6#

!8# !8#

!8# Observed

Δδ18O

OND

JFM JAS

4!

Meade KS

3!

!4#

!4#

!6#

Hagerman ID !6#

!8# !8# (4.0 – 2.65 Ma)

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Modern Δδ18O

CHAPTER 2 Quantifying the isotopic ‘continental effect’ Matthew J. Winnick1, C. Page Chamberlain1, Jeremy K. Caves1, Jeffrey M. Welker2 1

Department of Environmental Earth System Science, Stanford University, Stanford, CA 94305, USA 2

Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK, USA

Reproduced with permission from Winnick, M.J., Chamberlain, C.P., Caves, J.K., and Welker, J.M., Earth and Planetary Science Letters. Copyright 2014, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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ABSTRACT Since the establishment of the IAEA-WMO precipitation-monitoring network in 1961, it has been observed that isotope ratios in precipitation (δ2H and δ18O) generally decrease from coastal to inland locations, an observation described as the ‘continental effect.’ While discussed frequently in the literature, there have been few attempts to quantify the variables controlling this effect despite the fact that isotopic gradients over continents can vary by orders of magnitude. In a number of studies, traditional Rayleigh fractionation has proven inadequate in describing the global variability of isotopic gradients due to its simplified treatment of moisture transport and its lack of moisture recycling processes. In this study, we use a one-dimensional idealized model of water vapor transport along a storm track to investigate the dominant variables controlling isotopic gradients in precipitation across terrestrial environments. We find that the sensitivity of these gradients to progressive rainout is controlled by a combination of the amount of evapotranspiration and the ratio of transport by advection to transport by eddy diffusion, with these variables becoming increasingly important with decreasing length scales of specific humidity.

A

comparison of modeled gradients with global precipitation isotope data indicates that these variables can account for the majority of variability in observed isotopic gradients between coastal and inland locations. Furthermore, the dependence of the ‘continental effect’ on moisture recycling allows for the quantification of evapotranspiration fluxes from measured isotopic gradients, with implications for both paleoclimate reconstructions and large-scale monitoring efforts in the context of global warming and a changing hydrologic cycle.

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1. INTRODUCTION Oxygen isotopes in precipitation as recorded in authigenic minerals and biological archives are one of the most ubiquitous terrestrial paleoclimate tools. While the majority of studies utilizing these proxies attempt to reconstruct changes in climate using the evolution of δ18O or δD from a single location, an increasing number of studies have begun to look at changes through time across broader spatial scales as more and more records have become available (e.g. McDermott et al., 2011; Mix et al., 2011; Winnick et al., 2013; Liu et al., 2014; Caves et al., 2014). Specifically, the use of multiple locations allows for the analysis of changes in terrestrial isotopic gradients through time. This holds a distinct advantage over singlelocation studies: it allows for the elimination of upstream and source signals, which can dominate δ18O records (Lachniet, 2009; McDermott et al., 2011; Pausata et al., 2011). These terrestrial isotopic gradients have been used to assess a number of largescale climatic changes including latitudinal temperature gradients during the Eocene hothouse climate (Fricke and Wing, 2004; Speelman et al., 2010), the expansion of grassland ecosystems during the Mio-Pliocene (Mix et al., 2013), and the uplift of mountain belts (Mulch et al., 2006; Mix et al., 2011; Fan et al., 2014; Caves et al., in press). However, while many of these studies calculate inferred changes in specific environmental variables, there exists no generalized mechanistic framework to quantify hydrologic change from terrestrial isotopic gradients in precipitation. Herein, we seek to describe the modern controls on isotopic gradients in precipitation to better

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facilitate the quantification of changes in the hydrological cycle in the past and into the future. Studies of isotopic gradients are underpinned by the observation that isotopes in precipitation decrease with increasing distance from the ocean, generally referred to as the ‘continental effect’ (Dansgaard, 1964; Rozanski et al., 1993). A number of studies have looked at modern spatial isotopic gradients across continents in order to understand the main controlling factors (Ingraham and Taylor, 1991; Rozanski et al., 1993; Vachon et al 2010; Liu et al. 2010, 2013). These studies have shown a large range of values for the ‘continental effect’ spanning at least an order of magnitude across different geographies, as well as seasonally varying values within a specific region.

For example, average δ18O isotopic gradients have been measured as

2000 ppm (Beerling and Royer, 2011) and global temperatures 10-15° C hotter than modern (Zachos et al., 2001; Huber and Caballero, 2011). As such, the Early Eocene may represent an Earth system analogue for an equilibrium climate response to projected anthropogenic forcing over the next several centuries. Global warming in the Eocene was pronounced in the high latitudes, as indicated by

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the presence of Arctic crocodiles and palm trees, reconstructed polar temperatures 2040° C warmer than present, and evidence of largely ice-free poles (Greenwood and Wing, 1995; Markwick, 1994; Sluijs et al., 2009). As a result, meridional temperature gradients were reduced relative to today (Wolfe, 1995; Greenwood and Wing, 1995). This reduced temperature gradient was likely associated with dynamic changes in global hydrology and atmospheric latent heat transport. Reconstructed isotope ratios of hydrogen and oxygen (δD and δ18O) in precipitation are controlled by large-scale features of the hydrologic cycle and represent powerful tools for probing the dynamics of atmospheric latent heat transport in past climates. As such, they have been used extensively in Early Eocene climate reconstructions. For example, shallow latitudinal gradients of isotopes in precipitation along with high δD values recorded in high-latitude leaf waxes have been presented as evidence of an intensified hydrologic cycle with less mid-latitude rainout, potentially due to the reduced latitudinal temperature gradient and the poleward migration of midlatitude storm tracks (Fricke and Wing, 2004; Pagani et al., 2006). Reconstructions of

δ18Op have also been coupled to local temperature reconstructions to demonstrate the existence of a weaker spatial δ18O-temperature (δ18O-T) relationship in the Eocene relative to modern (Fricke and Wing, 2004; Secord et al., 2010; Zanazzi et al., 2015). These empirically-derived Eocene spatial δ18O-T relationships have further been used to directly estimate local temperature changes from δ18O records across major climatic perturbations within the Early Eocene, such as the Paleocene-Eocene Thermal Maximum (PETM) (Koch et al., 2003; Secord et al., 2010); however, studies of modern and Pleistocene climate have shown that large-scale spatial δ18O-T

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relationships may not be suitable for estimating local temperature changes through time (Rozanski et al., 1993; Lee et al., 2008). Despite their widespread use, relatively little work has been aimed at characterizing global variability in δD and δ18O under hothouse conditions from a geophysical perspective, with the exception of a single isotope-enabled general circulation model (GCM) experiment demonstrating that implementation of Eocene boundary conditions matches large-scale reconstructed patterns of isotopes in precipitation (Speelman et al., 2010). Here, we analyze the physical mechanisms driving global patterns of isotopes in precipitation during the Early Eocene using the isotope-enabled reactive transport model of Hendricks et al. (2000) driven by GCM and Reanalysis gridded climate data. Our motivation is to improve understanding of the physical drivers of isotope variability in hothouse climates and to further develop the framework for interpreting characteristics of the global hydrologic cycle from reconstructed isotopes in precipitation. Additionally, we develop a novel statistical Monte Carlo routine to simulate zonal variability in δ18O. The model of Hendricks et al. (2000) provides distinct advantages over isotope-enabled GCMs as it is (1) fast and inexpensive to run; (2) allows for a statistical treatment and detailed sensitivity analysis of transport type, changing temperature gradients, initial values, and other parameters; and (3) provides direct insight into the physics that drive observed δ18O and δD signals.

2. METHODS 2.1 Isotope model

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To investigate meridional profiles of isotopes in precipitation, we use the reactive transport model of Hendricks et al. (2000) based on the mixing ratio of water vapor in the atmosphere,

dw = ∇ [ K∇w ] − v∇w + E − P dt

(1),

where w is specific humidity, K is the coefficient of eddy diffusion, v is advection velocity, E is surface evaporation, and P is precipitation. We use zonally-averaged analytical solutions for steady-state advection- and eddy-only cases of Eq. 1, solving for the ratio of water vapor H218O/H216O expressed in delta notation as,

⎡ ⎛ θ⎞⎤ δ a = (δ ao − δ a∞ ) exp ⎢(α + α N d − 1) ⎜ − ⎟ ⎥ + δ a∞ (2) (advection-only), and ⎝ ⎠⎦ ⎣ ⎡ ⎛ θ⎞⎤ δ a = (δ ao − δ a∞ ) exp ⎢ α + α N d − 1 ⎜ − ⎟ ⎥ + δ a∞ (3) (eddy-only), where ⎝ ⎠⎦ ⎣

(

δ a∞ =

N dδ e − (1+ N d )(α − 1)10 3 α + α Nd − 1

)

(4),

(see Hendricks et al. (2000) for full derivation). Here, δa is the δ18O of water vapor, δ0a is the initial δ18O of water vapor, and δ∞a is the δ18O of water vapor as latitudinal distance (θ) goes to infinity. Equations 2, 3, and 4 are expressed in terms of the length scale of specific humidity that describes the latitudinal distance over which specific humidity goes to zero,

 = −w

dθ dw

(5),

and a non-dimensional Damköhler number that describes the degree of system closure, Nd =

E (6). P−E

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A full description of model variables is shown in Table S1. We force the isotope model with annually-averaged climate data for three separate scenarios representing (1) modern climate; (2) Eocene climate with atmospheric pCO2 of 2240 ppm; and (3) Eocene climate with atmospheric pCO2 of 4480 ppm. Variables for the modern scenario are from NCEP-DOE Reanalysis II data from 1979-2013 (Kanamitsu et al., 2002), and variables for both Eocene scenarios are from the CCSM3 experiments of Huber and Caballero (2011). Surface temperature (equilibrium fractionation during evaporation), surface relative humidity (kinetic fractionation during evaporation), temperature at 850 mb (equilibrium fractionation during precipitation), precipitation rate (Nd), evaporation rate (Nd), and column-integrated precipitable water (ℓ) are used to force the model (see APPENDIX C for details). The model is run from 25-90º N and S as model assumptions of poleward atmospheric moisture transport are violated in the tropics. We use a Monte Carlo routine to create 104 simulations for each analytical solution across the range of zonal variability for each input variable. As the model breaks down when precipitable water increases during poleward transport, we set the condition that when precipitable water increases, δa is calculated as the amount-weighted mean of δa at the previous latitude and δa of a simulation using zonally-averaged input parameters at the current latitude. Physically, this assumes that when precipitable water increases with latitude (e.g. when moving from a terrestrial to oceanic grid-cell), atmospheric moisture from a dry area is mixing with ambient, zonally-averaged moisture. Additionally, sublimation-driven recharge over modern Antarctica is assumed to involve no fractionation (Hendricks et al., 2000). We note that while any given

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simulation is not meant to be a realistic representation of water vapor transport as no condition is set to limit the zonal transport at each latitudinal step, this statistical treatment provides important insights into the range of zonal variability. Initial δ18Op at 25º N/S is set to -5.2 ± 2.6‰ (1σ) with a Gaussian distribution based on the modern tropical range (Aggarwal et al., 2007). Effects of changing this initial value are largest in the subtropics and are attenuated at higher latitudes due to the approach of meridional δa profiles to δ∞a with progressive rainout, which is unaffected by the initial value. 2.2 Data Modern precipitation isotope data is taken from the Global Network for Isotopes in Precipitation (Aggarwal et al., 2007), a compilation of Antarctic surface snow (Masson-Delmotte et al., 2008), and a survey of recent snow and ice accumulation in Northern Greenland (Fischer et al., 1998). GNIP data represents annual amount-weighted averages for stations with at least 3 years of data collection. For Eocene precipitation isotope data, we compile previously published proxy data representing >650 measurements from 15 different studies (Table S2) spanning the Early Eocene (49 to 57 Ma). The compilation includes data from lacustrine and pedogenic carbonate, hydrated smectite, biogenic phosphate from fossil teeth, and terrestrial organic matter n-alkanes. Where only proxy δD data is available, values are converted to δ18O assuming the modern meteoric water line. Where not calculated explicitly in the original publication, δ18Op is calculated assuming equilibrium fractionation using a temperature estimate from a proximal site or 25º C, as designated in Table S2.

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3. RESULTS 3.1 Modern data-model The modern data-model comparison is shown in Figure 1a. Modern observational data, as described in many previous studies, shows distinct latitudinal patterns. Between 0 and 45º N/S, δ18Op varies between -18 and 7.3‰ with a mean of 5.2 ± 2.6 (1σ) and no systematic latitudinal gradient. Anomalously low values of both observational data and Monte Carlo simulations within this latitudinal band represent high altitude terrestrial sites including the Himalayas, northern Andes, and southern North American Cordillera. The lack of correlation of δ18O with latitude, and by extension temperature (Rozanski et al., 1993), is the result of high Nd within this region where evaporative recharge overwhelms isotopic depletion by precipitation (Fig 3d) (Hendricks et al., 2000). Poleward of 45°, δ18Op decreases systematically with latitude due to progressive rainout as moderated by evaporative recharge and transport type (Dansgaard, 1964; Rozanski et al., 1993; Hendricks et al., 2000). Model δ18Op latitudinal profiles assuming eddy-only and advection-only transport simulate systematic decreases in mean δ18Op with latitude, as shown by simulations of zonally-averaged variables (Fig 1a). Eddy-only transport results in a significantly shallower latitudinal gradient than advection-only transport due to the associated atmospheric mixing (Eriksson, 1965; Hendricks et al., 2000), with differences of 5‰ and 18‰ at the North and South poles, respectively. The 5-95% percentile range of Monte Carlo simulations is shown by the gray shaded area in Figure 1a. These simulations reproduce the general patterns of latitudinal isotope

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variation along with the broad range of zonal variability. In particular, the model reproduces the anomalously low values of high altitude terrestrial environments in the mid-latitudes and of Antarctic and Greenland precipitation. However in both hemispheres, some of the observational data falls above the predicted range of variability between ~40-55º N/S. This results from the fact that, following the methods of Hendricks et al. (2000), we initialize the model within the evaporation-dominated latitudinal zone that extends to ~45º. When zonal evaporation exceeds zonal precipitation and specific humidity decreases due to decreasing temperature, the assumption of flow direction is violated, which in this case causes an unrealistic trend of isotopic depletion. If instead the model is initialized at the first latitude where zonal precipitation exceeds zonal evaporation, the model is able to capture these high mid-latitude values (Figure S1). We show this slightly unrealistic scenario in the main text as it accurately represents the lower bounds of δ18O variability in the lower latitudes and because high latitude values are unaffected by the initialization point due to the approach to δ∞a with systematic rainout. Alternatively, one could represent the range of tropical and subtropical variability using the δ18O value of locally-sourced initial rainout of an air parcel as an upper bound and the 5percentile Monte Carlo simulations as a lower bound. 3.2 Eocene data-model Proxy δ18O data from the Early Eocene is located solely in the Northern Hemisphere between modern-day latitudes of roughly 28-90º N (Fig 1b). In the subtropics and midlatitudes, proxy δ18O values fall within modern zonal variability and at the higher latitude sites emerge above the range of modern zonal variability.

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Local comparisons of Eocene proxy δ18O with modern annual values calculated using a detrended interpolation scheme (Bowen and Revenaugh, 2003; Bowen, 2008) show systematic isotopic enrichment in the Eocene relative to today with the exception of 1 locality, with anomalies ranging from -0.35 to 11.73‰ (Fig 2; Table S2). With a reduction in the δ18O latitudinal gradient, we would expect to observe a latitudinal trend in Eocene anomalies with the highest anomalies occurring at the highest latitudes; however, any existing trend is complicated by the post-Early Eocene uplift of the North American Cordillera which likely amplified the offset between Eocene and modern δ18O at many of the terrestrial proxy localities (Mix et al., 2011; Chamberlain et al., 2012) (Fig 2). Excluding these data, there appears to be a tentative trend with latitude. Simulated δ18O profiles display reduced latitudinal gradients with large increases in polar δ18O relative to the modern, matching the limited proxy data. The reduction in the isotope gradient is particularly pronounced in the Southern Hemisphere where δ18O is 32‰ and 46‰ greater than modern in the eddy-only and advection-only cases, respectively, although there is no existing proxy data in the Southern Hemisphere with which to compare. Additionally, all of the δ18O proxy data falls within the range of our Monte Carlo simulations in the Northern Hemisphere. However, we note that as in modern simulations, initialization of the model at 25º N/S may result in the underestimation of upper level bounds of δ18O in the mid-latitudes. The fact that our Monte Carlo simulations encapsulate low δ18O proxy values from parts of the Himalaya and North American Cordillera also provides independent validation of the large-scale topographical boundary conditions used in the Huber and

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Caballero (2011) GCM experiments. Similar to the modern climate, eddy-only transport results in a shallower δ18O gradient relative to advection-only transport, with a difference of ~6‰ at the poles. Our Monte Carlo simulations also match the general characteristics of isotope-enabled GCM Eocene δ18O profiles both in terms of mean profiles and zonal variability (Speelman et al., 2010, their Fig 5c). 3.3 Eocene simulation comparison A comparison of δ18O latitudinal profiles between the Eocene 2240 and 4480 ppm simulations is shown in Figure 1b. These two simulations are nearly identical in both the Northern and Southern Hemispheres both in terms of zonal-mean profiles for eddy- and advection-only scenarios as well as in the Monte Carlo range of values. Offsets between zonal-mean simulations in the two scenarios are less than 1‰ at the poles in all cases. As these latitudinal profiles are essentially identical, the 2240 ppm simulation also encapsulates the full range of δ18O proxy data, and these boundary conditions are therefore indistinguishable from the proxy record perspective, as will be discussed in further detail below.

4. DISCUSSION 4.1 Early Eocene δ 18O gradients Reduced latitudinal gradients of δ18Op in the Early Eocene simulations result primarily from a reduced temperature gradient through its effect on length scales of specific humidity (Fig 3a,b,c). Physically, this represents a lesser degree of rainout, and results from the formulation of the specific humidity length scale, which is equivalent to the derivative of the natural log of specific humidity (Eq 5). While the

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exponential increase in saturation vapor pressure with temperature causes specific humidity gradients to increase given some uniform temperature change, the length scale will remain relatively constant (Fig 3b,c). However, in the Early Eocene, greater temperature increases at the higher latitudes result in increased length scales of specific humidity (Fig 3c). This is particularly evident in the Southern Hemisphere (Fig. 3a) where polar amplification is most pronounced due to the complete collapse of the Antarctic Ice Sheet and the associated decrease in albedo. Length scales in the tropics and subtropics, however, are relatively unchanged in the Early Eocene simulations. Early Eocene GCM results also show changes in the spatial structure of evaporation and precipitation balance. Globally, E must equal P, but the spatial distribution of this balance can affect isotopic gradients through the Damköhler number. The most significant differences between the Early Eocene and modern Damköhler numbers occur in the Northern Hemisphere with the poleward expansion of the evaporation-dominated zone and a shift to a greater proportion of P relative to E from 50-80º N in the Early Eocene (Fig 3d). These effects offset each other, with the northward expansion of the evaporation-dominated zone increasing the latitudinal influence of isotopically heavy tropical moisture, and the increased proportion of P at the higher latitudes allowing for less evaporative recharge during latitudinal rainout. Additionally, a number of modeling studies have shown that the relative contribution of transient eddies to global meridional moisture transport increases with global temperature up to ~15º C higher than modern (Schneider et al., 2010; Caballero and Hanley, 2012). Theoretically, this would also contribute to a reduced latitudinal

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isotope gradient in the Early Eocene. Our simulations of zonally averaged Eocene and modern climates suggest that this effect may contribute a maximum additional 5‰ increase to high latitude δ18O assuming the transition from advection-only transport in the modern to eddy-only transport in the Eocene (Fig 2). Mean values of the two northern-most proxy localities hint at this increased role of transient eddies in the Early Eocene (Fig 2); however, additional proxy-based reconstructions are needed in the high latitudes to establish this with statistical confidence. As noted previously, δ18O-T relationships in the Early Eocene are different from modern both in terms of a weaker correlation and a lower value of δ18Op for a given temperature (Fricke and Wing, 2004; Speelman et al., 2010). Our modeling supports the hypothesis that lower δ18Op values for a given temperature result from minimal changes in δ18Oa of water exiting the subtropical evaporation-dominated zone (Fricke and Wing, 2004). We observe this characteristic even while neglecting postcondensation exchange associated with convective precipitation, which suggests that increases in Eocene high-latitude convection do not play a governing role in lower

δ18O for a given temperature as suggested by Speelman et al. (2010). Finally, due to the relative insensitivity of δ18Op equator-ward of the evaporation-dominated zone, reconstructed δ18O gradients cannot be used to distinguish between scenarios of tropical and subtropical warming or the existence of a ‘tropical thermostat’ (Pierrehumbert, 1995). 4.2 Insensitivity of δ 18O to temperature in hothouse climates As shown in Figure 1b, meridional profiles of precipitation isotopes between Eocene simulations with pCO2 of 2240 and 4480 ppm are nearly identical in the

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Northern and Southern Hemispheres. While global temperatures increase by ~5º C between these simulations, this warming is relatively uniform with only a small degree of polar amplification (Fig 3a). Due to the relative lack of polar amplification, latitudinal profiles of specific humidity closely match the exponential ClausiusClapeyron scaling of a theoretically imposed uniform 4.7º C temperature increase (Fig 3b). This exponential increase in specific humidity has little effect on the length scale term (Eq. 5, Fig 3c), as discussed above. Additionally, the balance of evaporation and precipitation undergoes little change as shown by Nd profiles (Fig 3d), despite the fact that absolute values of precipitation and evaporation rates increase in the 4480 ppm simulation. While the increase in temperature does affect equilibrium fractionation coefficients, these changes occur both during precipitation and evaporation and are largely offsetting. The comparison of these two simulations suggests that in the absence of significant polar amplification, δ18Op is insensitive to changes in global temperature. Whether or not this decoupling occurs immediately in the absence of large-scale terrestrial and sea ice — and the subsequent reduction in ice-albedo feedback strength — is a question that warrants further investigation. In either case, our modeling suggests that temporal relationships between δ18O and temperature in hothouse climates are extremely weak despite the persistence of spatial δ18O-T relationships that result from latitudinal rainout. This does not, however, preclude indirect controls of global temperature on local terrestrial δ18O as a result of differential regional warming, changes in circulation, and changes in terrestrial moisture recycling (Winnick et al., 2014). Additionally, the results of this sensitivity analysis along with the fact that

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proxy δ18Op falls within modeled variability suggests that GCMs are able to accurately simulate Early Eocene latitudinal temperature gradients poleward of 45º N, and that reconstructed latitudinal δ18O cannot be used to distinguish between radiative forcing scenarios. 4.3 Implications for δ D signals of Early Eocene Hyperthermals Recently, a number of high-resolution terrestrial organic n-alkane records across hyperthermal events during the Early Eocene (PETM and Eocene Thermal Maximum 2) have indicated pronounced decreases in δD during peak warming, with negative δD anomalies increasing with latitude (Pagani et al., 2006; Smith et al., 2007; Tipple et al., 2011; Krishnan et al., 2014; Krishnan et al., 2015). These hyperthermal events involved large pulses of carbon to the atmosphere-ocean reservoir and global warming on the order of 5-8 K over a geologically short timescale (103-104 yrs) (Zachos et al., 2003). Observations of local δD minimums during peak warming are counterintuitive, as spatial and temporal empirical δD-T relationships in the mid- and high latitudes are generally positive (Rozanski et al., 1993). Krishnan et al. (2014) present several hypotheses for the cause of these signals including changes in high latitude storminess, local vegetative change, and changes in δD of exported tropical water vapor. However, none of these are adequately able to describe the global nature of this signal or its latitudinal structure, with the magnitude of negative anomalies increasing with latitude. Additionally, Rayleigh distillation requires an increase in meridional temperature gradients to reproduce increased δD gradients, contrary to sea surface temperature reconstructions and GCM simulations of global warming (Krishnan et al., 2015).

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We suggest instead that these signals are recording changes in the dynamics of global latent heat transport. Idealized GCM experiments have shown that the midlatitude transient eddies that dominate latent heat transport to the high latitudes exhibit non-monotonic behavior with increasing global temperatures (Caballero and Langen, 2005; O’Gorman and Schneider, 2008; Schneider et al., 2010; Caballero and Hanley, 2012). Across a number of different simulations, latent heat flux by transient eddies increases with global temperatures up to ~15º C warmer than modern, after which they plateau and/or decrease. This is caused by decreases in eddy velocity and contracting mixing lengths that eventually overcome exponential increases in saturation vapor pressure (Caballero and Hanley, 2012). A decrease in the strength of mid-latitude transient eddies results in increased meridional isotope gradients with the transition from eddy-dominated flow towards advection-dominated flow (Fig 1,2). This would match the structure of observed δD signals both in terms of the anomaly direction and the increasing magnitude of anomalies with latitude. While the actual magnitude of this anomaly is dependent on the scaling between eddy and advection velocities in hothouse climates, a reduction in the strength of mid-latitude transient eddies provides a promising and testable mechanism for observed hyperthermal signals.

5. CONCLUSIONS Using a reactive transport model to simulate latitudinal isotope profiles in precipitation under Eocene hothouse conditions, we demonstrate that the observed reduced isotope gradient in the Early Eocene is primarily due to increased length

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scales of specific humidity caused by polar amplification of global warming. In the absence of significant polar amplification, these length scales are relatively unaffected by changing temperatures; consequently, latitudinal patterns of isotopes in precipitation are insensitive to global warming/cooling within existing hothouse conditions. We therefore suggest that observed changes in latitudinal isotope gradients during Early Eocene hyperthermal events may instead reflect theorized reductions in the strength of mid-latitude transient eddies. Ultimately, we demonstrate that proxybased reconstructions of precipitation isotopes represent a powerful tool for probing the dynamics of global hydrology under different climate regimes; however due to the current spatial paucity of data and the magnitude of zonal variability, quantitative inferences of Early Eocene climate are limited. Based on our simulations, we suggest that future campaigns targeting high latitude, near-coastal terrestrial organic material offer the greatest potential to contribute to the quantitative characterization of global hydrology in the Early Eocene.

6. ACKNOWLEDGEMENTS Proxy data compilation is included in APPENDIX C. R code used for analysis is available at http://purl.stanford.edu/js153pq5624. JKC is funded by an NSF GRF and a Stanford Graduate Fellowship. We thank Matthew Huber and Rodrigo Caballero for making their model output publically available.

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8. FIGURES FIGURE 1. Data-model comparison. (a) Modern simulations plotted against modern data from GNIP (circles), Antarctic surface snow (triangles), and Greenland surface snow (squares). Solid and dashed lines represent eddy- and advection-only simulations of zonally-averaged model variables, respectively. Gray shading represents 2σ range of Monte Carlo simulations. (b) Eocene simulations plotted against Eocene proxy data, where red and blue denote Eocene 2240 and 4480 ppm scenarios, respectively, solid and dashed lines and shadings as in (a), and modern data is shown in gray for reference.

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CHAPTER 4 Isotope mass-balance constraints on Pliocene sea level and East Antarctic Ice Sheet stability Matthew J. Winnick1 and Jeremy K. Caves1 1

Department of Earth System Science, Stanford University, Stanford, CA 94305, USA

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ABSTRACT The mid-Pliocene Warm Period (MPWP, 3.3–2.9 Ma), with reconstructed atmospheric pCO2 of 350–450 ppm, represents a potential analogue for climate change in the near future. Current highly cited estimates place MPWP maximum global mean sea level (GMSL) at 21 ± 10 m above modern, requiring total loss of the Greenland (GIS) and marine West Antarctic Ice Sheets (WAIS) and a substantial loss of the East Antarctic Ice Sheet (EAIS), with only a concurrent 2–3 ºC rise in global temperature. Many estimates of Pliocene GMSL are based on the partitioning of oxygen isotope records from benthic foraminifera (δ18Ob) into changes in deep-sea temperatures and terrestrial ice sheets. These isotopic budgets are underpinned by the assumption that the δ18O of Antarctic ice (δ18Oi) was the same in the Pliocene as it is today, and while the sensitivity of δ18Ob to changing meltwater δ18O has been previously considered, these analyses neglect conservation of

18

O/16O in the ocean-ice system. Using well-

calibrated δ18O-temperature relationships for Antarctic precipitation along with estimates of Pliocene Antarctic surface temperatures, we argue that the δ18Oi of the Pliocene Antarctic ice sheet was at minimum 1‰–4‰ higher than present. Assuming conservation of 18O/16O in the ocean-ice system, this requires lower Pliocene seawater

δ18O (δ18Osw) without a corresponding change in ice sheet mass. This effect alone accounts for 5%–20% of the δ18Ob difference between the MPWP interglacials and the modern. With this amended isotope budget, we present a new Pliocene GMSL estimate of 9–13.5 m above modern, which suggests the EAIS is less sensitive to radiative forcing than previously inferred from the geologic record.

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1. INTRODUCTION The magnitude of sea level rise to which anthropogenic global emissions of CO2 commit us over the coming centuries remains a pressing problem in the Earth sciences. The mid-Pliocene Warm Period (MPWP) offers a unique window into this problem, as it represents an Earth system equilibrated with modern to near-future radiative forcing (Pagani et al., 2009). Estimates of MPWP global mean sea level (GMSL) range between 10 m and 70 m above modern, with a value of 25 m often assumed for general circulation models (GCM) configured with Pliocene boundary conditions (Haywood et al., 2010). Historically well-cited estimates come primarily from field-mapped elevations of Pliocene shoreline deposits and depth paleoecology of benthic mollusk and foraminifera assemblages (e.g., Dowsett and Cronin, 1990; Kaufman and Brigham-Grette, 1993; Naish and Wilson, 2009; Miller et al., 2012); however, recent work has shown that these estimates are confounded by the effects of glacial isostatic adjustment (Raymo et al., 2011) and dynamic topography (Rowley et al., 2013). Alternatively, a number of studies have used oxygen isotope records from benthic foraminifera (δ18Ob) to independently constrain total ice sheet volume and Pliocene GMSL. In these studies, temperature controls on equilibrium fractionation during calcification are deconvolved from the evolution of seawater δ18O (δ18Osw) through several methods: (1) signal partitioning (Miller et al., 2012); (2) independent Mg/Ca temperature reconstructions (e.g., Dwyer and Chandler, 2009; Woodard et al., 2014) or, (3) models of water exchange into restricted basins (Rohling et al., 2014). Pliocene GMSL is then calculated assuming a relationship between δ18Osw and GMSL

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of 0.1‰ ± 0.02‰/10 m. Using this method, estimates of peak MPWP GMSL are up to 30 m above modern, necessitating the full deglaciation of the Greenland Ice Sheet (GIS), the West Antarctic Ice Sheet (WAIS), and as much as 30% of the East Antarctic Ice Sheet (EAIS). These estimates conflict with both cosmogenic nuclide data of EAIS thickness (Yamane et al., 2015) and physical ice sheet models forced with MPWP boundary conditions that are only able to simulate 1–29 m GMSL rise, even with the recent inclusion of dynamic ice-sheet processes (Dolan et al. 2011; Pollard and DeConto, 2009; de Boer et al. 2015; Pollard et al., 2015). The widely used 0.1‰/10 m relationship between δ18Osw and sea level is based on deglaciation following the Last Glacial Maximum (LGM), calibrated using estimates of volume and δ18Oi of the LGM ice sheets (Olausson, 1963; Dansgaard and Tauber, 1969), temperature-corrected change in δ18Ob between the LGM and Holocene (Emiliani, 1958; Shackleton and Opdyke, 1973), and independent estimates of deglacial sea-level rise (Fairbanks and Matthews, 1978). Implicit in this calibration is the assumption that δ18Oi does not vary with climate. The Last Glacial Maximum (LGM) –Holocene is characterized by the full-scale deglaciation of the Laurentide and Fenno-Scandanavian ice sheets. Consequently, while the temporal evolution of δ18Oi during LGM ice sheet growth and deglaciation amplifies δ18Osw signals (Mix and Ruddiman, 1984), comparisons between LGM and modern δ18Osw are still dominated by the large volumetric changes in terrestrial ice. In contrast, higher GMSL during the MPWP involves melting of currently extant ice sheets (i.e., GIS, WAIS, EAIS) and smaller changes in ice sheet volume compared to the Pleistocene. The transfer of 16O into these ice sheets as climate cooled from the MPWP to the modern increases δ18Osw

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without corresponding changes in ice sheet volume. Therefore, late Cenozoic cooling has the potential to amplify δ18Osw signals of glaciation, rendering the LGM-calibrated

δ18Osw-sea level relationship inappropriate for estimating Pliocene GMSL. Herein, we argue that the inclusion of this previously neglected process into the isotope massbalance of the ocean-ice system substantially reduces estimates of MPWP GMSL and reconciles δ18Ob-based sea level estimates with ice sheet models.

2. ANTARCTIC PLIOCENE TEMPERATURES AND d18O The fact that δ18Oi and temperature co-vary at high latitudes is wellestablished, and has been exploited to reconstruct Greenland and Antarctic surface temperatures from ice cores (Dansgaard, 1964; Jouzel et al., 1987; EPICA Community Members, 2004). Physically, this co-variation is the result of temperature-dependent changes in the saturation vapor pressure of water in the atmosphere that cause changes in rainout as moisture is transported poleward, towards and over the ice sheets. The precise isotopic composition is further moderated by vapor source conditions, kinetic effects of snow formation, inversion layer dynamics, and transport type (Jouzel and Merlivat, 1984; Hendricks et al., 2000). Globally, Pliocene temperatures were 2–3 ºC warmer than pre-industrial, and ensemble estimates from the Pliocene Model Intercomparison Project (PlioMIP) experiments indicate higher Antarctic temperatures, ranging from 2.5 to 12.5 °C above modern (Haywood et al., 2013); however, higher-end simulated temperatures are due to ice-albedo feedbacks caused by imposed deglaciated WAIS and reduced EAIS boundary conditions (Lunt et al., 2012). Proxy estimates of Pliocene Antarctic warmth

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from the Sirius Group in East Antarctica and reconstructed Ross Sea sea-surface temperatures range from 2 to 20 °C above modern (Retallack et al., 2001; Francis et al., 2007; McKay et al., 2012), though the chronology of the Sirius Group deposits is controversial (Barrett, 2013). Coupled Model Intercomparison Project Phase 5 (CMIP5) projections of summertime Antarctic warming in A.D. 2100 range from ~1–4 °C (Representative Concentration Pathways [RCPs] 2.6–8.5) even with no change in the areal distribution of the Antarctic Ice Sheet (IPCC, 2013). Modern observations, combined with reanalysis and GCM projections, show that the WAIS is one of the fastest warming regions on Earth (Bromwich et al., 2012), while EAIS accumulation is increasing at ~5%/°C due to the greater moisture-holding capacity of warmer air (Frieler et al., 2015). In short, though significant uncertainty surrounds Pliocene Antarctic temperature estimates, available evidence suggests that with near-modern pCO2, the climate was warmer and wetter resulting in higher δ18Oi. Given that the average residence time for ice in the WAIS and EAIS is 44 k.y. and 125 k.y., respectively (Lhomme et al., 2005), δ18Oi-T co-variability must be considered when comparing modern Antarctic ice to Pliocene Antarctic ice. 3. METHODS To test the sensitivity of the δ18Ob record and GMSL estimates to changing

δ18Oi, we use equations that describe the isotope mass-balance of 18O/16O in the oceanice system between modern and MPWP interglacial end-members: MO + MGIS + MWAIS + MEAIS = MpO + MpGIS + MpWAIS + MpEAIS, (1) and

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MORO + MGISRGIS + MWAISRWAIS + MEAISREAIS

=

MpORpO + MpGISRpGIS +

MpWAISRpWAIS + MpEAISRpEAIS, (2) where Mx and Rx represent total mass and

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O/16O ratio, respectively, of the modern

(O) and Pliocene (pO) ocean, GIS, WAIS, and EAIS. Modern Mx and Rx values are listed in Table 1. We assume RpO based on the 0.3‰ offset between modern and MPWP interglacial δ18Ob, calculated from the benthic stack of Lisiecki and Raymo (2005), and a bottom-water temperature effect that accounts for 0.1‰ of this offset (i.e., 67:33 signal partitioning ratio of Δδ18Osw:ΔT; Miller et al., 2012). To calculate RpWAIS and RpEAIS, we assume a linear temperature dependence of WAIS and EAIS

δ18Oi with possible end-member slopes of 0.42‰/ºC and 0.8‰/ºC, representing average modeled temporal δ18Oi-T based on GCM simulations of modern and LGM climate (Lee et al., 2008) and the modern spatial relationship (Masson-Delmotte et al., 2008), respectively. For RpGIS, we use the averaged modeled temporal δ18Op-T slope (0.37‰/°C) at the three ice-core localities on GIS examined in Lee et al. (2008). Because δ18Osw records an integrated signal from all terrestrial ice, we present two end-member scenarios of MpGIS and MpWAIS to examine the sensitivity of the δ18Ob record and sea-level estimates to variable δ18Oi: (1) We treat both the WAIS and GIS as entirely deglaciated in the Pliocene, and (2) we deglaciate only the marine-based sectors of the WAIS (Pollard and DeConto, 2009) and half of the GIS (Dolan et al., 2015) in the Pliocene. In both scenarios, we then solve for the two remaining variables (MpO and MpEAIS) which provides the required additional melt from the EAIS to account for the full δ18Osw change across the range of estimated Pliocene Antarctic temperatures (2–20 °C). Sensitivity analyses to differential Pliocene warming of the

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WAIS and GIS along with assumed Δδ18Osw:ΔT partitioning ratios of 80:20 and 50:50 are presented in the Data Repository. We note that our analysis is restricted to comparisons of end-member values of MPWP interglacials and the modern, though future work will aim to incorporate isotope mass-balance into the temporal evolution of δ18Oi within the Pliocene to investigate orbital-scale changes in sea level.

4. RESULTS AND DISCUSSION The temperature-dependent increases in δ18Oi act to amplify signals of terrestrial ice melt in δ18Ob records under warmer conditions; consequently, partitioning of the 0.3‰ δ18Ob signal into EAIS mass loss and increased δ18Oi becomes a function of Pliocene high-latitude temperature change. Deglaciation of half of the GIS and the marine-based portion of the WAIS (Scenario 2) combined with bottom-water temperature change accounts for 0.2‰ of the full MPWP-present offset (Fig. 1). As estimated Pliocene Antarctic temperatures increase, less EAIS mass loss must be invoked to account for the full 0.3‰ offset. Given the δ18Oi-T relationship of Masson-Delmotte et al. (2008), only a 7 °C increase is required to completely eliminate the need for any Pliocene EAIS mass loss. Under Scenario 1, even smaller temperature increases are needed to explain the δ18Ob record without invoking EAIS mass loss (APPENDIX D, Fig. 1). These deglaciation scenarios can be used to calculate the associated GMSL rise needed to reproduce the 0.3‰ δ18Ob offset using the sea level equivalent of each modern ice sheet (Fig. 2; Table 1). The total GMSL rise encapsulated in the δ18Ob record becomes a function of Pliocene Antarctic temperatures, with higher

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temperatures resulting in lower GMSL. Under Scenario 2, less total melt, and subsequently lower GMSL, is required to account for the δ18Ob record than under Scenario 1. In Scenario 2, the EAIS accounts for a greater proportion of the total meltwater signal, and as the EAIS has the lowest δ18Oi (–56.5‰), less total mass loss is needed to account for the δ18Ob record. We note that even without changes in δ18Oi (i.e., DT = 0), our maximum Pliocene GMSL estimates are only 15 m above modern, compared to an estimate of 21 m from Miller et al. (2012) using similar constraints. This estimate is lower due to two key differences. First, our mass balance budget allows for distinct meltwater signals from each of the ice sheets based on their modern δ18Oi. The generalized 0.1‰/10m sea level relationship derived from LGM–Holocene records assumes negligible contributions from the isotopically light EAIS to the total meltwater signal, and therefore leads to an overestimate of Pliocene sea level. Second, by considering independent estimates of mass changes and sea level rise due to deglaciation, we avoid the assumption that all mass loss contributes to global sea level implicit in the 0.1‰/10m sea level relationship. This is most significant for the WAIS where a significant mass proportion of the marine-based sector will not contribute to global sea level (Fretwell et al., 2013). Figure 2 also shows the increase in Pliocene δ18Oi and Antarctic temperature needed to account for the δ18Ob record without invoking additional mass loss from the EAIS. This point occurs where the GMSL rise is equal to the combined GMSL rise from GIS and WAIS melting in each of our deglaciation scenarios and occurs at Pliocene Antarctic temperatures of 3–13.1 °C above modern (marked by solid and

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dashed lines along the x-axis). Any additional temperature increase above this point implies an increase in EAIS mass. While some modeling studies suggest that EAIS growth may occur up to pCO2 levels of 400—560 ppm (Ligtenberg et al., 2013; de Boer et al., 2015), the increase in temperature needed to sufficiently alter δ18Oi is likely physically incompatible with EAIS mass growth. Additionally, changes in δ18O of other terrestrial water reservoirs such as global groundwater may amplify δ18Oi signals and further reduce Pliocene sea level estimates. However, we neglect these changes from our analysis as there are no estimates as to how the mass of these global reservoirs changed in magnitude or distribution in the Pliocene, and because δ18O of precipitation is less sensitive to changes in global temperature at lower latitudes.

5. IMPLICATIONS Though estimates of Pliocene Antarctic temperature have considerable uncertainty, we view a 2.5–5 °C increase as conservative, given that globally averaged Pliocene temperatures were 2–3 °C above modern. This translates into a 1–4‰ increase in the average δ18Oi of Antarctica. With these assumptions, we estimate that GMSL was ~9–13.5 m above modern, with a 2–4.5 m contribution from the EAIS. This estimate, with a maximum 8.5% loss of the EAIS, is significantly less than previous estimates based on paleoshorelines and benthic mollusk and foraminifera assemblages, and reconciles the δ18Ob record with ice-sheet models of the Pliocene WAIS and EAIS as well as recent cosmogenic nuclide data suggesting negligible Pliocene EAIS mass loss (Pollard and DeConto, 2009; de Boer et al., 2015; Yamane et

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al., 2015). Assuming the full uncertainty in Δδ18Osw:ΔT partitioning from 80:20– 50:50, the full range of calculated maximum GMSL becomes 5–17 m above modern (see the APPENDIX D). These estimates suggest that the EAIS is substantially less sensitive to radiative forcing than previously inferred from the MPWP, and that dramatic deglaciation of the EAIS under modern pCO2 is not supported by the geologic record.

6. ACKNOWLEDGMENTS We thank Jerry Mitrovica and two anonymous reviewers for comments that improved our study. Caves is funded by a National Science Foundation GRFP and a Stanford Graduate Fellowship. R code used in our analysis can be accessed at http://purl.stanford.edu/rm704hj0382.

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Pagani, M., Liu, Z., LaRiviere, J., and Ravelo, A.C., 2009, High Earth-system climate sensitivity determined from Pliocene carbon dioxide concentrations: Nature Geoscience, v. 3, p. 27–30, doi:10.1038/ngeo724. Pollard, D., and DeConto, R.M., 2009, Modelling West Antarctic ice sheet growth and collapse through the past five million years: Nature, v. 458, p. 329–332, doi:10.1038/nature07809. Pollard, D., Deconto, R.M., and Alley, R.B., 2015, Potential Antarctic Ice Sheet retreat driven by hydrofracturing and ice cliff failure: Earth and Planetary Science Letters, v. 412, p. 112–121, doi:10.1016/j.epsl.2014.12.035. Raymo, M.E., Mitrovica, J.X., O’Leary, M.J., DeConto, R.M., and Hearty, P.J., 2011, Departures from eustasy in Pliocene sea-level records: Nature Geoscience, v. 4, p. 328–332, doi:10.1038/ngeo1118. Retallack, G.J., Krull, E.S., and Bockheim, J.G., 2001, New grounds for reassessing palaeoclimate of the Sirius Group, Antarctica: Journal of the Geological Society, v. 158, p. 925–935, doi:10.1144/0016-764901-030. Rohling, E.J., Foster, G.L., Grant, K.M., Marino, G., Roberts, A.P., Tamisiea, M.E., and Williams, F., 2014, Sea-level and deep-sea-temperature variability over the past 5.3 million years: Nature, v. 508, p. 477–482, doi:10.1038/nature13230. Rowley, D.B., Forte, A.M., Moucha, R., Mitrovica, J.X., Simmons, N.A., and Grand, S.P., 2013, Dynamic topography change of the eastern United States since 3 million years ago: Science, v. 340, p. 1560–1563, doi:10.1126/science.1229180. Shackleton, N.J., and Opdyke, N.D., 1973, Oxygen isotope and palaeomagnetic stratigraphy of Equatorial Pacific core V28–238: Oxygen isotope temperatures

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and ice volumes on a 105 year and 106 year scale: Quaternary Research, v. 3, p. 39–55, doi:10.1016/0033-5894(73)90052-5. Woodard, S.C., Rosenthal, Y., Miller, K.G., Wright, J.D., Chiu, B.K., and Lawrence, K.T., 2014, Antarctic role in Northern Hemisphere glaciation: Science, v. 346, p. 847–851, doi:10.1126/science.1255586. Yamane, M., Yokoyama, Y., Abe-Ouchi, A., Obrochta, S., Saito, F., Moriwaki, K., and Matsuzaki, H., 2015, Exposure age and ice-sheet model constraints on Pliocene East Antarctic ice sheet dynamics: Nature Communications, v. 6, p. 7016, doi:10.1038/ncomms8016.

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8. TABLES AND FIGURES TABLE 1. Modern parameters used in Equations 1 and 2. Variable

Modern volume (106 km3) N.A. 2.9* 3§

Modern Sea-level Modern mass equivalent δ18O 18 (10 kg) (m) (‰) 1358 N.A. 0 2.66† 7.3* -35** 2.43†,# 3.4§ -41**

Ocean GIS WAIS marine-based WAIS non-marineN.A. 0.322†,# 0.9§ -41** based EAIS 23.5§ 21.55† 53.3§ -56.5** *Bamber et al. (2001) † Masses are calculated assuming an ice density of 917 kg/m3 (Fretwell et al., 2013). § Fretwell et al. (2013) # Calculation of the separate masses of the WAIS marine-based and non-marine-based sectors is shown in DR Section 2. **Lhomme et al. (2005)

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FIGURE 1. Attribution of δ18Ob changes between mid-Pliocene Warm Period (MPWP) and the present assuming 50% melting of the Greenland Ice Sheet and melting of the marine-based sectors of the West Antarctic Ice Sheet as a function of the estimated Pliocene temperature increase. Blue and red lines correspond to endmember δ18Oi-T relationships over Antarctica (see the x-axis). Area below red/blue line corresponds to signal explained by changes in the δ18Oi composition; area above is signal attributable to ice melt. Error bars above plot are full range of estimated Antarctic ΔT in the, Pliocene Model Intercomparison Project (PlioMIP) experiment, and proxy-based estimates.

t Mel O i

Obenthic

lt i Me O

0 0 T

0

  123  

6.26

  124  

C

6

C

Temperature Change ( °C)

B

IP

A

Pliocene Peak Sea Level (GMSL) (m)

PlioMIP Proxy

Th i Pa s S le tu os dy ho re O

Pliocene Peak Sea Level (GMSL)/ Ice Sheet SLE (m)

FIGURE 2. A: Total estimated global mean sea level (GMSL) due to melting of terrestrial ice at the mid-Pliocene Warm Period (MPWP) as a function of the estimated Pliocene temperature increase. Solid lines correspond to Scenario 1, and dashed lines correspond to Scenario 2. Horizontal gray lines are total Greenland Ice Sheet (GIS) and West Antarctic Ice Sheet (WAIS) sea-level equivalents for these scenarios. Error bars above plot are full range of estimated Antarctic ΔT as in Figure 1. B: Previouslypublished estimates of MPWP GMSL (APPENDIX D Table 1), organized by method. Our estimate is indicated at left. Dashed error bar at right indicates full range of estimates from Dolan et al. (2011); PlioMIP—Pliocene Model Intercomparison Project; EAIS—East Antarctic Ice Sheet; SLE—sea-level equivalent; IPCC— Intergovernmental Panel on Climate Change.

APPENDIX A Supporting Information for CHAPTER 1 Stable isotopic evidence of El Nino-like atmospheric circulation in the Pliocene western United States

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1. MODERN ENSO δ 18O SIGNALS While we incorporate over 10,000 separate weekly measurements of isotopes in precipitation in our analysis of modern ENSO signals, the time interval of observations is only 6 years and does not include large El Niño events such as took place in 1997-8. In order to validate these observed signals as features of ENSO teleconnections, we analyze model output of δ18O from the Stable Water Isotope Intercomparison

Group

(SWING)

publically

available

(http://atoc.colorado.edu/~dcn/SWING/datab-ase.php).

on

their

website

We use data from the

ECHAM-4 results of the S1b Experiment in which the model is forced with varying SST from the HadlSST data set. Seasonal El Niño δ18O anomalies based on the Niño 3.4 Index from 1950-2003 are shown in SFIG 1. In the winter (JFM), there are positive anomalies located in the Southwest and Northern US along with negative anomalies along the Southeast coast. This is in contrast to modern observations, which show negative anomalies along the West Coast. Similarly in the spring (AMJ), the Southwest and Northern US are characterized by positive anomalies. These regional signals match those observed in the modern dataset and are particularly relevant to the Southwest sites as is discussed in Section 4.1 of the main text. In the summer (JAS) there is a less coherent pattern of anomalies. Though small positive anomalies extend across portions of the Southern US, much of the US does not experience anomalies δ18O similar to the observational data. Finally in the fall (OND), the model shows a large zone of negative anomalies extending across the Southern US.

This signal is shifted east compared to

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observational data, though the signals match over the Great Plains region. This is relevant to the Meade, KS site as discussed in Section 4.1 of the main text. While there are some discrepancies between observed and modeled signals, there is very good agreement on the isotopic changes relevant to our discussion based on seasonality of carbonate formation at each locality (see discussion in main text). Therefore, we regard the isotopic anomalies observed in modern precipitation used in our analysis to be a robust feature of modern ENSO teleconnections.

2. PLIOCENE TOPOGRAPHY The isotope records presented do not appear to be primarily driven by changes in topography. In this section, we will describe the topographic environment of each site, expected signals of uplift, and previous research on regional topography. In addition, we present a new record of topography from the Southern Sierra Nevada. Moisture that reaches Hagerman, ID is advected west from the Pacific across the Cascades and Columbia Plateau. As such, the site is located in a zone of relatively low δ18Oprecip that is representative of upstream orographic rainout to the west. Across the late Pliocene, we observe a Δδ18O of approximately 1‰, a signal that cannot be explained by the rise of upstream topography. Moreover, it has been shown that the Cascade Range developed in the mid-Miocene and the isotopic rain shadow has persisted since then (Kohn et al., 2002; Takeuchi and Larson, 2005; Takeuchi et al., 2010). The Meade, KS locality is situated on the eastern edge of the central Rocky Mountains, and in terms of modern precipitation, the site is located within a steep δ18O

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gradient (Kendall and Coplen, 2001). We expect topographic rise to manifest as decreasing δ18O values across the Pliocene with decreasing efficiency of moisture delivery to the western Great Plains from the Gulf of Mexico. Instead, we observe increasing δ18O values through the late Pliocene, similar to Hagerman, ID and at odds with rising topography. More importantly, however, the concept of rising of largescale topography in this region is also in conflict with isotopic paleoaltimetry studies that have demonstrated the full development of modern δ18O gradients on the eastern edge of the Rockies by the late Eocene to Oligocene (39-29 Ma) (Mix et al., 2011; Chamberlain et al., 2012). The Camp Rice, NM and St David, AZ isotopic records are located at the southern edge of the Colorado Plateau. While Camp Rice carbonates do not cover the late Pliocene, St David carbonates record decreasing δ18O, which could be interpreted as decreasing efficiency of inland moisture transport with rising topography. This would conflict with a number of studies, however, that have shown stable or decreasing Colorado Plateau elevations since the Paleogene (Horton and Chamberlain, 2006; Mix et al., 2011; Huntington et al., 2010; Chamberlain et al., 2012). The San Timoteo, CA section is located at the windward corner of the Transverse and Peninsular ranges. There is sedimentological evidence that this region was tectonically active throughout the Pliocene, though it is debated whether this entailed the uplift or lateral translation of the Transverse Ranges (Albright, 1999; Weldon et al., 1993; Matti and Morton, 1993). Based on empirical relationships between precipitation isotopes and elevation (Poage and Chamberlain, 2001), the observed decrease in δ18O translates to ~1.5 km uplift in 1 million years – a scenario

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that, to our knowledge has not been proposed in previous research. This empirical relationship, however, is not valid at windward positions. Uplift or lateral translation may account for a portion of the observed signal through infiltration of high elevation waters to the lower, windward section of the basin or by elevation-induced increases in upstream precipitation (Galewsky, 2009). As the isotopic signals of these effects are reduced relative to the empirical leeward relationship, we do not believe the amount of inferred uplift is plausible (>3km); therefore, the observed signal cannot be fully explained by changes in elevation. Finally, conflicting evidence exists as to whether or not the Southern Sierra Nevada experienced uplift through the Pliocene (e.g.: Chamberlain et al., 2012), which may have impacted moisture delivery to the western US interior. In order to address this question, we collected lacustrine carbonates from the Coso formation of Owens Lake Valley, CA (Bacon et al., 1992) from 6 - 2 Ma located ~10km leeward of the Southern Sierra Nevada (SFIG 2).

Methods used to analyze isotopic values are

described in Section 2.1, main text, and isotopic values are included in APPENDIX A Table 1. This location is ideally situated to study topographic uplift for two reasons: 1) A recent study of storm trajectories has shown that moisture travelling inland will avoid pathways across high elevation when possible, so that only locations immediately leeward of high elevation will be isotopically sensitive to uplift (Lechler and Galewsky, 2013). 2) This location is situated north of the large spring and fall El Niño δ18O anomalies and is therefore insensitive to changes in the Pacific jet that may act to mask changes in uplift (FIG 3, main text). We include this data in APPENDIX A rather than the main text as it does not pertain to El Niño signals and because

  129  

minerals are lacustrine rather than pedogenic and as such reflect different formation processes. The isotopic evolution of the Coso formation is displayed in SFIG 2. With progressive uplift through the Pliocene, we would expect to observe clearly decreasing δ18O on the order of 3-6‰ based on the empirical δ18O v. elevation relationship (Poage and Chamberlain, 2001) and depending on the amount of uplift (~1-2.5 km). Instead, we observe a slight trend of increasing δ18O from 5 - 3 Ma on the order of ~1‰ followed by even higher values from 2.5 – 2.0 Ma that range from -14 to -10‰. The anomalously high values suggest potential evaporative enrichment, concurrent with regional drying during this time period discussed in the main text. These data suggest stable topography in the Southern Sierra Nevada through the Pliocene epoch.

3. REFERENCES Albright, L. B.: Magnetostratigraphy and biochronology of the San Timoteo Badlands, southern California, with implications for local Pliocene-Pleistocene tectonic and depositional patterns, Geol. Soc. Am. Bull., 111, 1265-1293, 1999. Bacon, C. R., Giovanetti, D. M., Duffield, W. A., Dalrymple, G. B., Drake, R. E.: Age of the Coso formation, Inyo County, California. Geological Survey Bulletin, 1527, 1-18, 1992. Bonham, S., Haywood, A., Lunt, D., Collins, M., and Salzmann, U.: El Niño-Southern Oscillation, Pliocene climate and equifinality, Philos. T. Roy. Soc. A., 367, 127-156, 2009. Chamberlain, C. P., Mix, H. T., Mulch, A., Hren, M. T., Kent-Corson, M. L., Davis, S.

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J., Horton, T. W., and Graham, S.A.: The Cenozoic climatic and topographic evolution of the western North American Cordillera, Am. J. Sci., 312, 213-262, 2012. Galewsky, J.: Orographic precipitation isotopic ratios in stratified atmospheric flows: Implications for paleoelevation studies, Geology, 37, 791-794, 2009. Horton, T. W. and Chamberlain, C. P.: Stable isotopic evidence for Neogene surface downdrop in the central Basin and Range Province, Geol. Soc. Am. Bull, 118, 475-490, 2006. Huntington, K. W., Wernicke, B. P., and Eiler, J. M.: Influence of climate change and uplift on Colorado Plateau paleotemperatures from carbonate clumped isotope thermometry, Tectonics, 29, TC3005, 2010. Kendall, C. and Coplen, T.B.: Distribution of oxygen-18 and deuterium in river waters across the United States, Hydrol. Process, 15, 1363-1393, 2001. Kohn, M. J., Miselis, J. L., and Fremd, T. J.: Oxygen isotope evidence for progressive uplift of the Cascade Range, Oregon, Earth. Planet. Sc. Lett., 204, 151-165, 2002. Lechler, A., Galewsky, J.: Refining Paleoaltimetry reconstructions of the Sierra Nevada, California, using air parcel trajectories, Geology, 41, 259-262, 2013. Matti, J. C. and Morton, D. M.: Paleogeographic evolution of the San Andreas Fault in Southern California: A reconstruction based on a new cross-fault correlation, in: The San Andreas fault system: Displacement, palinspastic reconstruction, and geologic evolution, edited by: Powell, R. E., Weldon, R. J., and Matti, J. C., Geol. Soc. Am. Mem., 178, 107–159, 1993.

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Mix, H. T., Mulch, A., Kent-Corson, M. L., and Chamberlain C. P.: Cenozoic migration of topography in the North American Cordillera, Geology, 39, 87-90, 2011. Poage, M. A. and Chamberlain, C. P.: Empirical relationships between elevation and the stable isotope composition of precipitation and surface waters: Considerations for studies of paleoelevation change, Am. J. Sci., 301, 1-15, 2001. Sohl, L. E., Chandler, M. A., Schmunk, R. B., Mankoff, K., Jonas, J. A., Foley, K. M., and Dowsett, H. J.: PRISM3/GISS topographic reconstruction,

U.S.

Geological Survey Data Series, 419, 6 pp., 2009. Takeuchi, A. and Larson, P. B.: Oxygen isotope evidence for the late Cenozoic development of an orographic rain shadow in eastern Washington, Geology 223, 127-146, 2005. Takeuchi, A., Hren, M. T., Smith, S. V., Chamberlain, C.P., and Larsen, P. B.: Pedogenic carbonate carbon isotopic constraints on paleoprecipitation: Evolution of desert in the Pacific Northwest, USA, in response to topographic development of the Cascade Range, Chemical Geology, 277, 323-335, 2010. Weldon, R. J., Meisling, K. E., and Alexander, J.: A speculative history of the San Andreas Fault in the central Transverse Ranges, California, in: The San Andreas fault system: Displacement, palinspastic reconstruction, and geologic evolution, edited by: Powell, R. E., Weldon, R. J., and Matti, J. C., Geol. Soc. Am. Mem., 178, 161–198, 1993.

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4. TABLES AND FIGURES FIGURE 1. Seasonal El Niño anomalies of modeled δ18Oprecip based on the Niño 3.4 Index from 1950-2003. Isotope data taken from Stable Water Isotope Intercomparison Group (SWING) [reference in CHAPTER 1].

JFM

Δδ18O

Latitude (°N)

60

3

AMJ

Δδ18O

60

3

2 50

2 50

1 40

0

1 40

0

-1 30

-1 30

-2 20

-3 -130

-120

-110

-100

-90

-80

-70

-2 20

-60

JAS

Δδ18O

60

-3 -130

3

-120

-110

-100

-90

-80

-70

-60

OND

Δδ18O

60

3

Latitude (°N)

2 50

2 50

1 40

0

1 40

0

-1 30

-1 30

-2 20

-3 -130

-120

-110

-100

-90

-80

-70

-60

-2 20

-3 -130

Longitude (°E)

-120

-110

-100

-90

-80

Longitude (°E)

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-70

-60

-12 -14 -16 -18 -20

δ18O (‰ VPDB)

-10

-8

FIGURE 2. δ18O values measured in lactustrine carbonates from the Coso formation in Owens Valley, CA. The location is represented by the gold star in the inset.

1

2

3

4 Age (Ma)

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5

6

TABLE 1. Isotope values of samples from Hagerman, ID, San Timoteo, CA, and Owens Valley, CA. Location Hagerman, ID

Sample Glenns Ferry Fm. Oolite ID-CH 01-07 ID-CH 02-07 ID-CH 03-07 ID-CH 04-07 ID-CH 05-07 ID-CH 06-07 ID-CH 07-07 ID-CH 08-07 ID-CH 09-07 ID-CH 10-07 Glenns Ferry Fm. ID-GF 01-07 ID-GF 02-07 ID-GF 03-07 ID-GF 04-07 Hagerman Fossil Beds ID-HFB 01-07 ID-HFB 02-07 ID-HFB 03-07 ID-HFB 05-07 ID-HFB 06-07 ID-HFB 07-07 ID-HFB 08-07 ID-HFB 09-07 ID-HFB 10-07 ID-HFB 11-07 ID-HFB 12-07 ID-HFB 13-07 ID-HFB 14-07 ID-HFB 15-07 ID-HFB 16-07 ID-HFB 17-07 Tuana Gravels Fm. TG 01-07 TG 03-07 TG 04-07 TG 05-07 TG 06-07 TG 07-07

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Age (Ma)

δ18O (‰ VPDB) 3.83 3.83 3.82 3.82 3.81 3.81 3.80 3.80 3.79 3.79

-17.83 -17.60 -16.79 -15.17 -16.64 -16.54 -15.75 -16.15 -16.66 -16.58

3.02 3.03 3.04 3.05

-15.15 -15.54 -15.54 -15.54

3.32 3.32 3.32 3.31 3.31 3.31 3.31 3.30 3.30 3.52 3.50 3.50 3.48 3.32 2.12 2.13

-15.63 -15.19 -15.72 -15.56 -15.21 -14.15 -15.19 -16.00 -16.30 -16.44 -16.33 -14.30 -15.81 -16.30 -14.58 -15.02

2.00 2.01 2.02 2.02 2.02 2.07

-15.82 -15.42 -15.65 -15.15 -15.83 -15.37

TG 08-07 TG 09-07

2.08 2.13

-15.69 -14.84

TG 10-07

2.13

-14.64

ID-BF 04-07 ID-BF 05-07

1.92 1.92

-15.68 -16.03

ID-BF 06-07

1.92

-15.86

ID-BF 07-07 ID-BF 08-07

1.92 1.92

-15.38 -15.46

CA - 11 - 01 CA - 11 - 02

2.10 2.13

-8.49 -9.41

CA - 11 - 03 CA - 11 - 04 CA - 11 - 05 CA - 11 - 06 CA - 11 - 07 CA - 11 - 08 CA - 11 - 09 CA - 11 - 10 CA - 11 - 11 CA - 11 - 12 CA - 11 - 13 CA - 11 - 14 CA - 11 - 15 CA - 11 - 16

2.30 2.50 2.60 2.70 2.80 2.90 3.05 3.08 3.09 3.09 3.11 3.12 3.15 3.17

-7.56 -9.49 -8.02 -9.46 -6.06 -5.43 -4.57 -9.22 -5.57 -6.84 -8.42 -7.80 -6.65 -7.15

CA - 11 - 17 CA - 11 - 18 CA - 11 - 19

3.19 3.20 3.21

-7.96 -5.44 -6.27

CA - 11 - 20 CA - 11 - 21 CA - 11 - 22

3.29 3.30 3.35

-7.85 -4.70 -7.92

CA - 11 - 23 CA - 11 - 24 CA - 11 - 25 CA - 11 - 26 CA - 11 - 27 CA - 11 - 28

3.39 3.42 3.50 3.54 3.75 3.80

-3.93 -4.50 -4.62 -5.10 -6.13 -5.96

CA - 11 - 29 Coso Formation LC - 1

3.90

-6.66

5.865092749

-15.65

LC - 2

5.745924677

-14.75

Bruneau Fm.

San Timoteo, CA

Owens Valley, CA

Jack Rabbit Trail

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LC - 3 LC - 4

5.655986509 5.5975267

-13.65 -16.15

LC - 5 LC - 6 LC - 7 LC - 8 LC - 9 LC - 10 LC - 11 LC - 12 LC - 13 LC - 14 LC - 15 LC - 16 LC - 17 LC - 18 LC - 19 LC - 20 UC - 1 UC - 2 UC - 3 UC - 4 UC - 5 UC - 6 UC - 7

5.557054525 5.584035975 5.545812254 5.523327712 5.512085441 5.467116358 5.422147274 5.37717819 5.341202923 5.296233839 4.891512085 4.882518269 4.815064643 4.545250141 4.540753232 4.320404722 4.32 4.292215569 4.264431138 4.208862275 4.181077844 4.153293413 4.125508982

-15.71 -11.1 -15.11 -17.55 -17.43 -16.75 -14.85 -15.73 -12.87 -14.34 -14.19 -14.71 -13.09 -15.08 -15.24 -14.68 -15.75 -15.69 -14.99 -13.44 -14.98 -14.51 -15.08

UC - 8 UC - 9 UC - 10 UC - 11 UC - 12

4.097724551 4.051417166 4.00510978 3.981956088 3.94491018

-15.64 -15.35 -15.39 -15.57 -14.74

UC - 13 UC - 14

3.917125749 3.898602794

-14.86 -14.66

UC - 15 UC - 16

3.838403194 3.805988024

-15.3 -14.8

UC - 17 UC - 18 UC - 19

3.778203593 3.745788423 3.731896208

-15.48 -14.65 -14.68

UC - 20 UC - 21

3.685588822 3.639281437

-15.05 -13.89

UC - 22 UC - 23

3.611497006 3.583712575

-13.95 -14

UC - 24

3.560558882

-14.15

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UC - 25

3.532774451

-13.52

UC - 26 UC - 27

3.509620758 3.486467066

-15.2 -15.5

UC - 28 UC - 29 UC - 30 UC - 31 UC - 32 UC - 33 UC - 34 UC - 35 UC - 36 UC - 37 UC - 38 UC - 39 UC - 40 UC - 41 UC - 42 UC - 43 UC - 44 UC - 45 UC - 46 UC - 47 UC - 48 UC - 49 UC - 50 UC - 51 UC - 52 UC - 53 UC - 54 UC - 55 UC - 56 UC - 57

3.440159681 3.398483034 3.37996008 3.34754491 3.301237525 3.25493014 3.231776447 3.199361277 3.143792415 3.09748503 3.060439122 3.032654691 3.000239521 2.986347305 2.97245509 2.944670659 2.916886228 2.870578842 2.801117764 2.740918164 2.685349301 2.629780439 2.555688623 2.467704591 2.398243513 2.338043912 2.277844311 2.217644711 2.078722555 2

-14.09 -13.67 -13.56 -15.18 -13.16 -14.82 -14.05 -14.08 -14.56 -13.33 -11.42 -13.62 -13.21 -13.68 -13.62 -14.49 -13.39 -13.45 -13.92 -14.55 -14.79 -14.05 -14.94 -12.1 -14.09 -12.98 -14.22 -14.6 -11.01 -9.79

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APPENDIX B Supporting information for CHAPTER 2 Quantifying the isotopic ‘continental effect’

  139  

TABLE 1. GNIP and USNIP site pairs and model variables. Season DJF

Site)1 Site)2 Latitude((°N) Longitude((°E) Latitude((°N) Longitude((°E) 20.02 110.21 24.35 109.40 22.32 114.17 24.35 109.40 25.07 110.08 28.12 113.04 48.36 24.57 47.90 1.90 51.30 3.75 50.92 5.78 51.30 3.75 50.35 7.58 51.30 3.75 50.50 9.95 51.30 3.75 52.10 8.73 51.30 3.75 52.30 10.45 51.30 3.75 50.32 11.88 51.30 3.75 49.80 9.90 51.30 3.75 51.35 12.43 51.30 3.75 49.02 12.07 51.57 4.93 50.92 5.78 51.57 4.93 50.35 7.58 51.57 4.93 52.10 8.73 51.57 4.93 52.30 10.45 51.57 4.93 51.35 12.43 51.57 4.93 50.50 9.95 51.57 4.93 50.32 11.88 51.57 4.93 52.47 13.40 52.10 5.18 51.83 6.60 52.10 5.18 52.10 8.73 52.10 5.18 52.30 10.45 52.10 5.18 52.47 13.40 52.10 5.18 51.35 12.43 52.10 5.18 50.32 11.88 52.10 5.18 50.07 19.88 52.10 5.18 49.12 19.73 52.93 4.78 52.10 8.73 52.93 4.78 52.30 10.45 52.93 4.78 51.35 12.43 52.93 4.78 52.47 13.40 52.93 4.78 52.07 23.41 52.80 5.05 52.10 8.73 52.80 5.05 52.30 10.45 52.80 5.05 51.35 12.43 52.80 5.05 52.47 13.40 52.80 5.05 52.07 23.41 43.68 21.07 46.17 8.78 43.68 21.07 46.57 8.33 43.68 21.07 46.65 8.30 43.68 21.07 46.73 8.20 43.95 4.82 46.17 8.78 43.95 4.82 46.57 8.33 43.95 4.82 46.65 8.30 43.95 4.82 46.73 8.20 44.42 8.85 46.17 8.78 43.71 10.40 46.17 8.78 44.18 10.42 46.17 8.78 44.09 11.08 46.17 8.78 46.22 6.28 46.57 8.33 46.22 6.28 46.65 8.30

Dataset

Location

GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP

Asia Asia Asia Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe

  140  

Distance)(km) 480 529 442 484 147 292 445 358 478 587 468 603 647 96 234 270 390 522 370 507 588 96 246 370 562 514 511 1052 1073 284 387 552 586 1260 260 363 526 560 1235 825 805 811 802 400 401 405 410 190 303 256 290 163 163

Δδ18O)(‰) 21.883 21.363 21.036 22.166 20.074 20.824 22.221 21.015 20.098 22.419 21.826 22.554 23.303 20.015 20.766 20.956 20.039 22.496 22.163 22.360 21.437 20.154 21.223 20.306 21.704 22.763 22.627 24.658 26.025 21.615 20.698 23.155 22.096 26.003 21.382 20.464 22.921 21.862 25.769 27.047 210.550 29.979 29.265 27.392 210.895 210.323 29.610 26.620 26.907 24.853 23.152 24.243 23.671

Δw)(mm) 28.438 24.637 23.373 22.016 20.340 20.755 21.274 21.159 21.230 21.584 21.559 21.472 22.884 0.031 20.384 20.788 20.859 21.101 20.903 21.213 20.971 20.196 20.510 20.581 20.692 20.823 20.935 22.024 21.475 20.495 20.566 20.808 20.678 21.880 20.420 20.491 20.733 20.603 21.805 24.033 24.046 24.065 24.054 23.130 23.143 23.162 23.151 21.631 22.906 22.050 22.319 21.286 21.304

w)(mm) 21.967 21.967 17.805 12.019 10.894 10.479 9.960 10.075 10.004 9.649 9.675 9.762 8.350 10.894 10.479 10.075 10.004 9.762 9.960 9.649 9.892 10.388 10.075 10.004 9.892 9.762 9.649 8.560 9.110 10.075 10.004 9.762 9.892 8.690 10.075 10.004 9.762 9.892 8.690 7.679 7.667 7.648 7.659 7.679 7.667 7.648 7.659 7.679 7.679 7.679 7.679 7.667 7.648

Nd 717.629 717.629 8.069 0.758 0.986 1.664 1.970 1.175 1.102 3.635 1.857 3.762 4.164 0.986 1.664 1.175 1.102 3.762 1.970 3.635 9.089 1.174 1.175 1.102 9.089 3.762 3.635 88.883 203.657 1.175 1.102 3.762 9.089 2.623 1.175 1.102 3.762 9.089 2.623 507.379 422.144 424.733 362.355 427.716 422.144 424.733 362.355 183.842 254.032 138.975 35.670 1.769 1.769

JJA

46.22 56.97 56.97 56.97 56.97 59.58 59.58 59.58 59.17 59.17 59.17 59.17 56.54 56.54 56.54 56.54 55.75 55.75 55.75 55.75 4.83 4.83 4.83 4.83 4.83 20.13 20.13 20.20 20.20 23.12 23.12 21.43 21.43 21.43 21.43 234.58 241.47 38.87 38.87 37.66 44.38 44.38 44.38 44.38 44.38 44.21 44.21 44.21 44.21 47.86 13.73 13.17 20.02 20.02 20.02

6.28 24.07 24.07 24.07 24.07 30.18 30.18 30.18 39.52 39.52 39.52 39.52 35.54 35.54 35.54 35.54 37.57 37.57 37.57 37.57 252.37 252.37 252.37 252.37 252.37 267.08 267.08 267.10 267.10 260.02 260.02 248.48 248.48 248.48 248.48 258.48 272.93 2123.05 2123.05 2119.80 2123.61 2123.61 2123.61 2123.61 2123.61 2122.25 2122.25 2122.25 2122.25 2123.93 100.50 100.80 110.21 110.21 110.21

46.73 56.54 55.75 56.13 54.37 56.54 59.17 58.39 58.39 56.13 58.01 56.07 56.13 58.39 58.01 56.07 56.13 58.39 58.01 56.07 20.13 20.20 23.12 28.77 29.98 28.77 29.98 29.98 28.77 28.77 29.98 23.12 28.77 29.98 215.60 236.80 241.15 37.66 38.74 38.74 44.21 44.29 43.46 41.66 45.69 44.29 43.46 41.66 45.69 46.76 19.88 19.88 24.35 25.07 26.35

8.20 35.54 37.57 43.49 39.43 35.54 39.52 49.37 49.37 43.49 56.18 57.06 43.49 49.37 56.18 57.06 43.49 49.37 56.18 57.06 267.08 267.10 260.02 263.92 267.82 263.92 267.82 267.82 263.92 263.92 267.82 260.02 263.92 267.82 256.10 259.83 271.33 2119.80 2119.23 2119.23 2122.25 2116.06 2113.55 2111.89 2113.97 2116.06 2113.55 2111.89 2113.97 2117.18 102.13 102.13 109.40 110.08 106.43

GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP GNIP GNIP GNIP GNIP GNIP

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Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America Asia Asia Asia Asia Asia

158 702 847 1191 1007 471 535 1109 575 417 976 1098 500 860 1240 1331 376 768 1162 1215 1721 1721 1222 1973 2370 1011 1097 1097 1011 750 1147 1302 1886 2340 1777 717 133 311 333 120 108 600 813 995 772 501 708 885 675 520 686 750 480 543 785

22.957 25.016 24.466 24.077 23.272 22.497 23.265 22.377 0.888 1.706 20.688 23.131 0.939 0.120 21.456 23.899 0.388 20.430 22.006 24.449 21.495 21.459 23.176 25.955 25.486 24.460 23.991 24.027 24.496 22.779 22.310 21.979 24.758 24.289 23.860 24.013 24.423 24.925 28.771 23.846 22.005 28.400 29.575 28.526 211.211 26.395 27.569 26.520 29.206 23.560 21.31 21.96 0.48 0.68 21.22

21.293 21.104 20.846 21.239 20.598 20.679 21.022 21.456 20.434 0.208 20.661 20.903 20.135 20.777 21.003 21.246 20.394 21.036 21.262 21.504 2.883 2.933 5.947 3.332 0.229 0.449 22.654 22.705 0.398 22.615 25.718 2.138 20.477 23.580 26.468 23.250 22.175 25.009 26.355 21.346 22.349 25.640 26.558 26.657 26.797 23.291 24.209 24.308 24.448 24.331 25.82 25.79 24.47 24.66 214.28

7.659 6.787 7.046 6.652 7.294 6.787 6.444 6.010 6.010 6.652 5.784 5.542 6.652 6.010 5.784 5.542 6.652 6.010 5.784 5.542 46.135 46.186 49.199 46.584 43.481 46.584 43.481 43.481 46.584 46.584 43.481 49.199 46.584 43.481 40.593 24.203 14.301 8.707 7.362 7.362 10.058 6.767 5.849 5.750 5.610 6.767 5.849 5.750 5.610 7.903 44.53 44.53 50.95 50.77 41.14

1.769 1.389 0.568 0.654 0.444 0.492 0.492 0.492 0.852 0.654 0.852 0.852 0.654 1.004 1.140 1.389 0.568 0.568 0.568 0.568 1.100 1.077 0.908 0.949 5.266 0.949 1.100 1.077 0.949 0.908 0.908 0.545 0.545 0.545 0.545 1001.000 1001.000 0.461 0.461 1.024 0.137 0.478 0.478 0.478 0.478 0.137 0.137 0.137 0.137 0.319 0.32 0.33 0.31 0.31 0.31

20.02 20.02 20.02 22.32 22.32 22.32 22.32 22.32 22.32 22.32 24.35 24.35 24.35 25.07 25.07 25.07 23.13 23.13 23.13 23.13 23.13 23.13 28.12 28.12 28.12 18.90 18.90 18.90 25.57 28.58 43.68 43.68 43.68 43.68 43.95 43.95 43.95 43.95 44.42 43.71 46.22 46.22 46.22 56.54 56.54 55.75 55.75 55.75 55.75 25.80 25.80 25.80 25.80 25.80 25.80

110.21 110.21 110.21 114.17 114.17 114.17 114.17 114.17 114.17 114.17 109.40 109.40 109.40 110.08 110.08 110.08 113.32 113.32 113.32 113.32 113.32 113.32 113.04 113.04 113.04 72.82 72.82 72.82 91.88 77.20 21.07 21.07 21.07 21.07 4.82 4.82 4.82 4.82 8.85 10.40 6.28 6.28 6.28 35.54 35.54 37.57 37.57 37.57 37.57 235.20 235.20 235.20 235.20 235.20 235.20

27.70 28.12 30.62 24.35 25.07 26.35 27.70 28.12 30.62 32.18 26.35 27.70 28.12 26.35 27.70 28.12 24.35 25.07 26.35 27.70 28.12 32.18 30.62 31.95 32.18 24.90 28.58 17.45 29.42 29.42 46.17 46.57 46.65 46.73 46.17 46.57 46.65 46.73 46.17 46.17 46.57 46.65 46.73 58.01 56.07 56.13 58.39 58.01 56.07 23.72 25.33 21.43 23.12 28.77 29.98

106.88 113.04 114.13 109.40 110.08 106.43 106.88 113.04 114.13 118.18 106.43 106.88 113.04 106.43 106.88 113.04 109.40 110.08 106.43 106.88 113.04 118.18 114.13 115.78 118.18 67.13 77.20 78.47 91.08 91.08 8.78 8.33 8.30 8.20 8.78 8.33 8.30 8.20 8.78 8.78 8.33 8.30 8.20 56.18 57.06 43.49 49.37 56.18 57.06 238.55 249.82 248.48 260.02 263.92 267.82

GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP

Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Asia Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe South>America South>America South>America South>America South>America South>America

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906 930 1213 529 500 886 922 635 902 1150 373 438 550 405 420 442 427 390 771 815 540 1100 308 508 663 885 1151 620 428 1350 825 805 811 802 400 401 405 410 190 303 163 163 158 1240 1331 376 768 1162 1215 412 1607 1540 2760 3200 3650

21.27 0.27 0.30 21.11 20.91 22.80 22.85 21.31 21.29 22.33 21.70 21.74 20.20 21.90 21.94 20.40 21.96 21.76 23.66 23.70 22.16 23.18 0.02 4.52 21.02 22.42 24.34 22.55 213.56 211.10 22.97 27.86 26.14 25.14 21.62 26.52 24.80 23.79 21.76 22.44 23.86 22.13 21.13 21.30 22.02 22.09 22.62 22.44 23.16 21.18 20.08 0.38 21.87 22.47 20.73

213.74 23.94 25.03 21.71 21.89 211.51 210.98 21.17 22.26 25.61 29.81 29.27 0.53 29.62 29.08 0.72 20.41 20.59 210.21 29.68 0.13 24.31 21.09 23.01 24.43 212.29 28.47 23.82 232.44 228.53 23.21 23.41 23.44 23.46 22.36 22.56 22.60 22.62 21.94 23.96 21.06 21.09 21.11 20.26 20.82 20.01 20.62 21.07 21.63 0.72 4.46 6.76 7.51 1.72 21.61

41.68 51.48 50.40 50.95 50.77 41.14 41.68 51.48 50.40 47.05 41.14 41.68 51.48 41.14 41.68 51.48 50.95 50.77 41.14 41.68 51.48 47.05 50.40 48.47 47.05 38.18 42.01 46.65 13.48 13.48 19.19 18.99 18.96 18.94 19.19 18.99 18.96 18.94 19.19 19.19 18.99 18.96 18.94 22.89 22.33 23.95 23.34 22.89 22.33 38.18 41.92 44.22 44.97 39.18 35.85

0.31 0.31 0.31 0.82 0.82 0.82 0.82 0.82 0.82 0.82 1.09 1.09 1.09 1.40 1.47 1.47 1.09 1.47 1.40 1.69 1.69 1.38 1.81 1.56 1.38 1.22 1.22 1.09 0.43 0.43 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 758.30 1001.00 1001.00 1001.00 17.29 17.29 15.65 15.65 15.65 15.65 1001.00 1001.00 254.18 1001.00 1001.00 1001.00

25.80 25.80 25.80 23.72 23.72 23.72 23.72 23.72 23.72 23.72 21.43 21.43 21.43 21.43 21.43 21.43 4.83 4.83 4.83 213.00 213.00 213.00 213.00 222.90 222.90 222.90 222.90 222.90 29.98 29.98 29.98 215.60 215.60 215.60 253.00 241.47 28.47 28.47 28.47 28.47 28.47 28.47 29.66 29.66 29.66 29.66 29.66 29.66 39.00 39.00 44.38 44.38 44.38 44.38 44.38

235.20 235.20 235.20 238.55 238.55 238.55 238.55 238.55 238.55 238.55 248.48 248.48 248.48 248.48 248.48 248.48 252.37 252.37 252.37 238.52 238.52 238.52 238.52 243.17 243.17 243.17 243.17 243.17 267.82 267.82 267.82 256.10 256.10 256.10 270.51 272.93 297.70 297.70 297.70 297.70 297.70 297.70 296.26 296.26 296.26 296.26 296.26 296.26 2123.08 2123.08 2123.61 2123.61 2123.61 2123.61 2123.61

20.20 20.13 215.60 25.33 21.43 23.12 28.77 29.98 20.13 20.20 25.33 23.12 20.13 20.20 28.77 29.98 20.13 20.20 4.70 215.85 215.60 220.47 216.29 220.47 227.47 230.58 231.75 230.08 227.47 230.58 231.75 220.47 227.47 216.29 254.78 241.15 33.39 34.97 36.59 36.80 38.67 39.10 33.39 34.97 36.59 36.80 38.67 39.10 37.79 38.79 44.21 45.22 44.29 43.46 46.76

267.10 267.08 256.10 249.82 248.48 260.02 263.92 267.82 267.08 267.10 249.82 260.02 267.08 267.10 263.92 267.82 267.08 267.10 274.13 247.93 256.10 254.67 268.08 254.67 258.83 264.58 260.73 251.18 258.83 264.58 260.73 254.67 258.83 268.08 268.28 271.33 297.64 297.52 2101.62 298.20 2100.91 296.61 297.64 297.52 2101.62 298.20 2100.91 296.61 2119.85 2119.25 2122.25 2118.51 2116.06 2113.55 2117.18

GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP GNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP

South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America South>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America

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3585 3585 2534 1274 1133 2375 2880 3320 3200 3200 450 1280 2085 2085 1905 2358 1736 1736 2403 1047 1905 1880 3158 1206 1651 2300 1983 1153 2150 2294 2500 555 1344 1275 245 133 542 736 971 929 1164 1175 439 606 930 813 1077 1039 308 329 112 425 607 812 567

23.42 22.62 0.71 1.11 1.56 20.69 21.28 0.46 21.43 22.24 20.46 22.25 23.00 23.80 22.85 21.11 21.38 22.18 28.47 21.17 0.33 22.81 28.39 21.12 21.92 23.34 20.98 21.39 22.49 23.91 21.55 23.13 23.93 28.71 20.93 25.34 20.43 0.05 21.68 20.50 21.79 20.24 22.04 21.56 23.29 22.11 23.40 21.85 22.76 22.73 21.97 25.27 25.46 24.68 24.39

6.78 6.75 211.27 3.74 6.04 6.79 1.00 22.33 6.03 6.06 22.30 0.75 20.01 0.01 25.04 28.38 1.19 1.21 211.05 29.35 24.87 26.63 219.21 0.78 22.52 28.44 28.22 22.92 214.71 220.62 220.41 21.75 25.05 214.34 20.15 22.06 22.24 22.70 210.99 24.96 210.08 25.80 23.44 23.89 212.18 26.16 211.28 27.00 23.11 24.34 21.91 22.19 23.71 24.88 21.63

44.24 44.21 26.19 41.92 44.22 44.97 39.18 35.85 44.21 44.24 41.92 44.97 44.21 44.24 39.18 35.85 44.21 44.24 31.97 21.71 26.19 24.44 11.85 24.44 21.14 15.22 15.44 20.74 21.14 15.22 15.44 24.44 21.14 11.85 8.91 10.67 35.97 35.52 27.23 33.25 28.13 32.41 35.97 35.52 27.23 33.25 28.13 32.41 13.27 12.04 15.67 15.39 13.87 12.70 15.94

2.07 1.99 1001.00 1001.00 254.18 1001.00 1001.00 1001.00 1.99 2.07 254.18 254.18 1.99 2.07 254.18 254.18 1.63 1.63 0.43 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 207.94 1001.00 1001.00 1001.00 1001.00 1001.00 1001.00 0.95 0.15 31.72 153.27 11.16 153.27 12.51 153.27 31.72 320.74 11.16 564.93 12.51 670.74 371.64 371.64 1001.00 1001.00 1001.00 1001.00 1001.00

44.21 44.21 44.21 44.21 47.86 47.86 47.86 47.86 47.86 47.86 30.81 30.81 30.81 30.81 30.81 30.81 30.81

2122.25 2122.25 2122.25 2122.25 2123.93 2123.93 2123.93 2123.93 2123.93 2123.93 290.18 290.18 290.18 290.18 290.18 290.18 290.18

45.22 44.29 43.46 46.76 46.76 48.51 45.69 44.29 45.22 43.46 34.17 34.00 37.43 38.74 35.96 37.70 40.93

2118.51 2116.06 2113.55 2117.18 2117.18 2114.00 2113.97 2116.06 2118.51 2113.55 293.09 289.80 288.67 287.48 284.29 285.05 290.72

USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP USNIP

North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America North>America

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320 496 714 487 513 736 790 716 504 942 463 358 756 911 794 893 1123

23.30 23.49 22.71 22.43 23.41 24.93 26.45 24.48 24.28 23.70 20.42 20.64 22.03 21.69 21.43 21.32 21.77

20.28 21.80 22.97 0.28 22.45 23.56 25.38 24.53 23.01 25.70 23.44 22.00 26.38 27.90 27.32 27.95 210.05

15.39 13.87 12.70 15.94 15.94 14.83 13.02 13.87 15.39 12.70 37.54 38.99 34.60 33.09 33.67 33.04 30.94

1001.00 1001.00 1001.00 1001.00 942.38 942.38 942.38 942.38 942.38 942.38 2.38 2.23 2.38 2.38 2.38 2.38 2.38

APPENDIX C Supporting information for CHAPTER 3 A mechanistic analysis of Early Eocene latitudinal gradients of isotopes in precipitation

  145  

1. TABLES AND FIGURES TABLE 1. Model variable descriptions. Full citation information included in CHAPTER 3.       Table&S1.&Model&variable&descriptions Variable

Description

Value

α

Equilibrium*coefficent*of* fractionation*of*water*vapor5liquid

Horita*and*Wesolowski* (1994),*T*=*T850*for* * 6.7123*10 *T *5*1.6664*10 *T precipitation*and*T*=*Ts*for* evaporation +*0.35041*109*T53

δa

δ18O*of*atmospheric*vapor

Calculated*from*Eq.*2,3

δa

o

18

Details

103ln(α)*=*57.6850*+* 3

51

(55.2*±*2.6)*5*103ln(α)

Initial*δ O*of*atmospheric*vapor

3

δe

δ18O*of*evaporating*surface*water

δp

δ18O*of*precipitation

Nd

Damköhler*Number

θ RH T850 Ts

Degree*Latitude Relative*Humidity Temperature*at*850*mb Surface*Temperature

6

52

δpo*=*55.2*±*2.6

510 ln(α)*+*14.2(15RH),****************** Eq*+*Kin*fractionation,* Gonfiantini*(1986) δp*over*modern*Antarctica δa*+*103ln(α) E/(P5E),*limited*to*abs(Nd)*