Articles | Volume 7, issue 5
Model experiment description paper 16 Sep 2014
Model experiment description paper | 16 Sep 2014
A suite of early Eocene (~ 55 Ma) climate model boundary conditions
N. Herold et al.
No articles found.
Philip L. Woodworth, J. A. Mattias Green, Richard D. Ray, and John M. Huthnance
Ocean Sci., 17, 809–818,Short summary
This special issue marks the 100th anniversary of the founding of the Liverpool Tidal Institute (LTI). The preface gives a history of the LTI founding and of its first two directors. It also gives an overview of LTI research on tides. Summaries are given of the 26 papers in the special issue. Their topics could be thought of as providing a continuation of the research first undertaken at the LTI. They provide an interesting snapshot of work on tides now being made by groups around the world.
Julia Rulent, Lucy M. Bricheno, Mattias J. A. Green, Ivan D. Haigh, and Huw Lewis
Nat. Hazards Earth Syst. Sci. Discuss.,
Preprint under review for NHESSShort summary
High coastal total water levels (TWL) can lead to flooding and hazardous conditions for coastal communities and environment. In this research we are using numerical models to study the interactions between three main components of the TWL (waves, tides and surges) at the UK and Irish coasts during winter 2013/14. The main finding of this research is that extreme waves and surges can indeed happen together, even at high tide, but they often occurred simultaneously 2–3 hours before high tide.
Eline Le Breton, Sascha Brune, Kamil Ustaszewski, Sabin Zahirovic, Maria Seton, and R. Dietmar Müller
Solid Earth, 12, 885–913,Short summary
The former Piemont–Liguria Ocean, which separated Europe from Africa–Adria in the Jurassic, opened as an arm of the central Atlantic. Using plate reconstructions and geodynamic modeling, we show that the ocean reached only 250 km width between Europe and Adria. Moreover, at least 65 % of the lithosphere subducted into the mantle and/or incorporated into the Alps during convergence in Cretaceous and Cenozoic times comprised highly thinned continental crust, while only 35 % was truly oceanic.
David K. Hutchinson, Helen K. Coxall, Daniel J. Lunt, Margret Steinthorsdottir, Agatha M. de Boer, Michiel Baatsen, Anna von der Heydt, Matthew Huber, Alan T. Kennedy-Asser, Lutz Kunzmann, Jean-Baptiste Ladant, Caroline H. Lear, Karolin Moraweck, Paul N. Pearson, Emanuela Piga, Matthew J. Pound, Ulrich Salzmann, Howie D. Scher, Willem P. Sijp, Kasia K. Śliwińska, Paul A. Wilson, and Zhongshi Zhang
Clim. Past, 17, 269–315,Short summary
The Eocene–Oligocene transition was a major climate cooling event from a largely ice-free world to the first major glaciation of Antarctica, approximately 34 million years ago. This paper reviews observed changes in temperature, CO2 and ice sheets from marine and land-based records at this time. We present a new model–data comparison of this transition and find that CO2-forced cooling provides the best explanation of the observed global temperature changes.
Daniel J. Lunt, Fran Bragg, Wing-Le Chan, David K. Hutchinson, Jean-Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Ayako Abe-Ouchi, Eleni Anagnostou, Agatha M. de Boer, Helen K. Coxall, Yannick Donnadieu, Gavin Foster, Gordon N. Inglis, Gregor Knorr, Petra M. Langebroek, Caroline H. Lear, Gerrit Lohmann, Christopher J. Poulsen, Pierre Sepulchre, Jessica E. Tierney, Paul J. Valdes, Evgeny M. Volodin, Tom Dunkley Jones, Christopher J. Hollis, Matthew Huber, and Bette L. Otto-Bliesner
Clim. Past, 17, 203–227,Short summary
This paper presents the first modelling results from the Deep-Time Model Intercomparison Project (DeepMIP), in which we focus on the early Eocene climatic optimum (EECO, 50 million years ago). We show that, in contrast to previous work, at least three models (CESM, GFDL, and NorESM) produce climate states that are consistent with proxy indicators of global mean temperature and polar amplification, and they achieve this at a CO2 concentration that is consistent with the CO2 proxy record.
Michiel Baatsen, Anna S. von der Heydt, Matthew Huber, Michael A. Kliphuis, Peter K. Bijl, Appy Sluijs, and Henk A. Dijkstra
Clim. Past, 16, 2573–2597,Short summary
Warm climates of the deep past have proven to be challenging to reconstruct with the same numerical models used for future predictions. We present results of CESM simulations for the middle to late Eocene (∼ 38 Ma), in which we managed to match the available indications of temperature well. With these results we can now look into regional features and the response to external changes to ultimately better understand the climate when it is in such a warm state.
J. A. Mattias Green and David T. Pugh
Ocean Sci., 16, 1337–1345,Short summary
Bardsey Island lies 3 km offshore the western end of the Llŷn Peninsula in northwestern Wales. However, the island is too small to show up in tidal databases based on satellite data, and thus they may not provide the correct local tides. Our new sea level data shows that the tidal currents in the satellite databases are one-third of the observed currents. Any investigation of other coastal activities, e.g. renewable energy installations, must use local observations to get the correct tides.
Gordon N. Inglis, Fran Bragg, Natalie J. Burls, Margot J. Cramwinckel, David Evans, Gavin L. Foster, Matthew Huber, Daniel J. Lunt, Nicholas Siler, Sebastian Steinig, Jessica E. Tierney, Richard Wilkinson, Eleni Anagnostou, Agatha M. de Boer, Tom Dunkley Jones, Kirsty M. Edgar, Christopher J. Hollis, David K. Hutchinson, and Richard D. Pancost
Clim. Past, 16, 1953–1968,Short summary
This paper presents estimates of global mean surface temperatures and climate sensitivity during the early Paleogene (∼57–48 Ma). We employ a multi-method experimental approach and show that i) global mean surface temperatures range between 27 and 32°C and that ii) estimates of
bulkequilibrium climate sensitivity (∼3 to 4.5°C) fall within the range predicted by the IPCC AR5 Report. This work improves our understanding of two key climate metrics during the early Paleogene.
Rohitash Chandra, Danial Azam, Arpit Kapoor, and R. Dietmar Müller
Geosci. Model Dev., 13, 2959–2979,Short summary
Forward landscape and sedimentary basin evolution models pose a major challenge in the development of efficient inference and optimization methods. Bayesian inference provides a methodology for estimation and uncertainty quantification of free model parameters. In this paper, we present an application of a surrogate-assisted Bayesian parallel tempering method where that surrogate mimics a landscape evolution model. We use the method for parameter estimation and uncertainty quantification.
Marie Laugié, Yannick Donnadieu, Jean-Baptiste Ladant, J. A. Mattias Green, Laurent Bopp, and François Raisson
Clim. Past, 16, 953–971,Short summary
To quantify the impact of major climate forcings on the Cretaceous climate, we use Earth system modelling to progressively reconstruct the Cretaceous state by changing boundary conditions one by one. Between the preindustrial and the Cretaceous simulations, the model simulates a global warming of more than 11°C. The study confirms the primary control exerted by atmospheric CO2 on atmospheric temperatures. Palaeogeographic changes represent the second major contributor to the warming.
Hannah S. Davies, J. A. Mattias Green, and Joao C. Duarte
Earth Syst. Dynam., 11, 291–299,Short summary
We have confirmed that there is a supertidal cycle associated with the supercontinent cycle. As continents drift due to plate tectonics, oceans also change size, controlling the strength of the tides and causing periods of supertides. In this work, we used a coupled tectonic–tidal model of Earth's future to test four different scenarios that undergo different styles of ocean closure and periods of supertides. This has implications for the Earth system and for other planets with liquid oceans.
Christopher J. Hollis, Tom Dunkley Jones, Eleni Anagnostou, Peter K. Bijl, Margot J. Cramwinckel, Ying Cui, Gerald R. Dickens, Kirsty M. Edgar, Yvette Eley, David Evans, Gavin L. Foster, Joost Frieling, Gordon N. Inglis, Elizabeth M. Kennedy, Reinhard Kozdon, Vittoria Lauretano, Caroline H. Lear, Kate Littler, Lucas Lourens, A. Nele Meckler, B. David A. Naafs, Heiko Pälike, Richard D. Pancost, Paul N. Pearson, Ursula Röhl, Dana L. Royer, Ulrich Salzmann, Brian A. Schubert, Hannu Seebeck, Appy Sluijs, Robert P. Speijer, Peter Stassen, Jessica Tierney, Aradhna Tripati, Bridget Wade, Thomas Westerhold, Caitlyn Witkowski, James C. Zachos, Yi Ge Zhang, Matthew Huber, and Daniel J. Lunt
Geosci. Model Dev., 12, 3149–3206,Short summary
The Deep-Time Model Intercomparison Project (DeepMIP) is a model–data intercomparison of the early Eocene (around 55 million years ago), the last time that Earth's atmospheric CO2 concentrations exceeded 1000 ppm. Previously, we outlined the experimental design for climate model simulations. Here, we outline the methods used for compilation and analysis of climate proxy data. The resulting climate
atlaswill provide insights into the mechanisms that control past warm climate states.
Alexander Harker, J. A. Mattias Green, Michael Schindelegger, and Sophie-Berenice Wilmes
Ocean Sci., 15, 147–159,Short summary
We used a computer model to help predict how changing sea levels around Australia will affect the ebb and flow of the tide. We found that sea-level rise and coastal flooding affect where energy from the tide is dissipated and how the tide flows around the coastline. We found that we must consider how sea-level rise will affect tides across the rest of the world, as that will have an impact on Australia too. This sort of investigation can help direct coastal management and protection efforts.
Hugo K. H. Olierook, Richard Scalzo, David Kohn, Rohitash Chandra, Ehsan Farahbakhsh, Gregory Houseman, Chris Clark, Steven M. Reddy, and R. Dietmar Müller
Solid Earth Discuss.,
Revised manuscript not accepted
Sascha Brune, Simon E. Williams, and R. Dietmar Müller
Solid Earth, 9, 1187–1206,Short summary
Fragmentation of continents often involves obliquely rifting segments that feature a complex three-dimensional structural evolution. Here we show that more than ~ 70 % of Earth’s rifted margins exceeded an obliquity of 20° demonstrating that oblique rifting should be considered the rule, not the exception. This highlights the importance of three-dimensional approaches in modelling, surveying, and interpretation of those rift segments where oblique rifting is the dominant mode of deformation.
Robert McKay, Neville Exon, Dietmar Müller, Karsten Gohl, Michael Gurnis, Amelia Shevenell, Stuart Henrys, Fumio Inagaki, Dhananjai Pandey, Jessica Whiteside, Tina van de Flierdt, Tim Naish, Verena Heuer, Yuki Morono, Millard Coffin, Marguerite Godard, Laura Wallace, Shuichi Kodaira, Peter Bijl, Julien Collot, Gerald Dickens, Brandon Dugan, Ann G. Dunlea, Ron Hackney, Minoru Ikehara, Martin Jutzeler, Lisa McNeill, Sushant Naik, Taryn Noble, Bradley Opdyke, Ingo Pecher, Lowell Stott, Gabriele Uenzelmann-Neben, Yatheesh Vadakkeykath, and Ulrich G. Wortmann
Sci. Dril., 24, 61–70,
J. A. Mattias Green, David G. Bowers, and Hannah A. M. Byrne
Ocean Sci. Discuss.,
Preprint withdrawnShort summary
In a double tide the ocean reaches high or low tide, starts to fall or rise, only to go back to a new high or low. Here, we describe three ways this can happen by dividing locations with observed double tides into three classes. This showed that double tides are more common than we thought, and more complicated than most textbooks claim because they only describe one class of double tides. This matters to shipping, coastal flood management, and other disciplines interested in sea-level change.
Jodie Pall, Sabin Zahirovic, Sebastiano Doss, Rakib Hassan, Kara J. Matthews, John Cannon, Michael Gurnis, Louis Moresi, Adrian Lenardic, and R. Dietmar Müller
Clim. Past, 14, 857–870,Short summary
Subduction zones intersecting buried carbonate platforms liberate significant atmospheric CO2 and have the potential to influence global climate. We model the spatio-temporal distribution of carbonate platform accumulation within a plate tectonic framework and use wavelet analysis to analyse linked behaviour between atmospheric CO2 and carbonate-intersecting subduction zone (CISZ) lengths since the Devonian. We find that increasing CISZ lengths likely contributed to a warmer Palaeogene climate.
Michiel Baatsen, Anna S. von der Heydt, Matthew Huber, Michael A. Kliphuis, Peter K. Bijl, Appy Sluijs, and Henk A. Dijkstra
Clim. Past Discuss.,
Revised manuscript not acceptedShort summary
The Eocene marks a period where the climate was in a hothouse state, without any continental-scale ice sheets. Such climates have proven difficult to reproduce in models, especially their low temperature difference between equator and poles. Here, we present high resolution CESM simulations using a new geographic reconstruction of the middle-to-late Eocene. The results provide new insights into a period for which knowledge is limited, leading up to a transition into the present icehouse state.
Wenchao Cao, Sabin Zahirovic, Nicolas Flament, Simon Williams, Jan Golonka, and R. Dietmar Müller
Biogeosciences, 14, 5425–5439,Short summary
We present a workflow to link paleogeographic maps to alternative plate tectonic models, alleviating the problem that published global paleogeographic maps are generally presented as static maps and tied to a particular plate model. We further develop an approach to improve paleogeography using paleobiology. The resulting paleogeographies are consistent with proxies of eustatic sea level change since ~400 Myr ago. We make the digital global paleogeographic maps available as an open resource.
Gary Shaffer, Esteban Fernández Villanueva, Roberto Rondanelli, Jens Olaf Pepke Pedersen, Steffen Malskær Olsen, and Matthew Huber
Geosci. Model Dev., 10, 4081–4103,Short summary
We include methane cycling in the simplified but well-tested Danish Center for Earth System Science model. We now can deal with very large methane inputs to the Earth system that can lead to more methane in the atmosphere, extreme warming and ocean dead zones. We can now study ancient global warming events, probably forced by methane inputs. Some such events were accompanied by mass extinctions. We wish to understand such events, both for learning about the past and for looking into the future.
Michael Rubey, Sascha Brune, Christian Heine, D. Rhodri Davies, Simon E. Williams, and R. Dietmar Müller
Solid Earth, 8, 899–919,Short summary
Earth's surface is constantly warped up and down by the convecting mantle. Here we derive geodynamic rules for this so-called
dynamic topographyby employing high-resolution numerical models of global mantle convection. We define four types of dynamic topography history that are primarily controlled by the ever-changing pattern of Earth's subduction zones. Our models provide a predictive quantitative framework linking mantle convection with plate tectonics and sedimentary basin evolution.
Hannah A. M. Byrne, J. A. Mattias Green, and David G. Bowers
Ocean Sci., 13, 599–607,Short summary
Some places experience double high tides, where the tide starts to ebb for a short while, only to briefly flood again before finally receding. The result is a very long high tide with weak currents, and is important for navigational purposes. The existing theory for when and where double high tides occur does not always capture them, and it can only be applied to double highs occurring on a twice-daily tide. Here, the criterion has been generalized to capture all double high or low tides.
Daniel J. Lunt, Matthew Huber, Eleni Anagnostou, Michiel L. J. Baatsen, Rodrigo Caballero, Rob DeConto, Henk A. Dijkstra, Yannick Donnadieu, David Evans, Ran Feng, Gavin L. Foster, Ed Gasson, Anna S. von der Heydt, Chris J. Hollis, Gordon N. Inglis, Stephen M. Jones, Jeff Kiehl, Sandy Kirtland Turner, Robert L. Korty, Reinhardt Kozdon, Srinath Krishnan, Jean-Baptiste Ladant, Petra Langebroek, Caroline H. Lear, Allegra N. LeGrande, Kate Littler, Paul Markwick, Bette Otto-Bliesner, Paul Pearson, Christopher J. Poulsen, Ulrich Salzmann, Christine Shields, Kathryn Snell, Michael Stärz, James Super, Clay Tabor, Jessica E. Tierney, Gregory J. L. Tourte, Aradhna Tripati, Garland R. Upchurch, Bridget S. Wade, Scott L. Wing, Arne M. E. Winguth, Nicky M. Wright, James C. Zachos, and Richard E. Zeebe
Geosci. Model Dev., 10, 889–901,Short summary
In this paper we describe the experimental design for a set of simulations which will be carried out by a range of climate models, all investigating the climate of the Eocene, about 50 million years ago. The intercomparison of model results is called 'DeepMIP', and we anticipate that we will contribute to the next IPCC report through an analysis of these simulations and the geological data to which we will compare them.
Nicholas Barnett-Moore, Rakib Hassan, Nicolas Flament, and Dietmar Müller
Solid Earth, 8, 235–254,Short summary
We use 3D mantle flow models to investigate the evolution of the Iceland plume in the North Atlantic. Results show that over the last ~ 100 Myr a remarkably stable pattern of flow in the lowermost mantle beneath the region resulted in the formation of a plume nucleation site. At the surface, a model plume compared to published observables indicates that its large plume head, ~ 2500 km in diameter, arriving beneath eastern Greenland in the Palaeocene, can account for the volcanic record and uplift.
Daniel J. Lunt, Alex Farnsworth, Claire Loptson, Gavin L. Foster, Paul Markwick, Charlotte L. O'Brien, Richard D. Pancost, Stuart A. Robinson, and Neil Wrobel
Clim. Past, 12, 1181–1198,Short summary
We explore the influence of changing geography from the period ~ 150 million years ago to ~ 35 million years ago, using a set of 19 climate model simulations. We find that without any CO2 change, the global mean temperature is remarkably constant, but that regionally there are significant changes in temperature which we link back to changes in ocean circulation. Finally, we explore the implications of our findings for the interpretation of geological indicators of past temperatures.
Matthew J. Carmichael, Daniel J. Lunt, Matthew Huber, Malte Heinemann, Jeffrey Kiehl, Allegra LeGrande, Claire A. Loptson, Chris D. Roberts, Navjit Sagoo, Christine Shields, Paul J. Valdes, Arne Winguth, Cornelia Winguth, and Richard D. Pancost
Clim. Past, 12, 455–481,Short summary
In this paper, we assess how well model-simulated precipitation rates compare to those indicated by geological data for the early Eocene, a warm interval 56–49 million years ago. Our results show that a number of models struggle to produce sufficient precipitation at high latitudes, which likely relates to cool simulated temperatures in these regions. However, calculating precipitation rates from plant fossils is highly uncertain, and further data are now required.
S. H. R. Rosier, G. H. Gudmundsson, and J. A. M. Green
The Cryosphere, 9, 1649–1661,Short summary
We use a full-Stokes model to investigate the long period modulation of Rutford Ice Stream flow by the ocean tide. We find that using a nonlinear sliding law cannot fully explain the measurements and an additional mechanism, whereby tidally induced subglacial pressure variations are transmitted upstream from the grounding line, is also required to match the large amplitude and decay length scale of the observations.
J. R. Buzan, K. Oleson, and M. Huber
Geosci. Model Dev., 8, 151–170,Short summary
We implemented the HumanIndexMod, which calculates 13 diagnostic heat stress metrics, into the Community Land Model (CLM4.5). The goal of this module is to have a common predictive framework for measuring heat stress globally. These metrics are in operational use by weather forecasters, industry, and agriculture. We show metric-dependent results of regional partitioning of extreme moisture and temperature levels in a 1901-2010 simulation.
S. H. R. Rosier, G. H. Gudmundsson, and J. A. M. Green
The Cryosphere, 8, 1763–1775,
J. Cannon, E. Lau, and R. D. Müller
Solid Earth, 5, 741–755,
S. Zahirovic, M. Seton, and R. D. Müller
Solid Earth, 5, 227–273,
S. J. Gallagher, N. Exon, M. Seton, M. Ikehara, C. J. Hollis, R. Arculus, S. D'Hondt, C. Foster, M. Gurnis, J. P. Kennett, R. McKay, A. Malakoff, J. Mori, K. Takai, and L. Wallace
Sci. Dril., 17, 45–50,
A. Goldner, N. Herold, and M. Huber
Clim. Past, 10, 523–536,
E. Gasson, D. J. Lunt, R. DeConto, A. Goldner, M. Heinemann, M. Huber, A. N. LeGrande, D. Pollard, N. Sagoo, M. Siddall, A. Winguth, and P. J. Valdes
Clim. Past, 10, 451–466,
M. Hosseinpour, R. D. Müller, S. E. Williams, and J. M. Whittaker
Solid Earth, 4, 461–479,
C. Heine, J. Zoethout, and R. D. Müller
Solid Earth, 4, 215–253,
N. Wright, S. Zahirovic, R. D. Müller, and M. Seton
Biogeosciences, 10, 1529–1541,
A. Goldner, M. Huber, and R. Caballero
Clim. Past, 9, 173–189,
R. L. Sriver, M. Huber, and L. Chafik
Earth Syst. Dynam., 4, 1–10,
R. D. Müller and T. C. W. Landgrebe
Solid Earth, 3, 447–465,
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Klaus Klingmüller and Jos Lelieveld
Geosci. Model Dev., 14, 4429–4441,Short summary
Soil moisture is of great importance for weather and climate. We present a machine learning model that produces accurate predictions of satellite-observed surface soil moisture, based on meteorological data from a climate model. It can be used as soil moisture parametrisation in climate models and to produce comprehensive global soil moisture datasets. Moreover, it may motivate similar applications of machine learning in climate science.
Jeremy McGibbon, Noah D. Brenowitz, Mark Cheeseman, Spencer K. Clark, Johann P. S. Dahm, Eddie C. Davis, Oliver D. Elbert, Rhea C. George, Lucas M. Harris, Brian Henn, Anna Kwa, W. Andre Perkins, Oliver Watt-Meyer, Tobias F. Wicky, Christopher S. Bretherton, and Oliver Fuhrer
Geosci. Model Dev., 14, 4401–4409,Short summary
FV3GFS is a weather and climate model written in Fortran. It uses Fortran so that it can run fast, but this makes it hard to add features if you do not (or even if you do) know Fortran. We have written a Python interface to FV3GFS that lets you import the Fortran model as a Python package. We show examples of how this is used to write
modelscripts, which reproduce or build on what the Fortran model can do. You could do this same wrapping for any compiled model, not just FV3GFS.
Alexander Pasternack, Jens Grieger, Henning W. Rust, and Uwe Ulbrich
Geosci. Model Dev., 14, 4335–4355,Short summary
Decadal climate ensemble forecasts are increasingly being used to guide adaptation measures. To ensure the applicability of these probabilistic predictions, inherent systematic errors of the prediction system must be adjusted. Since it is not clear which statistical model is optimal for this purpose, we propose a recalibration strategy with a systematic model selection based on non-homogeneous boosting for identifying the most relevant features for both ensemble mean and ensemble spread.
Daniel J. Lunt, Deepak Chandan, Alan M. Haywood, George M. Lunt, Jonathan C. Rougier, Ulrich Salzmann, Gavin A. Schmidt, and Paul J. Valdes
Geosci. Model Dev., 14, 4307–4317,Short summary
Often in science we carry out experiments with computers in which several factors are explored, for example, in the field of climate science, how the factors of greenhouse gases, ice, and vegetation affect temperature. We can explore the relative importance of these factors by
swapping in and outdifferent values of these factors, and can also carry out experiments with many different combinations of these factors. This paper discusses how best to analyse the results from such experiments.
Markus Adloff, Andy Ridgwell, Fanny M. Monteiro, Ian J. Parkinson, Alexander J. Dickson, Philip A. E. Pogge von Strandmann, Matthew S. Fantle, and Sarah E. Greene
Geosci. Model Dev., 14, 4187–4223,Short summary
We present the first representation of the trace metals Sr, Os, Li and Ca in a 3D Earth system model (cGENIE). The simulation of marine metal sources (weathering, hydrothermal input) and sinks (deposition) reproduces the observed concentrations and isotopic homogeneity of these metals in the modern ocean. With these new tracers, cGENIE can be used to test hypotheses linking these metal cycles and the cycling of other elements like O and C and simulate their dynamic response to external forcing.
Alessandro Anav, Adriana Carillo, Massimiliano Palma, Maria Vittoria Struglia, Ufuk Utku Turuncoglu, and Gianmaria Sannino
Geosci. Model Dev., 14, 4159–4185,Short summary
The Mediterranean Basin is a complex region, characterized by the presence of pronounced topography and a complex land–sea distribution including a considerable number of islands and straits; these features generate strong local atmosphere–sea interactions. Regional Earth system models have been developed and used to study both present and future Mediterranean climate systems. The main aims of this paper are to present and evaluate the newly developed regional Earth system model ENEA-REG.
Markus Drüke, Werner von Bloh, Stefan Petri, Boris Sakschewski, Sibyll Schaphoff, Matthias Forkel, Willem Huiskamp, Georg Feulner, and Kirsten Thonicke
Geosci. Model Dev., 14, 4117–4141,Short summary
In this study, we couple the well-established and comprehensively validated state-of-the-art dynamic LPJmL5 global vegetation model to the CM2Mc coupled climate model (CM2Mc-LPJmL v.1.0). Several improvements to LPJmL5 were implemented to allow a fully functional biophysical coupling. The new climate model is able to capture important biospheric processes, including fire, mortality, permafrost, hydrological cycling and the the impacts of managed land (crop growth and irrigation).
Dirk Barbi, Nadine Wieters, Paul Gierz, Miguel Andrés-Martínez, Deniz Ural, Fatemeh Chegini, Sara Khosravi, and Luisa Cristini
Geosci. Model Dev., 14, 4051–4067,
Cléa Denamiel, Petra Pranić, Damir Ivanković, Iva Tojčić, and Ivica Vilibić
Geosci. Model Dev., 14, 3995–4017,Short summary
The atmospheric results of the Adriatic Sea and Coast (AdriSC) climate simulation (1987–2017) are evaluated against available observational datasets in the Adriatic region. Generally, the AdriSC model performs better than regional climate models that have resolutions that are 4 times more coarse, except concerning summer temperatures, which are systematically underestimated. High-resolution climate models may thus provide new insights about the local impacts of global warming in the Adriatic.
Geosci. Model Dev., 14, 3603–3631,Short summary
Sea-floor sediments play an important role in biogeochemical cycling of elements (e.g. carbon, silicon, nutrients) in the ocean. Realistic sediment modules are, however, not yet commonly used in global ocean biogeochemical models. Here we present MEDUSA, a model of the processes taking place in the surface sea-floor sediments which control the interaction between the sediments and the ocean. MEDUSA can be configured to meet the exact needs of any given ocean biogeochemical model.
Max Kulinich, Yanan Fan, Spiridon Penev, Jason P. Evans, and Roman Olson
Geosci. Model Dev., 14, 3539–3551,Short summary
We present a novel stochastic approach based on Markov chains to estimate climate model weights of multi-model ensemble means. This approach showed improved performance (better correlation with observations) over existing alternatives during cross-validation and model-as-truth tests. The results of this comparative analysis should serve to motivate further studies in applications of Markov chain and other nonlinear methods to find optimal model weights for constructing ensemble means.
Jens Pfafferott, Sascha Rißmann, Matthias Sühring, Farah Kanani-Sühring, and Björn Maronga
Geosci. Model Dev., 14, 3511–3519,Short summary
The building model is integrated via an urban surface model into the urban climate model. There is a strong interaction between the built environment and the urban climate. According to the building energy concept, the energy demand results in a waste heat; this is directly transferred to the urban environment. The impact of buildings on the urban climate is defined by different physical building parameters with different technical facilities for ventilation, heating and cooling.
Anna B. Harper, Karina E. Williams, Patrick C. McGuire, Maria Carolina Duran Rojas, Debbie Hemming, Anne Verhoef, Chris Huntingford, Lucy Rowland, Toby Marthews, Cleiton Breder Eller, Camilla Mathison, Rodolfo L. B. Nobrega, Nicola Gedney, Pier Luigi Vidale, Fred Otu-Larbi, Divya Pandey, Sebastien Garrigues, Azin Wright, Darren Slevin, Martin G. De Kauwe, Eleanor Blyth, Jonas Ardö, Andrew Black, Damien Bonal, Nina Buchmann, Benoit Burban, Kathrin Fuchs, Agnès de Grandcourt, Ivan Mammarella, Lutz Merbold, Leonardo Montagnani, Yann Nouvellon, Natalia Restrepo-Coupe, and Georg Wohlfahrt
Geosci. Model Dev., 14, 3269–3294,Short summary
We evaluated 10 representations of soil moisture stress in the JULES land surface model against site observations of GPP and latent heat flux. Increasing the soil depth and plant access to deep soil moisture improved many aspects of the simulations, and we recommend these settings in future work using JULES. In addition, using soil matric potential presents the opportunity to include parameters specific to plant functional type to further improve modeled fluxes.
Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
Geosci. Model Dev., 14, 3159–3184,Short summary
This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
Jun'ya Takakura, Shinichiro Fujimori, Kiyoshi Takahashi, Naota Hanasaki, Tomoko Hasegawa, Yukiko Hirabayashi, Yasushi Honda, Toshichika Iizumi, Chan Park, Makoto Tamura, and Yasuaki Hijioka
Geosci. Model Dev., 14, 3121–3140,Short summary
To simplify calculating economic impacts of climate change, statistical methods called emulators are developed and evaluated. There are trade-offs between model complexity and emulation performance. Aggregated economic impacts can be approximated by relatively simple emulators, but complex emulators are necessary to accommodate finer-scale economic impacts.
Meng-Zhuo Zhang, Zhongfeng Xu, Ying Han, and Weidong Guo
Geosci. Model Dev., 14, 3079–3094,Short summary
The Multivariable Integrated Evaluation Tool (MVIETool) is a simple-to-use and straightforward tool designed for evaluation and intercomparison of climate models in terms of vector fields or multiple fields. The tool incorporates some new improvements in vector field evaluation (VFE) and multivariable integrated evaluation (MVIE) methods, which are introduced in this paper.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077,Short summary
The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Nicholas J. Leach, Stuart Jenkins, Zebedee Nicholls, Christopher J. Smith, John Lynch, Michelle Cain, Tristram Walsh, Bill Wu, Junichi Tsutsui, and Myles R. Allen
Geosci. Model Dev., 14, 3007–3036,Short summary
This paper presents an update of the FaIR simple climate model, which can estimate the impact of anthropogenic greenhouse gas and aerosol emissions on the global climate. This update aims to significantly increase the structural simplicity of the model, making it more understandable and transparent. This simplicity allows it to be implemented in a wide range of environments, including Excel. We suggest that it could be used widely in academia, corporate research, and education.
Tongwen Wu, Rucong Yu, Yixiong Lu, Weihua Jie, Yongjie Fang, Jie Zhang, Li Zhang, Xiaoge Xin, Laurent Li, Zaizhi Wang, Yiming Liu, Fang Zhang, Fanghua Wu, Min Chu, Jianglong Li, Weiping Li, Yanwu Zhang, Xueli Shi, Wenyan Zhou, Junchen Yao, Xiangwen Liu, He Zhao, Jinghui Yan, Min Wei, Wei Xue, Anning Huang, Yaocun Zhang, Yu Zhang, Qi Shu, and Aixue Hu
Geosci. Model Dev., 14, 2977–3006,Short summary
This paper presents the high-resolution version of the Beijing Climate Center (BCC) Climate System Model, BCC-CSM2-HR, and describes its climate simulation performance including the atmospheric temperature and wind; precipitation; and the tropical climate phenomena such as TC, MJO, QBO, and ENSO. BCC-CSM2-HR is our model version contributing to the HighResMIP. We focused on its updates and differential characteristics from its predecessor, the medium-resolution version BCC-CSM2-MR.
Olivier Marti, Sébastien Nguyen, Pascale Braconnot, Sophie Valcke, Florian Lemarié, and Eric Blayo
Geosci. Model Dev., 14, 2959–2975,Short summary
State-of-the-art Earth system models, like the ones used in CMIP6, suffer from temporal inconsistencies at the ocean–atmosphere interface. In this study, a mathematically consistent iterative Schwarz method is used as a reference. Its tremendous computational cost makes it unusable for production runs, but it allows us to evaluate the error made when using legacy coupling schemes. The impact on the climate at longer timescales of days to decades is not evaluated.
Steven R. Brus, Phillip J. Wolfram, Luke P. Van Roekel, and Jessica D. Meixner
Geosci. Model Dev., 14, 2917–2938,Short summary
Wind-generated waves are an important process in the global climate system. They mediate many interactions between the ocean, atmosphere, and sea ice. Models which describe these waves are computationally expensive and have often been excluded from coupled Earth system models. To address this, we have developed a capability for the WAVEWATCH III model which allows model resolution to be varied globally across the coastal open ocean. This allows for improved accuracy at reduced computing time.
Elisa Ziegler and Kira Rehfeld
Geosci. Model Dev., 14, 2843–2866,Short summary
Past climate changes are the only record of how the climate responds to changes in conditions on Earth, but simulations with complex climate models are challenging. We extended a simple climate model such that it simulates the development of temperatures over time. In the model, changes in carbon dioxide and ice distribution affect the simulated temperatures the most. The model is very efficient and can therefore be used to examine past climate changes happening over long periods of time.
Qun Liu, Matthew Collins, Penelope Maher, Stephen I. Thomson, and Geoffrey K. Vallis
Geosci. Model Dev., 14, 2801–2826,Short summary
Clouds play an vital role in Earth's energy budget, and even a small change in cloud fields can have a large impact on the climate system. They also bring lots of uncertainties to climate models. Here we implement a simple diagnostic cloud scheme in order to reproduce the general radiative properties of clouds. The scheme can capture some key features of the cloud fraction and cloud radiative properties and thus provide a useful tool to explore unsolved problems relating to clouds.
Martina Messmer, Santos J. González-Rojí, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 14, 2691–2711,Short summary
Sensitivity experiments with the WRF model are run to find an optimal parameterization setup for precipitation around Mount Kenya at a scale that resolves convection (1 km). Precipitation is compared against many weather stations and gridded observational data sets. Both the temporal correlation of precipitation sums and pattern correlations show that fewer nests lead to a more constrained simulation with higher correlation. The Grell–Freitas cumulus scheme obtains the most accurate results.
Pengfei Wang, Jinrong Jiang, Pengfei Lin, Mengrong Ding, Junlin Wei, Feng Zhang, Lian Zhao, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yongqiang Yu, Xuebin Chi, and Hailong Liu
Geosci. Model Dev., 14, 2781–2799,Short summary
Global ocean general circulation models are a fundamental tool for oceanography research, ocean forecast, and climate change research. The increasing resolution will greatly improve simulations of the models, but it also demands much more computing resources. In this study, we have ported an ocean general circulation model to a heterogeneous computing system and have developed a 3–5 km model version. A 14-year integration has been conducted and the preliminary results have been evaluated.
Chao Sun, Li Liu, Ruizhe Li, Xinzhu Yu, Hao Yu, Biao Zhao, Guansuo Wang, Juanjuan Liu, Fangli Qiao, and Bin Wang
Geosci. Model Dev., 14, 2635–2657,Short summary
Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.
Andrew J. Wiltshire, Eleanor J. Burke, Sarah E. Chadburn, Chris D. Jones, Peter M. Cox, Taraka Davies-Barnard, Pierre Friedlingstein, Anna B. Harper, Spencer Liddicoat, Stephen Sitch, and Sönke Zaehle
Geosci. Model Dev., 14, 2161–2186,Short summary
Limited nitrogen availbility can restrict the growth of plants and their ability to assimilate carbon. It is important to include the impact of this process on the global land carbon cycle. This paper presents a model of the coupled land carbon and nitrogen cycle, which is included within the UK Earth System model to improve projections of climate change and impacts on ecosystems.
Pirkka Ollinaho, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom, and Heikki Järvinen
Geosci. Model Dev., 14, 2143–2160,Short summary
OpenEnsemble 1.0 is a novel dataset that aims to open ensemble or probabilistic weather forecasting research up to the academic community. The dataset contains atmospheric states that are required for running model forecasts of atmospheric evolution. Our capacity to observe the atmosphere is limited; thus, a single reconstruction of the atmospheric state contains some errors. Our dataset provides sets of 50 slightly different atmospheric states so that these errors can be taken into account.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010,Short summary
We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Hui Wan, Shixuan Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, and Huiping Yan
Geosci. Model Dev., 14, 1921–1948,Short summary
Numerical models used in weather and climate research and prediction unavoidably contain numerical errors resulting from temporal discretization, and the impact of such errors can be substantial. Complex process interactions often make it difficult to pinpoint the exact sources of such errors. This study uses a series of sensitivity experiments to identify components in a global atmosphere model that are responsible for time step sensitivities in various cloud regimes.
Johannes Horak, Marlis Hofer, Ethan Gutmann, Alexander Gohm, and Mathias W. Rotach
Geosci. Model Dev., 14, 1657–1680,Short summary
This process-based evaluation of the atmospheric model ICAR is conducted to derive recommendations to increase the likelihood of its results being correct for the right reasons. We conclude that a different diagnosis of the atmospheric background state is necessary, as well as a model top at an elevation of at least 10 km. Alternative boundary conditions at the top were not found to be effective in reducing this model top elevation. The results have wide implications for future ICAR studies.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593,Short summary
A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Sonia Jerez, Laura Palacios-Peña, Claudia Gutiérrez, Pedro Jiménez-Guerrero, Jose María López-Romero, Enrique Pravia-Sarabia, and Juan Pedro Montávez
Geosci. Model Dev., 14, 1533–1551,Short summary
This research explores the role of aerosols when modeling surface solar radiation at regional scales (over Europe). A set of model experiments was performed with and without dynamical modeling of atmospheric aerosols and their direct and indirect effects on radiation. Results showed significant differences in the simulated solar radiation, mainly driven by the aerosol impact on cloudiness, which calls for caution when interpreting model experiments that do not include aerosols.
Sara Top, Lola Kotova, Lesley De Cruz, Svetlana Aniskevich, Leonid Bobylev, Rozemien De Troch, Natalia Gnatiuk, Anne Gobin, Rafiq Hamdi, Arne Kriegsmann, Armelle Reca Remedio, Abdulla Sakalli, Hans Van De Vyver, Bert Van Schaeybroeck, Viesturs Zandersons, Philippe De Maeyer, Piet Termonia, and Steven Caluwaerts
Geosci. Model Dev., 14, 1267–1293,Short summary
Detailed climate data are needed to assess the impact of climate change on human and natural systems. The performance of two high-resolution regional climate models, ALARO-0 and REMO2015, was investigated over central Asia, a vulnerable region where detailed climate information is scarce. In certain subregions the produced climate data are suitable for impact studies, but bias adjustment is required for subregions where significant biases have been identified.
Yaqiong Lu and Xianyu Yang
Geosci. Model Dev., 14, 1253–1265,Short summary
Crop growth in land surface models normally requires high-temporal-resolution climate data, but such high-temporal-resolution climate data are not provided by many climate model simulations due to expensive storage, which limits modeling choices if there is an interest in a particular climate simulation that only saved monthly outputs. Our work provides an alternative way to use the monthly climate for crop yield projections. Such an approach could be easily adopted by other crop models.
Rumi Ohgaito, Akitomo Yamamoto, Tomohiro Hajima, Ryouta O'ishi, Manabu Abe, Hiroaki Tatebe, Ayako Abe-Ouchi, and Michio Kawamiya
Geosci. Model Dev., 14, 1195–1217,Short summary
Using the MIROC-ES2L Earth system model, selected time periods of the past were simulated. The ability to simulate the past is also an evaluation of the performance of the model in projecting global warming. Simulations for 21 000, 6000, and 127 000 years ago, and a simulation for 1000 years starting in 850 CE were simulated. The results showed that the model can generally describe past climate change.
Qiong Zhang, Ellen Berntell, Josefine Axelsson, Jie Chen, Zixuan Han, Wesley de Nooijer, Zhengyao Lu, Qiang Li, Qiang Zhang, Klaus Wyser, and Shuting Yang
Geosci. Model Dev., 14, 1147–1169,Short summary
Paleoclimate modelling has long been regarded as a strong out-of-sample test bed of the climate models that are used for the projection of future climate changes. Here, we document the model experimental setups for the three past warm periods with EC-Earth3-LR and present the results on the large-scale features. The simulations demonstrate good performance of the model in capturing the climate response under different climate forcings.
Gill M. Martin, Richard C. Levine, José M. Rodriguez, and Michael Vellinga
Geosci. Model Dev., 14, 1007–1035,Short summary
Our study highlights a number of different techniques that can be employed to investigate the sources of model error. We demonstrate how this methodology can be used to identify the regions and model components responsible for the development of long-standing errors in the Asian summer monsoon. Once these are known, further work can be done to explore the local processes contributing to this behaviour and their sensitivity to changes in physical parameterisations and/or model resolution.
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Paniz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia and Africa. How the model configuration, horizontal and vertical resolution and choice of driving data is influencing the model performance for the five domains is assessed, with the purpose to aid the planning and design of regional climate simulations in the future.
Trang Van Pham, Christian Steger, Burkhardt Rockel, Klaus Keuler, Ingo Kirchner, Mariano Mertens, Daniel Rieger, Günther Zängl, and Barbara Früh
Geosci. Model Dev., 14, 985–1005,Short summary
A new regional climate model was prepared based on a weather forecast model. Slow processes of the climate system such as ocean state development and greenhouse gas emissions were implemented. A model infrastructure and evaluation tools were also prepared to facilitate long-term simulations and model evalution. The first ICON-CLM results were close to observations and comparable to those from COSMO-CLM, the recommended model being used at the Deutscher Wetterdienst and CLM Community.
Klaus Wyser, Torben Koenigk, Uwe Fladrich, Ramon Fuentes-Franco, Mehdi Pasha Karami, and Tim Kruschke
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
This paper describes the large ensemble done by SMHI with the EC-Earth3 climate model. The ensemble comprises 50 realisations of the historical experiment and four different future projections for CMIP6. We describe the creation of the initial states for the large ensemble and the reduced set of output variables. A first look at the results illustrates the changes in the climate during this century and puts them in relation to the uncertainty from the model's internal variability.
Michael Steiner, Beiping Luo, Thomas Peter, Michael C. Pitts, and Andrea Stenke
Geosci. Model Dev., 14, 935–959,Short summary
We evaluate polar stratospheric clouds (PSCs) as simulated by the chemistry–climate model (CCM) SOCOLv3.1 in comparison with measurements by the CALIPSO satellite. A cold bias results in an overestimated PSC area and mountain-wave ice is underestimated, but we find overall good temporal and spatial agreement of PSC occurrence and composition. This work confirms previous studies indicating that simplified PSC schemes may also achieve good approximations of the fundamental properties of PSCs.
Zhaoyuan Yu, Dongshuang Li, Zhengfang Zhang, Wen Luo, Yuan Liu, Zengjie Wang, and Linwang Yuan
Geosci. Model Dev., 14, 875–887,Short summary
Few lossy compression methods consider both the global and local multidimensional coupling correlations, which could lead to information loss in data compression. Here we develop an adaptive lossy compression method, Adaptive-HGFDR, to capture both the global and local variation of multidimensional coupling correlations and improve approximation accuracy. The method can achieve good compression performances for most flux variables with significant spatiotemporal heterogeneity.
Franziska Winterstein and Patrick Jöckel
Geosci. Model Dev., 14, 661–674,Short summary
Atmospheric methane is currently a hot topic in climate research. This is partly due to its chemically active nature. We introduce a simplified approach to simulate methane in climate models to enable large sensitivity studies by reducing computational cost but including the crucial feedback of methane on stratospheric water vapour. We further provide options to simulate the isotopic content of methane and to generate output for an inverse optimization technique for emission estimation.
Ruth Petrie, Sébastien Denvil, Sasha Ames, Guillaume Levavasseur, Sandro Fiore, Chris Allen, Fabrizio Antonio, Katharina Berger, Pierre-Antoine Bretonnière, Luca Cinquini, Eli Dart, Prashanth Dwarakanath, Kelsey Druken, Ben Evans, Laurent Franchistéguy, Sébastien Gardoll, Eric Gerbier, Mark Greenslade, David Hassell, Alan Iwi, Martin Juckes, Stephan Kindermann, Lukasz Lacinski, Maria Mirto, Atef Ben Nasser, Paola Nassisi, Eric Nienhouse, Sergey Nikonov, Alessandra Nuzzo, Clare Richards, Syazwan Ridzwan, Michel Rixen, Kim Serradell, Kate Snow, Ag Stephens, Martina Stockhause, Hans Vahlenkamp, and Rick Wagner
Geosci. Model Dev., 14, 629–644,Short summary
This paper describes the infrastructure that is used to distribute Coupled Model Intercomparison Project Phase 6 (CMIP6) data around the world for analysis by the climate research community. It is expected that there will be ~20 PB (petabytes) of data available for analysis. The operations team performed a series of preparation "data challenges" to ensure all components of the infrastructure were operational for when the data became available for timely data distribution and subsequent analysis.
Camilla Mathison, Andrew J. Challinor, Chetan Deva, Pete Falloon, Sébastien Garrigues, Sophie Moulin, Karina Williams, and Andy Wiltshire
Geosci. Model Dev., 14, 437–471,Short summary
Sequential cropping (also known as multiple or double cropping) is a common cropping system, particularly in tropical regions. Typically, land surface models only simulate a single crop per year. To understand how sequential crops influence surface fluxes, we implement sequential cropping in JULES to simulate all the crops grown within a year at a given location in a seamless way. We demonstrate the method using a site in Avignon, four locations in India and a regional run for two Indian states.
Chao Wang, Xingqin An, Qing Hou, Zhaobin Sun, Yanjun Li, and Jiangtao Li
Geosci. Model Dev., 14, 337–350,
Kalyn Dorheim, Steven J. Smith, and Ben Bond-Lamberty
Geosci. Model Dev., 14, 365–375,Short summary
Simple climate models are frequently used in research and decision-making communities because of their tractability and low computational cost. Simple climate models are diverse, including highly idealized and process-based models. Here we present a hybrid approach that combines the strength of two types of simple climate models in a flexible framework. This hybrid approach has provided insights into the climate system and opens an avenue for investigating radiative forcing uncertainties.
David N. Bresch and Gabriela Aznar-Siguan
Geosci. Model Dev., 14, 351–363,Short summary
Climate change is a fact and adaptation a necessity. The Economics of Climate Adaptation methodology provides a framework to integrate risk and reward perspectives of different stakeholders, underpinned by the CLIMADA impact modelling platform. This extended version of CLIMADA enables risk assessment and options appraisal in a modular form and occasionally bespoke fashion yet with high reusability of functionalities to foster usage in interdisciplinary studies and international collaboration.
Paul A. Ullrich, Colin M. Zarzycki, Elizabeth E. McClenny, Marielle C. Pinheiro, Alyssa M. Stansfield, and Kevin A. Reed
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
TempestExtremes (TE) is a multifaceted framework for feature detection, tracking, and scientific analysis of regional or global Earth-system datasets. Version 2.1 of TE now provides extensive support for nodal and areal features. This paper describes the algorithms that have been added to the TE framework since version 1.0, and gives several examples of how these can be combined to produce composite algorithms for evaluating and understanding atmospheric features.
Amante, C. and Eakin, B. W.: ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis, NOAA Technical Memorandum, 2009.
Backman, J., Duncan, R. A., Peterson, L. C., Baker, P. A., Baxter, A. N., Boersma, A., Cullen, J. L., Droxler, A. W., Fisk, M. R., Greenough, J. D., Hargraves, R. B., Hempel, P., Hobart, M. A., Hurley, M. T., Johnson, D. A., Macdonald, A. H., Mikkelsen, N., Okada, H., Rio, D., Robinson, S. G., Schneider, D., Swart, P. K., Tatsumi, Y., Vandamme, D., Vilks, G., and Vincent, E.: Site 707, ODP Ocean Drilling Program, 1988.
Bar-Or, R., Erlick, C., and Gildor, H.: The role of dust in glacial–interglacial cycles, Quaternary Sci. Rev., 27, 201–208, https://doi.org/10.1016/j.quascirev.2007.10.015, 2008.
Barker, P. F. and Thomas, E.: Origin, signature and palaeoclimatic influence of the Antarctic Circumpolar Current, Earth-Sci. Rev., 66, 143–162, 2004.
Barker, P. F., Filippelli, G. M., Florindo, F., Martin, E. E., and Scher, H. D.: Onset and role of the Antarctic Circumpolar Current, Deep Sea Res. Pt. II, 54, 2388–2398, https://doi.org/10.1016/j.dsr2.2007.07.028, 2007.
Barrera, E. B., Lohmann, J., and Kyger, C.: Strontium isotope and benthic foraminifer stable isotope results from Oligocene sediments at Site 803, ODP Ocean Drilling Program, 1993.
Barron, E. J.: Paleogeography and Climate, 180 Million Years to the Present, University of MIAMI, 1980.
Barron, E. J.: Explanations of the Tertiary global cooling trend, Palaeogeogr. Palaeocl., 50, 45–61, 1985.
Barron, E. J. and Peterson, W. H.: Mid-Cretaceous ocean circulation: Results from model sensitivity studies, Paleoceanography, 5, 319–337, https://doi.org/10.1029/PA005i003p00319, 1990.
Barron, E. J. and Peterson, W. H.: The Cenozoic ocean circulation based on ocean General Circulation Model results, Palaeogeogr. Palaeocl., 83, 1–28, 1991.
Barron, E. J., Thompson, S. L., and Schneider, S. H.: An Ice-Free Cretaceous? Results from Climate Model Simulations, Science, 212, 501-508, https://doi.org/10.1126/science.212.4494.501, 1981.
Bice, K. L., Barron, E. J., and Peterson, W. H.: Continental runoff and early Cenozoic bottom-water sources, Geology, 25, 951–954, 1997.
Bice, K. L., Barron, E. J., and Peterson, W. H.: Reconstruction of realistic early Eocene paleobathymetry and ocean GCM sensitivity to specified basin configuration, Oxford Monographs on Geology and Geophysics, 39, 227–247, 1998.
Braconnot, P., Harrison, S. P., Kageyama, M., Bartlein, P. J., Masson-Delmotte, V., Abe-Ouchi, A., Otto-Bliesner, B., and Zhao, Y.: Evaluation of climate models using palaeoclimatic data, Supplement, Nature Clim. Change, 2, 417–424, 2012.
Cramer, B. S., Miller, K. G., Barrett, P. J., and Wright, J. D.: Late Cretaceous–Neogene trends in deep ocean temperature and continental ice volume: Reconciling records of benthic foraminiferal geochemistry (δ18O and Mg/Ca) with sea level history, J. Geophys. Res.-Oceans, 116, C12023, https://doi.org/10.1029/2011jc007255, 2011.
Crowley, C. W.: An atlas of Cenozoic climates, Masters of science in geology, The University of Texas, 2012.
Dalziel, I. W. D., Lawver, L. A., Norton, I. O., and Gahagan, L. M.: The Scotia Arc: Genesis, Evolution, Global Significance, Annu. Rev. Earth Pl. Sc., 41, 767–793, https://doi.org/10.1146/annurev-earth-050212-124155, 2013a.
Dalziel, I. W. D., Lawver, L. A., Pearce, J. A., Barker, P. F., Hastie, A. R., Barfod, D. N., Schenke, H.-W., and Davis, M. B.: A potential barrier to deep Antarctic circumpolar flow until the late Miocene?, Geology, 41, 947–950, https://doi.org/10.1130/g34352.1, 2013b.
DeConto, R. M. and Pollard, D.: Rapid Cenozoic glaciation of Antarctica induced by declining atmospheric CO2, Nature, 421, 245–249, 2003.
DeConto, R. M., Galeotti, S., Pagani, M., Tracy, D., Schaefer, K., Zhang, T., Pollard, D., and Beerling, D. J.: Past extreme warming events linked to massive carbon release from thawing permafrost, Supplement, Nature, 484, 87–91, 2012.
Donn, W. L. and Shaw, D. M.: Model of climate evolution based on continental drift and polar wandering, Geol. Soc. Am. Bull., 88, 390–396, https://doi.org/10.1130/0016-7606(1977)88<390:mocebo>2.0.co;2, 1977.
Dutton, J. F. and Barron, E. J.: Miocene to present vegetation changes; a possible piece of the Cenozoic cooling puzzle, Geology, 25, 39–41, 1997.
Egbert, G. D., Ray, R. D., and Bills, B. G.: Numerical modeling of the global semidiurnal tide in the present day and in the last glacial maximum, J. Geophys. Res.-Oceans, 109, C03003, https://doi.org/10.1029/2003jc001973, 2004.
Fisher, R. L., Bunce, E. T., Cernock, P. J., Clegg, D. C., Cronan, D. S., Damiani, V. V., Dmitriev, L. V., Kinsman, D. J., Roth, P. H., Thiede, J., and Vincent, E.: Site 237, DSDP Deep Sea Drilling Project, 1974.
Fuetterer, D. K.: Bioturbation and trace fossils in deep sea sediments of the Walvis Ridge, southeastern Atlantic, Leg 74, DSDP Deep Sea Drilling Project; IPOD International Phase of Ocean Drilling, 1984.
Galewsky, J.: Orographic precipitation isotopic ratios in stratified atmospheric flows: Implications for paleoelevation studies, Geology, 37, 791–794, https://doi.org/10.1130/g30008a.1, 2009.
Garrett, C. and Kunze, E.: Internal Tide Generation in the Deep Ocean, Annu. Rev. Fluid Mech., 39, 57–87, https://doi.org/10.1146/annurev.fluid.39.050905.110227, 2007.
Gent, P. R., Danabasoglu, G., Donner, L. J., Holland, M. M., Hunke, E. C., Jayne, S. R., Lawrence, D. M., Neale, R. B., Rasch, P. J., Vertenstein, M., Worley, P. H., Yang, Z.-L., and Zhang, M.: The Community Climate System Model Version 4, J. Climate, 24, 4973–4991, https://doi.org/10.1175/2011jcli4083.1, 2011.
Goldner, A., Huber, M., and Caballero, R.: Does Antarctic glaciation cool the world?, Clim. Past, 9, 173–189, https://doi.org/10.5194/cp-9-173-2013, 2013.
Golonka, J.: Chapter 6 Phanerozoic palaeoenvironment and palaeolithofacies maps of the Arctic region, Geological Society, London, Memoirs, 35, 79–129, https://doi.org/10.1144/m35.6, 2011.
Green, J. A. M. and Huber, M.: Tidal dissipation in the early Eocene and implications for ocean mixing, Geophys. Res. Lett., 40, 2707–2713, https://doi.org/10.1002/grl.50510, 2013.
Harrison, S. P. and Prentice, C. I.: Climate and CO2 controls on global vegetation distribution at the last glacial maximum: Analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations, Global Change Biol., 9, 983–1004, 2003.
Heavens, N. G., Shields, C. A., and Mahowald, N. M.: A paleogeographic approach to aerosol prescription in simulations of deep time climate, Journal of Advances in Modeling Earth Systems, 4, M11002, https://doi.org/10.1029/2012ms000166, 2012.
Heinemann, M., Jungclaus, J. H., and Marotzke, J.: Warm Paleocene/Eocene climate as simulated in ECHAM5/MPI-OM, Clim. Past, 5, 785–802, https://doi.org/10.5194/cp-5-785-2009, 2009.
Henrot, A.-J., François, L., Favre, E., Butzin, M., Ouberdous, M., and Munhoven, G.: Effects of CO2, continental distribution, topography and vegetation changes on the climate at the Middle Miocene: a model study, Clim. Past, 6, 675–694, https://doi.org/10.5194/cp-6-675-2010, 2010.
Hetzel, R., Dunkl, I., Haider, V., Strobl, M., von Eynatten, H., Ding, L., and Frei, D.: Peneplain formation in southern Tibet predates the India-Asia collision and plateau uplift, Geology, 39, 983–986, https://doi.org/10.1130/g32069.1, 2011.
Hill, D. J., Haywood, A. M., Valdes, P. J., Francis, J. E., Lunt, D. J., Wade, B. S., and Bowman, V. C.: Paleogeographic controls on the onset of the Antarctic circumpolar current, Geophys. Res. Lett., 40, 5199–5204, https://doi.org/10.1002/grl.50941, 2013.
Hollis, C. J., Taylor, K. W. R., Handley, L., Pancost, R. D., Huber, M., Creech, J. B., Hines, B. R., Crouch, E. M., Morgans, H. E. G., Crampton, J. S., Gibbs, S., Pearson, P. N., and Zachos, J. C.: Early Paleogene temperature history of the Southwest Pacific Ocean: Reconciling proxies and models, Earth Planet. Sc. Lett., 349–350, 53–66, https://doi.org/10.1016/j.epsl.2012.06.024, 2012.
Huber, M.: Progress in greenhouse climate modelling, in: Reconstructing Earth's Deep-Time Climate, edited by: Linda Ivany, B. H., Paleontological Society, 2012.
Huber, M. and Caballero, R.: The early Eocene equable climate problem revisited, Clim. Past, 7, 603–633, https://doi.org/10.5194/cp-7-603-2011, 2011.
Huber, M., Sloan, L. C., and Shellito, C.: Early Paleogene oceans and climate; fully coupled modeling approach using the NCAR CCSM, in: Causes and consequences of globally warm climates in the early Paleogene, edited by: Wing, S. L., Gingerich, P. D., Schmitz, B., and Thomas, E., Geological Society of America (GSA), Boulder, CO, 2003.
Iakovleva, A. I., Brinkhuis, H., and Cavagnetto, C.: Late Palaeocene–Early Eocene dinoflagellate cysts from the Turgay Strait, Kazakhstan; correlations across ancient seaways, Palaeogeogr. Palaeocl., 172, 243–268, https://doi.org/10.1016/S0031-0182(01)00300-5, 2001.
Janecek, T. R. and Rea, D. K.: Eolian deposition in the northeast Pacific Ocean: Cenozoic history of atmospheric circulation, Geol. Soc. Am. B., 94, 730–738, https://doi.org/10.1130/0016-7606(1983)94<730:editnp>2.0.co;2, 1983.
Jayne, S. R., Laurent, L. C. S., and Gille, S. T.: Connections Between Ocean Bottom Topography and Earth's Climate, Oceanography, 17, 65–74, 2004.
Kaplan, J. O., Bigelow, N. H., Prentice, I. C., Harrison, S. P., Bartlein, P. J., Christensen, T. R., Cramer, W., Matveyeva, N. V., McGuire, A. D., Murray, D. F., Razzhivin, V. Y., Smith, B., Walker, D. A., Anderson, P. M., Andreev, A. A., Brubaker, L. B., Edwards, M. E., and Lozhkin, A. V.: Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections, J. Geophys. Res., 108, 8171, https://doi.org/10.1029/2002jd002559, 2003.
Kump, L. R. and Pollard, D.: Amplification of Cretaceous Warmth by Biological Cloud Feedbacks, Science, 320, 5873, https://doi.org/10.1126/science.1153883, 2008.
Langford, R. P., Wilford, G. E., Truswell, E. M., Totterdell, J. M., Yeung, M., Isem, A. R., Yeates, A. N., Bradshaw, M., Brakel, A. T., Olissoff, S., Cook, P. J., and Strusz, D. L.: Palaeogeographic Atlas of Australia, edited by: Australia, G., Canberra, 2001.
Lawver, L. A., Gahagan, L. M., and Dalziel, I. W. D.: A Different Look at Gateways: Drake Passage and Australia/Antarctica, in: Tectonic, Climatic, and Cryospheric Evolution of the Antarctic Peninsula, American Geophysical Union, 5–33, 2011.
Liu, Z., Pagani, M., Zinniker, D., DeConto, R., Huber, M., Brinkhuis, H., Shah, S. R., Leckie, R. M., and Pearson, A.: Global Cooling During the Eocene-Oligocene Climate Transition, Science, 323, 1187–1190, https://doi.org/10.1126/science.1166368, 2009.
Livermore, R., Hillenbrand, C.-D., Meredith, M., and Eagles, G.: Drake Passage and Cenozoic climate: An open and shut case?, Geochem. Geophy. Geosyst., 8, Q01005, https://doi.org/10.1029/2005gc001224, 2007.
Lunt, D. J., Valdes, P. J., Jones, T. D., Ridgwell, A., Haywood, A. M., Schmidt, D. N., Marsh, R., and Maslin, M.: CO2-driven ocean circulation changes as an amplifier of Paleocene-Eocene thermal maximum hydrate destabilization, Geology, 38, 875–878, https://doi.org/10.1130/g31184.1, 2010.
Lunt, D. J., Dunkley Jones, T., Heinemann, M., Huber, M., LeGrande, A., Winguth, A., Loptson, C., Marotzke, J., Roberts, C. D., Tindall, J., Valdes, P., and Winguth, C.: A model-data comparison for a multi-model ensemble of early Eocene atmosphere-ocean simulations: EoMIP, Clim. Past, 8, 1717–1736, https://doi.org/10.5194/cp-8-1717-2012, 2012.
Lyle, M.: Could early Cenozoic thermohaline circulation have warmed the poles?, Paleoceanography, 12, 161–167, 1997.
Mackensen, A. and Berggren, W. A.: Paleogene benthic foraminifers from the southern Indian Ocean (Kerguelen Plateau): biostratigraphy and paleoecology, Proceedings of the Ocean Drilling Program, Scientific Results, 120, 1992.
Markwick, P. J.: The palaeogeographic and palaeoclimatic significance of climate proxies for data-model comparisons, in: Deep-Time Perspectives on Climate Change: Marrying the Signal from Computer Models and Biological Proxies, edited by: Williams, M., Haywood, A. M., Gregory, J., and Schmidt, D. N., Geological Society Special Publication, 251–312, 2007.
Markwick, P. J. and Valdes, P. J.: Palaeo-digital elevation models for use as boundary conditions in coupled ocean-atmosphere GCM experiments: a Maastrichtian (late Cretaceous) example, Palaeogeogr. Palaeocl., 213, 37–63, 2004.
Micheels, A., Bruch, A. A., Uhl, D., Utescher, T., and Mosbrugger, V.: A Late Miocene climate model simulation with ECHAM4/ML and its quantitative validation with terrestrial proxy data, Palaeogeogr. Palaeocl., 253, 251–270, 2007.
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, https://doi.org/10.1130/g31450.1, 2011.
Molnar, P., Boos, W. R., and Battisti, D. S.: Orographic Controls on Climate and Paleoclimate of Asia: Thermal and Mechanical Roles for the Tibetan Plateau, Annu. Rev. Earth Pl. Sci., 38, 77–102, https://doi.org/10.1146/annurev-earth-040809-152456, 2010.
Morley, R. J.: Cretaceous and Tertiary climate change and the past distribution of megathermal rainforests, in: Tropical Rainforest Responses to Climatic Change, Springer Praxis Books, Springer Berlin Heidelberg, 1–31, 2007.
Müller, R. D., Sdrolias, M., Gaina, C., and Roest, W. R.: Age, spreading rates, and spreading asymmetry of the world's ocean crust, Geochem. Geophy. Geosyst., 9, Q04006, https://doi.org/10.1029/2007gc001743, 2008a.
Müller, R. D., Sdrolias, M., Gaina, C., Steinberger, B., and Heine, C.: Long-Term Sea-Level Fluctuations Driven by Ocean Basin Dynamics, Science, 319, 1357–1362, 2008b.
Neale, R. B., Richter, J. H., Conley, A. J., Park, S., Lauritzen, P. H., Gettelman, A., Williamson, D. L., Rasch, P. J., Vavrus, S. J., Taylor, M. A., Collins, W. D., Zhang, M., and Lin, S.-J.: Description of the NCAR Community Atmosphere Model (CAM 4.0) National Center for Atmospheric Research, 2010.
Otto-Bliesner, B. L. and Upchurch, G. R.: Vegetation-induced warming of high-latitude regions during the Late Cretaceous period, Nature (London), 385, 804–807, 1997.
Perch-Nielsen, K., Supko, P. R., Boersma, A., Carlson, R. L., Dinkelman, M. G., Fodor, R. V., Kumar, N., McCoy, F., Thiede, J., and Zimmerman, H. B.: Site 357; Rio Grande Rise, DSDP Deep Sea Drilling Project, 1977.
Phillips, J. D. and Forsyth, D.: Plate Tectonics, Paleomagnetism, and the Opening of the Atlantic, Geol. Soc. Am. B., 83, 1579–1600, https://doi.org/10.1130/0016-7606(1972)83[1579:ptpato]2.0.co;2, 1972.
Pollard, D. and DeConto, R. M.: Hysteresis in Cenozoic Antarctic ice-sheet variations, Global Planet. Change, 45, 9–21, 2005.
Polzin, K. L., Toole, J. M., Ledwell, J. R., and Schmitt, R. W.: Spatial Variability of Turbulent Mixing in the Abyssal Ocean, Science, 276, 93–96, https://doi.org/10.1126/science.276.5309.93, 1997.
Roberts, C. D., LeGrande, A. N., and Tripati, A. K.: Climate sensitivity to Arctic seaway restriction during the early Paleogene, Earth Planet. Sc. Lett., 286, 576–585, https://doi.org/10.1016/j.epsl.2009.07.026, 2009.
Rosenbloom, N., Shields, C., Brady, E. C., Levis, S., and Yeager, S. G.: Using CCSM3 for Paleoclimate Applications, National Center for Atmospheric Research, 2011.
Scher, H. D. and Martin, E. E.: Timing and Climatic Consequences of the Opening of Drake Passage, Science, 312, 428–430, https://doi.org/10.1126/science.1120044, 2006.
Schlich, R.: Sites 246 and 247, DSDP Deep Sea Drilling Project, 1974.
Schubert, G. and Sandwell, D.: Crustal volumes of the continents and of oceanic and continental submarine plateaus, Earth Planet. Sc. Lett., 92, 234–246, 1989.
Scotese, C. R. and Golonka, J.: Paleogeographic Atlas, PALEOMAP Progress Report 20-0692, Department of Geology, University of Texas at Arlington, 34, 1992.
Sessa, J. A., Ivany, L. C., Schlossnagle, T. H., Samson, S. D., and Schellenberg, S. A.: The fidelity of oxygen and strontium isotope values from shallow shelf settings: Implications for temperature and age reconstructions, Palaeogeogr. Palaeocl., 342–343, 27–39, https://doi.org/10.1016/j.palaeo.2012.04.021, 2012.
Sewall, J. O. and Sloan, L. C.: Come a little bit closer: A high-resolution climate study of the early Paleogene Laramide foreland, Geology, 34, 81–84, https://doi.org/10.1130/g22177.1, 2006.
Sewall, J. O., Sloan, L. C., Huber, M., and Wing, S.: Climate sensitivity to changes in land surface characteristics, Global and Planetary Change, 26, 445-465, 2000.
Shellito, C. J. and Sloan, L. C.: Reconstructing a lost Eocene paradise: Part I. Simulating the change in global floral distribution at the initial Eocene thermal maximum, Global Planet. Change, 50, 1–17, 2006a.
Shellito, C. J. and Sloan, L. C.: Reconstructing a lost Eocene Paradise, Part II: On the utility of dynamic global vegetation models in pre-Quaternary climate studies, Global Planet. Change, 50, 18–32, 2006b.
Shellito, C. J., Sloan, L. C., and Huber, M.: Climate model sensitivity to atmospheric CO2 levels in the Early-Middle Paleogene, Palaeogeogr. Palaeocl., 193, 113–123, 2003.
Shellito, C. J., Lamarque, J.-F., and Sloan, L. C.: Early Eocene Arctic climate sensitivity to pCO2 and basin geography, Geophys. Res. Lett., 36, https://doi.org/10.1029/2009gl037248, 2009.
Simmons, H. L., Jayne, S. R., Laurent, L. C. S., and Weaver, A. J.: Tidally driven mixing in a numerical model of the ocean general circulation, Ocean Model., 6, 245–263, https://doi.org/10.1016/S1463-5003(03)00011-8, 2004.
Sloan, L. C.: Equable climates during the early Eocene; significance of regional paleogeography for North American climate, Geology, 22, 881–884, 1994.
Sloan, L. C. and Rea, D. K.: Atmospheric carbon dioxide and early Eocene climate: A general circulation modeling sensitivity study, Palaeogeogr. Palaeocl., 119, 275–292, 1996.
Stein, C. A. and Stein, S.: A model for the global variation in oceanic depth and heat flow with lithospheric age, Nature, 359, 123–129, 1992.
Stickley, C. E., Brinkhuis, H., Schellenberg, S. A., Sluijs, A., Röhl, U., Fuller, M., Grauert, M., Huber, M., Warnaar, J., and Williams, G. L.: Timing and nature of the deepening of the Tasmanian Gateway, Paleoceanography, 19, PA4027, https://doi.org/10.1029/2004pa001022, 2004.
Stocker, T., Qin, D., and Platner, G.: Climate Change 2013: The Physical Science Basis, Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Summary for Policymakers (IPCC, 2013), 2013.
Strömberg, C. A. E.: Evolution of Grasses and Grassland Ecosystems, Annu. Revi. Earth Pl Sci., 39, 517–544, https://doi.org/10.1146/annurev-earth-040809-152402, 2011.
Torsvik, T. H., Carlos, D., Mosar, J., Cocks, L. R. M., and Malme, T. N.: Global reconstructions and North Atlantic paleogeography 440 Ma to recent, BATLAS – Mid Norway plate reconstruction atlas with global and Atlantic perspectives, 18–39, Geological Survey of Norway, 2002.
Utescher, T. and Mosbrugger, V.: Eocene vegetation patterns reconstructed from plant diversity – A global perspective, Palaeogeogr. Palaeocl., 247, 243–271, https://doi.org/10.1016/j.palaeo.2006.10.022, 2007.
Vincent, E., Gibson, J. M., and Brun, L.: Paleocene and early Eocene microfacies, benthonic foraminifera, and paleobathymetry of Deep Sea Drilling Project sites 236 and 237, western Indian Ocean, DSDP Deep Sea Drilling Project, 1974.
Vinogradov, A. P.: Atlas of the Lithological-paleogeographical Maps of the USSR, Soviet Union Ministerstvo geologii, Moscow, 1967.
Whittaker, J. M., Goncharov, A., Williams, S. E., Müller, R. D., and Leitchenkov, G.: Global sediment thickness data set updated for the Australian-Antarctic Southern Ocean, Geochem. Geophy. Geosyst., 14, 3297–3305, https://doi.org/10.1002/ggge.20181, 2013.
Wilson, D. S., Jamieson, S. S. R., Barrett, P. J., Leitchenkov, G., Gohl, K., and Larter, R. D.: Antarctic topography at the Eocene–Oligocene boundary, Palaeogeogr. Palaeocl., 335–336, 24–34, https://doi.org/10.1016/j.palaeo.2011.05.028, 2012.
Winguth, A., Shellito, C., Shields, C., and Winguth, C.: Climate Response at the Paleocene–Eocene Thermal Maximum to Greenhouse Gas Forcing – A Model Study with CCSM3, J. Climate, 23, 2562–2584, https://doi.org/10.1175/2009jcli3113.1, 2009.
Wohlfahrt, J., Harrison, S., Braconnot, P., Hewitt, C., Kitoh, A., Mikolajewicz, U., Otto-Bliesner, B., and Weber, S.: Evaluation of coupled ocean–atmosphere simulations of the mid-Holocene using palaeovegetation data from the northern hemisphere extratropics, Clim. Dynam., 31, 871–890, https://doi.org/10.1007/s00382-008-0415-5, 2008.
Wolfe, J. A.: Distribution of major vegetational types during the Tertiary, in: Geophysical Monograph, edited by: Sundquist, E. T. and Broecker, W. S., American Geophysical Union, Washington, DC, 357–375, 1985.
Wolfe, J. A., Forest, C. E., and Molnar, P.: Paleobotanical evidence of Eocene and Oligocene paleoaltitudes in midlatitude western North America, Geol. Soc. Am. B., 110, 664–678, https://doi.org/10.1130/0016-7606(1998)110<0664:peoeao>2.3.co;2, 1998.
Wright, N., Zahirovic, S., Müller, R. D., and Seton, M.: Towards community-driven paleogeographic reconstructions: integrating open-access paleogeographic and paleobiology data with plate tectonics, Biogeosciences, 10, 1529–1541, https://doi.org/10.5194/bg-10-1529-2013, 2013.
Zachos, J. C., Röhl, U., Schellenberg, S. A., Sluijs, A., Hodell, D. A., Kelly, D. C., Thomas, E., Nicolo, M., Raffi, I., Lourens, L. J., McCarren, H., and Kroon, D.: Rapid Acidification of the Ocean During the Paleocene-Eocene Thermal Maximum, Science, 308, 1611–1615, https://doi.org/10.1126/science.1109004, 2005.
Ziegler, A. M., Scotese, C. R., and Barrett, S. F.: Mesozoic and Cenozoic Paleogeographic Maps, in: Tidal Friction and the Earth's Rotation II, edited by: Brosche, P. and Sündermann, J., Springer Berlin Heidelberg, 240–252, 1982.
Ziegler, A. M., Rowley, D. B., Lottes, A. L., Sahagian, D. L., Hulver, M. L., and Gierlowski, T. C.: Paleogeographic Interpretation: With an Example From the Mid-Cretaceous, Annu. Rev. Earth Pl. Sci., 13, 385–428, https://doi.org/10.1146/annurev.ea.13.050185.002125, 1985.