Articles | Volume 7, issue 4
Clim. Past, 7, 1075–1087, 2011
https://doi.org/10.5194/cp-7-1075-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Clim. Past, 7, 1075–1087, 2011
https://doi.org/10.5194/cp-7-1075-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 11 Oct 2011
Research article | 11 Oct 2011
Uncertainties in modelling CH4 emissions from northern wetlands in glacial climates: the role of vegetation parameters
C. Berrittella and J. van Huissteden
Related subject area
Subject: Climate Modelling | Archive: Modelling only | Timescale: Pleistocene
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
Understanding the Australian Monsoon change during the Last Glacial Maximum with a multi-model ensemble
Effect of high dust amount on surface temperature during the Last Glacial Maximum: a modelling study using MIROC-ESM
The role of regional feedbacks in glacial inception on Baffin Island: the interaction of ice flow and meteorology
Quantifying the influence of the terrestrial biosphere on glacial–interglacial climate dynamics
Intra-interglacial climate variability: model simulations of Marine Isotope Stages 1, 5, 11, 13, and 15
A GCM comparison of Pleistocene super-interglacial periods in relation to Lake El'gygytgyn, NE Arctic Russia
Global sensitivity analysis of the Indian monsoon during the Pleistocene
Interaction of ice sheets and climate during the past 800 000 years
Simulating last interglacial climate with NorESM: role of insolation and greenhouse gases in the timing of peak warmth
Impact of geomagnetic excursions on atmospheric chemistry and dynamics
Assessing the impact of Laurentide Ice Sheet topography on glacial climate
Interdependence of the growth of the Northern Hemisphere ice sheets during the last glaciation: the role of atmospheric circulation
Different ocean states and transient characteristics in Last Glacial Maximum simulations and implications for deglaciation
Why could ice ages be unpredictable?
Assessing the impact of late Pleistocene megafaunal extinctions on global vegetation and climate
The last interglacial (Eemian) climate simulated by LOVECLIM and CCSM3
LGM permafrost distribution: how well can the latest PMIP multi-model ensembles perform reconstruction?
Tropical vegetation response to Heinrich Event 1 as simulated with the UVic ESCM and CCSM3
Influence of Last Glacial Maximum boundary conditions on the global water isotope distribution in an atmospheric general circulation model
A new global reconstruction of temperature changes at the Last Glacial Maximum
Modelling snow accumulation on Greenland in Eemian, glacial inception, and modern climates in a GCM
Modelling large-scale ice-sheet–climate interactions following glacial inception
Sensitivity of the North Atlantic climate to Greenland Ice Sheet melting during the Last Interglacial
The impact of different glacial boundary conditions on atmospheric dynamics and precipitation in the North Atlantic region
Present and LGM permafrost from climate simulations: contribution of statistical downscaling
The key role of topography in altering North Atlantic atmospheric circulation during the last glacial period
Modeling Mediterranean Ocean climate of the Last Glacial Maximum
A comparison of climate simulations for the last glacial maximum with three different versions of the ECHAM model and implications for summer-green tree refugia
Changes in atmospheric variability in a glacial climate and the impacts on proxy data: a model intercomparison
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.
Mi Yan, Bin Wang, Jian Liu, Axing Zhu, Liang Ning, and Jian Cao
Clim. Past, 14, 2037–2052, https://doi.org/10.5194/cp-14-2037-2018, https://doi.org/10.5194/cp-14-2037-2018, 2018
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
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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