Articles | Volume 14, issue 12
https://doi.org/10.5194/cp-14-2037-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/cp-14-2037-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2018
Research article |
| 20 Dec 2018
| 20 Dec 2018
Understanding the Australian Monsoon change during the Last Glacial Maximum with a multi-model ensemble
Key Laboratory of Virtual Geographic Environment, Ministry of Education, State key Laboratory of Geographical Environment Evolution, Jiangsu Provincial Cultivation Base, School of Geography Science,
Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
Bin Wang
Department of Atmospheric Sciences, University of Hawai'i at Mānoa, Honolulu, HI 96825, USA
Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, 210044, China
Jian Liu
CORRESPONDING AUTHOR
Key Laboratory of Virtual Geographic Environment, Ministry of Education, State key Laboratory of Geographical Environment Evolution, Jiangsu Provincial Cultivation Base, School of Geography Science,
Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
Axing Zhu
Key Laboratory of Virtual Geographic Environment, Ministry of Education, State key Laboratory of Geographical Environment Evolution, Jiangsu Provincial Cultivation Base, School of Geography Science,
Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA
Liang Ning
Key Laboratory of Virtual Geographic Environment, Ministry of Education, State key Laboratory of Geographical Environment Evolution, Jiangsu Provincial Cultivation Base, School of Geography Science,
Nanjing Normal University, Nanjing, 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
Climate System Research Center, Department of Geosciences, University of Massachusetts, Amherst, 01003, USA
Jian Cao
Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Surface mass balance and climate of the Last Glacial Maximum Northern Hemisphere ice sheets: simulations with CESM2.1
A transient coupled general circulation model (CGCM) simulation of the past 3 million years
Atmosphere–cryosphere interactions during the last phase of the Last Glacial Maximum (21 ka) in the European Alps
Summer surface air temperature proxies point to near-sea-ice-free conditions in the Arctic at 127 ka
On the importance of moisture conveyor belts from the tropical eastern Pacific for wetter conditions in the Atacama Desert during the mid-Pliocene
Modeled storm surge changes in a warmer world: the Last Interglacial
No changes in overall AMOC strength in interglacial PMIP4 time slices
The role of ice-sheet topography in the Alpine hydro-climate at glacial times
Simulating glacial dust changes in the Southern Hemisphere using ECHAM6.3-HAM2.3
Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice-sheet–climate coupled model
The role of land cover in the climate of glacial Europe
Simulated stability of the Atlantic Meridional Overturning Circulation during the Last Glacial Maximum
Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4)
Evaluation of Arctic warming in mid-Pliocene climate simulations
Simulating Marine Isotope Stage 7 with a coupled climate–ice sheet model
Comparison of past and future simulations of ENSO in CMIP5/PMIP3 and CMIP6/PMIP4 models
An empirical evaluation of bias correction methods for palaeoclimate simulations
Hypersensitivity of glacial summer temperatures in Siberia
Distorted Pacific–North American teleconnection at the Last Glacial Maximum
Effect of high dust amount on surface temperature during the Last Glacial Maximum: a modelling study using MIROC-ESM
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Costanza Del Gobbo, Renato R. Colucci, Giovanni Monegato, Manja Žebre, and Filippo Giorgi
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Louise C. Sime, Rahul Sivankutty, Irene Vallet-Malmierca, Agatha M. de Boer, and Marie Sicard
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Mark Reyers, Stephanie Fiedler, Patrick Ludwig, Christoph Böhm, Volker Wennrich, and Yaping Shao
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Zhiyi Jiang, Chris Brierley, David Thornalley, and Sophie Sax
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Patricio Velasquez, Martina Messmer, and Christoph C. Raible
Clim. Past, 18, 1579–1600, https://doi.org/10.5194/cp-18-1579-2022, https://doi.org/10.5194/cp-18-1579-2022, 2022
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We investigate the sensitivity of the glacial Alpine hydro-climate to northern hemispheric and local ice-sheet changes. We perform sensitivity simulations of up to 2 km horizontal resolution over the Alps for glacial periods. The findings demonstrate that northern hemispheric and local ice-sheet topography are important role in regulating the Alpine hydro-climate and permits a better understanding of the Alpine precipitation patterns at glacial times.
Stephan Krätschmer, Michèlle van der Does, Frank Lamy, Gerrit Lohmann, Christoph Völker, and Martin Werner
Clim. Past, 18, 67–87, https://doi.org/10.5194/cp-18-67-2022, https://doi.org/10.5194/cp-18-67-2022, 2022
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We use an atmospheric model coupled to an aerosol model to investigate the global mineral dust cycle with a focus on the Southern Hemisphere for warmer and colder climate states and compare our results to observational data. Our findings suggest that Australia is the predominant source of dust deposited over Antarctica during the last glacial maximum. In addition, we find that the southward transport of dust from all sources to Antarctica happens at lower altitudes in colder climates.
Aurélien Quiquet, Didier M. Roche, Christophe Dumas, Nathaëlle Bouttes, and Fanny Lhardy
Clim. Past, 17, 2179–2199, https://doi.org/10.5194/cp-17-2179-2021, https://doi.org/10.5194/cp-17-2179-2021, 2021
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In this paper we discuss results obtained with a set of coupled ice-sheet–climate model experiments for the last 26 kyrs. The model displays a large sensitivity of the oceanic circulation to the amount of the freshwater flux resulting from ice sheet melting. Ice sheet geometry changes alone are not enough to lead to abrupt climate events, and rapid warming at high latitudes is here only reported during abrupt oceanic circulation recoveries that occurred when accounting for freshwater flux.
Patricio Velasquez, Jed O. Kaplan, Martina Messmer, Patrick Ludwig, and Christoph C. Raible
Clim. Past, 17, 1161–1180, https://doi.org/10.5194/cp-17-1161-2021, https://doi.org/10.5194/cp-17-1161-2021, 2021
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This study assesses the importance of resolution and land–atmosphere feedbacks for European climate. We performed an asynchronously coupled experiment that combined a global climate model (~ 100 km), a regional climate model (18 km), and a dynamic vegetation model (18 km). Modelled climate and land cover agree reasonably well with independent reconstructions based on pollen and other paleoenvironmental proxies. The regional climate is significantly influenced by land cover.
Frerk Pöppelmeier, Jeemijn Scheen, Aurich Jeltsch-Thömmes, and Thomas F. Stocker
Clim. Past, 17, 615–632, https://doi.org/10.5194/cp-17-615-2021, https://doi.org/10.5194/cp-17-615-2021, 2021
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The stability of the Atlantic Meridional Overturning Circulation (AMOC) critically depends on its mean state. We simulate the response of the AMOC to North Atlantic freshwater perturbations under different glacial boundary conditions. We find that a closed Bering Strait greatly increases the AMOC's sensitivity to freshwater hosing. Further, the shift from mono- to bistability strongly depends on the chosen boundary conditions, with weaker circulation states exhibiting more abrupt transitions.
Bette L. Otto-Bliesner, Esther C. Brady, Anni Zhao, Chris M. Brierley, Yarrow Axford, Emilie Capron, Aline Govin, Jeremy S. Hoffman, Elizabeth Isaacs, Masa Kageyama, Paolo Scussolini, Polychronis C. Tzedakis, Charles J. R. Williams, Eric Wolff, Ayako Abe-Ouchi, Pascale Braconnot, Silvana Ramos Buarque, Jian Cao, Anne de Vernal, Maria Vittoria Guarino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina A. Morozova, Kerim H. Nisancioglu, Ryouta O'ishi, David Salas y Mélia, Xiaoxu Shi, Marie Sicard, Louise Sime, Christian Stepanek, Robert Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 17, 63–94, https://doi.org/10.5194/cp-17-63-2021, https://doi.org/10.5194/cp-17-63-2021, 2021
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The CMIP6–PMIP4 Tier 1 lig127k experiment was designed to address the climate responses to strong orbital forcing. We present a multi-model ensemble of 17 climate models, most of which have also completed the CMIP6 DECK experiments and are thus important for assessing future projections. The lig127ksimulations show strong summer warming over the NH continents. More than half of the models simulate a retreat of the Arctic minimum summer ice edge similar to the average for 2000–2018.
Wesley de Nooijer, Qiong Zhang, Qiang Li, Qiang Zhang, Xiangyu Li, Zhongshi Zhang, Chuncheng Guo, Kerim H. Nisancioglu, Alan M. Haywood, Julia C. Tindall, Stephen J. Hunter, Harry J. Dowsett, Christian Stepanek, Gerrit Lohmann, Bette L. Otto-Bliesner, Ran Feng, Linda E. Sohl, Mark A. Chandler, Ning Tan, Camille Contoux, Gilles Ramstein, Michiel L. J. Baatsen, Anna S. von der Heydt, Deepak Chandan, W. Richard Peltier, Ayako Abe-Ouchi, Wing-Le Chan, Youichi Kamae, and Chris M. Brierley
Clim. Past, 16, 2325–2341, https://doi.org/10.5194/cp-16-2325-2020, https://doi.org/10.5194/cp-16-2325-2020, 2020
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The simulations for the past climate can inform us about the performance of climate models in different climate scenarios. Here, we analyse Arctic warming in an ensemble of 16 simulations of the mid-Pliocene Warm Period (mPWP), when the CO2 level was comparable to today. The results highlight the importance of slow feedbacks in the model simulations and imply that we must be careful when using simulations of the mPWP as an analogue for future climate change.
Dipayan Choudhury, Axel Timmermann, Fabian Schloesser, Malte Heinemann, and David Pollard
Clim. Past, 16, 2183–2201, https://doi.org/10.5194/cp-16-2183-2020, https://doi.org/10.5194/cp-16-2183-2020, 2020
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Our study is the first study to conduct transient simulations over MIS 7, using a 3-D coupled climate–ice sheet model with interactive ice sheets in both hemispheres. We find glacial inceptions to be more sensitive to orbital variations, whereas glacial terminations need the concerted action of both orbital and CO2 forcings. We highlight the issue of multiple equilibria and an instability due to stationary-wave–topography feedback that can trigger unrealistic North American ice sheet growth.
Josephine R. Brown, Chris M. Brierley, Soon-Il An, Maria-Vittoria Guarino, Samantha Stevenson, Charles J. R. Williams, Qiong Zhang, Anni Zhao, Ayako Abe-Ouchi, Pascale Braconnot, Esther C. Brady, Deepak Chandan, Roberta D'Agostino, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Polina A. Morozova, Rumi Ohgaito, Ryouta O'ishi, Bette L. Otto-Bliesner, W. Richard Peltier, Xiaoxu Shi, Louise Sime, Evgeny M. Volodin, Zhongshi Zhang, and Weipeng Zheng
Clim. Past, 16, 1777–1805, https://doi.org/10.5194/cp-16-1777-2020, https://doi.org/10.5194/cp-16-1777-2020, 2020
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El Niño–Southern Oscillation (ENSO) is the largest source of year-to-year variability in the current climate, but the response of ENSO to past or future changes in climate is uncertain. This study compares the strength and spatial pattern of ENSO in a set of climate model simulations in order to explore how ENSO changes in different climates, including past cold glacial climates and past climates with different seasonal cycles, as well as gradual and abrupt future warming cases.
Robert Beyer, Mario Krapp, and Andrea Manica
Clim. Past, 16, 1493–1508, https://doi.org/10.5194/cp-16-1493-2020, https://doi.org/10.5194/cp-16-1493-2020, 2020
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Even the most sophisticated global climate models are known to have significant biases in the way they simulate the climate system. Correcting model biases is therefore essential for creating realistic reconstructions of past climate that can be used, for example, to study long-term ecological dynamics. Here, we evaluated three widely used bias correction methods by means of a global dataset of empirical temperature and precipitation records from the last 125 000 years.
Pepijn Bakker, Irina Rogozhina, Ute Merkel, and Matthias Prange
Clim. Past, 16, 371–386, https://doi.org/10.5194/cp-16-371-2020, https://doi.org/10.5194/cp-16-371-2020, 2020
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Northeastern Siberia is currently known for its harsh cold climate, but remarkably it did not experience large-scale glaciation during the last ice age. We show that the region is also exceptional in climate models. As a result of subtle changes in model setup, climate models show a strong divergence in simulated glacial summer temperatures that is ultimately driven by changes in the circumpolar atmospheric stationary wave pattern and associated northward heat transport to northeastern Siberia.
Yongyun Hu, Yan Xia, Zhengyu Liu, Yuchen Wang, Zhengyao Lu, and Tao Wang
Clim. Past, 16, 199–209, https://doi.org/10.5194/cp-16-199-2020, https://doi.org/10.5194/cp-16-199-2020, 2020
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The paper shows, using climate simulations, that the Pacific–North American (PNA) teleconnection was distorted or completely broken at the Last Glacial Maximum (LGM). The results suggest that ENSO would have little direct impact on North American climates at the LGM.
Rumi Ohgaito, Ayako Abe-Ouchi, Ryouta O'ishi, Toshihiko Takemura, Akinori Ito, Tomohiro Hajima, Shingo Watanabe, and Michio Kawamiya
Clim. Past, 14, 1565–1581, https://doi.org/10.5194/cp-14-1565-2018, https://doi.org/10.5194/cp-14-1565-2018, 2018
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The behaviour of dust in terms of climate can be investigated using past climate. The Last Glacial Maximum (LGM; 21000 years before present) is known to be dustier. We investigated the impact of plausible dust distribution on the climate of the LGM using an Earth system model and found that the higher dust load results in less cooling over the polar regions. The main finding is that radiative perturbation by the high dust loading does not necessarily cool the surface surrounding Antarctica.
Leah Birch, Timothy Cronin, and Eli Tziperman
Clim. Past, 14, 1441–1462, https://doi.org/10.5194/cp-14-1441-2018, https://doi.org/10.5194/cp-14-1441-2018, 2018
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We investigate the regional dynamics at the beginning of the last ice age, using a nested configuration of the Weather Research and Forecasting (WRF) model with a simple ice flow model. We find that ice sheet height causes a negative feedback on continued ice growth by interacting with the atmospheric circulation, causing warming on Baffin Island, and inhibiting the initiation of the last ice age. We conclude that processes at larger scales are needed to overcome the regional warming effect.
Taraka Davies-Barnard, Andy Ridgwell, Joy Singarayer, and Paul Valdes
Clim. Past, 13, 1381–1401, https://doi.org/10.5194/cp-13-1381-2017, https://doi.org/10.5194/cp-13-1381-2017, 2017
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We present the first model analysis using a fully coupled dynamic atmosphere–ocean–vegetation GCM over the last 120 kyr that quantifies the net effect of vegetation on climate. This analysis shows that over the whole period the biogeophysical effect (albedo, evapotranspiration) is dominant, and that the biogeochemical impacts may have a lower possible range than typically estimated. This emphasises the temporal reliance of the balance between biogeophysical and biogeochemical effects.
Rima Rachmayani, Matthias Prange, and Michael Schulz
Clim. Past, 12, 677–695, https://doi.org/10.5194/cp-12-677-2016, https://doi.org/10.5194/cp-12-677-2016, 2016
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A set of 13 interglacial time slice experiments was carried out using a CCSM3-DGVM to study global climate variability between and within the Quaternary interglaciations of MIS 1, 5, 11, 13, and 15. Seasonal surface temperature anomalies can be explained by local insolation anomalies induced by the astronomical forcing in most regions and by GHG forcing at high latitudes and early Bruhnes interglacials. However, climate feedbacks may modify the surface temperature response in specific regions.
A. J. Coletti, R. M. DeConto, J. Brigham-Grette, and M. Melles
Clim. Past, 11, 979–989, https://doi.org/10.5194/cp-11-979-2015, https://doi.org/10.5194/cp-11-979-2015, 2015
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Evidence from Pleistocene sediments suggest that the Arctic's climate went through multiple sudden transitions, warming by 2-4 °C (compared to preindustrial times), and stayed warm for hundreds to thousands of years. A climate modelling study of these events suggests that the Arctic's climate and landscape drastically changed, transforming a cold and barren landscape as we know today to a warm, lush, evergreen and boreal forest landscape only seen in the modern midlatitudes.
P. A. Araya-Melo, M. Crucifix, and N. Bounceur
Clim. Past, 11, 45–61, https://doi.org/10.5194/cp-11-45-2015, https://doi.org/10.5194/cp-11-45-2015, 2015
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By using a statistical tool termed emulator, we study the sensitivity of the Indian monsoon during the the Pleistocene. The originality of the present work is to consider, as inputs, several elements of the climate forcing that have varied in the past, and then use the emulator as a method to quantify the link between forcing variability and climate variability. The methodology described here may naturally be applied to other regions of interest.
L. B. Stap, R. S. W. van de Wal, B. de Boer, R. Bintanja, and L. J. Lourens
Clim. Past, 10, 2135–2152, https://doi.org/10.5194/cp-10-2135-2014, https://doi.org/10.5194/cp-10-2135-2014, 2014
P.M. Langebroek and K. H. Nisancioglu
Clim. Past, 10, 1305–1318, https://doi.org/10.5194/cp-10-1305-2014, https://doi.org/10.5194/cp-10-1305-2014, 2014
I. Suter, R. Zech, J. G. Anet, and T. Peter
Clim. Past, 10, 1183–1194, https://doi.org/10.5194/cp-10-1183-2014, https://doi.org/10.5194/cp-10-1183-2014, 2014
D. J. Ullman, A. N. LeGrande, A. E. Carlson, F. S. Anslow, and J. M. Licciardi
Clim. Past, 10, 487–507, https://doi.org/10.5194/cp-10-487-2014, https://doi.org/10.5194/cp-10-487-2014, 2014
P. Beghin, S. Charbit, C. Dumas, M. Kageyama, D. M. Roche, and C. Ritz
Clim. Past, 10, 345–358, https://doi.org/10.5194/cp-10-345-2014, https://doi.org/10.5194/cp-10-345-2014, 2014
X. Zhang, G. Lohmann, G. Knorr, and X. Xu
Clim. Past, 9, 2319–2333, https://doi.org/10.5194/cp-9-2319-2013, https://doi.org/10.5194/cp-9-2319-2013, 2013
M. Crucifix
Clim. Past, 9, 2253–2267, https://doi.org/10.5194/cp-9-2253-2013, https://doi.org/10.5194/cp-9-2253-2013, 2013
M.-O. Brault, L. A. Mysak, H. D. Matthews, and C. T. Simmons
Clim. Past, 9, 1761–1771, https://doi.org/10.5194/cp-9-1761-2013, https://doi.org/10.5194/cp-9-1761-2013, 2013
I. Nikolova, Q. Yin, A. Berger, U. K. Singh, and M. P. Karami
Clim. Past, 9, 1789–1806, https://doi.org/10.5194/cp-9-1789-2013, https://doi.org/10.5194/cp-9-1789-2013, 2013
K. Saito, T. Sueyoshi, S. Marchenko, V. Romanovsky, B. Otto-Bliesner, J. Walsh, N. Bigelow, A. Hendricks, and K. Yoshikawa
Clim. Past, 9, 1697–1714, https://doi.org/10.5194/cp-9-1697-2013, https://doi.org/10.5194/cp-9-1697-2013, 2013
D. Handiani, A. Paul, M. Prange, U. Merkel, L. Dupont, and X. Zhang
Clim. Past, 9, 1683–1696, https://doi.org/10.5194/cp-9-1683-2013, https://doi.org/10.5194/cp-9-1683-2013, 2013
T. Tharammal, A. Paul, U. Merkel, and D. Noone
Clim. Past, 9, 789–809, https://doi.org/10.5194/cp-9-789-2013, https://doi.org/10.5194/cp-9-789-2013, 2013
J. D. Annan and J. C. Hargreaves
Clim. Past, 9, 367–376, https://doi.org/10.5194/cp-9-367-2013, https://doi.org/10.5194/cp-9-367-2013, 2013
H. J. Punge, H. Gallée, M. Kageyama, and G. Krinner
Clim. Past, 8, 1801–1819, https://doi.org/10.5194/cp-8-1801-2012, https://doi.org/10.5194/cp-8-1801-2012, 2012
J. M. Gregory, O. J. H. Browne, A. J. Payne, J. K. Ridley, and I. C. Rutt
Clim. Past, 8, 1565–1580, https://doi.org/10.5194/cp-8-1565-2012, https://doi.org/10.5194/cp-8-1565-2012, 2012
P. Bakker, C. J. Van Meerbeeck, and H. Renssen
Clim. Past, 8, 995–1009, https://doi.org/10.5194/cp-8-995-2012, https://doi.org/10.5194/cp-8-995-2012, 2012
D. Hofer, C. C. Raible, A. Dehnert, and J. Kuhlemann
Clim. Past, 8, 935–949, https://doi.org/10.5194/cp-8-935-2012, https://doi.org/10.5194/cp-8-935-2012, 2012
G. Levavasseur, M. Vrac, D. M. Roche, D. Paillard, A. Martin, and J. Vandenberghe
Clim. Past, 7, 1225–1246, https://doi.org/10.5194/cp-7-1225-2011, https://doi.org/10.5194/cp-7-1225-2011, 2011
F. S. R. Pausata, C. Li, J. J. Wettstein, M. Kageyama, and K. H. Nisancioglu
Clim. Past, 7, 1089–1101, https://doi.org/10.5194/cp-7-1089-2011, https://doi.org/10.5194/cp-7-1089-2011, 2011
C. Berrittella and J. van Huissteden
Clim. Past, 7, 1075–1087, https://doi.org/10.5194/cp-7-1075-2011, https://doi.org/10.5194/cp-7-1075-2011, 2011
U. Mikolajewicz
Clim. Past, 7, 161–180, https://doi.org/10.5194/cp-7-161-2011, https://doi.org/10.5194/cp-7-161-2011, 2011
K. Arpe, S. A. G. Leroy, and U. Mikolajewicz
Clim. Past, 7, 91–114, https://doi.org/10.5194/cp-7-91-2011, https://doi.org/10.5194/cp-7-91-2011, 2011
F. S. R. Pausata, C. Li, J. J. Wettstein, K. H. Nisancioglu, and D. S. Battisti
Clim. Past, 5, 489–502, https://doi.org/10.5194/cp-5-489-2009, https://doi.org/10.5194/cp-5-489-2009, 2009
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